Podcasts about circulation genomic

Join the Sanders Sisters as they welcome the holidays and the last episode of their first season of Floss & FlipFlops! In this episode, the sisters discuss the 12 medical conditions on Santa's list that can indicate a bigger systemic complication, and how you can integrate your knowledge of these conditions in helping your patients achieve lifelong health! Floss and Flip-Flops with the Sanders sisters features hosts dental hygienist and speaker Katrina M. Sanders, RDH, and podiatrist Dr Elizabeth Sanders, DPM. Together, the sisters discuss the oral-systemic link and its impact—from your teeth down to your toes. The podcast is produced monthly by Dental Products Report® and Modern Hygienist®, in partnership with The Sanders sisters. For additional content for dental professionals visit DPR and MH at dentalproductsreport.com. Katrina Sanders, RDH, can be reached at:  Website: katrinasanders.com Facebook Instagram LinkedIn EPISODE 12 REFERENCES: Tattersall, M. C., et. al. (2015). Asthma Predicts Cardiovascular Disease Events: The Multi-Ethnic Study of Atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 35(6), 1520-1525. Yeh, E. T. H., & Bickford, C. L. (2009). Cardiovascular Complications of Cancer Therapy: Incidence, Pathogenesis, Diagnosis, and Management. J Am Coll Cardiol, 53(24), 2231-2247. Chaikriangkrai, K., et. a l. (2015). Additive prognostic value of coronary artery calcium score and renal function in patients with acute chest pain without known coronary artery disease: up to 5-year follow-up. Int J Cardiovasc Imaging. 31(8), 1619-1626. Liu, Y., et. al. (2014). Kidney Stones and Cardiovascular Risk: A Metaanalysis of Cohort Studies. Am J Kidney Dis, 64(3), 402-410. Uddin, S. M. I., et. al. (2018). Erectile Dysfunction as an Independent Predictor of Future Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis. Circulation. doi:10.1161/circulationaha.118.033990 Clarson, L. E., et. al. (2015). Increased risk of vascular disease associated with gout: a retrospective, matched cohort study in the UK Clinical Practice Research Datalink. Annals of the Rheumatic Diseases, 74(4), 642-647 Beckman, J., Duncan, M., et al. HIV and PAD. March 12, 2018.  Circulation; 10.1161.117.032647 van Nimwegen, F. A., et. al. (2015). Cardiovascular disease after Hodgkin lymphoma treatment: 40-year disease risk. JAMA Intern Med. doi: 10.1001/jamainternmed.2015.1180 Rodondi, N., et al. (2010). Subclinical hypothyroidism and the risk of coronary heart disease and mortality. JAMA, 304(12), 1365-1374. Larsson Susanna, C., et. al. (2019) Thyroid Function and Dysfunction in Relation to 16 Cardiovascular Diseases: A Mendelian Randomization Study. Circulation: Genomic and Precision Medicine, 0(0). doi:10.1161/CIRCGEN.118.002468 Adelborg, K., et. al. (2018). Migraine and risk of cardiovascular diseases: Danish population based matched cohort study. Bmj, 360. doi:10.1136/bmj.k 96 Chapple ILC, Potential mechanisms underpinning the nutritional modulation of periodontal inflammation.  J Am Dent Assoc. 2009; 140 (2): 178-184. Hujoel P. Dietary carbohydrates and dental-systemic diseases.  J Dental Res. 2009; 88 (6): 490-502. Lee M, et al "Current Helicobacter pylori infection is significantly associated with subclinical coronary atherosclerosis in healthy subjects: A cross-sectional study" PloS One 2018; 13(3): e0193646. Shah NH, LePendu P., Bauer-Mehren A., et al. (June 10, 2015). Proton Pump Inhibitor Usage and the risk of MI in the general population. LLoS ONE 10(6). Mercado FB, Marshall RI, Bartold PM. Inter-relationships between rheumatoid arthritis and periodontal disease. A Review. J Clin Periodontol 2003; 30: 761-772.

Jane Ferguson:                  Hi there. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, and this is Episode 36 from February 2020.                                                 First up, we have “Identification of Circulating Proteins Associated with Blood Pressure Using Mendelian Randomization” from Sébastien Thériault, Guillaume Paré, and colleagues from McMaster University in Ontario. They set out to assess whether they could identify protein biomarkers of hypertension using a Mendelian randomization approach. They analyzed data from a genome-wide association study of 227 biomarkers which were profiled on a custom Luminex-based platform in over 4,000 diabetic or prediabetic participants of the origin trial.                                                 They constructed genetic predictors of each protein and then used these as instruments for Mendelian randomization. They obtained systolic and diastolic blood pressure measurements in almost 70,000 individuals, in addition to mean arterial pressure and pulse pressure in over 74,000 individuals, all European ancestry with GWAS data, as part of the International Consortium for Blood Pressure.                                                 Out of the 227 biomarkers tested, six of them were significantly associated with blood pressure traits by Mendelian randomization after correction for multiple testing. These included known biomarkers such as NT-proBNP, but also novel associations including urokinase-type plasminogen activator, adrenomedullin, interleukin-16, cellular fibronectin and insulin-like growth factor binding protein-3. They validated all of the associations apart from IL-16 in over 300,000 participants in UK Biobank. They probed associations with other cardiovascular risk markers and found that NT-proBNP associated with large artery atherosclerotic stroke, IGFBP3 associated with diabetes, and CFN associated with body mass index.                                                 This study identified novel biomarkers of blood pressure, which may be causal in hypertension. Further study of the underlying mechanisms is required to understand whether these could be useful therapeutic targets in hypertensive disease.                                                 The next paper comes from Sony Tuteja, Dan Rader, Jay Giri and colleagues from the University of Pennsylvania and it's entitled, “Prospective CYP2C19 Genotyping to Guide Antiplatelet Therapy Following Percutaneous Coronary Intervention: A Pragmatic Randomized Clinical Trial”.                                                 They designed a pharmacode genomic trial to assess effects of CYP2C19 genotyping on antiplatelet therapy following PCI. Because loss of function alleles in CYP2C19 impair the effectiveness of clopidogrel, the team were interested in understanding whether knowledge of genotype status would affect prescribing in a clinical setting. They randomized 504 participants to genotype guided or usual care groups and assessed the rate of prasugrel or ticagrelor prescribing in place of clopidogrel within each arm. As a secondary outcome, they assessed whether prescribers adhere to genotype guided recommendations. Of genotyped individuals, 28% carried loss of function alleles. Within the genotype guided group overall, there was higher use of prasugrel or ticagrelor with these being prescribed to 30% of patients compared with only 21% in the usual care group. Within genotype individuals carrying loss of function alleles, 53% were started on prasugrel or ticagrelor, demonstrating some adherence to genotype guided recommendations.                                                 However, this also meant that 47% of people whose genotype suggested reduced effectiveness were nevertheless prescribed clopidogrel. This study highlights that even when genotype information is available, interventional cardiologists consider clinical factors such as disease presentation and may weight these more highly than genotype information when selecting antiplatelet therapy following PCI.                                                 The next paper is about “Deep Mutational Scan of an SCN5A Voltage Sensor and comes to us from Andrew Glazer, Dan Roden and colleagues from Vanderbilt University Medical Center. In this paper, the team aim to characterize the functional consequences of variants and the S4 voltage sensor of domain IV and the SCN5A gene using a high throughput method that they developed. SCN5A encodes the major voltage gated sodium channel in the heart and variants in SCN5A can cause multiple distinct genetic arrhythmia syndromes, including Brugada syndrome, long QT syndrome, atrial fibrillation, and dilated cardiomyopathy, and have been linked to sudden cardiac death.                                                 Because of this, there's considerable interest in understanding the functional and clinical consequences of different variants, but previous approaches were time consuming and results were often inconclusive with many variants being classified as uncertain significance. This newly developed deep mutational scanning approach allows for simultaneous assessment of the function of thousands of variants, making it much more efficient than low throughput patch clamping. The team assessed the function of 248 variants using a triple drug assay in HEK293T cells expressing each variant and they identified 40 putative gain of function and 33 putative loss of function variants. They successfully validated eight of nine of these by patch clamping data. Their study highlights the effectiveness of this deep mutational scanning approach for investigating variants in the cardiac sodium channel SCN5A gene and suggests that this may also be an effective approach for investigating putative disease variants and other ion channels.                                                 The next article is a research letter from Connor Emdin, Amit Khera, and colleagues from Mass General Hospital in the Broad Institute entitled, “Genome-Wide Polygenic Score and Cardiovascular Outcomes with Evacetrapib in Patients with High-Risk Vascular Disease: A Nested Case-Control Study”. In this study, the team set out to probe the utility of using polygenic risk scores to predict the risk of major adverse cardiovascular events within individuals already known to be at high cardiovascular risk and to assess whether genetic scores can identify individuals who would benefit from the use of a CETP inhibitor such as Evacetrapib. They analyze data from the ACCELERATE trial which had tested Evacetrapib in a high risk population, and they found no effect on the incidents of major adverse cardiovascular events overall. Within a nested case-control sample of individuals experiencing major CVD events versus no events, they applied a polygenic risk score and found that the score predicted major cardiovascular events.                                                 Patients in the highest quintile of the risk score were at 60% higher risk of a major cardiovascular event than patients in the lowest quintile. There was no evidence of any interaction between the genetic risk score and Evacetrapib. These data suggest that genetic risk scores may have utility in identifying individuals at high risk events but may not have utility in identifying individuals who may derive more benefit from CETP inhibition. The next letter concerns “Epigenome-Wide Association Study Identifies a Novel DNA Methylation in Patients with Severe Aortic Valve Stenosis” and comes from Takahito Nasu, Mamoru Satoh, Makoto Sasaki and colleagues from Iwate Medical University in Japan. They were interested in understanding whether differences in DNA methylation could underlie the risk of aortic valve stenosis. They conducted an EWAS or epigenome-wide association study of peripheral blood mononuclear cells or PBMCs from 44 individuals with aortic stenosis and 44 disease free controls.                                                 They collected samples at baseline before a surgical intervention in the individuals with aortic stenosis and collected a follow-up sample one year later. They found that DNA methylation at a site on chromosome eight mapping to the TRIB1, or tribbles homolog one gene, was lower in the aortic stenosis group than in the controls at baseline. They replicated the association in an independent sample of 50 cases and 50 controls. TRIB1 MRNA levels were higher in the aortic stenosis group than the controls. When they looked at methylation status one year after aortic valve replacement or a transcatheter aortic valve implantation in patients with stenosis, they found that DNA methylation had increased in the cases while TRIB1 MRNA decreased. These data suggests that methylation status of TRIB1 and expression of TRIB1 may relate to the disease processes in aortic stenosis such as hemodynamic dysregulation and they can be reversed through surgical intervention. Changes in the methylation status of TRIB1 could be a novel biomarker of response to aortic valve replacement.                                                 The next letter comes from Niels Grote Beverborg, Pim van der Harst, and colleagues from University Medical Center Groningen and is entitled, “Genetically Determined High Levels of Iron Parameters Are Protective for Coronary Artery Disease”. Their study addresses the conflicting hypotheses that high iron status is either deleterious or protective against cardiovascular disease. The team constructed genetic predictors of serum iron status using 11 previously identified snips and tested the genetic association with CAD in UK Biobank data from over 408,000 white participants. Overall, the genetic score for higher iron status was associated with protection against CAD. Ten of the snips suggested individual neutral or protective effects of higher iron status on CAD, while one iron increasing snip was associated with increased risk of disease but this was thought to be likely through an iron independent mechanism. Overall, these data suggest that a genetic predisposition to higher iron status does not increase risk of CAD and is actually protective against disease.                                                 The final letter is entitled, “Confidence Weighting for Robust Automated Measurements of Popliteal Vessel Wall MRI” and comes from Daniel Hippe, Jenq-Neng Hwang, and colleagues from the University of Washington. They were interested in assessing whether images of popliteal artery wall incidentally obtained during knee MRI as part of an osteoarthritis study could be used to study the development and progression of atherosclerosis. They developed an automated deep learning based algorithm to segment and quantify the popliteal artery wall in images obtained over 10 years in over 4,700 individuals. Their approach, which they named FRAPPE, or fully automated and robust analysis technique for popliteal artery evaluation, was able to reduce the average time required for segmentation analysis from four hours to eight minutes per image. They applied weights based on confidence for each segment to automatically improve the accuracy of aggregate measurements such as mean wall thickness or mean lumen area. Their data suggest that this automated method can rapidly generate useful information on atherosclerosis from MRI images obtained as part of other studies. When combined with other data. This approach may facilitate novel discovery in secondary analyses of existing studies in an efficient and cost effective way.                                                 And that's all for issue one of 2020. Come back next time for more of the latest papers from Circulation: Genomic and Precision Medicine. Speaker 2:                           This podcast is copyright American Heart Association 2020.  

Jane Ferguson:                  Hi, everyone. Welcome to episode 35 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center, and an associate editor at Circulation: Genomic and Precision Medicine. This episode is first airing in December 2019. Let's see what we published this month.                                                 Our first paper is an “Integrated Multiomics Approach to Identify Genetic Underpinnings of Heart Failure and Its Echocardiographic Precursors: The Framingham Heart Study” from Charlotte Anderson, Ramachandran Vasan and colleagues from Herlev and Gentofte Hospital, Denmark and Boston University.                                                 In this paper, the team investigated the genomics of heart failure, combining GWAS with methylation and gene expression data, to prioritize candidate genes. They analyzed four heart failure related and eight echocardiography related phenotypes in several thousand individuals, and then identified SNPs, methylation markers, and differential gene expression associated with those phenotypes. They then created scores for each gene, based on the rank of statistical significance, aggregated across the different omics analysis.                                                 They examined the top ranked genes for evidence of pathway enrichment, and also looked up top SNPs for PheWAS associations in UK Biobank, and examined tissue specific expression in public data. While their data cannot definitively identify causal genes, they highlight several genes of potential relevance to heart failure pathogenesis, which may be promising candidates for future mechanistic studies.                                                 The next paper is “Genetic Determinants of Lipids and Cardiovascular Disease Outcomes: A Wide-Angled Mendelian Randomization Investigation” and comes from Elias Allara, Stephen Burgess and colleagues, from the University of Cambridge and the INVENT consortium. While it has been established, therapies to lower LDL cholesterol and triglycerides lead to lower risk of coronary artery disease, it remains less clear whether these lipid lowering efforts can also reduce risk for other cardiovascular outcomes. The team set out to address this question using Mendelian randomization. They generated genetic predictors of LDL cholesterol and triglycerides using data from the Global Lipids Genetics Consortium, and then assessed whether genetically predicted increased LDL and triglycerides associated with risk of cardiovascular phenotypes using UK Biobank data. Beyond CAD, they found that higher LDL was associated with abdominal aortic aneurysm and aortic valve stenosis. High triglyceride levels were positively associated with aortic valve stenosis and hypertension, but inversely associated with venous thromboembolism and hemorrhagic stroke.                                                 High LDL cholesterol and triglycerides were also associated with heart failure, which appeared to be mediated by CAD. Their data suggests that LDL lowering may have additional cardiovascular benefits in reducing aortic aneurism and aortic stenosis, while efforts to lower triglycerides may reduce the risk of aortic valve stenosis, but could result in increased thromboembolic risk.                                                 Next up is a paper from Steven Joffe, G.L. Splansky and colleagues, from the University of Pennsylvania and Boston University, on “Preferences for Return of Genetic Results Among Participants in the Jackson Heart Study and Framingham Heart Study”. There has been increasing discussion and concern about how to handle genetic data, and whether genetic results should be returned to participants, and under which circumstances. In this study, the teams that had to assess what participants themselves think. They query participants in the Jackson Heart Study, the Framingham Heart Study and the FHS Omni cohort, presenting them with potential scenarios that varied by five factors including phenotype severity, actionability, reproductive significance and relative of the absolute risk of the phenotype.                                                 Across all scenarios, 88 to 92% of respondents said that they would definitely or probably want to learn their result. In Jackson Heart Study respondents, factors increasing the desire for results included a positive attitude towards genetic testing, lower education, higher subjective numeracy, and younger age. The five pre-identified factors did not affect desire to receive results in Jackson Heart Study. Among Framingham Heart Study respondents, desire for results was associated with higher absolute risk, presentability, reproductive risk and positive attitudes towards genetic testing. Among FHS Omni respondents, desire for results was associated with positive attitudes towards genetic testing and younger age. Overall, these data show that across a variety of studies, there a high level of interest in receiving genetic results and that these are not necessarily linked to the phenotype or clinical significance of the results themselves.                                                 The next paper concerns “Peripheral Blood RNA Levels of QSOX1 and PLBD1 Are New Independent Predictors of Left Ventricular Dysfunction after Acute Myocardial Infarction” and this comes from Martin Vanhaverbeke, Peter Sinnaeve and colleagues, from University Hospital Leuven. They were interested in understanding whether they could identify subsequent left ventricular dysfunction in patients who suffered an acute myocardial infarction. They obtained blood and performed RNA-Seq at multiple time points in 143 individuals, following acute MI, to identify transcripts that were associated with subsequent LV dysfunction. They validated candidate gene transcripts in a validation sample of 449 individuals, confirming that expression of QSOX1 and PLBD1 at admission, were associated with LV dysfunction at follow-up. Adding QSOX1 to a model, consisting of clinical variables and cardiac biomarkers, including NT proBNP, had an incremental predictive value. They took their findings to a pig model and found that whole blood expression of both genes was associated with neutrophil infiltration in these ischemic myocardium. This study suggests that expression of QSOX1 and PLBD1 following MI, may have utility in predicting development of LV dysfunction and may be markers of cardiac inflammation.                                                 The next paper is a research letter from Hanna Hanania, Denver Sallee and Dianna Milewicz, from the University of Texas Health Science Center, and Emory University School of Medicine. Who set out to answer the question, “Do HCN4 Variants Predisposed to Thoracic Aortic Aneurysms and Dissections?” Previous work has suggested that rare variants in HCN4 associated with thoracic aortic disease, including ascending aortic dilation, left ventricular noncompaction cardiomyopathy, and sinus bradycardia. However, the evidence for disease segregation was relatively weak. The team set out to explore these potential associations using exome sequencing data from 521 individuals, from 347 unrelated families with heritable thoracic aortic disease, as well as 355 individuals with early onset sporadic aortic dissections, but no family history of disease. They identified a missense variant G482R, which segregated with disease in four unrelated families, was absent from the nomad database and was predicted to disrupt protein function and have deleterious effects. Their data support the evidence that HCN4 rare variants can cause heritable thoracic aortic disease with left ventricular noncompaction cardiomyopathy and bradycardia.                                                 Our final paper is a white paper from H. Li, X. J. Luo and colleagues, from the National Heart, Lung and Blood Institute at the NIH, and will likely interest anybody who applies for NIH grants, which I'm assuming is most of you listening to this podcast. Their paper on, “Portfolio Analysis of Research Grants in Data Science Funded by the National Heart, Lung, and Blood Institute”, delves into the type of data science research funded by NHLBI between fiscal year 2008 and fiscal year 2017. They identified 630 data science focused grants, funded by NHLBI, using keywords for bioinformatics and computational biology. They then analyzed the distribution of these grants across different disease areas and compared the results to data science grants funded by other NIH institutes or centers. Around 64% of funded grants were for cardiovascular disease with 22% in lung and airway disease, 12% in blood disease and 2% in sleep.                                                 NHLBI's investment in data science research grants averaged about 1% of its overall research grant investment, and this remained constant over the 10-year period. However, this proportion does not include other large scale investment by NHLBI in building data science platforms through other mechanisms. Of relevance to our listeners across all institutes, most funded data science research grants were related to genomics and other omics data. In this paper they include lots of graphs breaking down grant distributions across different categories, so it's worth a look as you plan your next grant application.                                                 That's all for December and the final episode of 2019. Thanks for listening and happy holidays to all who celebrate. I'm excited to be back in 2020, to kick off the next decade of exciting advances in genomic and precision cardiovascular medicine.                                                 This podcast was brought to you by Circulation: Genomic and Precision Medicine, and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                  Hi there. Welcome to the November 2019 issue of Getting Personal: Omics of the Heart. I'm Jane Ferguson. This is your podcast from Circulation: Genomic and Precision Medicine. Let's get started.                                                 First up from Eric Curruth, Christopher Haggerty and colleagues from Geisinger, we have a paper entitled, “Prevalence and Electronic Health Record-based Phenotype of Loss-of-function Genetic Variance in Arrhythmogenic Right Ventricular Cardiomyopathy-associated Genes”. In this study, the team set out to understand the phenotypic consequences of variants and desmosome genes which has been associated with a arrhythmogenic right ventricular cardiomyopathy or ARVC. In clinical genetic testing, secondary findings of pathogenic or likely pathogenic variants in desmosome genes are recommended for clinical reporting. However, relatively little is known about the phenotypic consequences of these variants in a general clinical population.                                                 The team obtained whole exome sequencing data for over 61,000 individuals from the DiscovEHR cohort, part of the Geisinger MyCode Community Health Initiative. They then screened individuals for a putative loss of function variants in PKP2, DSC2, DSG2, and DSP. They evaluated ARVC diagnostic criteria using previously conducted ECG and echocardiograms and performed a phenom-wide association study or PHeWAS using EHR derived phenotypes. They found 140 people with an ARVC variant in one of the four genes, none of whom had an existing diagnosis of ARVC in the EHR.                                                 Further, there were no measurable differences in their ECG or echocardiogram findings compared with matched controls. There were also no associations with any heart disease phenotypes as assessed by PHeWAS. Overall, they report a prevalence of ARVC loss of function variants of around one in 435 in a general clinical population of predominantly European descent, but they did not find evidence that these variants associated with specific phenotypes. Thus, the clinical relevance of putative loss of function variants in desmosome genes still remains to be determined.                                                 The next paper is titled, “MRAS Variants Cause Cardiomyocyte Hypertrophy in Patients-specific iPSC-derived Cardiomyocytes”. Additional evidence for MRS as a definitive Noonan syndrome susceptibility gene. This comes from Erin Higgins, Michael Ackerman, and colleagues from the Mayo Clinic. They were interested in understanding whether a recently identified Noonan syndrome variant in the MRS gene was necessary and sufficient to cause Noonan syndrome with cardiac hypertrophy. They generated induced pluripotent STEM cell or IPS C lines from patient derived cells carrying the glycine 23 veiling variant and MRS. In addition to isogenic control cells where the pathogenic variant was corrected back to wild-type using CRISPR CAS nine gene editing, they also created a disease model cell line by introducing the MRS variant into unrelated control cells.                                                 They then comprehensively characterized the phenotypes of the three cell lines using a variety of approaches including microscopy, immunofluorescence, single cell RNA seek, Western blot, qPCR, and live cell calcium imaging. Both the patient derived and the disease model IPS cardiomyocytes were larger than control cells and demonstrated changes in gene expression and intracellular pathway signaling characteristic of cardiac hypertrophy. The patient and disease model cells also displayed impaired calcium handling. Through in-vitro phenotyping, the team was able to demonstrate that the glycine 23 veiling MRS variant elicits a cardiac hypertrophy phenotype and IPSC cardiomyocytes, that strongly suggests that this variant is responsible for the observed Noonan syndrome associated cardiac hypertrophy in the effected patients.                                                 Next up is a review from Christopher Lee, Iftikhar Kullo, and colleagues also from the Mayo Clinic on “New Case Detection by Cascade Testing in Familial Hypercholesterolemia: A Systematic Review of the Literature”. In this review they set out to systematically assess cascade testing programs for familial hypercholesterolemia, a disease which has a prevalence of about one and 250 but is estimated to be diagnosed in under 10% of patients. They identified published studies across the world which had conducted cascade testing and had reported the number of index cases and number of relatives tested and had also specified their methods of contacting relatives and testing.                                                 Using these criteria, they identified 10 studies for inclusion spanning several European countries, South Africa, New Zealand, Australia, and Brazil. The team calculated the proportion of relatives testing positive and the number of new cases per index case to facilitate comparison between studies. The mean number of programs was 242 with an average of 826 relatives per study. The average yield was 45%, ranging from 30 to 60%. the mean new cases per index case was 1.65 with a range of 0.22 to 8.0. Studies that use direct contact versus indirect contact for relatives and those that tested beyond first degree relatives had a greater yield. Further, active sample collection versus collection at clinic and using genetic testing versus biochemical testing was similarly associated with a higher yield. Despite differences between the United States and other countries, applying these strategies when establishing new cascade testing programs in the US may help promote success of these programs.                                                 Our next paper concerns “Randomization of Left-right Asymmetry and Congenital Heart Defects: The Role of DNAH5 in Humans and Mice”. And this was conducted by Tabea Nöthe-Menchen, Heymut Omran, and colleagues from University Children's Hospital Muenster and the PCD study group. They were interested in understanding the relationship between congenital heart defects and laterality defects where internal organs are atypically positioned, such as in a mirror image as occurs in situs inversus. Ciliary dyskinesia is thought to play a role in situs inversus and the most frequently mutated gene in primary ciliary dyskinesia is DNAH5. The team does hypothesize that DNAH5 mutations may play a role in congenital heart disease. They characterized phenotypes in 132 patients with primary ciliary dyskinesia carrying disease causing DNAH5 mutations and also studied left right access establishment using a DNAH5 mutant mouse model.                                                 66% of patients in their study had laterality defects, 88% of whom presented with situs inversus totalis and 6% presented with congenital heart disease. In the mass model, they observed immotile cilia, impaired flow with the left right organizer and randomization of nodal signaling with normal reversed or bilateral expression of key molecules. Their study thus demonstrates that mutation of DNAH5 is associated with congenital heart defects and they further highlight the ciliary mechanisms underlying defects and development of left right positioning during embryogenesis. Consideration of celiopathy related symptoms may be warranted when examining patients with congenital heart defects.                                                 Next up, we have a research letter from William Goodyear, Marco Perez and colleagues from Stanford University on “Broad Genetic Testing in a Clinical Setting Uncovers a High Prevalence of Titan Loss-of-Function Variants in Very Early-Onset Atrial Fibrillation”. They were interested in understanding genetic determinants of atrial fibrillation and hypothesized that causal genetic variants would be enriched in individuals with very early onset AF, who are diagnosed with AF under the age of 45 with no other significant comorbidities. They identified 25 families comprising 23 unrelated patients with very early onset AF who had been evaluated and received genetic counseling at Stanford between 2014 and 2018.                                                 The mean age of AF diagnosis was 27.2 years and 76% of patients were male. 40% of patients had a first or second degree relative with very early onset AF, while 36% at first or second degree relatives with either early onset idiopathic cardiomyopathy, unexplained sudden death or strokes. 85% of patients were identified as having at least one rare variant in a cardiomyopathy associated gene. Six patients carried actionable pathogenic or likely pathogenic variants, four of which were in the titan gene.                                                 A subset of individuals were further evaluated by MRI or computed tomography on average 817 days after their first presentation and this revealed high rates of cardiac abnormalities including reduced ventricular function, chamber enlargement, borderline LV non compaction, or late gadolinium enhancement. These were not noted on echocardiogram at presentation, suggesting there may have been subsequent disease development or progression. Overall, this study highlights a high rate of familial disease and implicates an association between very early onset AF and rare variants in titan before the clinical onset of cardiomyopathy.                                                 The final letter this month comes from Yu Xia, Shaoxian Chen, Ping Li, Jian Zhuang and colleagues from Guangdong Academy of Medical Sciences and is entitled, “A Novel Mutation in MYH6 in Two Unrelated Chinese Han Families with Familial Atrial Septal Defect”. They report on two unrelated families who presented with secundum atrial septal defect or ASD2. Whole exome sequencing revealed a novel variant and the MYH6 gene in both families, with the same variant present in all effected individuals but not in unaffected family members or unrelated controls. Because other variants in MYH6 have been reported to effect myofibril formation. The team studied the effect of the novel variant on the myofibrillar organization through transient transfection of CTC 12 cells. The MYH6 E526K variant was associated with a reduced striated I pattern and increased non-striated patterning. There was no effect on ATPase activity.                                                 Protein modeling suggested a variant of the effective position would reduce hydrogen bonding between alpha helices in the actin interface two region, increasing the volume of the cavity between the alpha helices and promoting the exposure of the alkaline side chain in the actin binding region. This could impair the interaction between the myosin motor head and actin. What these data suggests are that this novel MYH6 heterozygous variant may underlie ASD2 in two unrelated Chinese Han families by impairing myofibrillar organization.                                                 That's all for November 2019. Thank you for listening and I look forward to being back in December for the final episode of 2019.                                                 This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association council on genomic and precision medicine. This program is copyright American Heart Association 2019.

Jane Ferguson:                Hello. Welcome to episode 33 of Getting Personal: Omics Of The Heart, your podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. This episode is from October 2019. Let's get started.                                            First up is a paper from Sébastien Thériault, Yohan Bossé, Jean-Jacques Schott and colleagues from Laval University, Quebec and INSERM in Mont. They published on genetic association analyses, highlight IL6, ALPL and NAV1 as three new susceptibility genes underlying Calcific Aortic Valve Stenosis.                                            In this paper, they were interested in finding out whether they could identify novel susceptibility genes for Calcific Aortic Valve Stenosis, or CAVS, which is a severe and often fatal condition with limited treatment options other than surgical aortic valve replacement. They conducted a GWAS meta-analysis across four European ancestry cohorts comprising over 5,000 cases and over 354,000 controls. They identified four loci at genome-wide significance, including two known loci in LPA and PALMD as well as two novel loci, IL6 which encodes the interleukin six cytokine, and ALPL, which encodes an alkaline phosphatase. They then integrated transcriptomic data from 233 human aortic valves to conduct the transcriptome wide association study and find an additional risk locus associated with higher expression of NAV1 encoding neuron navigator one. Through fine mapping, integrating conservation scores, and methylation peaks, they narrowed down the putative causal variants at each locus identifying one snip in each of PALMD and IL6 as likely causal in addition to two candidates snips at ALPL and three plausible candidate snips in NAV1.                                            Phenome-Wide Association Analysis, or PheWAS of the top candidate functional snips found that the IL6 risk variant associated with higher eosinophil count, pulse pressure and systolic blood pressure. Overall, this study was able to identify novel loci associated with CAVS potentially implicating inflammation and hypertension in CAVS etiology. Additional functional studies are required to further explore these potential mechanisms.                                            Next up is a paper from Elisavet Fotiou, Bernard Keavney and colleagues from the University of Manchester. Their paper entitled Integration of Large-Scale Genomic Data Sources With Evolutionary History Reveals Novel Genetic Loci for Congenital Heart Disease explored the genetic etiology of sporadic non syndromic congenital heart disease using an evolution informed approach. Ohnologs are related genes that have been retained following ancestral whole genome duplication events which occurred around 500 million years ago. The authors hypothesized that ohnologs which were retained versus duplicated genes that were lost were likely to have been under greater evolutionary pressure due to the need to maintain consistent gene dosage. For example, as could occur when the resulting proteins form complexes that require stochiometric balance.                                            Thus, ohnologs may be enriched for genes that are sensitive to dosage. The group analyzed copy number variant data from over 4,600 non syndromic coronary heart disease patients as well as whole exome sequence data from 829 cases of Tetralogy of Fallot. Compared to control data obtained from public databases, there was evidence for significant enrichment in CHD associated variants in ohnologs but not in other duplicated genes arising from small scale duplications. Through this and various other filtering steps to prioritize likely variants, the group was able to identify 54 novel candidate genes for congenital CHD highlighting the utility of considering the evolutionary origin of genes in the search for disease relevant biology.                                            Next, we have a clinical letter entitled Pathological Overlap of Arrhythmogenic Right Ventricular Cardiomyopathy and Cardiac Sarcoidosis from Ashwini Kerkar, Victoria Parikh and colleagues at Stanford University. They describe a case of a 50 year old woman previously healthy and a long distance runner who presented with tachycardia. She was found to have normal left ventricular size but severe right ventricular enlargement and systolic dysfunction. Genetic testing using an Arrhythmogenic Right Ventricular Cardiomyopathy or ARVC panel identified a variant in DSG2. through cascade testing it was found that two of the patient's three children also carried this variant. The patient experienced worsening RV failure and subsequently underwent heart transplantation at age 55. Pathology of the heart showed evidence of cardiac sarcoidosis. There have been some previous reports of overlap in ARVC and cardiac sarcoid pathology but not in cases with a high confidence genetic diagnosis such as this one.                                            This case raises the possibility of shared disease mechanisms underlying ARVC and cardiac sarcoidosis and suggests that therapies aimed at immune modulation may also have utility in ARVC. However, further work is required to test this hypothesis. Our next paper is a perspective piece from Babken Asatryan and Helga Servatius from Bern University Hospital. In Revisiting the Approach to Diagnosis of Arrhythmogenic Cardiomyopathy: Stick to the Arrhythmia Criterion!, they outline the challenges in defining diagnostic criteria for a Arrhythmogenic Right Ventricular Cardiomyopathy or ARVC, given the variable presentation of the disease. Given recent advances in knowledge, particularly in recognizing disease overlap with Arrhythmogenic Left Ventricular Cardiomyopathy or ALVC and Biventricular Arrhythmogenic Cardiomyopathy, a new clinical perspective was warranted. The Heart Rhythm Society updated their recommendations this year to introduce a new umbrella term that better encompasses the spectrum of disease, Arrhythmogenic Cardiomyopathy or ACM. This recommends the arrhythmia criterion Should be used as a first line screening criteria for ACM.                                            This is a broad criteria and a definitive diagnosis of ACM requires exclusion of systemic disorders such as sarcoidosis, amyloidosis, mild carditis, Chagas disease, and other cardiomyopathies. Implementation of this new approach to diagnosis may require more extensive investigation of arrhythmias including the use of ambulatory ECG monitors or cardiac loop recorders. These changes may also affect who's referred for genetic testing, potentially shifting diagnoses towards genotype rather than phenotype based disease classifications. Despite challenges and adopting new approaches, it is hoped that these changes will ultimately serve to improve risk stratification and allow for improved disease management and intervention to prevent sudden cardiac death.                                            We end with a scientific statement chaired by Sharon Cresci and co-chaired by Naveen Pereira with a writing group representing the AHA Councils on Genomic and Precision Medicine, Cardiovascular and Stroke Nursing and Quality of Care and Outcomes Research entitled Heart Failure in the Era of Precision Medicine: A Scientific Statement From the American Heart Association. This paper provides a comprehensive overview of the current state of omics technologies as they relate to the development and progression of heart failure and considers the current and potential future applications of these high throughput data for precision medicine with respect to prevention, diagnosis and therapy of heart failure. They discuss advances in genomics, pharmacogenomics, epigenomics, proteomics, metabolomics, and the microbiome, and integrate the findings from this rapidly developing field as they pertain to new methods to diagnose, treat, and prevent heart failure.                                            And that's it for October. I hope to see many of you at AHA Scientific Sessions in Philadelphia in November and look forward to bringing you more of the best new science next month. Thanks for listening. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hi, everyone. Welcome to Getting Personal: Omics of the Heart, the monthly podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center and an associate editor at CircGen. This is episode 32 from September 2019. Starting off this month, we have a paper on Genetic Mosaicism in Calmodulinopathy brought to us by Lisa Wren, Alfred George and colleagues from Northwestern University. They were interested in exploring the disease phenotypes that result from variation in the calmodulin genes, CALM1, 2 and 3.                                            Mutations in calmodulin are known to associate with congenital arrhythmia, but the group hypothesized that there may be a broader range of phenotypes associated with calmodulin mutations. They report on four unrelated families all with pro bands exhibiting symptoms of prolonged QTC interval and documented ventricular arrhythmia. They conducted targeted exome sequencing in these individuals and in their families and identified mutations in calmodulin genes, including two novel mutations. In one family with multiple occurrences of intrauterine fetal demise, there was evidence for sematic mosaicism in both parents.                                            The team studied the two novel mutations and found that the variants led to alterations in a calcium binding site resulting in impaired calcium binding. In human induced pluripotent stem cell derived cardiomyocytes, the team showed that the mutations impaired calcium dependent inactivation of L-type calcium channels and prolonged action potential duration. Their study not only demonstrates that mutations in calmodulins can cause dysregulation of L-type calcium channels, but that parental mosaicism maybe a factor in families with unexplained fetal arrhythmia or fetal demise.                                            Our next paper come from Wan G Pang, Christiana Kartsonaki, Michael Holmes and Zing Min Chen from the University of Oxford and Peking University Health Science Center and is entitled Physical Activity, Sedentary Leisure Time, Circulating Metabolic Markers, and Risk of Major Vascular Diseases. In this study, the authors were interested in finding out whether circulating metabolites are associated with the relationship between physical inactivity or sedentary behavior and increased risk of cardiovascular disease. They identified over 3000 cases of incident CVD from the China Kadoorie Biobank and included over 1400 controls without CVD. They measured 225 different metabolites and baseline plasma samples using NMR.                                            They used measures of self-reported physical activity and sedentary leisure time to associate physical activity with circulating metabolites, and then they ran analysis to relate the metabolites to CVD. Physical activity and sedentary leisure time were associated with over 100 metabolic markers. In general, the patterns of associations were similar using either activity measure. Physical activity was inversely related to very low and low density HDL particles, but positively related to large and very large HDL particle concentrations. Physical activity was also inversely associated with alanine, glucose, lactate, acetoacetate, and glycoprotein acetyls.                                            When they examined the associations of these same metabolites with CVD, the directions were generally consistent with expectation, going on the premise that physical activity is protective, and that sedentary behavior is a risk factor for CVD. Their analyses suggests that metabolite markers could explain about 70% of the protective associations of physical activity and around 50% of the risk associations of sedentary leisure time with cardiovascular disease. Next up, we have a paper on Biallelic Variants in ASNA1, Encoding a Cytosolic Targeting Factor of Tail-Anchored Proteins, Cause Rapidly Progressive Pediatric Cardiomyopathy, coming from Judith Verhagen, Ingrid van de Laar and colleagues from University Medical Center Rotterdam.                                            Their focus was on pediatric cardiomyopathies, which are both clinically and genetically heterogeneous. They had identified a family where two siblings had died during early infancy of rapidly progressive dilated cardiomyopathy. Through exome sequencing, they identified variants in the ASNA-1 gene and established that the children were compound heterozygotes for the variants. This highly conserved gene encodes an ATPase, which is required for post-translational membrane insertion of tail-anchored proteins. The team looked at expression of this protein in patient samples and then followed this up with functional analyses using cells and zebrafish. They found that one of the variants was predicted to result in a premature stop codon.                                            In support of this, they observed decreased protein expression in myocardial tissue and skin fibroblasts. The other variant caused a missense mutation, and the team found that this resulted in protein misfolding, as well as less effective tail-anchored protein insertion. In zebrafish, knock out of the ASNA1 gene resulted in reduced cardiac contractility and early lethality, which could not be rescued by either version of the variant mRNA. This translational study highlights the importance of the ASNA1 gene as a cardiomyopathy susceptibility gene and further reveals the importance of tail-anchored membrane protein insertion pathways in cardiac function.                                            The next paper from Karni Moshal, Gideon Koren and colleagues from Brown University is entitled LITAF Regulates Cardiac L-Type Calcium Channels by Modulating NEDD 4-1 Ubiquitin Ligase. In this paper, the authors report on the role of ubiquitination as a crucial component in cardiac ion channel turnover and action potential duration. Previous genome wide association studies of QT interval had identified snips in or near genes regulating protein ubiquitination, particularly the LITAF or lipopolysaccharide-induced tumor necrosis factor gene. Using zebrafish, the team performed optical mapping in hearts to identify calcium and found that knocked down of LITAF resulted in an increase in calcium transients.                                            They studied intracellular calcium handling and rapid derived cardiomyocytes and found that over expression of LITAF caused a decrease in L-type calcium channel current and abundance of the L-type calcium channel alpha1c sub unit or Cava1c, whereas LITAF knocked down increased calcium channel current and Cava1c protein. LITAF downregulated total and surface pools of Cava1c via increased Cava1c ubiquitination and lysosomal degradation in tsA201 kidney cells. There was evidence of colocalization between LITAF and L-type calcium channel, or LTCC, in the tsA201 kidney cells and in cardiomyocytes. In the tsA201 cells, NEDD4-1 protein increased Cava1c ubiquitination, but a catalytically inactive form of NEDD4-1 had no effect.                                            Cava1c ubiquitination was further increased by co-expressed LITAF NEDD4-1, but not the inactive version of NeNEDD4-1. NEDD4-1 knockdown abolished the negative effect of LITAF on L-type calcium channel current and Cava1c levels in three week old rapid cardiomyocytes. Taken together, these data show that LITAF acts as an adapter protein promoting NEDD4-1 mediated ubiquitination and subsequent degradation of LTCC, highlighting LITAF as a novel regulator of cardiac excitation. Rounding out this issue is a review on the Gut Microbiome and Response to Cardiovascular Drugs from Sony Tuteja and Jane Ferguson from the University of Pennsylvania and Vanderbilt University Medical Center.                                            Since that last author is me, I'm sure I have a biased view of the importance of the topic, but the increasing awareness of the microbiome in every aspect of health has also led to increased awareness of the role of commensal microbiota in drug metabolism, including in the metabolism of drugs used to treat cardiovascular diseases. In this article, we aim to review what is currently known about how the gut microbiome interacts with cardiovascular drugs and to summarize some of the mechanisms whereby gut microbiota might affect drug metabolism. Early evidence suggests that the gut microbiome modulates response to statins and antihypertensive medications, but there may be many other drugs that are susceptible to interaction with microbiota.                                            Drug metabolism by the gut microbiome can result in altered drug pharmacokinetics and pharmacodynamics or in the formation of toxic metabolites which can interfere with drug response. While we are still in a relatively early stage in this field, we suggest that a better understanding of the complex interactions of the gut microbiome, host factors and response to medications will be important for the development of novel precision therapeutics in cardiovascular disease prevention and treatment. That's all for the September issue of Circulation: Genomic and Precision Medicine. Come back next month for the next installment. Thanks for listening.                                            This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hello, and welcome to Getting Personal, Omics of the Heart, your monthly podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. It is August, 2019, and this is episode 31. Let's get started.                                            Our first paper comes from Freyja van Lint and Cynthia James, from University Medical Center Utrecht, and is entitled Arrhythmogenic Right Ventricular Cardiomyopathy-Associated Desmosomal Variants Are Rarely De Novo, Segregation and Haplotype Analysis of a Multinational Cohort. In this study, the team was interested in exploring variants that are associated with arrhythmogenic right ventricular cardiomyopathy or ARVC. ARVC is often attributable to pathogenic variants in genes encoding cardiac desmosomal proteins, but the origin of these variants had not been comprehensively studied.                                            The investigators identified ARVC probands meeting 2010 task force criteria from three ARVC registries in the United States and Europe and who had undergone sequencing of desmosomal genes. All 501 probands, 322 of them, or over 64%, carried a pathogenic or likely pathogenic variant in the desmosomal genes PKP2, DSP DSG2, DSC2, and JUP. The majority of these, over 75%, we're not unique with these variants occurring in more than one proband.                                            The team performed cascade screening and were able to identify the parental origin of almost all of the variants. However, they identified three de novo variants, including two whole gene deletions. They conducted haplotype analysis for 24 PKP2 variants across 183 seemingly unrelated families and concluded that all of these variants originated from common founders.                                            This analysis sheds light on the origin of variants in desmosomal genes and suggests that the vast majority of these ARVC variants originate from ancient founders with only a very small proportion of de novo variants. These data can inform clinical care particularly concerning genetic counseling and cascade screening of relatives.                                            The next paper continues a theme of cardiomyopathy and comes from Derk Frank, Ashraf Yusuf Rangrez, Corinna Friedrich, Sven Dittmann, Norbert Frey, Eric Schulze-Bahr and colleagues from University Medical Center Schleswig-Holstein. In this paper, Cardiac α-Actin Gene Mutation Causes Atrial-Septal Defects Associated with Late-Onset Dilated Cardiomyopathy, the team was interested in understanding the genetics of familial atrial-septal defect. They studied large multi-generational family with 78 family members and mapped a causal variant on chromosome 15q14, which caused nonsynonymous change in exon 5 of the ACTC1 gene.                                            In silico tools predicted this variant to be deleterious. Analysis of myocardial tissue from an affected individual revealed sarcomeric disarray, myofibrillar degeneration, and increased apoptosis. Proteomic analysis highlighted extracellular matrix proteins as being affected. The team over-expressed the mutation in rats and found structural defects and increased apoptosis in neonatal rat ventricular cardiomyocytes and confirmed defects in actin polymerization and turnover which affected contractility. These data implicate the variant in ACTC1 as causing atrial-septal defects and late-onset cardiomyopathy in this family and revealed the underlying molecular mechanisms affecting development and contractility.                                            The next paper is entitled Characterization of the CACNA1C-R518C Missense Mutation in the Pathobiology of Long-QT Syndrome Using Human Induced Pluripotent Stem Cell Cardiomyocytes Shows Action Potential Prolongation and L-Type Calcium Channel Perturbation, and it comes from Steven Estes, Michael Ackerman and colleagues at the Mayo Clinic. They set out to use patient-derived human induced pluripotent stem cells to understand the pathogenicity of a variant in the CACNA1C gene in Long-QT Syndrome.                                            They obtained cells from dermal punch biopsy from an individual with long-QT and a family history of sudden cardiac death who carried an R518C missense mutation in CACNA1C. Starting with fibroblasts, they reprogrammed the cells into iPSCs and then differentiated these into cardiomyocytes. They corrected the mutation back to wild type using CRISPR/Cas9 and then compared the cardiomyocytes carrying the original patient mutation with isogenic corrected cardiomyocyte controls. They found significant differences in action, potential duration, and in calcium handling.                                            Patch clamp analysis revealed increased L-type calcium channel window current in the original mutation-carrying cells in addition to slow decay time and increased late calcium current compared with the isogenic corrected control human iPSC cardiomyocytes. These data strongly suggest that CACNA1C is a long-QT susceptibility gene and demonstrate the potential in using patient-derived iPSCs and CRISPR/Cas9 to understand underlying mechanisms linking variants to disease.                                            The final paper this month is Blood Pressure-Associated Genetic Variants in the Natriuretic Peptide Receptor-1 Gene Modulate Guanylate Cyclase Activity and comes from Sara Vandenwijngaert, Chris Newton-Cheh and colleagues on behalf of the CHARGE+ Exome Chip Blood Pressure Consortium, the CHD Exome+ Consortium, the Exome BP Consortium, the GoT2D Consortium, the T2D-GENES Consortium, and the UK Biobank CardioMetabolic Consortium Blood Pressure Working Group.                                            This team wanted to understand how variants in the NPR-1 gene affect the function of the atrial natriuretic peptide receptor-1. They performed a meta-analysis across over 491,000 unrelated individuals, including both low frequency and rare variants in NPR-1 to identify their association with blood pressure. They identified three nonsynonymous variants associated with altered blood pressure at genome-wide significance and examined the function of these variants in vitro.                                            Using cells expressing either wild type NPR-1 or one of the three identified variants, they explored the impact of the variants on the ability of cells to catalyzes the conversion of guanosine triphosphate to cyclic 3′,5′-guanosine monophosphate in response to binding of atrial or brain natriuretic peptide. Increased levels of cyclic GMP are known to decrease blood pressure by inducing by natriuresis, diuresis, and vasodilation.                                            Two variants which associated with high blood pressure in the population meta-analysis were associated with decreased cyclic GMP in response to ANP or BNP in vitro, while one variant which associated with lower blood pressure in humans was associated with higher cyclic GMP production in vitro. These data show that variants affecting loss or gain of function in guanylate cyclase activity could have downstream effects on blood pressure at the population level.                                            That's it for this month. Thank you for listening. We will be back with more next month. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hi everyone. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson and this is episode 30 from July 2019.                                            First up we have a paper, the Subtype Specificity of Genetic Loci Associated With Stroke in 16664 cases and 32792 Controls, from Matthew Trailer and colleagues on behalf of the NINDS Stroke Genetics Network and the International Stroke Genetics Consortium.                                            They were interested in understanding whether genetic loci previously found to be associated with stroke have distinct associations with stroke subtypes, specifically ischemic and hemorrhagic stroke. They compiled data sets through an international consortium to analyze 16664 stroke cases and 32792 controls, all of European ancestry. The cases were subtyped using two different stroke classification systems: the Trial of ORG 10172 in Acute Stroke Treatment, or TOAST system, and the Causative Classification of Stroke, or CCS system.                                            They selected genetic loci for consideration based on previous association with stroke in general or stroke subtypes in the MEGASTROKE consortium, which had included a large number of the subjects included in the present study. They used a Bayesian multinomial logistic regression approach to evaluate the association of snips at each locus with stroke subtypes identified under the TOAST and CCS classifications, giving five different case groups compared with a set of controls.                                            16 loci were taken forward for further analysis. There were seven loci which associated with both ischemic and hemorrhagic strokes subtypes, four which clearly associated with either ischemic or hemorrhagic stroke, with the rest showing less consistent effects. One locus, EDNRA, showed opposite affects for ischemic and hemorrhagic stroke. Overall, the findings indicate a large degree of genetic heterogeneity, but some overlap, suggesting common underlying pathophysiological pathways in different stroke subtypes, potentially related to small vessel disease. More detailed phenotyping and further analysis in large samples is required to fully understand genetic mechanisms underlying the risk of different stroke subtypes.                                            And, just to add, this paper was previously submitted to the pre-print server Bio Archive. We support open science and are always happy to consider papers that have been submitted to pre-print servers. So, if you have a particularly cool paper on Bio Archive that fits our scope, do feel free to send it our way.                                            Next up, we have a paper from Fabiola del Greco, Cristian Pattaro, Peter Pramstaller, Alessandera Rossini, and colleagues, from Eurac Research Institute for Biomedicine. This paper, entitled Lipidomics, Atrial Conduction, and Body Mass Index, Evidence from Association, Mediation, and Mendelian Randomization Models, aims to investigate the mechanisms underlying associations between circulating lipids and atrial conduction. They used mass spectrometry measurement of 151 sphingo- and phospholipids in plasma or serum from individuals who had undergone electrocardiogram measurements to ascertain P-wave duration.                                            They first looked for associations in 839 individuals from the micro islets in South Tyrol, or MICROS study, based in Italy, and replicated in 951 participants of the Orkney Complex Disease Study, ORCADES, based in Scotland. They identified and replicated an association between levels of phosphatidylcholine 38-3 and P-wave duration, which was independent of cholesterol, triglycerides, and glucose levels.                                            However, the association was mediated by BMI, and suggested that increased BMI may cause both increased levels of PC38-3 and longer P-wave duration, suggesting a role for body mass in altered lipids in atrial electrical activity.                                            The next paper is a research letter from Hana Bangash, Iftikhar Kullo, and colleagues from the Mayo Clinic on Use of Twitter to Promote Awareness of Familial Hypercholesterolemia.                                            Scientists and health professionals are increasingly using Twitter to communicate. This team wondered whether organized awareness campaigns, including Twitter events like Tweetathons, really make a different. They analyzed Twitter activity related to familial hypercholesterolemia in September 2018, during national cholesterol education month, which included an international familial hypercholesterolemia awareness day and Tweetathon. They also analyzed tweets from August and October 2018, where there was no formal awareness campaign and compared the FH Twitter activity with that of colorectal cancer, which did not have any formal awareness campaigns at that time.                                            In September, FH-related tweets increased by 152.9% compared to August, and then declined by over 58% in October. The topic reach for familial hypercholesterolemia was 11.1 million in August, and increased over 250% in September to 37.7 million. The reach declined by over 71% in October to just over 10 million. In comparison, the reach for colorectal cancer declined from 453 million in August to 300 million in September and then increased to 677 million in October, which happened to be breast cancer awareness month.                                            These data suggest that awareness campaigns like national cholesterol education month do lead to an increase in Twitter activity. However, this increase isn't necessarily sustained during the following month, and it remains unclear whether Twitter activity actually translates into a wider awareness amongst providers or patients, which could translate into clinical benefits. Nonetheless, as the use of Twitter increases, this may be a promising avenue to promote awareness and to disseminate knowledge.                                            And, of course, I have to take this opportunity to mention that Circulation: Genomic and Precision Medicine is on Twitter and you can follow us @Circ_Gen to keep up with what's going on at the journal.                                            Next up, we have a letter entitled B-iallelic Mutations in NUP205 and NUP210 Are Associated with Abnormal Cardiac Left-Right Patterning from WeiCheng Chen, Yuan Zhang, Sunhu Yang, Xiangyu Zhou, and colleagues from Tongji University.                                            They set out to understand the genetic underpinnings of cardiac left-right patterning and to probe why individuals with situs inversus totalis, or SIT, where the chest organs are in a complete mirror image to typical, have almost no symptoms or complications, while individuals with heterotaxy, who have abnormal organ arrangement that is not a mirror image, typically have severe phenotypes including congenital heart disease.                                            They performed whole exome and whole genome sequencing in 61 family trios with SIT or heterotaxy and identified ballielic missense mutations in nucleoporins NUP205 and NUP210. Nucleoporins comprise the main components of the nuclear pore complex in eukaryotic cells. The team generated induced pluripotent sense cells from peripheral blood cells of an affected patient and a healthy control, and found that there were impairments in protein interactions in the variant cells, particularly interactions with another crucial nucleoporin, NUP93.                                            In zebra fish, NUP205 knockdown resulted in left-right assymetry and defects in heart looping formation in a subset of fish embryos. Knockdown of both NUP205 and NUP93 resulted in impairments in cilia and human retinal pigment epithelial cells. Gene expression analysis revealed affects in known cilia genes NEC2 and NEC3.                                            Overall, this study provides evidence that mutations in nucleoporins NUP205 and NUP210 may cause defects in cardiac left/right patterning, potentially through effects on ciliary function.                                            This issue closes with a letter and response conversation around a recent article on missense mutations in the FLNC gene, causing familial restrictive cardiomyopathy. Hisham Ahamed and Muthiah Subramanian from Amrita Institute of Medical Scientists write to share a case of a woman presenting with features of heart failure and muscular weakness consistent with distal myopathy who was found to carry a deletion in exome 37 of the FLNC gene. This case adds to the previous evidence published by Alvaro Roldan Sofia and Julian Palomino-Doza in March 2019 in our journal, Highlighting Mutations in the FLNC Gene in Cardiomyopathy.                                            That's all for this month. Come back in August for your roundup of the next issue. Thanks for listening!                                            This podcast was brought to you by Circulation: Genomic and Precision Medicine, and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association, 2019.  

Jane Ferguson:                Hi, everyone. Welcome to episode 29 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University Medical Center and an associate editor at Circ: Genomic and Precision Medicine. Let's dive in and see what's new in the June issue.                                            First up, Validation of Genome-Wide Polygenic Risk Scores for Coronary Artery Disease in French Canadians from Florian Wünnemann, Guillaume Lettre and colleagues from the University of Montreal. Polygenic scores have the potential to be used to predict disease risk, but have not been broadly validated in different populations. This team was interested in whether polygenic risk scores that have been found to predict coronary artery disease in European ancestry subjects in the UK Biobank would also predict disease in French Canadians. They calculated two different polygenic risk scores in over 3600 cases and over 7000 controls and tested their ability to predict prevalent, incident and recurrent CAD.                                            Both scores predicted prevalent CAD, but did not perform as well in predicting incident or recurrent disease. This maybe because the majority of subjects were on statant treatment. Overall, the study confirms that polygenic risk scores for CAD developed in European ancestry can be used in other populations of European ancestry. However, further work is needed to develop and validate polygenic risk scores in other ancestries and to explore whether well performing risk scores can be developed to predict incident or recurrent disease.                                            Our next paper comes from Farnaz Shoja-Taheri, Michael Davis and colleagues from Emory University and is entitled Using Statistical Modeling to Understand and Predict Pediatric Stem Cell Function. Stem cell therapy is emerging as a potential therapeutic option for treating pediatric heart failure, which otherwise can only be cured through heart transplantation. The success of stem cell therapy depends on many variables, including the reparative ability of the infused cells. In this paper, the author set out to test whether they could predict the behavior of c-kit+ progenitor cells or human CPCs using RNA seq and computational modeling.                                            They obtained CPCs from 32 patients, including eight neonates whose cells are thought to have the highest reparative capacity, and they performed RNA sequencing. The team had previously developed regression models that could link gene expression data from sequencing to phenotypes in the cells, and they tested these models in the CPC cell lines. They tested seven neonate cell lines in vitro and found that cellular proliferation and the chemotactic potential of condition media matched what was predicted by the RNA seq-based model.                                            They used pathway analysis to identify potential mechanisms regulating CPC performance and identified several genes related to immune response, including interleukins and chemokines. They further confirmed the presence of cytokines at the protein level that were associated with well performing cells showing that at least one of the outcomes could be functionally predicted using an ELISA ASA. This type of approach may prove useful to inform ongoing clinical trials to stem cell therapy in congenital heart disease.                                            The next paper, Systems Pharmacology Identifies an Arterial Wall Regulatory Gene Network Mediating Coronary Artery Disease Side Effects of Antiretroviral Therapy comes to us from Itziar Frades, Johan Björkegren, Inga Peter and colleagues from the Icahn School of Medicine at Mount Sinai. They were interested in understanding mechanisms whereby antiretroviral therapy for HIV leads to increased risk for coronary artery disease. They analyzed the transcriptional responses to 15 different antiretroviral therapy or ART drugs in human cell lines and cataloged the common transcriptional signatures.                                            They then cross-referenced these against gene networks associated with CAD and CAD related phenotypes. They found that 10 of 15 ART response networks were enriched for differential expression and connectivity in an atherosclerotic arterial wall of regulatory gene network identified as causal for CAD. They used cholesteryl ester loaded foam cells in an in vitro model to validate their findings and found that ART treatment increased cholesteryl ester accumulation in foam cells which was prevented when the key network regulator gene, PQBP1, was silenced.                                            Their study highlights a gene network which is altered in response to ART and which promotes foam cells formation, highlighting a mechanistic link between HIV treatment and CAD. Targeting this network potentially through PQBP1 maybe a way to reduce the risk of CAD in individuals treated with antiretroviral drugs. The next paper comes from Brooke Wolford, Whitney Hornsby, Cristen Willer, Bo Yang and colleagues from the University of Michigan and is entitled Clinical Implications of Identifying Pathogenic Variants in Individuals With Thoracic Aortic Dissection. They were interested in whether exome sequencing in individuals with thoracic aortic dissection could identify disease associated variance.                                            They conducted exome sequencing in 240 patients and 258 controls and screened 11 genes for potentially pathogenic variance. They identified 24 variance in six genes across 26 cases with no potentially pathogenic variance identified in the controls. They found that carriers of pathogenic variance had significantly earlier age of onset of dissection, higher rates of root aneurysm and greater incidents of aortic disease in family members, while patients without identified variance had more hypertension and a higher rate of smoking.                                            Their study suggests that genetic testing should be considered in patients with thoracic artery dissection particularly in individuals with early age of onset before age 50 and no hypertension with the possibility of cascade screening to follow to identify at risk family members before onset of dissection and possible death. Our next paper is a research letter from Seyedeh Zekavat, Pradeep Natarajan and colleagues from Harvard Medical School, Investigating the Genetic Link Between Arterial Stiffness and Atrial Fibrillation. They aimed to investigate whether arterial stiffness is causal for atrial fibrillation using Mendelian randomization to probe genetic causality.                                            They calculated the genetic component of the arterial stiffness index or ASI, a noninvasive measure of arterial stiffness, in over 131,000 individuals in the UK Biobank. They then assessed whether the genetic predictors of ASI defined as the top six independent variance were also associated with atrial fibrillation in over 225,000 participants in the UK Biobank and in over 588,000 individuals from a multi-ethnic GWAS. They found that the ASI genetic risk score was significantly associated with incident atrial fibrillation in both the UK Biobank and the multi-ethnic AF GWAS.                                            The association held true even after adjustment for age, sex, smoking status, prevalent heart failure, prevalent hypertension, prevalent CAD, prevalent hypercholesterolemia, prevalent diabetes, heart rate, alcohol intake and exercise frequency in the UK Biobank participants. Because some people have hypothesized that atrial fibrillation may actually precede and cause arterial stiffness, the team did the reverse Mendelian randomization experiment and tested whether genetic predictors of AF were associated with the arterial stiffness index. They found no association suggesting that AF does not cause arterial stiffness.                                            In summary, this paper provides genetic evidence supporting arterial stiffness as a causal contributor to atrial fibrillation and suggests that future randomized controlled studies would be warrantied to assess whether methods to reduce arterial stiffness could be protective against atrial fibrillation. The next research letter comes from Scott Damrauer, Kara Hardie, Reed Pyeritz and colleagues from the University of Pennsylvania and is entitled FBN1 Coding Variants and Nonsyndromic Aortic Disease. In this study, the authors were interested in characterizing the frequency of variance associated with Marfan syndrome in the general population.                                            They analyzed data from the Penn Medicine BioBank looking at 12 variance in the FBN1 gene all of which have been reported to associate with Marfan syndrome. Of almost 11,000 individuals who underwent exome sequencing, they identified 70 individuals who were carriers of one of the 12 preselected FBN1 variance. These individuals ranged in age from age 28 to 87 years and 56% of them were male. They combed through clinical data from the participant's electronic health records, including office notes, diagnostic tests and imaging studies.                                            Two individuals had a clinical diagnosis of Marfan syndrome while 21 individuals had evidence of cardiovascular phenotypes related to Marfan syndrome including mitral valve disease, dilated sinus of valsalva, dilated ascending aorta, descending thoracic or abdominal aneurysms or dissections or had undergone surgical procedures involving the mitral valve or thoracic aorta. Compared to age and sex matched controls without known or suspected pathogenic FBN1 variance, the FBN1 variant carriers were significantly more likely to have Marfan syndrome related cardiovascular disease.                                            Although the majority of individuals carrying FBN1 variance did not have documented cardiovascular disease in this study, the data were somewhat limited, meaning that some affected individuals could have been missed. Thus, while the penetrance of these variance appears to be variable, the severe consequences of these FBN1 variance observed in some individuals suggests that clinical screening for carries of these variance is important. To round up this month's issue, we have a scientific statement led by Ferhaan Ahmad and Elizabeth McNally on Establishment of Specialized Clinical Cardiovascular Genetics Programs: Recognizing the Need and Meeting Standards.                                            This statement comes from the American Heart Association Council on Genomic and Precision Medicine, the Council on Arteriosclerosis, Thrombosis and Vascular Biology, the Council on Basic Cardiovascular Sciences, the Council on Cardiovascular and Stroke Nursing, the Council on Clinical Cardiology and the Stroke Council. In this statement, the writing group lays out the importance of establishing specialized centers of care for individuals affected by inherited cardiovascular diseases. As cardiovascular genetics as a field continues to grow and as genomic medicine becomes part of practice, it is essential for programs to evolve to include this new knowledge and specialization.                                            There are significant challenges in interpreting genetic test results and in evaluating counseling and managing the care of genetically at risk family members who have inherited pathogenic variance, but not yet shown signs of disease. Establishing specialized programs to combine cardiovascular medicine and genetics expertise is an effective way to allow for the integration of multiple types of clinical and genetic data and to improve diagnosis, prognostication and cascade family testing in affected individuals and their families.                                            Training individuals in genetic cardiology will allow for improved care and management of risk in affected or at risk individuals and potentially pave the way for genotype specific therapy. This important and timely scientific statement outlines current best practices for delivering cardiovascular genetic evaluation and care in both the pediatric and the adult settings with a focus on team member expertise and conditions that most benefit from genetic evaluation.                                            That's all for this month. Thank you as always for listening and come back next month for the next installment of papers in Genomic and Precision Medicine. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Dr Amit Khera:                  Welcome to Circulation On The Run. Our weekly podcast summary and backstage pass to the Journal. I'm Dr Amit Khera, associate editor and digital strategies editor from UT Southwestern Medical Center in Dallas, and I had the distinct privilege of standing in for Dr Carolyn Lam and Greg Hundley this week. Twice a year, we are very fortunate to have some unique podcasts when we don't have circulation issues, and in the past we've met with many fellows in training and heard about some interesting studies that they're doing. Today we have a very special podcast we have not done before, and that is one where we had the opportunity to learn about our Circulation Family of Journals, and more importantly to hear from the dynamic editors in chief of these various journals. I think you're really going to enjoy it, we'll walk through and hear from each one of them, hear about some of the innovative things that are happening, some of the future that they see for their journal in their field, and I really enjoyed it, and I'm sure you will as well. So, without further ado, we'll start with our first editor. Dr Sunil Rao:                      I'm Sunil Rao. I'm an intervention cardiologist at Duke, and I'm the Editor-in-Chief for Circulation Cardiovascular Interventions, which is one of the daughter journals of the Circulation Family. We publish articles really related to the broad spectrum of interventional cardiology, from coronary interventions to peripheral arterial disease, and Endovascular interventions to structural heart disease interventions. We also published review articles in all of those areas, as well as any health policy or outcomes studies that are in that space. Dr Amit Khera:                  Tell us what are some of the innovative things that your journal is doing this year. Dr Sunil Rao:                      We're really excited about two things, one is our extremely successful Assistant Editor program that we launched last year at A.H.A. 2018. This is a program where we have five early career individuals that are within five years of completing their fellowship program who joined the editorial team at Circulation Cardiovascular interventions, and in that role they really learn a lot about the mechanics of how scientific publishing works, they commit to doing manuscript reviews, and receive feedback on improving their peer review process, and even independently handles some manuscripts as well, that are in their areas of interest. This is our way, I think, of encouraging the next generation to stay engaged with science, and with the scientific publishing process. It's been extremely successful. Assistant editors are part of our team for a two year term. So, in 2020, we will be selecting the next class of assistant editors, and after their term is ended, they join our editorial board as editorial board members. So, we're really excited about that, it's been an overall positive experience, for I think everybody involved. The second thing that we're really excited about is that we launched a social media presence for the journal, which it previously did not have. So, we have a very active Circulation Cardiovascular Interventions Twitter handle, I encourage all the listeners to join Twitter if you're not on Twitter, and if you are on Twitter please follow at Cirque intervened. It's " at C.I.R.C.I.N.T.V.". That is the official Twitter handle for our journal. Dave Fishman is our social media editor, and Chadi Alraies is our assistant social media editor, and we're not just tweeting out the articles, and providing summaries when the papers get published, we're holding Twitter journal clubs once a month ,and these have been extremely successful, it's an hour long Twitter journal club where the discussion gets very intense, and there's a lot of back and forth. We try to have the authors on as well, so that they can explain the rationale for their study, some of the challenges that they face when they are doing the study, and hopefully provide some implications for clinical practice, and what the next steps are. That's a way for us to engage our readership, it's almost a form of post publication peer review, which I think is becoming very popular. In addition, remember we don't have a print format of our journals, so this is a way to get the readership more engaged with the Web site, and to come to our website and learn what elsewhere publishing, and how they can get involve with the Journal as well, both as authors who submit their work, or if they want a peer review for us, please contact us and let us know. Dr Amit Khera:                  I really love hearing about the Twitter journal club, I know that they are well received, and certainly getting a lot of traction. Tell us about what initiatives or topics you're most excited about this year, and maybe some things that are coming later in the year. Dr Sunil Rao:                      We're really excited about the big areas in interventional cardiology, which are coronary physiology, we've published quite a few papers on looking at different physiological parameters, and how they can drive the appropriate use of PCI and how that affects outcomes. I think that's going to continue to be a huge topic over the next year, Certainly such a heart disease has exploded, and with the data on low risk patients undergoing TAVR, and having really good outcomes, we're seeing a lot more submissions in the low risk TAVR space, the other area that's really exploding right now is Mitral and Tricuspid Valve Interventions, one of the areas that I think has seen a tremendous amount of device innovation. So, we're seeing a lot of submissions from really high quality papers in that space, but I think it's also important to note, that unlike previous iterations of the Journal, we're actually having a review article, we're trying to have a review article every month on a major area that is burgeoning, so that the readership can understand the overall lay of the land, with respect to evidence, how that guy's clinical practice, and what's coming next. So, we've published quite a few review articles already, and there are more to come, and I think that's a really important way for the readership to keep current with what's going on in Interventional Cardiology. Dr Amit Khera:                  What about the advancing aspects of your subspecialty? There's so much going on in interventional cardiology, it's a bit dizzying, just tell us a little bit about some of the ways that your journal's helping advance that mission, not just now but perhaps in the future. Dr Sunil Rao:                      I think one of the challenges that we have at Interventional Cardiology, and maybe this is true across Cardiology, is that the evidence is developed very rapidly, and oftentimes it almost seems like the field is lurching back and forth in certain areas, a prime example of that is the drug coated balloon controversy for Peripheral Interventions. The Journal Of The American Heart Association published a meta-analysis, showing that there may be an association between the use of these devices and increased mortality, that has led to a lot of discussion in the interventional community, and quite frankly I think there's a fair amount of confusion out there about whether we should be using these devices, should we put a moratorium on these devices, is the signal real, if it is, what's the mechanism of death. So, a lot of conversation around that, in fact, it's led to what's going to be a focused FDA meeting in June, specifically on the drug coated balloon controversy. Where I see our journal playing a role is really in trying to, not only publish the latest science, which is rigorous in the field for controversial topics such as this, but also to help provide some context for that science, and I think our integrated strategy of original science review articles, and social media really helps us to communicate with the readership, and with the Interventional Cardiology community writ large, meaning not just physicians, but also Cath lab staff, nurses, noninvasive cardiologists who obviously have patients who are undergoing interventions, and even policymakers, to keep them abreast of what's going on, so that they can have the same level or base of knowledge, so that the conversation is on a level playing field. Dr Amit Khera:                  Okay, well you heard it from Dr Sunil Rao. Thank you for your time. Dr Kiran Musunuru:        I'm Kiran Musunuru, I'm the outgoing Editor-in-Chief of Circulation Genomic and Precision Medicine. Let me start by saying a little bit about the content of the journal, it considers all types of articles related to, as the name implies, Genomic and Precision Medicine, and more specifically, Clinical Genetics, the molecular basis of complex cardiovascular disorders, considered at a variety of levels, that can include a lot of different, what we would call Omics Techniques, from Genomics to Transcriptomics, Proteomics, Metabolomics, Metagenomics, and, so forth. It also deals with big data applications, that includes Electronic Health Record Data, Patient generated data combined with any of the things I've already mentioned, Genome Wide Association Studies, Pharmacogenomics, Gene Therapy, Therapeutic Gene Editing, Systems Biology. So, it's a pretty comprehensive look at all the various topics that would fall under the rubric of Genomic and Precision Medicine. Dr Amit Khera:                  Now, Dr Musunuru, you mentioned the outgoing Editor-in-Chief, let's introduce the incoming Editor-in-Chief, Thatcher Christopherson Semsarian. Dr Chris Semsarian:         I'm the incoming Editor-in-Chief. My name is Chris Semsarian, I'm a cardiologist at the Royal Prince Alfred Hospital in Sydney, Australia. Dr Amit Khera:                  What are some of the innovations you and the Journal are doing this year, or, what are some of the things you see coming in the future? Dr Kiran Musunuru:        Something I'm very excited about, is that we are just starting a pilot project with the American Heart Association's Institute for Precision Cardiovascular Medicine. The institute has a very nice platform called the Precision Medicine platform, and, in brainstorming last year, we realized there was a very nice opportunity to try to create a new type of journal article. There's also a big move in science nowadays to improve transparency, and rigor, and reproducibility, especially in science. The idea being that ideally other investigators should be able to take one team's work, and be able to run through the entire analytical process, and reproduce the original findings, and perhaps even find ways to improve upon those original findings, and, so we realized working with the institute's Precision Medicine Platform, we had the opportunity to actually make a new type of article, we think of, as the paper of tomorrow, a virtual article. The idea would be, that we would have primary data on the Precision Medicine Platform, the analytical tools used to process the data would also be on the Precision Medicine Platform, the analytical plan, in the form of a so-called Jupiter notebook, that basically takes people step by step through exactly which tools were used in which order, in which way, with which parameters, would be on the Precision Medicine Platform, and then there would be some verbal explanation, some background, to explain the context of these analysis, and to really put it into perspective, as how it fits into the body of literature, and so the idea would be, this would live on the Precision Map Platform in a virtual format, and then anyone else who is interested in this work could come, and actually directly interact with the data, and the tools, and the analytical plan, and could actually rerun the entire papers work from scratch, thus reproducing it, and then could actually tweak the analytical plan, or install tools of their own, and be able to build upon the work that had already been done. It's a very different way of thinking about journal articles, more as living entities rather than static work that just lives on a page, and is there as reported, and then never has an opportunity to be fully produced or improved upon. Dr Amit Khera:                  There's so much happening in the space of genomics, and obviously, we hear the word "Precision Medicine" so commonly. Tell us a bit about how your journal in specific is advancing the mission of your area. Dr Kiran Musunuru:        I'll say a little bit, and then maybe turn it over to Chris, give his perspective as the incoming Editor-in-Chief. I think it's a vibrant field, but it's also a very new field, it's evolving rapidly, and I think the Journal has a very important role to play, and not only reporting the results that are coming out of studies in this field, but actually having a role to play in helping to shape the field, helping to define the field, it's very exciting, it's very much in rapid evolution. Just ten years ago or so, when the Journal first started, we were just starting to see the first Genome Wide Association studies, and now we've gone so far beyond that.                                                 Now, again, we're talking about these large bio banks, we're talking about Precision Medicine, we're talking about applying this information in health care, we're talking about combining all of these various streams of data and many levels to be able to do studies, that are, I would even say, exponentially advanced beyond what we able to do just ten years ago, and so, it's very exciting times for the journal, then maybe I can ask Chris to share his thoughts on that. Dr Chris Semsarian:         Yeah Kiran, I mean, it's a great honor system to follow in your amazing footsteps, and what you've done for the Journal, and as the incoming Editor-in-Chief, I really want to sort of try, and build on the platform that you've established over the last few years, and really, one of the areas that I'm particularly interested in is the area of Translation of Genomic Findings. I mean, ultimately what we do in our lives, as clinicians, is to help patients improve diagnosis, to improve the treatment of these patients, and to be able to do studies with very basic understanding of how our genomes work, and how Narcotic Genes interact, and translating those findings into these improved diagnostic approaches, and even in guiding management is really exciting, I think, in terms of clinical medicine, and improving patient care as we look ahead. I really want to be able to continue to publish really, state of the art, novel, innovative, research areas, that you've already covered, Kiran, which would lead to better care of our patients, who are ultimately the beneficiaries of this type of amazing work.                                                 So, I'm really excited looking at the Journal, it's a tremendous area of interest and research, where there's twenty-two thousand genes approximately now genomes, and we really don't understand most of them in terms of their intricate function, and I figured it's a great time ahead, in terms of Precision Medicine. Dr Amit Khera:                  Okay, well, that was Dr Kiran Musunuru, and Christopher Semsarian, we appreciate both of your time today for Circulation on the Run. Dr Paul Wang:                   I'm Dr Paul Wang, I'm the Editor-in-Chief of Circulation Arrhythmia and Electrophysiology. Our Journal covers really the expanse of our field, going from basic mechanisms of arrhythmias, so very basic science work, to really clinical practice, clinical outcomes, to population based studies, and genetic based considerations in our field. So, we really feel we encompass the entire range, and there really isn't any topic within our area, that we don't feel is outside our realm. Dr Amit Khera:                  I know there's so many innovative things you're doing, Dr Wang, with your journal. Why don't you tell us a little bit about your plans for this year. Dr Paul Wang:                   We've been excited; our team has been at the Journal for two years now, and we focused on a number of different areas. So, I think one of our biggest advances, and we've tried to be more responsive to the authors, so we've really reduced the time to first decision very substantially, from over twenty days, to ten days or less, I think we hit a record of 7.8 days in the journal. So, really, we hope we're more responsive, we've involved the editorial board, we've substantially expanded it, so that more of our reviews of greater proportion going to our editorial board, which is a really fabulous, internationally recognized group, with really high quality reviews, so we've been very pleased, with both a level of science that we've received, as well as the level of the reviews that we have. One other area is, we really want to make sure that the reviewers, who do much of the heavy lifting, in addition to our editors for The Journal, and so we've established a new Reviewer Recognition Award System, they can be designated as silver, gold or platinum, and we've reached out to department chairs, or their deans, and recognizing that they won this prestigious award for their performance, and great work with the Journal, so there are a number of different things that, in fact, we think we've made some advances in, the other areas are really that of extending our reach, and so, one of the things we concentrated on, initially with the adding of podcasts, so we do that monthly.                                                 All the articles are now available in review, and then what we're starting at our new initiatives is, we'll be starting a Twitter Journal Club. I've been recording at least two of our articles, as the interview with the authors, and then we're going to be having a journal club, in which we will have the opportunity for people around the world to comment, and have a discussion that will really be exciting, we think. So, there are a number of other areas that we're thinking about, in terms of that kind of work. Dr Amit Khera:                  The field of Electrophysiology seems to be changing by the day, maybe you can tell us a little bit, about how the journal is advancing the mission of the field of electrophysiology. Dr Paul Wang:                   So, one of the things that we focused on is the role the Journal can play, in terms of connecting with other elements of our field, and one of the ways that we've really concentrated on is, in particular, working closely with the American Heart Association, and its committees. We're related to a number of committees, but particularly, there is a committee on Electrocardiography, Electrophysiology, part of the Clinical Cardiology Council, and so, we work very closely with that group, and, in fact, we've invited that group to create proposals for a number of review articles, state-of-the-art reviews, that we hope will come out in the next year or so. The ways in which we can tie together our committees to AHA overall, I think, is really the direction we're looking for our journal, and we feel we can play a very novel, and innovative role in that regard. We, for example, also reached out to the American Heart Association funded researchers in our area, and invited them to participate in the journal, participate in our committees, become fellows or FAHA's of the American Heart Association, so we really want to create this family, a real community, and sense of community, that we hope will stem from the Journal. So, we're very excited about the future, and what we might be able to achieve together. Dr Amit Khera:                  Thank you so much, Dr Paul Wang for your time today, and we appreciate your insights on Circulation, Arrhythmia and Electrophysiology. Dr Nancy Sweitzer:          Hi, I'm Nancy Sweitzer. I'm the Editor-in-Chief of the Journal Circulation Heart Failure. At Circ Heart Failure, we deal with all things related to heart failure. Heart failure is an expanding specialty, relatively new subspecialty in cardiology, and we're very interested in the physiology, and mechanisms of heart failure, as well as treatments of heart failure, and the innovative evolution of the specialty which includes Advanced Hemodynamics, Mechanical Circulatory Support, and transplant as therapies, as well as all Implanted Device Therapies, and new, and Innovative Pharmacologic, and Gene Therapies as well. Dr Amit Khera:                  Tell us a bit about initiatives, or features in Circulation Heart Failure, that you're planning on tackling not only this year, but into the future. Dr Nancy Sweitzer:          The effort we're most excited about at Circulation Heart Failure has been ongoing now for a little over a year, but continues, and is really focused on the emerging scientists in the Heart Failure Space; we call it our "Featured Emerging Investigator Spotlight", and this spotlight focuses on authors of manuscripts, who are within ten years of their terminal training, and can take full responsibility for the content of a manuscript. When we publish a featured emerging investigator article, which we've done more than half of the months since launching the feature in late 2017, we schedule a Twitter Journal Club with that author, where we participate, over the course of several hours, in pretty intensive conversation, about not only the science, but career development in Heart Failure Space, the importance of mentoring, and sponsorship obstacles that people are facing in development as physician scientists or scientists, and insights they may have into fostering success in the Heart Failure Space. This has been a great feature, we launched it because we feel that the emerging scientists, in the Heart Failure Space, need a virtual community in those critical years, before you have a lot of resources to start traveling, and setting up a network that's based on personal interaction, and we felt that, the modern era of social media was perfect for this. We found our emerging investigators are getting to know one another, they participate in one another's Journal Clubs, the Journal Clubs are incredibly fun, and interactive and we're getting a lot of Twitter engagement from the Heart Failure Community, there's a lot of "Twitteratti" in Heart Failure that really are engaged, and engaged with the Journal, which has really been fun for all of us, I think, so that's the thing we're most excited about. Dr Amit Khera:                  It's really wonderful to hear how you're spotlighting authors in creative ways. Tell us a bit about how your journal is advancing the mission of Heart Failure and Transplantation. Dr Nancy Sweitzer:          I see the journal as central to advancement of the subspecialty, as I mentioned earlier, Heart Failure is a relatively young subspecialty in the United States, we received a CGMC designation as a subspecialty just in 2008, just eleven years ago, and it's been a board certifiable subspecialty only since 2014. So, we're very young, and I think really developing into our own. We've seen tremendous growth in the number of people seeking subspecialty training in Advanced Heart Failure and Transplant Cardiology, and we are really enjoying helping the Journal evolve with the specialty, as it evolves, and that's happening very actively right now. So, I think what Heart Failure is in 2019 is different than what it was just five years ago in 2014. We're doing a lot more ,as I mentioned, Complex Chemo Dynamic Thinking, thinking about the path of physiology in our patients, and how we can target that effectively, not only with existing therapies, but with strategies, and, as I mentioned, the burgeoning growth of Mechanical Circulatory Support, and support devices, which the field has embraced quite actively, and The Journal is increasingly publishing content in these spaces, as well as the spaces of Advanced Heart Failure, but, I guess also, we're interested in every aspect of Heart Failure, from Complex Multidisciplinary Care Management, to Palliative Care, to the interaction of the heart with other organ systems, and Heart Failure such as the brain, we have a paper on Cognitive Function Abnormalities, and Heart Failure in this month's issue. So, the interaction with the brain, the kidney, the liver, many other organs, that are affected when the heart becomes quite ill with Advanced Heart Disease. So, basically we're interested in everything that touches Heart Failure Development Care, and treatment of patients with Heart Failure, and particularly we're interested in the newest and latest. We love publishing, and some of our highest impact papers in the last couple years have been new therapies, just being tested for the first time in patients with heart failure. Small studies that may not have large impact in terms of heart outcomes, but where we're learning about the pathophysiology of the disease, and new treatments, that's really exciting to us. We've published a couple of methods papers in the last year, really innovative models. One describing a model of pacing in mice, which has been a really challenging thing to do in Heart Failure, but several groups have now developed Tachycardia induced Cardiomyopathy models in mice, which is important for rapid discovery work, because mice have such a short reproductive span, and can be genetically altered, and then a recent publication on the methods paper, looking at a new initiative by the FDA, to potentially approve therapies based on patient reported outcomes, rather than just heart mortality and morbidity outcomes, so we're really excited about the innovations, and the Heart Failure Space, the work that describes where we're going as a field and as a profession. You'll see some features coming up in the journal, from opinion leaders across the globe on where this specialty sits in 2019, and where we, as the leaders in the field, can guide it as we move into our next decade, and I think that some of the most exciting work the journals doing. Dr Amit Khera:                  Thank you, Dr Sweitzer. We really appreciate your time today for the podcast, and your insights on the Journal. Dr Robert Gropler:          Good afternoon, I'm Rob Gropler. I'm the Editor-in-Chief of Circulation Cardiovascular Imaging. It's one of the journals within the family of Circulation Journals, and our focus is really on being the most influential source of leading edge imaging sciences, as it relates to transforming cardiovascular care, so what that means is, that we're interested in all imaging studies that are applied to the care of the cardiovascular patient, and although our primary focus is really on clinicians, and researchers, but we also want to expand our viewership, if you will, to anyone who is interested in how imaging is used to understand Cardiovascular Medicine, and to treat patients with Cardiovascular Disease. So, we are edged in all forms of imaging, this can be from MR, to echo, to nuclear, to CPT, to optical imaging, it involves all types of disease, ranging from Congenital Heart Disease, up to diseases in the elderly, it also involves not just it is in humans, but also understanding disease in the preclinical space, particularly as it helps us understand new technologies that may ultimately reach human use, either for investigational purposes, or ultimately, to be used in the treatment of a patient with Cardiovascular Disease. Dr Amit Khera:                  What are some innovative things you and the Journal are planning for this year? Dr Robert Gropler:          We're doing quite a few things. One of the first things we did, as you know, were relatively new, where we've only been an editorial team, if you will, for one year. One of the major efforts has been to increase our presence, in terms of digital media strategies, across the board. And so, this meant expand our Twitter presence, if you will. It also meant increasing our offerings in that digital space by, for example, having a journal club, what we would do is on a every other month basis, discuss a paper we published that's of significant interest via Twitter. And it would involve the authors, the associate editors who actually manage that study, as well as the editorialist who wrote about that study, and it leads to very unique insights into how that paper is being viewed by the scientific community at large, and also potentially how that information will be implemented in terms of transforming clinical care.                                                 We've added what we call a teaching file. If you think about imagers, imagers learn by seeing images. And the more they can see images, put them in the context of clinical cases, the more they understand what an image means when they see it. So, what we do now is we accept a large number of what we call imaging cases. These are specific unique cases that have a history, and then a short write up about them.                                                 And those are gathered each month, but then they're downloaded into a file. And then, anyone with access to the Journal can then look at, use to learn from, to potentially use for talks to enhance their own education the education of others. And we have found that to be, again, another offering that our readers particularly like. Dr Amit Khera:                  And how do you see Circulation Cardiovascular Imaging advancing the mission of imaging, which seems to be ever-expanding, and ever-growing? Dr Robert Gropler:          We're really in the education business. And what that means is that we're educating at a multi-scale level. Just educating a practitioner on what technology can do, how it's helping cardiovascular medicine, yes, that's important. But what we're also doing, is we're educating the scientists as to here as some of the new findings that were coming out because of imaging. And then that, in turn, will help direct them or signal them as to where is the science leading them, and what should be their next steps?                                                 We're also educating the general public as to what can imaging do, and how does imaging change cardiovascular medicine for the better, and what they can expect from that. And we're also educating the regulatory bodies, if you will, that determine what imaging can be done in the clinical environment and so on, and the importance of these imaging techniques.                                                 So number one, I think we always have to maintain that focus, as to that's our goal. Now, that being said, I think the question becomes how do you convey that concept? And where we have to continually evolve.                                                 And I think they were very smart years ago to make it a digital-only journal, as opposed to combined print and digital. So, I think that was actually very savvy. But the digital net component now has to expand. And that means our offerings have to reflect not just that people learn in different ways, that is, we have to have not just, if you will, a didactic or print equivalent component of a paper. But it also should be audio-based, such as this podcast. But they also need to be varied as in terms of the types of offerings, and their brevity or length, if you will. Dr Amit Khera:                  Thank you, Dr Robert Gropler, the Editor-in-Chief of Circulation Imaging. We really appreciate your time today. Dr Robert Gropler:          Thank you very much. You have a great day. Dr Amit Khera:                  Well, I'm sure you enjoyed this as I did. We really got incredible insight from the Editors-in-Chief of our Circulation family of journals. We learned so much about the broad array of subspecialties that they cover, and all the exciting and innovative things they're doing to really advance the missions of their fields, and also for the authors and for science.                                                 Well, again, I'm Amit Khera, associate editor from UT Southwestern, Digital Strategies editor for Circulation. And next week, you'll have your usual hosts, Carolyn Lam and Greg Hundley. Dr Carolyn Lam:                This program is copyright American Heart Association 2019.  

Jane Ferguson:  Hi, everyone. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. It's May 2019, and this is episode 28. So let's see what papers we have in the journal this month.                              First up, a paper from Mengyao Yu, Nabila Bouatia-Naji and colleagues from the Inserm Cardiovascular Research Center in Paris, entitled GWAS-Driven Gene-set Analyses, Genetic and Functional Follow-Up Suggest Glis1 as a Susceptibility Gene for Mitral Valve Prolapse.                              In this paper, they set out to characterize the genetic contributions to mitral valve prolapse, or MVP, to better understand the biological mechanisms underlying disease. They applied the gene-set enrichment analysis for QWAS tool and the pathway enrichment tool DEPICT to existing GWAS for MVP in a French sample to identify gene sets associated with MVP. They find significant enrichment of genes involved in pathways of relevance to valve biology and enrichment for gene expression in tissues of relevance to cardiovascular disease.                              They zeroed in a Glis family zinc finger gene Glis1 with consistently strong pattern of evidence across the GWAS enrichment and transcription analyses. They replicated the association between Glis1 and MVP in a UK biobank sample. They found that Glis1 is expressed in valvular cells during embryonic development in mice, but is mostly absent at later times. They targeted two Glis1 orthologs in zebrafish and found that knockdown of Glis1 B was associated with a significant increase in the incidence of severe atrioventricular regurgitation. These data highlight Glis1 as a potential regulator of cardiac valve development with relevance for risk of mitral valve prolapse.                              Next up is a paper from Gina Peloso, Akihiro Namuro, Sek Kathiresan and colleagues from Boston University, Kanazawa University, and Mass General Hospital. In their paper, Rare Protein Truncating Variance in APOB, Lower LDL-C, and Protection Against Coronary Heart Disease, the team was interested in understanding whether protein truncating variance in APOB underlying familial hypobetalipoproteinemia confer any protection against coronary heart disease.                              They sequenced the APOB gene in 29 Japanese families with hypobetalipoproteinemia as well as in over 57,000 individuals, some with early onset CHD and some without CHD. They found that presence of an APOB truncating variant was associated with lower LDL cholesterol and lower triglycerides, and also with significantly lower risk for coronary heart disease. This study confirms that variance in APOB, leading to reduced LDL and triglycerides are also protective against coronary heart disease. :                            The next paper entitled Mortality Risk Associated with Truncating Founder Mutations in Titin comes to us from Mark Jansen, Dennis Dooijes, and colleagues from University Medical Center Utrecht. They analyzed the effect of titin truncating variance on mortality in Dutch families. Titin truncating variants are associated with dilated cardiomyopathy, but have a very variable penetrance.                              In this study, the authors looked at three titin truncating variants, established to be founder mutations, and traced the pedigrees back to 18th century ancestors. They looked at 61 individuals on the transmission line and 360 of their first-degree relatives. They find no evidence for excess mortality in variant carriers overall. However, when they restrict it to individuals over 60 years of age, they did find a significant difference in mortality, which was also observed in individuals born after 1965. What these data tell us is that these titin truncating variants have a relatively mild phenotype with effects on mortality only manifesting later in life in many carriers. Given increases in life expectancy over the past several decades, the prevalence of morbidity and mortality attributable to titin truncating variants may increase. Genetic screening may identify genotype-positive, phenotype-negative individuals who would benefit from preventative interventions.                              Continuing on the theme of genetic variance, we have a paper from John Giudicessi, Michael Ackerman, and colleagues from the Mayo Clinic, Assessment and Validation of a Phenotype-Enhanced Variant Classification Framework to Promote or Demote RYR2 Missense Variants of Uncertain Significance. In this paper, they aim to find a better way to classify variants of unknown significance, of VUS, in the RYR2 gene. Variants in this gene are commonly associated with catecholaminergic polymorphic ventricular tachycardia, or CPVT.                              They examined 72 distinct variants in 84 Mayo Clinic cases and find that 48% were classified as VUS under ACMG guidelines. The rate was similar in a second sample from the Netherlands, with 42% of variants originally classified as VUS. They developed a diagnostic scorecard to incorporate a pretest clinical probability of CPVT, which included various clinical criteria, including symptoms and stress test results. Application of the phenotype enhanced ACMG criteria brought the VUS rate down to 7% in Mayo Clinic and 9% in the Dutch samples. The majority of VUS were reclassified as likely pathogenic.                              This study highlights how incorporation of disease-specific phenotype information can help to improve variant classification and reduce the ambiguity of reporting variants of unknown significance.                              We also have a number of research letters in the journal this month. From Karine Ngoyen, Gilbert Habib, and coauthors from Marseilles, we have a paper entitled Whole Exome Sequencing Reveals a Large Genetic Heterogeneity and Revisits the Causes of Hypertrophic Cardiomyopathy, Experience of a Multicentric study of 200 French Patients. In this study, they examined the genetic contributions to hypertrophic cardiomyopathy, or HCM, in 200 individuals as part of the HYPERGEN study and compared the benefits of whole exome sequencing compared with targeted sequencing of candidates' sarcomeric genes. All subjects had HCM documented by echocardiography.                              In the whole exome sequencing data, they first looked for mutations within 167 genes known to be involved in cardiomyopathies or other hereditary diseases. Of these 167 virtual panel genes, they find variants in 101 genes. Following whole exome sequencing, over 87% of the patients had an identified pathogenic, or likely pathogenic, mutation compared with only 35% of patients who only had targeted sequencing of sarcomeric genes.                              This highlights the generic heterogeneity of HCM and suggests that whole exome sequencing has utility in identifying variants not covered by sarcomeric gene panels.                              The next letter is from Wouter Te Rijdt, Martin [Vandenberg] and colleagues from University Medical Center Groningen and states that [dissynchronopathy] can be a manifestation of heritable cardiomyopathy. They hypothesized that left bundle branch block, also designated as dissynchronopathy, may be a manifestation of familial cardiomyopathy.                              They analyzed patients from a database of cardiac resynchronization therapy and identified super-responders whose left ventricular dysfunction was normalized by therapy. They carried out targeted sequencing in 60 known cardiomyopathy genes in 16 of these super-responder individuals and identified several variants, including a pathogenic variant in troponin T in one individual and variants of unknown significance in nine individuals. Pedigree analysis identified multiple family members with dilated cardiomyopathy.                              This study highlights that dissynchronopathy can be a manifestation of DCM, but that affected individuals may still benefit from cardiac resynchronization therapy.                              The next letter entitled Targeted Long-Read RNA Sequencing Demonstrates Transcriptional Diversity Driven by Splice-Site Variation in MYBPC3 comes from Alexandra Dainis, Euan Ashley, and colleagues from Stanford University. They set out to understand whether transcriptome sequencing could improve the diagnostic yield over genome sequencing in patients with hypertrophic cardiomyopathy. In particular, they hypothesized that long-read sequencing would allow for identification of alternative splicing linked to disease variance. They used long-read RNA and DNA sequencing to target the MYBPC3 gene in an individual with severe HCM who carried a putative splice-site altering variant in the gene. They were able to obtain heart tissue for sequencing and included several HCM and control subjects in addition to the patient with the MYBPC3 variant.                              They identified several novel isoforms that were only present in the patient sample, as well as some additional isoforms, including retained introns, extended exons, and an additional cryptic exon, which would not have been predicted based on the DNA variant. While the effects on protein function is not known, the transcripts are predicted to be translated.                              This analysis highlights the effect of a rare variant on transcription of MYBPC3 and provides additional evidence to link the variant to disease. This is a really nice approach, which could be used to probe causality and mechanisms, not only for cardiovascular disease, but for other rare variants in many disease settings.                              We finish with a perspective piece from Nosheen Reza, Anjali Owens, and coauthors from the University of Pennsylvania entitled Good Intentions Gone Bad, The Dangers of Sponsored Personalized Genomics. They present a case of a 23-year-old woman who presented for genetic counseling and evaluation after discovering she carried a likely pathogenic MYH7 variant associated with cardiomyopathy. She had no significant medical history, but had participated in employer-sponsored genetic testing motivated to identify potential variants related to cancer given a family history of cancer.                              After receiving her results, she experienced considerable anxiety and stopped exercising out of fear of cardiac complications. She visited an ER after experiencing chest pain, something she had not experienced previously. There was no appropriate counseling available at her institution for her genetic test results, leading her to seek out the additional counseling. Thus, while she was initially motivated to complete genetic testing because her employer offered it free of change, she ended up incurring costs related to the followup evaluation and counseling. Ultimately, she had no significant clinical findings. Although the variant had been listed as likely pathogenic, other sources consider it to be of unknown significance.                              This story highlights the psychological and financial impact that genetic testing can have on individuals, particularly when carried out without any pretest counseling or accessible post-test support when variants are identified.                              Despite the considerable promise of personalized medicine, there are many complexities to be considered, particularly with direct-to-consumer testing and employer-sponsored testing. This perspective highlights the ethical considerations and urges caution to maintain the best interests of patients.                              That's all for this month. Thanks for listening. I look forward to bringing you more next month.                              This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hello and welcome to Getting Personal: Omics of the Heart, your podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University Medical Center, and this is episode 27 from April 2019.                                            This month, I talk to Riyaz Patel, the first author on not one, but two articles published this issue, presenting analyses from the GENIUS-CHD consortium. But before we get to the interview, let's review what else was published this month.                                            First up, we have a paper from Tamiel Turley, Timothy Olson and colleagues from the Mayo Clinic, entitled Rare Missense Variants in TLN1 Are Associated With Familial and Sporadic Spontaneous Coronary Artery Dissection. In this study, the authors were interested in identifying novel susceptibility genes for spontaneous coronary artery dissection or SCAD, which predominantly affects young women who appeared otherwise healthy. They conducted whole exome sequencing in a family with three affected family members and found a rare missense variant in the TLN1, or talin 1, gene. This gene encodes the talin protein which is part of the integrin adhesion complex linking the actin cytoskeleton to the extracellular matrix. This gene and protein is highly expressed in coronary arteries. They went on to sequence additional sporadic cases of SCAD, and they found additional talin 1 variants in these individuals. While there was evidence for incomplete penetrance, these data implicate TLN1 as a disease-associated gene in both familial and sporadic SCAD.                                            The next paper comes from Miroslaw Lech, Jane Burns, and colleagues from UCSD School of Medicine and Momenta Pharmaceuticals and is entitled Circulating Markers of Inflammation Persist In Children And Adults With Giant Aneurysms After Kawasaki Disease. Kawasaki disease is the most common cause of acquired pediatric heart disease, but disease progression can vary a lot, and it's likely modulated by complex gene-environment interactions. Coronary artery aneurysms occur in about 25% of untreated patients, but early treatment with intravenous immunoglobulin or aspirin reduces the risk for these aneurysms to 5%, suggesting an important role for inflammation. In this study, the authors applied shotgun proteomics, transcriptomics, and glycomics on eight pediatric Kawasaki disease patients at the acute, subacute, and convalescent time points. They identified inflammatory profiles characterizing acute disease which resolved during the subacute and convalescent time points, except for in the patients who went on to develop giant coronary artery aneurysms. They went on to carry out proteomics on nine Kawasaki disease adults with giant coronary artery aneurysms and matched healthy controls, and they confirmed the inflammatory profiles in the adult samples.                                            In particular, calprotectin, which is composed of S100A8 and S100A9, was elevated in the plasma of patients with CAA, an association they confirmed in additional samples of pediatric and adult Kawasaki disease patients and healthy controls. These data suggest that calprotectin may serve as a biomarker of ongoing inflammation in Kawasaki disease patients following acute illness, and may be able to identify individuals at increased risk of aneurysms.                                            Next up, we have a research letter, Heart BioPortal: An Internet-of-Omics for Human Cardiovascular Disease Data, from Bohdan Khomtchouk, Tim Assimes, and colleagues from Stanford University. They had noticed that, in contrast to the field of cancer research, there were no open access platforms for cardiovascular disease data that offered users the ability to visualize and explore high quality data. They set out to fix this and developed the Heart BioPortal, which is accessible at www.heartbioportal.com. This portal allows the user to integrate existing CDD related omics data sets in real time and provides intuitive visualization and analyses in addition to data downloads. The primary goals are to support gene, disease, or variant-specific request, and to visualize the search results in a multi-omics context.                                            They currently collate gene expression, genetic association, and ancestry allele frequency information for over 23,000 human genes and almost 6,000 variants across 12 broadly defined cardiovascular diseases spanning 199 different research studies. And this is just the start, they're hoping to add more studies, more data, and functionality for querying CDD drug targets, along with lots more. This is a really great resource which will no doubt be of real value to the community. I urge you to go online, check it out, put in your favorite gene, and see what you find.                                            Riyaz Patel, Folkert Asselbergs, and many, many collaborators published Subsequent Event Risk in Individuals With Established Coronary Heart Disease: Design and Rationale of the GENIUS-CHD Consortium and Association of Chromosome 9p21 with Subsequent Coronary Heart Disease Events: A GENIUS-CHD Study Of Individual Participant Data. These papers present the design of the genetics of subsequent coronary heart disease, or GENIUS-CHD consortium, which was established to facilitate discovery and validation of genetic variants and biomarkers for risk of subsequent CHD events in individuals with established CHD. The consortium currently includes 57 studies from 18 countries, recruiting over 185,000 participants with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. All studies collected biological samples and followed up study participants prospectively for subsequent events. Enrollment into the individual studies took place between 1985 to the present day, and the duration of follow-up ranges from nine months to 15 years. Participants have mostly European ancestry, are more likely to be male, and were recruited between 40 to 75 years of age.                                            In their first analysis using these data, they investigated whether the established 9p21 locus associated with subsequent events in individuals with established coronary heart disease. Confirming previous smaller studies, they showed that while genotype at 9p21 is associated with coronary disease when compared to healthy controls, 9p21 genotype is not associated with a risk of future events in people who already have coronary disease. Dr. Patel joins me to tell me more about the GENIUS-CHD consortium and the analyses described in these papers.                                            Today, I'm joined by Dr. Riyaz Patel, who's an associate professor at University College London and a cardiologist at the Barts Heart Centre in London. Dr. Patel, thank you so much for joining me. Dr. Riyaz Patel:                Pleasure to be on, thanks. Jane Ferguson:                So, as we're going to discuss, you are the lead author on two back-to-back publications that were published in Circ Gen this month exploring genetic predictors of coronary heart disease as part of the GENIUS-CHD consortium. Before we delve fully into them, could you tell us a little bit about your background and how you got into this research field? Dr. Riyaz Patel:                Yes. I'm an academic cardiologist, as you know, and I first got into genetics of coronary disease about 12-13 years ago, now, around the time that genome wide association studies were about to take off, or were taking off. I studied, I worked at Emory University, in fact, in Atlanta, in the US. We had a very big cohort of patients who had coronary disease, who were undergoing coronary angiography. At that time, we were doing quite a lot of genetic association studies and biomarker work in patients with heart disease. One of the key problems we often encountered was sort of looking for replication cohorts and trying to do things at a bigger scale than what we had available. So that kind of really was the initial driver for trying to bring together a bigger collaboration to take that sort of work to the next level. Jane Ferguson:                It sounds like you've got valuable expertise, because looking at the author list for these papers, I think it's one of the longest author lists I've ever seen. It's a huge endeavor. I'd love to hear more about how that got started and how you managed to build this consortium, and you know, and tell us what the consortium actually is. Dr. Riyaz Patel:                Yeah, it's been a labor of love. And essentially, I started when I returned back to the UK and we were looking to develop this further. We had already collaborated with several colleagues in the US and abroad from my time at Emory. So, we pulled together a small group of people who we were already working together with and then we did predicts of systematic searches of literature to identify cohorts who were also doing similar things. Again, investigating people with heart disease and looking at subsequent event risk. So, we did that and then we systematically approached, very much, as many people as we could find and over the course of the last, maybe 3 or 4 years, we've brought together a small community of collaborators around the world, and as you rightly said, it's a very long list. In total, we're counting around 180 or so investigators. But, in a way, that also speaks to how this consortium is not just a collection of studies. It is a collection of people and a lot of expertise was brought to the table because of that. People have been thinking about these questions for many, many years and this platform essentially is an opportunity for everyone to share that knowledge. Dr. Riyaz Patel:                So that's kind of how the consortium started and is being pulled together. We operate on a sort of loose memorandum of understanding where every member of the consortium is free to participate in studies as they wish. We run analysis in a federated way which means that [inaudible 00:10:50] scripts are shared and people standardize their data and then they run analyses locally and they only share summary level data so that obviously overcomes the big governance hurdle. So, that's pretty much how the consortium works at moment. Jane Ferguson:                Yeah. I'm sure there was probably a lot of challenges along the way in figuring this out and getting scripts that work for everybody, dealing with all the people, so how do you do this? Do you have regular phone calls with 180 people on it? Do you have lots and lots of emails? Dr. Riyaz Patel:                (laughs) Jane Ferguson:                How's it actually working? Dr. Riyaz Patel:                So, we have a steering committee which is represented by at least one person from each study. So, that limits the number of people down to about, a more manageable number, about 50 or 60. And we do have regular teleconferences, particularly in the early days when we were still pulling everything together. Now, we try and meet at least once a year, if not twice at year at the major conferences, at the European Site of Cardiology and one of the big American meetings, ACC or AHA, so that's usually a good face to face meeting that we have with everyone and then as with all consortia, we have regular email lists and contact through that means. Jane Ferguson:                So, now that you've got everybody together, you have over 185,000 participants as part of this from 18 different countries. So, how have you been able to use all of these different data and harmonize the different phenotypes and sort of put everything together to actually run the analyses. Dr. Riyaz Patel:                The way we started off is by asking everyone to share almost an inventory of what they have collected. We then sought to try and standardize all of the core variables: age, sex, smoking and so forth. Once we were happy about the key variables had been standardized, units were the same and so forth, we then created, effectively a GENIUS-CHD data set that each cohort had curated. So, this was the main way of harmonizing the data set. Now, obviously, there are a lot of other differences between each of these studies. So, we have within the consortium a combination of different studies. We have randomized clinical trials, we have cohort studies, we have nested cohorts from larger population studies and we try and, in all of the analyses, we have pre specified subgroup analyses to try and look out and check for any heterogeneity that is introduced because of all of this. But the biggest, sort of, difference that we have factored in is that each of these studies collects patients with different types of coronary heart disease. Dr. Riyaz Patel:                So, there are about ... 40% or so are acute coronary syndrome recruited patients, where these people are recruited at the time or after their acute event. And a similar proportion are recruited when they're much more stable. So, in all of our analyses we do try and factor in the differences in terms of the type of CHD patients are enrolled with but everything else, as best as we can, we have tried to standardize including all of the outcomes. So, for example, we share the ICD codes that would define a particular type of outcome across all the different cohorts, so even if you're in a different country, they will generally be reasonably well standardized. Jane Ferguson:                Mm-hmm (affirmative), yeah, yeah. I think it's important and I can see the pros and the cons, you know, you have more diversity and you're representing a broader spectrum of disease by including everybody but then, of course, it's hard to figure it out, but I'd say it gives you a lot of versatility with the types of analyses you can do. Jane Ferguson:                As we mentioned, there's two papers so people can go online and read those two papers. And the first one, is sort of the design and goes really into detail of how you guys set this up and I think is a really nice, sort of, example of, if anybody else was trying to (laughs) do something like this, of how to follow it. But then you also did, sort of, an initial analysis, right, to show what this consortium can actually do. I looked at 9p21, so I'd love to hear more about those analyses. Dr. Riyaz Patel:                Yeah, so 9p21 is one of the most reproduced variants with coronary disease across the world. And it's remarkable how well replicated it's been in all sorts of settings in different countries. But the key thing is that it's been associated mostly in case controlled studies or in first event type of studies. And when we looked at this question some years ago now, at whether a variation of chromosome 9p21 is also associated with subsequent events, IE., we could test in people who've already had a heart attack or coronary disease, does it predict a worse outcome for them. We found that it hadn't. Dr. Riyaz Patel:                [inaudible 00:16:06] was in the literature metro analyses and, sort of, all the caveats that come with that. So, we thought that as a feasibility analysis within the consortium, "why don't we also look at 9p21," which we did and this time around, we were able to identify that 93,000 people with coronary heart disease who had our primary endpoint of coronary heart disease death or MI subsequent to other index events. Again, we confirmed our previously met analyses findings that in this particular setting, 9p21 doesn't seem to associate with risk of subsequent events. And that sort of fits with our understanding of 9p21 so far. And interestingly, in one of our analyses, we identified that it does associate with risk of repeat revascularization. And from what we know about 9p21 so far, it seems to associate with risk of atheroma development or progression as opposed to perhaps plaque vulnerability or rupture which might give you an acute coronary event. Dr. Riyaz Patel:                So, it's been a good example, I think, and really an illustration of how this consortium can work at scale. We have a lot of flexibility in terms of different subgroups that we can look at. And we really drilled down in this paper at all the possible reasons why a neutral finding may have occurred. We've looked at selection bias, we've looked at all the different subgroups which was can do because of the scale of the analysis. So, yeah, so that's kind ... it's really, the findings are not particularly novel in their own right but it is a very good example of feasibility of a consortium. Jane Ferguson:                Yeah, I agree. Because it is, so often, if you get, sort of, a negative finding, you keep wondering, "Well, was it just the power? Do we not ... are we not able to find it?" But, I think, with the scale that you have, you're really able to drill down and say, "Look, we really think there's nothing here. It's a true negative finding." You know, 9p21 is not associated with subsequent events, although, I think the revascularization is interesting and that can, sort of, inform, I guess, more basic research into the the mechanisms of 9p21. Dr. Riyaz Patel:                Exactly. Exactly. Jane Ferguson:                So, what's next? I'm sure there's a lot more papers and analyses that are, sort of, to come out of this. So, can you give us, sort of, a sneak peek of what you're working on now? Dr. Riyaz Patel:                Yeah, so, like with 9p21, we did have a selection of variants to answer important questions. So, for example, we were looking at the role of PCSK9 variation to try and see how that relates in this particular setting, given that trials have already reported on the effective drug. And similarly, we're also looking at interlinking six receptor blockade as a, sort of, similar sort of [inaudible 00:19:11] randomization study to look at the validity of a drug target in a secondary prevention setting. Dr. Riyaz Patel:                Beyond that, we are looking at genome wide association studies and, hopefully, once that is done, the consortium will be in a position to do lots of quick look-ups or all sorts of different questions in genetic variation to inform drug target analyses. So, those are immediate priorities, but we are also, in parallel, looking at non-genetic analyses, so, once again, there are lots of standard clinical risk factors that we need to explore a bit more thoroughly in this setting. So as you're aware, there are various paradoxes that keep creeping up in studies where patients have coronary heart disease already, so the obesity paradox is a good example. And what we're hoping to do, is we're hoping to drill down into many of these observational findings in this particular setting, which hasn't really been done, simply again, because the lack of available resources of anything at this scale. Jane Ferguson:                It's exciting and it sounds like you have a really powerful set of different data sets to be able to ask a lot of interesting questions. So, I'm excited to see what's gonna come out next. Dr. Riyaz Patel:                The other key thing we're working on is also about risk prediction. So, again, one of the things we're missing in the clinical community is good risk prediction tools for subsequent event risk among patients with heart disease. We are working with various colleagues to try and develop better risk prediction algorithms for people who've survived coronary event or have coronary disease. Jane Ferguson:                Alright, that's really interesting and that feeds in really nicely then to, sort of, the precision medicine approach. Well, congratulations on building this. I think that's a huge effort in itself and then also in these two papers that were published this month. I think it's really, really, really great work. Dr. Riyaz Patel:                Well thank you. And a key message here is that we want to build and expand this community of investigators around the world who are looking at risk question because individually, I think, we've all struggled with various, sort of, issues. But collectively, I think we have so much more potential to really address some big questions. And the consortium, as I mentioned, is not just investigator led in terms of what we're doing. We're also very open to collaboration and for people wishing to replicate their own findings and are looking for similar cohorts or larger scale validation opportunities so that is also another key advantage in benefit or risk consortium. Jane Ferguson:                Well, that's wonderful. So, if anyone has either data sets that they want to contribute, are you still, sort of, accepting new investigators? Dr. Riyaz Patel:                Absolutely. Very much so. I mean, in the paper, we do mention that we are limited, particularly in terms of cohorts that are enriched for female patients as well as cohorts enriched for patients who are non-Caucasian, in terms of ethnicity. Because, again, those are important patient groups that we need to address. But, generally speaking, we are absolutely open to including anyone who's interested and who meets the inclusion criteria which is collecting people with coronary heart disease, have got genotyping or examples stored for future analysis and have prospective outcomes connected. Jane Ferguson:                And is there a minimum size of sample that somebody needs to participate? Dr. Riyaz Patel:                Ideally, we'd like to, sort of, set that level at about 1,000 recruited patients. But again, if someone has a very deeply phenotyped cohort and that are interested, we'd be more than happy to discuss that and take that to the steering group. Jane Ferguson:                Okay, wonderful. So, people can just email you if they wanna contact- Dr. Riyaz Patel:                Absolutely. Jane Ferguson:                You any further. Dr. Riyaz Patel:                We also have a website, which is for the consortium, which also has contact details on there. Jane Ferguson:                Okay, perfect. Alright, so let me see. Your email is riyaz.patel@ucl.ac.uk- Dr. Riyaz Patel:                Right. Jane Ferguson:                And then the website for the consortium? Dr. Riyaz Patel:                Www.genius-chd.org Jane Ferguson:                Okay. Perfect. Thank you. So, any listeners that are interested, we'll urge them to either go to the website, read some more, go read the papers, email you directly to talk more. Thank you so much for joining me and for talking about this work. Dr. Riyaz Patel:                Thank you for having me. Jane Ferguson:                That's it for April. Come back in May for the next issue. And thank you for listening.                                            This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hello, and welcome to episode 26 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. It's March 2019, and I'm ready to spring into this month's papers, and apparently make really bad seasonal related jokes. Sorry all. Okay, let's get started.                                            First up, is a paper from Oren Akerborg, Rapolas Spalinskas, Sailendra Pradhananga, Pelin Sahlén and colleagues from the Royal Institute of Technology in Solna, Sweden entitled "High Resolution Regulatory Maps Connect Vascular Risk Variants to Disease Related Pathways." Their goal was to identify non-coding variants associated with coronary artery disease, particularly those with putative enhancers and to map these to changes in gene function. They generated genomic interaction maps using Hi-C chromosome confirmation capture, coupled with sequence capture in several cell types, including aortic and ethelial cells, smooth muscle cells and LPS stimulated THP-1 macrophages.                                            They captured over 25,000 features and they additionally sequenced the cellular transcriptomes and looked at epigenetic signatures using chromatin immunoprecipitation. They looked at regions interacting with gene promoters and found significant enrichment for enhancer elements. Looking at variants previously implicated in genome-wide associated studies, they identified 727 variants with promoter interactions and they were able to assign potential target genes for 398 GWAS variants.                                            In many cases, the gene associated with a particular variant was not the closest neighbor, highlighting the importance of considering chromatin lupane when assigning intergenic variants to a gene. They identified several variants that interacted with multiple promoters, influencing expression of several genes simultaneously.                                            Overall, this paper is a great resource for the community and takes many of these GWAS hits to the next level in starting to understand their biological relevance. They have a lot of supplemental material available online so it's definitely worth checking that out and taking a look for your favorite non-coding variant or chromosomal region to see if you can get some more information on it.                                            Next up, Pierrick Henneton, Michael Frank and colleagues from the Hopital Europeen Georges-Pompidou in Paris bring us "Accuracy of Clinical Diagnostic Criteria For Patients with Vascular Ehlers-Danlos Syndrome in a Tertiary Referral Center." The authors were interested in determining the accuracy of the diagnostic criteria used to select patients for genetic testing for suspected vascular Ehlers-Danlos syndrome. This is because, despite the Villefrench criteria being recommended for diagnosis, the accuracy of the diagnostic criteria was never formally tested.                                            They selected 519 subjects, including 384 probands and 135 relatives who had been seen between 2001 and 2016. They assessed the sensitivity and specificity of the Villefrench classification. Almost 32% of tested individuals carried a pathogenic COL3A1 variant. The sensitivity of the Villefrench criteria was 79% with a negative predictor value of 87%. Symptomatic probands had the highest accuracy at 92% sensitivity and 95% negative predictive value. However, the specificity was just 60%.                                            Applying revised diagnostic criteria from 2017, it was actually less accurate because even though there was an increase in specificity, the sensitivity was reduced. Overall diagnostic performance was worst in individuals under 25 and neither set of diagnostic classifications allowed for early clinical diagnosis in individuals without a family history.                                            Our next paper is a Mendelian randomization analysis from Susanna Larsson, Stephen Burgess and colleagues from Uppsala University and the University of Cambridge. This paper entitled "Thyroid Function And Dysfunction In Relation to Sixteen Cardiovascular Diseases: A Mendelian Randomization Study" aims to understand how subclinical thyroid dysfunction relates to risk of cardiovascular diseases. They generated genetic predictors for thyroid stimulating hormone, or TSH, through a GWAS meta-analysis in over 72,000 individuals. They then analyzed the association of genetically predicted TSH with cardiovascular outcomes in large GWAS studies of atrial fibrillation, coronary artery disease, and ischemic stroke, and further assessed associations with phenotypes in the UK Biobank.                                            They found genetically decreased TSH levels and hyperthyroidism were associated with increased risk of atrial fibrillation but not other tested phenotypes. Overall, these data support a causal role for TSH and thyroid dysfunction in atrial fibrillation but not in other cardiovascular diseases.                                            The next paper is also a Mendelian randomization analysis from members of the same group, Susanna Larsson, Stephen Burgess and colleagues published "Resting Heart Rate and Cardiovascular Diseases: A Mendelian Randomization Analysis." In this letter, they describe a study of the relationship between genetically increased resting heart rate and cardiovascular diseases. They constructed genetic predictors of resting heart rate and similarly to the previous study, used that as an instrument to test for associations with coronary artery disease, atrial fibrillation, and ischemic stroke in the cardiogram, atrial fibrillation, and mega stroke consortia respectively.                                            They also looked at 13 CVD outcomes in the UK Biobank. They found that genetically predicted heart rate was inversely associated with atrial fibrillation with suggestive evidence for an inverse association with ischemic, cardioembolic, and large artery stroke. The inverse association with AF was replicated in the UK Biobank, supporting previous reports linking resting heart rate to atrial fibrillation.                                            Next up, we have a letter from Robyn Hylind, Dominic Abrams, and colleagues from Boston Children's Hospital. This study entitled "Phenotypic Characterization of Individuals with Variants in Cardiovascular Genes in the Absence of a Primary Cardiovascular Indication For Testing" describes their work to probe incidental findings for potential cardiovascular disease variants in individuals undergoing clinical genomic sequencing for non-cardiac indications.                                            They included 33 individuals who had been referred as carrying variants that were indicated as being associated with cardiovascular disease in primary or secondary findings. The variants were reclassified using the 2015 ACMG guidelines, and then were compared to the original classification report obtained at the time of sequencing.                                            Of 10 pathogenic or likely pathogenic variants, only four of these were actually considered pathogenic or likely pathogenic after reclassification under the 2015 ACMG criteria, and none of these were associated with a cardiac phenotype. None of the variants could be definitively linked to any cardiac phenotype.                                            The costs ranged from $75 to over $3700 per subject with a cost per clinical cardiac finding estimated at almost $14,000. This study highlights the relatively high cost and low yield of investigating potential cardiovascular variants and prompts consideration of how to implement strategies to ensure that variant reporting maximizes clinical return but minimizes the financial, time, and psychological burdens inherent in lengthy follow-ups.                                            The next paper is a clinical letter from Serwet Demirdas, Gerben Schaaf and colleagues from Erasmus University Rotterdam  entitled "Delayed Diagnosis of Danon Disease in Patients Presenting with Isolated Cardiomyopathy." They report on a clinical case of a 14-year-old boy presenting with cardiac arrest due to ventricular fibrillation during exercise. Echocardiography and MRI showed cardiac concentric hypertrophy, particularly in the left ventricle. The boy's mother had died at age 31 after being diagnosed with peripartum dilated cardiomyopathy.                                            Sequencing in the boy revealed a variant in the LAMP2 gene, known to be responsible for Danon disease, which typically presents as cardiomyopathy, skeletal myopathy, and intellectual disability. This same LAMP2 variant was found in preserved maternal tissue, but not in other family members. In this case, there was no evidence of muscle or intellectual abnormalities. However, sequencing had allowed for this diagnosis of Danon disease in the child and posthumously in his mother. This study demonstrates a utility of using extended gene panels in clinical sequencing to aid in diagnosis and to inform management of patients.                                            The next letter is from Alvaro Roldan, Julian Palomino-Doza, Fernando Arribas and colleagues from University Hospital of the 12th of October in Madrid and is entitled "Missense Mutations in the FLNC Causing Familial Restrictive Cardiomyopathy: Growing Evidence." This report also highlights clinical cases. In this case, two individuals with variants in the filamin C, or FLNC gene. Two unrelated individuals presenting with restricting cardiomyopathy were sequenced and found to carry two different variants in the FLNC gene, one of which had not been previously reported.                                            This expands the number of reported cases of filamin C mutations in restrictive cardiomyopathy and highlights the need for further study of the pathophysiology linking filamin C to cardiac function.                                            Finally, we have some correspondence related to a previously published article. In the letter, Christopher Chung, Briana Davies, and Andrew Krahn comment on the recently published article from Jody Ingles on concealed arrhythmogenic right ventricular cardiomyopathy in sudden unexplained cardiac death events. In that paper earlier this year, they had reported on four cases of individuals presenting with cardiac arrest or sudden cardiac death, attributable to concealed arrhythmogenic right ventricular cardiomyopathy with underlying mutations in the plakophilin-2 gene. In the letter from Chung et al, they report similar findings where individuals may first experience electrical phenotypes before manifesting structurally detectable disease. Indeed, in their response to this letter, Ingles et al report identification of an additional case since publication of their original article.                                            Taken together, this further strengthens the case for development of additional strategies to identify at risk individuals and predict and prevent disease events.                                            That's all for the papers for March 2019. Go online to check them out and follow us on Twitter @Circ_Gen to see new papers as they are published online. Thanks for listening. Until next month everyone. This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hi everybody. Welcome to Episode 25. I'm Jane Ferguson. This is Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine, and it is February 2019. Let's get started.                                            The first paper this issue is a concurrent publication and comes to us from 29 different editors-in-chief of 27 major cardiovascular journals, led by Joseph Hill, editor-in-chief of Circulation. This editorial, entitled Medical Misinformation: Vet the Message! gives a pointed reminder of the real life risks of misinformation that spreads rapidly through social media and influences people who are making crucial decisions about healthcare for themselves and their families. Quoting directly from the paper they say, "We, the editors-in-chief of the major cardiovascular scientific journals around the globe, sound the alarm that human lives are at stake. People who decline to use a statin when recommended by their doctor, or parents who withhold vaccines from their children, put lives in harm’s way."                                            In this editorial they call on those in the media to do a better job of taking responsibility for the information they disseminate. In particular, in evaluating content before disseminating it, and avoiding false equivalencies where overwhelming scientific evidence favors one side of the so called "debate." I'll add to that that those of us who are medical or scientific professionals need to do our best to take the time to explain our science to those around us. The science underlying most of medicine is complex and hard to explain and sometimes incomplete, but we do a disservice to people if we don't at least try. Let's all join the editors in calling everyone to vet information and hold those with power in the media accountable for the spread of misinformation they enable.                                            Next up this issue, a paper from Jody Ingles, Birgit Funke, and co-authors from the University of Sydney, Harvard Medical School and others, entitled Evaluating the Clinical Validity of Hypertrophic Cardiomyopathy Genes. As panels for clinical genetic testing expands to include more genes, there are more and more variants that are detected and reported to patients, but do not necessarily have underlying evidence to support or disprove pathogenicity. This group aimed to systematically assess the validity of potential gene disease associations with hypertrophic cardiomyopathy and left ventricular hypertrophy by curating variants based on multiple lines of genetic and experimental evidence.                                            They categorized genes based on the strength of evidence of disease causation and reviewed HCM variant classification in the ClinVar variant and phenotype repository. They selected 57 genes to study based on those which were frequently included on test panels or had previous reports of association with HCM. Of HCM genes, only 24% were characterized as having definitive evidence for disease causation, 10% of the genes had moderate evidence, while 66% had limited or no evidence for disease causation. Of syndromic genes, 50% were definitively associated with left ventricular hypertrophy. Of over 4,000 HCM variants in ClinVar, 31% were in genes that, on review, had limited or no evidence for association with disease.                                            What this study shows is that many genes that are included on panels for diagnostic testing for HCM actually have little evidence for any relationship to disease. Systematic curation is required to improve the accuracy of information being acquired and reported to patients and families with HCM.                                            Moving on to the next paper. This manuscript describes the international Triadin Knockout Syndrome Registry: The Clinical Phenotype and Treatment Outcomes of Patients with Triadin Knockout Syndrome. It comes from Daniel Clemens, Michael Ackerman and colleagues from the Mayo Clinic. So, Triadin Knockout Syndrome is a rare inherited arrhythmia syndrome and it is caused by recessive null mutations in the cardiac triadin gene. To improve the ability to study this rare syndrome, this group established the International Triadin Knockout Syndrome Registry, with the goal of including patients across the world with homozygous or compound heterozygous triadin null mutations. The registry currently includes 21 patients from 16 families who have been carefully phenotyped and many of whom exhibit T wave inversions and have transient QTC prolongation.                                            The average age for first presentation with cardiac arrest or syncope was three years of age. Despite a variety of treatments, the majority still have recurrent breakthrough cardiac events. These data highlight the importance of conducting testing for triadin mutations in patients, particularly young children presenting with cardiac arrest, and as this registry grows it will enable a better understanding of the disease and hopefully pave the way for future triadin gene therapy trials.                                            The next paper comes from Daiane Hemerich, Folkert Asselbergs and colleagues from Utrecht University, and is entitled Integrative Functional Annotation of 52 Genetic Loci Influencing Myocardial Mass Identifies Candidate Regulatory Variants and Target Genes. They were interested in whether variants that have been associated with myocardial mass may exert their influence through regulatory elements. They analyze the hearts of hypertrophic cardiomyopathy patients and non-disease controls and ran ChIP-seq in 14 patients and 4 controls and RNA-seq in 11 patients and 11 controls.                                            They selected 52 loci that have been associated with electric cardiogram defined abnormalities in amplitude and duration of the QRS complex and looked specifically at these gene regions. They found differential expression of over 2,700 different genes between HCM and control. They further found differential acetylation over 7,000 regions. They identified over 1000 super enhancers that were unique to the HCM samples. They found significant enrichment for differential regulation between disease and control hearts within the loci previously associated with HCM, compared with loci not associated with HCM. They analyzed regions where putative causal SNPs overlapped regulatory regions, and identified 74 co-localized variants within 20 loci, with particular enrichment for SNPs in differentially expressed promoters. They confirmed associations with 18 previously implicated genes, as well as identifying 14 new genes. Overall, what this study demonstrates is that by looking at regulatory features that differ in affected tissues between disease and healthy individuals, we can learn more about the underlying mechanisms of disease.                                            Moving on, we have a paper entitled Interleukin-6 Receptor Signalling and Abdominal Aortic Aneurysm Growth Rates from Ellie Paige, Marc Clément, Daniel Freitag, Dirk Paul, Ziad Mallatt and colleagues from the University of Cambridge. They aimed to investigate a specific SNP in the Interleukin-6 receptor rs2228145, which has been associated with abdominal aortic aneurysms. Inflammation is thought to be a contributor to aneurism progression. The authors hypothesized that the IL-6 receptor's SNP may affect aneurysm growth. They use data from over 2,800 subjects from nine different prospective cohorts and examine the effect of genotype on annual change in aneurysm diameter. Although there was a significant association between genotype and baseline aneurysm size, there was no statistically significant association with growth over time. It appeared that growth was less in minor allele carriers, but the effect if true, was small and the analyses were not powered for small effect sizes.                                            Sample sizes are limited for cohorts with abdominal aortic aneurysms and the authors already used all available worldwide data. In complimentary experiments in mice, they examined the effect of blocking the IL-6 receptor pathway. They found that selective blockage of the IL-6 trans-signaling pathway mediated by soluble IL-6 receptor was associated with improved survival in two different mouse models. However, blocking the classical membrane-bound IL-6 signaling pathway in addition to the trans-signaling pathway did not lead to improved survival. Although the severe lack of enough subjects for well powered genetic analyses is a major limitation for the study of abdominal aortic aneurism and humans, this paper demonstrates the potential relevance of the IL-6 trans-signaling pathway and aneurysm growth, and suggests that further interrogation of this pathway may be informative in figuring out new ways to prevent aneurysm progression and rupture.                                            Next, we have the first of two research letters this issue. The letter on Common Genetic Variation in Relation to Brachial Vascular Dimensions and Flow-Mediated Vasodilation comes to us from Marcus Dorr, Renate Schnabel and co-authors from several institutions including University Heart Center in Hamburg. They were interested in gaining a better understanding of the genetics underlying vascular function. They ran a meta-analysis of brachial artery diameter, maximum brachial artery diameter adjusted for baseline diameter, and flow-mediated dilation in over 17,000 individuals of European ancestry from six different GWA studies. They sought to replicate findings in over 9,500 newly genotyped individuals. They identified two novel SNPs for baseline brachial artery diameter, but no SNPs reached significance or replication from maximum brachial artery diameter or flow-mediated dilation. One of the significant SNPs was located in the insulin-like growth factor binding protein 3, or IGFBP-3 gene. They analyzed plasma IGFBP-3 protein levels in 1,400 individuals and found a significant association with brachial artery diameter.                                            The second SNP they identified is located within the AS3MT gene for arsenite methyltransferase, and this SNP appears to be an eQTL for AS3MT expression in monocytes and arterial tissue. Along with identifying these two genes with potential involvement in baseline brachial artery diameter, this study also supports a low genetic component to flow-mediated dilation, indicating that environmental factors may be or more influential in FMD.                                            The final research letter comes from Alexis Williams, Craig Lee and colleagues from the University of North Carolina and is entitled CYP2C19 Genotype-Guided Antiplatelet Therapy and 30-Day Outcomes After Percutaneous Coronary Intervention. It is known that loss of function variants in CYP2C19 effect bioactivation of clopidogrel, and CYP2C19 genotyping is increasingly used to guide antiplatelet therapies. The authors were interested in whether genotype-guided therapy is effective in reducing major adverse cardiovascular events in the short term, specifically in the 30 days following percutaneous coronary intervention, when most MACE occurs. They followed over a thousand individuals undergoing PCI and CYP2C19 testing and looked at atherothrombotic and bleeding outcomes. Consistent with implementation of genotype-guided therapy, individuals carrying loss of function alleles were less likely to be prescribed clopidogrel.                                            However, out of loss of function carriers, those who did take clopidogrel had significantly higher risk of MACE with no difference in bleeding risk. There was no difference by therapy in individuals without a loss of function allele. What this study shows us is that even in the 30 days following PCI, genotype-guided therapy can be effective in protecting individuals carrying loss of function CYP2C19 variants.                                            And that's it from us for February. Go online to ahajournals.org/journal/circgen to read the full papers, access videos and more, and of course to delve into the podcast archives. Thank you for listening and I look forward to bringing you more next month. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.  

Jane Ferguson:                Hello everyone, and happy new year. Welcome to episode 24 of Getting Personal: Omics of the Heart. It's January 2019, I am Jane Ferguson, an assistant professor at Vanderbilt University Medical Center and an associate editor at Circulation Genomic and Precision Medicine. We have a great line-up of papers this month in the journal, so let's jump right into the articles.                                            First up, a paper from Christopher Nelson, Nilesh Samani, and colleagues from the University of Lester entitled, "Genetic Assessment of Potential Long-Term On-Target Side Effects of PCSK9 Inhibitors."                                            I think most listeners are well aware of the efficacy of PCSK9 inhibition in reducing cardiovascular risk. However, as a relatively new treatment option, we do not yet have data on potential long-term side effects of PCSK9 inhibition. In this study, they utilized genetics as a proxy to understand potential long-term consequences of lower PCSK9 activity. They examined a PCSK9 variant that associates with lower LDL, as well as examining two LDL-lowering variants in HMGCR, the target of statins, which served as a positive control of sorts. They used data from over 479,000 individuals in the UK Biobank and looked for associations between the three LDL-lowering variants and 80 different phenotypes.                                            For the PCSK9 variant, the allele which is associated with lower LDL was significantly associated with the higher risk of type 2 diabetes, higher BMI, higher waist circumference, higher waist-hip ratio, higher diastolic blood pressure, as well as increased risk of type 2 diabetes and insulin use. The HMGCR variants were similarly associated with type 2 diabetes as expected.                                            Mediation analysis suggested that the effect of the PCSK9 variant on type 2 diabetes is independent of its effect on obesity. There were nominal associations between the PCSK9 variant and other diseases, including depression, asthma, chronic kidney disease, venous thromboembolism, and peptic ulcer.                                            While genetics cannot fully recapitulate the information that would be gained from long-term clinical follow up, these data suggest that like statins, PCSK9 inhibition may increase the risk of diabetes and potentially other disease. Overall, the cardiovascular efficacy of PCSK9 inhibition may outweigh these other risks, however, future studies should carefully examine these potential side effects.                                            Next up, we have a paper from Xiao Cui, Fang Qin, Xinping Tian, Jun Cai, and colleagues from Peking Uni and Medical College, on "Novel Biomarkers for the Precise Diagnoses and Activity Classification of Takayasu's Arteritis."                                            They were interested in identifying protein biomarkers of Takayasu arteritis, to improve diagnosis and understanding of disease activity in this chronic vascular disease. They ran a proteomic panel including 440 cytokines on 90 individuals, including individuals with active disease, inactive disease, and healthy controls. They found a number of candidates and validated one protein, TIMP-1, as a specific diagnostic biomarker for Takayasu arteritis. For assessing disease activity, there was no single biomarker that could be used for classification, however, the combination of eight different cytokines identified through random forest-based recursive feature elimination and [inaudible] regression, including CA 125, FLRG, IGFBP-2, CA15-3, GROa, LYVE-1, ULBP-2, and CD 99, were able to accurately discriminate disease activity versus inactivity.                                            Overall, this study was able to identify novel biomarkers that could be used for improved diagnosis and assessment of Takayasu arteritis, and may give some clues as to the mechanisms of pathogenesis.                                            Our next paper is entitled, "Familial Sinus Node Disease Caused By Gain of GIRK Channel Function," and comes from Johanna Kuß, Birgit Stallmeyer, Marie-Cécile Kienitz, and Eric Schulze-Bahr, from University Hospital Münster. They were interested in understanding novel genetic underpinnings of inherited sinus node dysfunction.                                            A recent study identified a gain of function mutation in GNB2 associated with sinus node disease. This mutation led to enhanced activation of the G-protein activated inwardly rectifying potassium channel, or GIRK, prompting the researchers to focus their interest on the genes encoding the GIRK subunits, KCNJ3 and KCNJ5. They sequenced both genes in 52 patients with idiopathic sinus node disease, and then carried out whole exome sequencing in family members of patients with potential disease variants in either gene. They identified a non-synonymous variant in KCNJ5, which was not present in the EVS or ExAC databases, and which segregated with disease in the affected family. This variant was associated with increased GIRK currents in a cell system, and in silico models, predicted the variant altered or spermine binding site within the GIRK channel. Thus, this study demonstrated that a gain of function mutation in a GIRK channel subunit associates with sinus node disease, and suggests that modulation of GIRK channels may be a viable therapeutic target for cardiac pacemaking.                                            Our next paper, "Key Value of RNA Analysis of MYBPC3 Splice-Site Variants in Hypertrophic Cardiomyopathy," comes from Emma Singer, Richard Bagnall, and colleagues from the Centenary Institute and the University of Sydney.                                            They wanted to understand the impact of variants in MYBCP3, a known hypertrophic cardiomyopathy gene, on splicing. They recruited individuals with a clinical diagnosis of hypertrophic cardiomyopathy and genetic testing of cardiomyopathy-related genes. They further examined individuals with a variant in MYBCP3 which had an in silico prediction to affect splicing. They sequenced RNA from blood or from fixed myocardial tissue and assessed the relationship between each DNA variant and gene splicing variation.                                            Of 557 subjects, 10% carried rare splice site variants. Of 29 potential variants identified, they examined 9 which were predicted to affect splicing, and found that 7 of these were indeed associated with splicing errors.                                            Going back to the families, they were able to reclassify four variants in four families from uncertain clinical significance to likely pathogenic, demonstrating the utility of using RNA analysis to understand pathogenicity in genetic testing.                                            The next paper this issue comes from Catriona Syme, Jean Shin, Zdenka Pausova, and colleagues from the University of Toronto, and is entitled, "Epigenetic Loci of Blood Pressure: Underlying Hemodynamics in Adolescents and Adults."                                            A recent large meta epigenome-wide association study identified methylation loci that associate with blood pressure. In this study, they wanted to understand more about how these loci related to blood pressure and hemodynamics. They recruited adolescents and middle-aged adults and assessed 13 CPG loci for associations with hemodynamic markers, including systolic and diastolic blood pressure, heart rate, stroke volume, and total peripheral resistance, measured over almost an hour during normal activities. Several of the loci replicated associations with blood pressure, and two of these also showed age-specific associations with hemodynamic variables. One site in PHGDH was particularly associated with blood pressure and stroke volume in adolescents, as well as with body weight and BMI, where lower methylation resulting in higher gene expression associated with higher blood pressure. A second site in SLC7A11 associated with blood pressure in adults but not adolescents, with lower methylation and consequent higher gene expression associated with increased blood pressure.                                            Overall, this study indicates that methylation mediated changes in gene expression may modulate blood pressure and hemodynamic responses in an age-dependent manner.                                            Next up is a research letter from Ben Brumpton, Cristen Willer, George Davey Smith, Bjørn Olav Åsvold, and colleagues from the Norwegian University of Science and Technology, entitled, "Variation in Serum PCSK9, Cardiovascular Disease Risk, and an Investigation of Potential Unanticipated Effects of PCSK9 Inhibition: A GWAS and Mendelian Randomization Study in the Nord-Trøndelag Health Study, Norway."                                            As we heard about from the first study this issue, the long-term side effects of PCSK9 inhibition remain unknown. In this study, they also applied a genetic approach to understand potential unanticipated consequences of PCSK9 inhibition. They analyzed phenotypes from over 69,000 participants in the Nord-Trøndelag Health Study and measured serum PCSK9 in a subset.                                            In PCSK9 GWAS of over 3,600 people, with replication in over 5,000 individuals from the twin gene study. They defined a genetic risk score for serum PCSK9 and assessed the relationship between genetically predicted PCSK9 and outcomes. They saw the expected associations between lower PCSK9 and lower LDL and coronary heart disease risk. However, there was minimal evidence for associations with other outcomes.                                            While our first study in this issue, from Nelson, et al, found that lower PCSK9 from a single genetic variant was associated with higher diabetes risk, this risk was not found here using the genetic risk score. Differences in the genetic definitions and in the populations used can perhaps explain these differences between the two studies, but overall, the studies are consistent in suggesting that long-term PCSK9 inhibition is unlikely to be associated with major adverse outcomes.                                            Our second research letter comes from Young-Chang Kwon, Bo Kyung Sim, Jong-Keuk Lee, and colleagues from Asan Medical Center in Seoul, on behalf of the Korean Kawasaki Disease Genetics Consortium. The title is, "HLA-B54:01 is Associated with Susceptibility to Kawasaki Disease," and reports on novel Kawasaki disease variants.                                            HLA genes have been previously associated with disease, and in this report, the authors sequenced selected axons in HLA-DRB1, HLA-DQB1, HLA-A, HLA-B, HLA-C, and HLA-DBP1 in 160 Kawasaki disease patients and 278 controls. They find a significant association with HLA-B, and replicated this in a sample of 618 Kawasaki disease patients, compared with over 14,000 in-house controls. They identified specific amino acid residues conferring disease susceptibility, highlighting HLA-B as a potential modulator of Kawasaki disease.                                            Our third and final research letter concerns "Serum Magnesium and Calcium Levels and Risk of Atrial Fibrillation: a Mendelian Randomization Study," and comes to us from Susanna Larsson, Nikola Drca, and Karl Michaëlsson, from the Karolinska Institute.                                            Because magnesium and calcium are known to influence atrial fibrillation, this group was interested in whether genetic predictors of serum methyls associated with disease. They constructed genetic predictors from GWAS of calcium in over 61,000 individuals, and GWAS of magnesium in over 23,000 individuals. They applied these predictors to an AF GWAS including over 65,000 cases and over 522,000 controls. Genetically predicted magnesium was inversely associated with atrial fibrillation, while there was no association with genetically predicted calcium.                                            While this study does not definitively prove causality, future studies aimed at assessing whether dietary or other strategies to raise serum magnesium are protective against AF may yield novel strategies for disease prevention.                                            And that's it from us for this month. Thank you for listening, and come back next month for more from Circulation Genomic and Precision Medicine.                                            This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association, 2019.  

Jane Ferguson:  Hello, everyone. Welcome to Episode 23 of Getting Personal, Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. It's December 2018. I'm Jane Ferguson. So let's get started.                              This month I talked to Dr. Merlin Butler from Kansas University Medical Center about an interesting clinical case he described recently in the Journal of Pediatric Genetics, concerning cardiac presentations in a case of classic Ehlers-Danlos syndrome with COL5A1 mutations.                              Keep listening for that interview, but first, let's talk about the papers in this month's issue of the Journal.                              Our first paper, entitled "Effects of Genetic Variance Associated With Familial Hypercholesterolemia on LDL Cholesterol Levels and Cardiovascular Outcomes in the Million Veteran Program." Comes from Yan Sun, Peter Wilson and co-authors on behalf of the V.A. Million Veterans Program. They were interested in the relatively between variants in LDLR, APOB and PCSK9, and LDL cholesterol in the general population. Low-frequency variants in these genes have been identified to underlie the greatly elevated LDL cholesterol seen in cases of familial hypercholesterolemia, but the effects of the population level are unknown.                              Using data from the Million Veterans Program, the team analyzed the associations between putatively pathogenic variants and the maximum recorded LDL cholesterol level, as measured repeatedly over a 15-year period, in over 330,000 participants. They restricted analysis to variants that were present in at least 30 people and found that eight of the 16 variants tested were associated with significantly higher LDL cholesterol. Through phenome-wide association analysis, they found that carriers had a higher likelihood of a diagnosis of hypercholesterolemia or coronary heart disease, but not of other diagnoses. Even though individuals carrying risk variants generally reduce their LDL cholesterol through statin treatment, they still had residual risk, suggesting that even earlier initiation of treatment may be required in individuals with genetic risk of high HDL.                              Continuing the theme, the next paper comes from Laurens Reeskamp, Merel Hartgers, Kees Hovingh and colleagues from the University of Amsterdam, and is entitled, "A Deep Intronic Variant in LDLR in Familial Hypercholesterolemia: Time to Widen the Scope?" This team had encountered a family with familial hypercholesterolemia, who did not carry a coding mutation in LDLR, APOB or PCSK9, and they wanted to figure out what was causing the elevated LDL cholesterol in this family. They conducted whole-genome sequencing in nine family members, five affected and four unaffected. They found a variant in an intron in LDLR, which resulted in an insertion of 97 nucleotides, leading to a frame shift in premature stop codon in exon 15 of LDLR. They confirmed the disease segregation in a second family, and found a frequency of over 0.2% in additional FH cases without a confirmed mutation.  This study highlights the need to consider more than just exons when looking for causal variants, particularly in families where no coding mutations are identified.                              Next up, from Kathryn Siewert and Ben Voight from University of Pennsylvania, a paper reporting that "Bivariate Genome-Wide Association Scan Identified 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease." This paper started with a premise that, because heritable plasma lipids are genetically linked to coronary artery disease, we would have greater power to detect variants contributing to both traits by conducting joint GWAS analysis, rather than independent analyses for lipids or coronary disease, as has been done traditionally. Using data from over 500,000 individuals for CAD and over 180,000 individuals from the Global Lipid Genetics Consortium, they conducted a bivariate GWAS and identified six previously unreported loci that associated with CAD and either triglycerides, LDL cholesterol or total cholesterol. Many of these loci also had signals for effects on gene expression of genes in the region, suggesting that these novel loci may affect lipid levels and CAD risk through modulation of gene expression. Interestingly, for some of the newly-identified loci, there were multiple potential regulatory targets, suggesting that these loci may affect lipids and CAD through separate mechanisms. Overall, for closely-linked traits such as lipids and CAD, this joint GWAS approach gives additional power to detect novel variants.                              The next article comes from Terry Solomon, John-Bjarne Hansen and colleagues from University of California-San Diego and the Arctic University of Norway. Their paper concerns the "Identification of Common and Rare Genetic Variation Associated With Plasma Protein Levels Using Whole-Exome Sequencing and Mass Spectrometry." They were interested in identifying genetic variants that associate with plasma protein levels, both to understand genetic regulation and to identify potential sources of bias, where a genetic variant affects the assay used to quantify the protein, without necessarily altering biological components of the protein. Using data from 165 participants of the Tromsø Study, they quantified 664 proteins in plasma by tandem mass tag mass spectrometry and genotypes by whole-exome sequencing. They identified 109 proteins or peptides associated with genotype, and of these identified 49 that appeared to be technical artifacts based on genotype data.  Of the rest, many of the genetic variants affected protein level by modulation of RNA, but some appeared to directly affect protein metabolism. Their method of quantifying multiple peptides from each protein and sequencing exons allowed them to identify spurious associations that would often be missed, and highlights the large number of artifacts that could be present in protein quantitative trait locus studies. At the same time, they show that over half of the pQTLs are real, with genetic variants affecting circulating proteins through diverse mechanisms.                              Our last of the full-length original research articles also applied proteomics. "Proteomic Analysis of the Myocardium in Hypertrophic Obstructive Cardiomyopathy" comes from Caroline Coats, Perry Elliott and coauthors from University College, London. They obtained myocardial samples from 11 patients with hypertrophic cardiomyopathy and measured over 1500 proteins using label-free proteomic analysis. They compared protein expression to six control samples from healthy hearts. They identified 151 proteins that were differentially expressed in HCM hearts, compared with control, and they validated a subset of these using an additional 65 myocardial samples from healthy and diseased subjects. Of eight validated differentially expressed proteins, they represented pathways in metabolism, muscle contraction, calcium regulation and oxidative stress. Of particular interest, they highlighted lumican as a novel disease protein, and showed the potential of proteomics to identify mechanisms underlying HCM.                              We have two research letters this month, the first from Hisato Suzuki, Kenjiro Kosaki and coauthors from Keio University School of Medicine at Tokyo. It's titled, "Genomic Comparison With Supercentenarians Identifies RNF213 as a Risk Gene for Pulmonary Arterial Hypertension." In this letter, they were interested in identifying genetic variants underlying pulmonary arterial hypertension. They hypothesized that individuals with extremely long lifespan would be less likely to carry potentially pathogenic variants. They performed whole-exome sequencing in 76 individuals with PAH and compared them to 79 supercentenarians who had lived for over 110 years. They report variants in RNF213 and TMEM8A that were present in PAH but not in the controls, suggesting these genes may be important in the pathophysiology of PAH.                              The second research letter comes from Tessa Barrett, Jeffrey Berger and colleagues from New York University School of Medicine, and is entitled, "Whole-Blood Transcriptome Profiling Identifies Women With Myocardial Infarction With Nonobstructive Coronary Artery Disease: Findings From the American Heart Association Go Red for Women Strategically Focused Research Network." Most of the 750,000 acute MIs occurring in the U.S. each year are caused by obstructive coronary artery disease, but around 15% of the acute MIs occur in individuals whose arteries have less than 50% stenosis and are defined as unobstructed. These individuals are more likely to be female and of higher morbidity and mortality. In this AHSAFRM-funded project, the team sequenced whole-blood RNA from 32 women who presented with an MI with or without CAD, or controls. They report several thousand transcripts differing between groups on conducted pathway analysis, which highlighted several pathways, most notably estrogen signaling. This suggests that estrogen may be a novel component in MIs occurring in the absence of obstructive disease.                              We also have two clinical letters this month. The first, "Desmoplakin Variant-Associated Arrhythmogenic Cardiomyopathy Presenting as Acute Myocarditis," is brought to us by Kaitlyn Reichl, Chetan Shenoy and colleagues from University of Minnesota Medical School. They report a case of a 24-year-old man presenting with acute myocarditis, who was found to have a pathogenic variant in desmoplakin underlying arrhythmogenic cardiomyopathy, also present in his father and one brother. This case highlights myocarditis as a possible initial presentation of arrhythmogenic cardiomyopathy, which requires cardiac MRI and genetic testing for full evaluation.                              The second clinical letter comes from Judith Verhagen, Marja Wessels and co-authors from University Medical Center, Rotterdam, and is entitled, "Homozygous Truncating Variant in PKP2 Causes Hypoplastic Left Heart Syndrome." They report on a family with consanguineous parents, where two children were affected with left ventricular hypoplasia, leading to intrauterine death in one child and death at day 19 of life in a second child. Sequencing identified a variant in PKP2, which encodes plakophilin 2. Both parents were heterozygous for the mutation, and their affected children were homozygous for the mutation. This mutation resulted in disorganization of the sarcomere and affected localization of other proteins affecting gap junctions. The case highlights PKP2 variants as causal in hypoplastic left heart syndrome.                              Dr. Merlin Butler is a professor at Kansas University Medical Center and Director of their Division of Research and Genetics. Dr. Butler joined me to discuss an interesting case of Ehlers-Danlos Syndrome in a father and son, with heart failure in the father. This case is in press in the Journal of Pediatric Genetics, and the prepublication version is available online, published on the 13th of October 2018. We'll tweet out a link to that paper, if you're interested in viewing the full case, but here's Dr. Butler, who joined me to discuss it now. Dr. Butler:          ... I'm a clinical geneticist here at University of Kansas Medical Center, and I see both adult and pediatric patients, but one of the more common reasons for referral to my adult side clinical genetic services is connective tissue disorders. And that's how we were involved with this particular family, a son and father, that led to my interest in looking at the question about genetics of cardiac transplantation of those patients that present for cardiology services because of heart failure and worked up and ultimately end up as a candidate for transplantation.                              And that transpired in this particular family, which the patient was a 13-year-old boy who was referred into the clinic because of connective tissue disorder. Actually the primary care wanted to rule out Ehlers-Danlos Syndrome. And so we evaluated the 13-year-old boy in the clinic setting, and then we ordered comprehensive connective tissue and next-generation DNA sequencing panel, and lo and behold, he had a mutation of the classical gene that causes classic Ehlers-Danlos, the collagen 5A1 gene. The gene variant was classified as unknown clinical significance, which is often the case as we know with this technology, next-generation sequencing. Regardless of the condition we're looking at, we find about 10% of time, the panel of tests, the panel of genes that come back that are tested. 10% of the time we find no variants, no spelling errors, no mutations. 10% of the time the results come back from the commercial laboratory ... these are clinic patients, so it's done in commercially-approved laboratories, clinically-approved laboratories ... and we find that about 10% is pathogenic, which means it's disease-causing. The gene variant or mutation has been reported before. There is information in the literature that we know that it causes disease, Ehlers-Danlos, whatever type.                              About 80% of the time, the results come back as unknown clinical significance, and this is related to connective tissue. You probably order a test in cardiology or any other service and you'll find the same area. Most of the variants come back as unknown. What is meant by that is they haven't been reported previously in the literature, and therefore we don't know ... They may be disease-causing, that particular change, but we don't know that. We as geneticists, we have to then figure out whether that gene variant is a mutation or background noise. So we go through a process by where we try to characterize that particular gene finding to see whether it could be causative in that particular patient we see, or if it looks like it's probably tolerated and is just background noise, and it has really probably no apparent phenotypic change resulting from that particular gene variant.                              So this particular gene variant that we found, the collagen 5A1, did meet the criteria. We looked for computer programs and silica prediction to see if it was tolerated or damaging. We looked at how common that gene variant is seen in the general population, looking at exact various types of genome databases at the laboratories used to search for that variant in the population that's been serviced by genetic services, to see how rare it is or how common it is. We also check to see if it's a missense change, missense variant that is, one amino acid got switched for a different amino acid. There are five classes of amino acids, so if they stay within the same class, that change one amino acid to the next probably doesn't have much meaning, but if it changes to an entirely different class, like positive to negative, hydrophilic to hydrophobic, that could make a big change at the protein translation level, and therefore impact on protein development and function.                              And then we looked to see if it's conserved in evolution. The laboratories that we use, they look at approximately 80 different animals, mammals, vertebrates, primates, non-mammal vertebrates, to see if that particular spelling change is conserved throughout evolution. If it is, if C is always that position 205 in the coding sequence of that gene throughout evolution, that means you need to have C at that position, not A, G or T, because that would be conserved and impact that we don't want to change that, because it's conserved through evolution.                              So those kind of criteria, how common it is in the population, how conserved it is, what the amino acid change might be and what the computer programs predict that change might relate to the function of the protein. So we used those criteria, found this gene variant, although it hadn't been reported before ... well, it hasn't been characterized as pathogenic. In this particular family, 13-year-old son and 55-year-old father, they both had the classical features of classic Ehlers-Danlos, so that gene variant, we know at this point is informative. Dr. Ferguson:    That's a really helpful introduction to how you go about looking at variants and screening them and picking the ones of most importance. So you had this 13-year-old patient who came in and then you tested the patient, and then did you also test both parents? Other family members? Dr. Butler:          Well, the mother was no longer in the loop, so the primary care, the pediatrician, referred this 13-year-old boy because of joint laxity. He had experienced multiple spontaneous knee dislocations, beginning around nine years of age. He was 13 when I saw him in clinic. He had a history of knee pain, generalized joint hypermobility, loose skin, excessive bruising and poor scarring. And he had that history coming in, and we certainly could identify those findings on this patient. In fact, we reported this patient in the literature. The title of the paper is "Classic Ehlers-Danlos Syndrome in a Son and Father with a Heart Transplant Performed in the Father," published in Journal of Pediatric Genetics, but during a genetics clinic visit, we assessed a hypermobility Beighton scale, that we used to determine the degree of hypermobility, hyperflexibility, and we recorded a score of eight out of nine. Nine is the maximum number. And what we use as kind of a cut-off, this score is five or more, five out of nine or more, then that would indicate that probably there is some kind of joint issues, connective tissue disorder in the way.                              He had no heart murmur detected, normal rate and rhythm, but a previous echocardiogram showing he had no valvular problems but he had aortic root dilation. He also had skin marbling, atrophic scars, particularly on the lower leg, and increased pigment secondary to easy bruising. He had asymmetry of the anterior body wall, pretty classical findings that we recognize in Ehlers-Danlos. Dr. Ferguson:    So the reason we're talking to you about this is actually less related to the son, right? And then related to what you found in the father. Dr. Butler:          The father, right. So the father was 55 years old when we saw him. So we did testing on the son, based on his examinations, and then we obtained DNA and we found out, had the sequencing. We found he had a gene variant of the collagen 5A1 gene. And the collagen 5A1 codes for collagen, low fibrils protein changes, and that's a classical finding we see in Ehlers-Danlos. So we then, on follow-up, we looked more closely at the father, based on what we found in the child, and the father is 55 years of age and he exhibited similar clinical features seen in his son, including stretchable, thin skin, poor scarring, hypermobile joints, with pain and easy bruising. He had a Beighton score of six out of nine, but due to multiple knee surgeries, we were really not able to able to assess his knee findings.                              And he had strabismus repair when he was like 12 years of age. He had surgery on his right knee due to frequent dislocations, and had bilateral foot surgeries due to flat feet, pes planus. He had a stroke at 37 years of age, but without hypertension. At 43 years of age he underwent a heart transplant because of heart failure with no known cause, such as infections or anatomical defects or metabolic problems seen. And at 54 years of age he had fusion of the lower vertebrae, correct complications, nerve compression, impacting ambulation. So he had multiple, multiple problems, and we did DNA testing on him. He also had the same gene variant of the collagen 5A1 gene, which causes classic Ehlers-Danlos Syndrome. Dr. Ferguson:    Yeah, so he essentially had been undiagnosed his entire life, I guess. Dr. Butler:          In his entire life, he just kind of lived with it. Obviously no one really picked it up because he had multiple, multiple orthopedic surgeries. Of course he had the cardiac transplant because of a very large heart size. They didn't really find out what had taken place with that. They didn't find any reason why he had heart failure. So, because of this connective tissue issue, I began to think more closely about this. Could somehow his cardiac transplantation due to no determined reason why he had heart failure, could that somehow be related to a connective tissue problem, such as classic Ehlers-Danlos?                              And classic Ehlers-Danlos is fairly common, about one in 20,000 people. As far as our concern in the field of genetics, one in 20,000 is common, because we see rare diseases. So one in 20,000 is common. There's like six different categories of Ehlers-Danlos in classic and hypermobile form, vascular form, but he had the clinical findings, he and his son, and he had mutation of a gene that causes classic Ehlers-Danlos.                              So the thrust of this communication is, could it be that there may be a group of individuals that are on a heart transplantation service, waiting to be transplanted, that might have a connective tissue disorder, such as Ehlers-Danlos or one of the other connective tissue disorders, that could be an issue and a causation of their cardiac issues? We know that there are around 70 genes being recognized that cause connective tissue, and these numbers increase all the time as we learn more about genetics and the capabilities of testing. There are over 130 recognized genes that are thought to play a role in hereditary cardiomyopathies and there are now thought to be over 230 genes that are commercially available in a comprehensive cardiovascular next-generation DNA panels, and several of those genes are collagen genes.                              So we know there are hundreds of genes that play a role with cardiac health, I guess. Disturbance of those genes, several of those could be connective tissue. Obviously there's others involved, too ... myopathies and conduction issues. But the question I would have, the focus is, could there be a group that would have a connective tissue? And why is that important? Well, not only do they have issues when it comes to these multiple surgical concerns, but they may have, obviously, concerns that might be related to complications of surgery. We know that connective tissue disorders, they have poor wound healing, scarring and other tissue involvement such as vascular anomalies, aneurysms. So they become ... whether it's for cardiac procedures or whether it's orthopedic, whatever ... they become poor candidates for surgical intervention, for surgical operation procedures, because of the complications of surgery. Connective tissue, poor wound healing, scarring.                              And because connective tissue is involved in not only the skin, but involves internal organs such as the vessels, where you're concerned about aneurysms and vascular anomalies, that could be playing a role. So there may be more complications related to the surgical procedures than your typical patient who undergoes heart transplantation.                              So I think that would be important to know, so I would encourage, for the cardiology services, for patients that are on these transplant care and services, to consider a comprehensive genetic DNA analysis to look at connective tissues, as well as other causations of cardiac disease. As I mentioned, there's over 200 different genes been recognized now on comprehensive DNA testing panels related to cardiac and connective tissue problems.                              So, I would encourage that patients that are on the transplant list, they should undergo a next-generation detailed comprehensive connective and cardiovascular panel ... they're certainly available in several laboratory settings ... that might help lead to not only the diagnosis of the cardiac issues, but might help in medical management and monitoring and the surveillance, as well as the surgical interventions and care following the surgical procedures might be taking place.                              Frequently have an arterial wall might be a little fragile and obviously clamping during surgical procedures for an extended period of time might cause some trauma, even to a normal artery, let alone an artery that might be disorganized because of connective tissue problem. Dr. Ferguson:    Yeah. Dr. Butler:          So those complications might occur as well, too, during the procedure or following the procedure. Even there may not be any aneurysms going in, there might be a weakness of the arterial wall at the clamp site that could lead to an aneurysm following the procedure, so it needs to be monitored.                              So I'm just bringing these to the medical attention that may or may not be out there, but I want to bring this to ... You know, there have been over 90,000 heart transplants been done since 1983, at least that many, and there's 23 million people worldwide that are affected with congestive heart failure, and that's about 7.5 million people in North America. Dr. Ferguson:    Yeah. Dr. Butler:          So it's out there. Some of these genetic conditions are rare, but collectively they're common. Ehlers-Danlos, one in 20,000, is probably considered rare, but yet it still is not rare to the person that has it. Dr. Ferguson:    Right, right, and maybe enriched in these patient populations. So is this something you think that could be sort of found with more careful physical exams, or do you think that [crosstalk] genomic sequencing is sort of the best way to get at this? Dr. Butler:          Well, I think that Beighton scale we just mentioned, the hypermobility scale, just to see if there's, you know, if it's pretty common. Most adults can't put their palms on the floor when they're standing up. Dr. Ferguson:    I certainly can't. Dr. Butler:          That is usually not gonna happen for multiple reasons. But maybe some of the cardiologists are, but those that aren't, maybe they should consider, just check for hyperflexibility in their adult patient. [crosstalk] Dr. Ferguson:    Yeah, that seems like an easy [crosstalk] click-and-check, right? Dr. Butler:          Right. There being loose skins, poor scarring. You can ask the patient, obviously. Easy bruisability and poor scars, and it's pretty obvious in these conditions. I mean, on a physical exam it jumps out at you, particularly the multiple scars and bruising on the lower extremities with the pigmented because of iron deposits. You'll see that pretty clear in the scarring issues.                              And they'll tell you, too. I mean, the patients, they know. "Oh, yeah. I'm very hyperflexible." So you just ask the question and the patients will tell you. They say yes, and then it might need further testing physically; that is, actually do the exam and see if they have, on this Beighton scale, what the hyperflexibility score looks like. And if it is positive ... what we consider positive is five and above, five out of nine ... then those would candidates for a comprehensive DNA testing, whether it's related to cardiomyopathies, but I think connective tissue collection genes. Like I say, there's roughly 70 of these genes out there now that we test for in the commercial clinical laboratory setting. That should be monitored, as well as adding other genes if need be. So I'd encourage that.                              Physical examination number one. If it's positive, then check into a DNA panel for these types of disorders. It could help long-term for the care and outcome of the patient. Dr. Ferguson:    Yeah. I do think that's really important from the patient perspective and then, if more of these cases start being reported, I think it's very interesting also from the research perspective to find out what are the mechanisms that are potentially linking these mutations to cardiac disorders which have- [crosstalk] Dr. Butler:          That's true, and also realize that a lot of these patients have hypotension, and that can lead to some complications before, during and after surgical intervention, too. Dr. Ferguson:    Yeah. Dr. Butler:          So that's important to realize. Dr. Ferguson:    Very important. Yeah. So thank you for telling us about this interesting case and for raising this. I think it's an important issue and I'm sure a lot of the cardiologists and clinicians listening will start to look out for connective tissue disorders in their own patients. Dr. Butler:          I think, first thing is just ask questions. Are you hyperflexible? And they'll tell you. It's something that is very obvious to the patient. It will be obvious to the physician once he or she puts their hands on the patient, examine the patient, they realize, "Oh, this patient really is quite hyperflexible, digits and arms and knees and elbows," et cetera, et cetera. But, just ask the question, are they hyperflexible? If they say no, then the connective tissue is lower. It still could be. There could still be some aneurysms, those kind of things going on because there's, like I say, there's 70 genes, and there's six types of Ehlers-Danlos, so there's many other conditions out there that kind of look like an Ehlers-Danlos, but they're not. They may have another gene involving protein that's related to connective tissue, but not in the Ehlers-Danlos group of disorders or genes. Still could play a role. Could be similar. They may [inaudible] aneurysms, and that's important to know before they get into the procedures, too. Dr. Ferguson:    Yeah, really important, really interesting. Thank you so much for joining us.                              Thanks, everyone, for listening. And I wish you all the best for the holiday season, and a very happy new year. We're looking forward to bringing you lots more in 2019.                              This podcast was brought to you by Circulation: Genomic and Precision Medicine, and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association, 2018.  

Jane Ferguson:                Hello, welcome to Getting Personal: Omics of the Heart, Episode 22. This is a podcast from Circulation: Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. I am Jane Ferguson and it's November 2018.                                            Our first article comes from Carlos Vanoye, Alfred George and colleagues from Northwestern University Feinberg School of Medicine and is entitled, High Throughput Functional Evaluation of KCNQ1 Decrypts Variance of Unknown Significance.                                            So a major growing problem in clinical genomics is that following the identification of a variant that is potentially linked to a disease phenotype, without further interrogation, it's really hard to make sense of the functional significance of that variant. Right now, the large number of variants of unknown significance lead to confusion for patients and clinicians alike. To allow for accurate diagnoses and the best treatment plans, we need a way to be able to screen variants to assess their function in a fast and cost-effective manner.                                            In this paper, the authors decided to focus in the KCNQ1 gene, a cardiac ion channel, which can affect arrhythmias. They aim to assess whether a novel high-throughput functional evaluation strategy could identify functional mutations, as well as an in vitro electrophysiological approach. Which is effective, but expensive and time-consuming. Their approach capitalized on an existing automated electrophysiological recording platform that had originally had been developed for drug discovery essays.                                            They selected 78 variants in KCNQ1 and assessed their function using the High-Throughput platform, which coupled high efficiency, cell electroporation with automated plain or patch clamp recording. They compared the results to traditional electrophysiological essays and find a high rate of concordance between the two methods. Overall, they were able to reclassify over 65% of the variants tested, with far greater efficiency than traditional methods.                                            While this method will not work for all genes and phenotypes, the authors have demonstrated an efficient method for functional interrogation of variants. Which may greatly accelerate discovery and conditions such as Long QT or other congenital arrhythmias.                                            The next paper, Nocturnal Atrial Fibrillation Caused by Mutations in KCND2 Encoding Poor Forming Alpha Subunit of the Cardiac KV 4.2 Potassium Channel, comes from Max Drabkin, Ohad Birk, and colleagues at Soroka University Medical Center in Israel. This paper also focuses on cardiac ion channels and the role of mutations in atrial fibrillation.                                            In a family with early-onset peroxisomal AF across three generations, whole XM sequencing revealed a variant in KCND2 encoding the KV 4.2 Potassium Channel, which segregated consistent with autosomal dominant heredity. This variant resulted in a replacement of a conserved [inaudible] residue with an arginine. To investigate functional consequences of this novel variant, they conducted experiments in xenopos laevis oocytes and found that there is decreased voltage depended channel and activation and impaired formation of the KV 4.2 Homotetramer and the KV 4.2, KV 4.3 Heterotetramer.                                            Overall, this study shows that a novel mutation in a conserved Protein kinase C Phosphorylation site within the KV 4.2 Potassium Channel underlies the phenotypes observed in a family of peroxisomal atrial fibrillation. The targeting Atrial KV 4.2 might be an effective therapeutic avenue.                                            Next up, Michael Levin and Scott Damrauer and colleagues from the University of Pennsylvania published an article entitled, Genomic Risks Stratification Predicts All-Cause Mortality After Cardiac Catheterization.                                            They were interested in understanding the utility of polygenic risk scores for disease prediction. They constructed a genome Y genetic risk score for CAD and applied it to individuals from the Penn Medicine Bio-bank who had undergone Coronary angiography and genotyping.                                            They included over 139,000 variants for the 1,500 ancestry subjects who were included and classified them as high or low polygenic risk. Individuals who were classified as high polygenic risk were shown to have higher risk of All-Cause mortality than low polygenic risk individuals despite no differences in traditional risk factor profiles. This was particularly evident in individuals with high genetic risk but no evidence of angiographic CAD.                                            Adding the polygenic risk score to a traditional risk assessment model was able to improve prediction of five year All-Cause mortality. Highlighting the utility of a polygenic score and underscoring traditional risk factors do not yet fully capture mortality risk.                                            The next article entitled, "Bio-marker Glycoprotein Acetyls is Associated with the Risk of A Wide Spectrum of Incident Diseases and Stratifies Mortality Risk in Angiography Patients" comes from Johannes Kettunen, Scott Ritchie, Peter Würtz and colleagues from the University of Oulu Finland.                                            GlycA is a circulating biomarker that reflects the amount of Glycated proteins in the circulation. It has been associated with cardiovascular disease, Type 2 Diabetes, and all-cause mortality. In this paper, the authors used electronic health record data from over 11,000 adults from the finish general population previously included in the "FINRISK" and "Dilgom" studies and they tested for a associations between GlycA and 468 different health outcomes over an 8-12 year follow up. They report new associations between GlycA and multiple conditions including incident alcoholic liver disease, chronic renal failure, glomerular diseases, chronic obstructive pulmonary disease, inflammatory polyarthric disease and hypertension.                                            These associations held true even after adjusting for CRP suggesting that GlycA represents an independent biological contributor to inflammation and disease. Their findings highlight potential utility for GlycA as a biomarker of many diseases and underscore the importance future functional and mechanistic studies to understand how GlycA is linked to disease risk.                                            Our last original research article entitled, "Tissue Specific Differential Expression of Novel Jeans and Long Intergenic Non-coding RNAs in Humans with Extreme Response to Endotoxic glycemia comes from Jane Ferguson, Murdock Riley, and colleagues from Vanderbilt University, Columbia University, and the University of Pennsylvania. That first author is none other than me, so I'm not unbiased reader of this particular manuscript, but I'd like to tell you a little bit about it anyway.                                            We were interested in understanding the transcriptional changes that occur in tissues during acute inflammation. As part of the genetics of evoked responses to Niacin and Endotoxemia, or gene study, we recruited healthy individuals and performed an inpatient endotoxin challenge where we administered a low dose of LPS and looked at the systemic inflammatory response. Individuals vary greatly in the degree of their inflammatory response to LPS and we identified high and low responders, men and women, of African and European ancestry, who had responses in the top or bottom 10% for cytokines and fever.                                            We conducted RNA seek and adipose tissue in 25 individuals and CD-14 positive monosites for 15 individuals in pre and two or four hours post LPS samples. We found that the differences in transcriptional response between high or low responders are mostly explained by magnitude rather than discrete sets of genes.                                            So some core genes were altered similarly, in both groups, but overall the high responders mounted a large transcription of response to LPS or low responders rather than mounting an anti-inflammatory response actually just barely responded on the transcription level. We saw clear tissue specificity between manosites and adipose tissue we identified several long non-coding RNAs that were up or down regulated in response to LPS and validated these independent samples one of these link RNAs which we have now named Monosite LPs induced link RNA regulator vile six or Mahler Isle six, with highly regulated by LPs and monosites but not in adipose tissue.                                            We [inaudible] THP-1 monosites and find a significant effect on iOS six expression suggesting that this is a novel link RNA that regulates Isle six expression in manosites potentially through a cd-86 dependent pathway. Overall our data revealed tissue specific transcriptional of changes that correlate with clinical inflammatory responses and highlight the role of specifically incarnate and inflammatory response.                                            Next up is a research letter entitled "Reduced Sodium Current in Native Cardiomyocytes of a Regatta Syndrome Patient Associated with Beta Two Central Mutation" published by Constance Schmidt, Felix Wiedmann, Ibrahim El-Battrawy, Dierk Thomas, and co-authors from University Hospital Heidelberg. They obtained cardiomyocytes from a patient with Regatta Syndrome previous whole XM sequencing had implicated a variant in the Beta Two Syntrophin or "SNTB2" gene as potentially causal in this individual. Expression analysis showed lower SNTB2 expression and atrial tissue of the affected individual compared with controls.                                            They performed electrophysiology on the Microcytes and found reduced peak sodium density and reduced late sodium current. They co-express wild type or mutant SNTB2 in heck 293 T cells and [inaudible] with the cardiac sodium channel NAV-1.5 and found a significant effect on binding which adversely affected sodium currents. This study nicely demonstrates the functional effect of this SNTB2 mutation underlying Regatta Syndrome in this patient.                                            A second research letter comes from A.T. van den Hoven and Jolien Roos- Hesselink and colleagues from Erasmus University Medical Center in the Netherlands and is entitled "Aortic Dimensions and Clinical Outcome in Patients with SMAD three mutations, they were interested in understanding how the Aortic dilation comment individuals with SMAD three mutations compared to individuals with other syndrome and causes of Aortic dilation.                                            In 28 patients with SMAD three mutations, there were significant growth in the Sinotubular Junction the ascending Aorta on the diaphragm over an average of 10 years of follow up at reads far higher population averages but lower than might be seen in other syndromes, such as [inaudible]. Intensive management and preventive surgery and many of the patients prevented any mortality in this group.                                            Rounding out this issue is a clinical letter entitled "Concealed Arrhythmogenic  Right Ventricular Cardiomyopathy in Sudden unexplained Cardiac Death events from Jodie Ingles, Chris Semsarian, and colleagues from the University of Sydney, Australia. They report on for clinical cases where individuals presented in early adulthood with unexplained cardiac arrest, which was later found to be attributable to mutations in the PKP2 gene. PKP2 or, Plakophilin 2, encodes an integral component of the Desmosome, which is important and Cell-Cell adhesion. Further PKP2 is involved in transcriptional activation of genes controlling intracellular calcium cycling. This gene has been implicated arrhythmogenic right ventricular cardiomyopathy in individuals with cardiac structural abnormalities. These four cases where unrelated individuals were all fans to have loss of function variants and PKP2 underlying sudden cardiac death or events, despite structurally normal hearts. This prompts questions on the clinical management of such cases of concealed ARVC.                                            That's all from us for November, thanks to all of you out there listening. We'll be back in December for the final episode of 2018.                                            This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2018.                                             

Speaker 1:           Hi, everyone. Welcome to episode 21 of Getting Personal, Omics of the Heart from October 2018. I'm Jane Ferguson, an Assistant Professor at Vanderbilt University Medical Center and an Associate Editor at Circulation: Genomic and Precision Medicine. We have a great issue this month. So, let's dive straight in. First up, an article on "Loss-of-Function ABCC8 Mutations in Pulmonary Arterial Hypertension" from Michael Bohnen, Wendy Chung and colleagues from Columbia University. In pulmonary arterial hypertension, or PAH, compromised pulmonary arterial function can raise pressure in the pulmonary artery which leads to increased pulmonary vascular resistance. This ultimately results in right heart failure. While PAH is relatively rare, it has a high rate of mortality. Some genetic underpinnings have been identified, notably the KCNK3 gene identified by the same research group where they find that mutations result in potassium channelopathy. However, here the authors hypothesized that other genetic contributors also exist and that identification of these could highlight new therapeutic targets to improve treatment and outcomes in PAH. In their study, the authors performed exome sequencing for discovery of novel disease variants in 233 PAH patients, 99 of whom had pediatric-onset and 134 with adult-onset. They sequenced a replication sample of 680 individuals with adult-onset PAH. They found a de novo missense variant in the ABCC8 gene in one patient and then found 10 more ABCC8 variants in other unrelated patients in the discovery and replication samples. Half of these were novel mutations and all were located in conserved regions and predicted to be deleterious. They screened over 33,000 subjects from the Exome Aggregation Consortium and over 49,000 from the Regeneron-Geisinger DiscovEHR study and found significant overrepresentation on rare ABCC8 variants in the PAH cases compared with population controls. ABCC8 encodes sulfonylurea receptor ... part of the potassium ATP channel. The authors determined that it is expressed in lungs in both PAH and healthy individuals and is particularly localized to alveolar macrophages and proximal pulmonary arteries. They expressed eight of the newly discovered ABCC8 mutations in COS cells, which are a monkey-derived, fiberglass-like cell line and they assessed the effects on function. They used patch-clamp experiments to assess potassium ATP channel activity and recorded efflux rates of Rubidium-86. Every mutation was associated with impairments in one or both functional assays, suggesting that mutations in ABCC8 are responsible for PAH by a modulating potassium channel function and flux. An existing drug, Diazoxide, targets ABCC8 and has anti-hypertensive and insulin-lowering effects. The authors find that all mutants were pharmacologically activated by Diazoxide in the functional assays. Now, whether this drug would be safe or effective in PAH remains unknown, but these findings open up targeting of ABCC8 as a possible treatment in PaH and highlight the importance of potassium channels in PAH. Our next paper also used whole-exome sequencing for novel discovery. Marzia de Bortoli, Alessandra Rampazza and colleagues from the University of Padua in Italy published "Whole-Exome Sequencing Identifies Pathogenic Variants in TJP1 Gene Associated With Arrhythmogenic Cardiomyopathy". Arrhythmogenic Cardiomyopathy, or ACM, is one of the most common causes of sudden unexpected death in athletes and young people. It is known to be frequently caused by mutations in genes encoding mechanical junction proteins of the intercalated disks within the cardiac muscle. However, some individuals with ACM do not have any mutations in known genes. This research group was interested in finding novel causal gene mutation and they use whole-exome sequencing to identify mutations from a single patient in Italy. They used InSilica tools to screen for potentially damaging mutations which brought their list of candidate mutations down to 52 and this was topped by a novel mutation in the TJP1 gene which was predicted to be highly deleterious using various algorithms. Using Sanger sequencing, they found that this mutation was also present in several family members. A second mutation in TJP1, also predicted to be damaging, was identified in a second Italian family. They then screened a sample of 43 Dutch and German subjects diagnosed with ACM and found that, once again, mutations in TJP1 topped the list as predicted to be damaging. The TJP1, or tight junction protein 1, encodes the intercalated disk proteins ZO1. The identified mutations may affect folding and local interactions within the protein, affecting protein-protein interactions and gap junction organization. Well, within this paper, they were not able to fully disentangle the mechanisms linking these mutations to disease, given that the prevalence of TJP1 mutations in their ACM samples was almost 5%. Screening for TJP1 mutations in ACM cohorts may identify many additional affected subjects. Further research into TJP1 is needed to identify how these variants may cause ACM. If you want to read more about this paper, you can check out the accompanying editorial from Jason Roberts ... Western University, Ontario ... in this same issue. Next up is a paper from Natsuko Tamura, Yasuhiro Maejima, Mitsuaki Isobe and colleagues from Tokyo Medical and Dental University entitled "Single-nucleotide Polymorphism of the MLX Gene Is Associated With Takayasu Arteritis". Takayasu Arteritis, or TAK, is an autoimmune disease causing aortic vasculitis that is poorly understood and disproportionately affects young Asian women. In previous genome-wide associations, study of TAK in Japanese individuals conducted by this group, indicated SNPs in the MLX gene. In this paper, the authors aim to identify mechanisms linking MLX mutations with TAK. The top GWAS SNP rs665268 is a missense mutation causing L-Glutamine Arginine substitution in the DNA binding site of MLX. They found that this SNP was associated with severity in disease in TAK. With additional copies of the risk alleles associated with more severe aortic regurgitation and greater number arterial lesions. In mice, the highest expression of MLX was found in the aortic valves. Using crystallography, they found that the missense mutation likely stabilizes a complex formed between MLX and MondoA. Immunoprecipitation experiments confirmed that the missense mutation was associated with enhanced MLX MondoA heterodimer formation and MLX transcriptional activity. This resulted in upregulation of TXNIP and higher TXNIP expression is associated with increased intracellular oxidative stress and the authors found for increased oxidative stress in cells carrying the MLX mutation. Further, additional cell experiments showed evidence of this MLX mutation reduces autophagy and stimulates inflammasome activation. Overall, through a series of really elegant experiments, the authors demonstrate that a missense mutation in MLX leads to inflammasome activation and accumulation of cells within the aorta, potentially underlying the pathophysiology seen in TAK patients and highlighting novel causal pathways that may be probed therapeutically.regular Our next paper from Danxin Wang, Wolfgang Sadee and colleagues from the University of Florida and The Ohio State University, also delves into the functional impact of disease-associated SNPs. In their paper, "Interactions Between Regulatory Variants in CYP7A1 Promoter and Enhancer Regions Regulate CYP7A1 Expression", they used a series of experiments to demonstrate how SNPs in CYP7A1 ... which have been associated with cholesterol and cardiovascular disease ... are related to gene function. CYP7A1 is a gene which coordinates a key pathway for cholesterol removal from the body because it encodes an enzyme which is rate-limiting for bioassay synthesis from cholesterol. Although several SNPs in the gene have been associated with cardiovascular phenotypes, the reported effects on gene function have been inconsistent and/or unclear. Because of the linkage disequilibrium between SNPs, it has been hard to understand which SNP or SNPs are actually functional. What this team set out to do was to systematically screen functionality of individual CYP7A1 SNPs to understand the independent effects of each functional variant. First, they used chromatin conformation capture, or 4C assay, to identify regions that associated with a CYP7A1 promoter. They found three distinct regions with evidence of enhancer function and [phonetic 00:09:05] active A>G regulation. They, next, used CRISPR Cas9 to delete each of the three regions in HepG2 cells and assess effects on CYP7A1 expression. One region had no effect, while one led to increased expression and one led to decreased expression ... thus, identifying the presence of both enhancer and repressor regions. Using reporter gene assays, they confirmed the effects seen in CRISPR experiments. Based on reported SNP associations, they narrowed down candidate functional SNPs within the regions and constructed reporter assays containing haplotypes of potential functional SNPs. They were able to identify two SNPs acting together to determine differences in CYP7A1 gene expression. Because these SNPs are in LD, but the minor alleles have effects in opposite directions, considering genotype at both SNPs is required to understand the effects on gene expression. This explains why previous studies found inconsistent results. Both during the functional experiments, they went to human samples and they assessed the combined effect of the two SNPs on clinical phenotypes. Designating people as high or low activity based on the two SNPs, they found significant differences in cholesterol and in the likelihood to reach cholesterol targets on statin, as well as in the risk of MI. This paper is a lovely example of how careful functional interrogation can tease out a complex problem and I think it highlights how much more of this type of work needs to be done for the many other genomic regions with confusing or discord in associations. The last full-length article concerns the "Effect of Ascertainment Bias on Estimates of Patient Mortality in Inherited Cardiac Diseases" and comes from Eline Nannenberg, Imke Christiaans and colleagues at the Academic Medical Center, Amsterdam. They were interested in how much ascertainment bias and the tendency to publish findings from more severe disease cases affects the mortality estimates that are used to guide clinicians and genetic counselors when helping patients understand their disease prognosis. They revisited three inherited cardiac diseases including idiopathic ventricular fibrillation associated with a mutation in DPP6, SCN5A overlap syndrome associated with SCN5A mutations, and Arrhythmogenic Cardiomyopathy caused by a founder PLN mutation. They analyzed mortality over 2-10 years of clinical screening and cascade screening and found that the median age of survival quickly increased in all three conditions. In many cases, the reason that a mutation was identified was because of severe disease in that patient or family, but as the authors highlight here, this can bias publications towards associating the variant with more severe phenotypes and higher mortality. Following up the initial findings with additional screening and tracking of affected individuals is important to subsequently give a more accurate estimation of the effect of the mutation which can be used to inform treatment plans. Moving on to this month's research letters, Catherine Hajek, Jerome Rotter and colleagues from LA BioMed and the University of South Dakota, published the results of their study, "A Coronary Heart Disease Genetic Risk Score Predicts Cardiovascular Disease Risk in Men, Not Women: The Multi-Ethnic Study of Atherosclerosis". The genetic risk scores are being increasingly applied to estimate disease risk in individuals. However, these scores are based on the GWAS discovery from specific populations which have often been disproportionately male and with individuals of European ancestry. In this letter, the authors wanted to understand whether coronary heart disease genetic risk scores performed the same in men and women of European ancestry. Using data from the MESA Study, they applied a 46 locus genetic risk score to over 2500 individuals. In men, this risk score was strongly associated with event rates. However, in women, there was no association. Given the known differences in disease pathophysiology and manifestation between men and women, this finding additionally highlights the need to conduct genetic studies in underrepresented groups so that we can design scores that accurately predict risk within specific groups. Our next letter comes from Xiao Wang and Kiran Musunru at the University of Pennsylvania ... "Confirmation of Causal rs9349379- PHACTR1 Expression Quantitative Trait Locus in iPSC Endothelial Cells". They were interested in understanding the affect of a coronary disease SNP in the PHACTR1 gene on gene expression. Previous efforts to investigate this had yielded conflicting results showing either a significant eQTL effect for PHACTR1 and vascular tissue or no effect on PHACTR1, but an effect on a distal gene EDN1 in endothelial cells. For this study, the authors used CRISPR Cas9 to introduce the SNP to iPS cells and then expanded isogenic lines at the major and minor allele homozygous and differentiated these into endothelial cells. They find that the major allele was associated with significantly higher factorial expression, but no difference in EDN1 expression. Thus, based on these experiments, it appears that PHACTR1 may indeed be the causal gene in that region underlying the GWAS signal and whether or not EDN1 is involved remains unclear. Our next letter is a clinical letter from Nosheen Raza, Anjali Owens and co-authors at the University of Pennsylvania. They report on "ACTA1 Novel Likely Pathogenic Variant in a Family With Dilated Cardiomyopathy". In this case report, they describe that the discovery of a mutation in ACTA1 in a family with dilated cardiomyopathy, but no skeletal muscle symptoms. As a gene that is predominantly expressed in skeletal muscle, ACTA1 mutations have previously been associated with skeletal muscle myopathies and would not have been expected to cause cardiac symptoms in the absence of skeletal muscle dysfunction. However, sequencing suggests that this variant is a causal mutation in this family, highlighting the need to consider potential mechanisms for cardiac muscle specifics of highly expressed skeletal muscle genes. Our second clinical letter comes from Laura Zahavich, Seema Mital and co-authors from the Hospital for Sick Children in Ontario. They report a "Novel Association of a De Novo CALM2 Mutation With Long QT Syndrome and Hypertrophic Cardiomyopathy". They report finding mutation in the calcium transporter CALM2 gene in the child who presented with hypertrophic cardiomyopathy and ultimately died from sudden cardiac death. While this patient also had some variants of un-insignificance, the CALM2 gene is highly conserved and mutations are likely to be pathogenic. The CALM2 is not on all of the clinical genetic testing panels and in this case, whole-exome sequencing was required to identify a mutation. CALM2 have been described in other individuals and together with the findings reported here, there's compelling evidence for inclusion of CALM2 on cardiomyopathy in clinical testing panels. This issue also contains a perspective article from Michael Mackley, Elizabeth Ormondroyd and colleagues from the University of Oxford entitled "From Genotype to Phenotype: Clinical Assessment and Participant Perspective of a Secondary Genomic Finding Associated with Long QT Syndrome". They describe some of the challenges arising from more widespread genetic testing including how to deal with incidental findings. A larger number of people including apparently healthy individuals are receiving sequencing results that highlight potential disease-related mutations, but with varying penetrance and uncertain effects. This perspective paper highlights the issues through case study and discusses future directions and challenges in this rapidly growing area. Finally, we ride out this issue with an AHA scientific statement on "Cardiovascular Health in Turner Syndrome: A Scientific Statement From the American Heart Association" led by Michael Silberbach and Jolien Roos-Hesselink and a group of co-authors representing the American Heart Association Council on Cardiovascular Disease in the Young; Council on Genomic and Precision Medicine; and Council on Peripheral Vascular Disease. In this statement, they discuss the cardiovascular complications that commonly occur in girls and women Turner syndrome. Cardiovascular disease contributes significantly to premature death in individuals with Turner syndrome. Because of the unique nature of the cardiac presentations in Turner syndrome, better clinical guidelines are needed to improve diagnosis and treatment of [phonetic 00:17:26] ischemia in these individuals. This statement takes a first step to outline suggestions to improve clinical practice and highlights the work that still remains to be done to inform disease management. That rounds out the October issue of Circulation: Genomic and Precision Medicine. Thanks for listening! You can go online to ahajournals.org/journal/circgen to access the latest issue and browse previous issues. As a last reminder, AHA Sessions is approaching fast and I hope to see many of you in Chicago, November 10-12. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is Copyright American Heart Association, 2018.  

Jane Ferguson: Hi everyone. Welcome to episode 20 of Getting Personal Omics of the Heart, the podcast brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Council on Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University. It's September 2018 and let's dive straight into the papers from this month's issue of Circulation: Genomic and Precision Medicine.                                 We're starting off with some pharmacogenomics. Bruce Peyser, Deepak Voora and colleagues from Duke University published an article entitled, "Effects of Delivering SLCO1B1 Pharmacogenetic Information in Randomized Trial and Observational Settings."                                 Although statins are generally well tolerated, 5-15% of patients taking statins for LDL lowering and cardiovascular protection end up developing statin associated muscular symptoms. Because onset of muscular symptoms associated with discontinuing statin use, as well as increased cardiovascular morbidity, there is a clear need to identify ways to prevent or reduce symptoms in these people. Variants affecting statin related myopathy have previously been discovered through GWAS, including a variant in the SLCO1B1 gene, which also has been shown to relate to statin myalgia and discontinuation of statin use. The risks appear to be greatest with simvastatin, indicating the people at risk of muscle complications may do better on either low-dose Simvastatin or another statin. However, there's still some uncertainty surrounding the risks and benefits of various statins as they pertain to risk of muscular symptoms.                                 The authors have previously shown that pharmacogenetics testing led to increased number of people reporting statin use, but effects of pharmacogenetic testing on adherence, prescribing, and LDL cholesterol had never been tested in a randomized control trial. In this study, they randomized 159 participants to either genotype informed statin therapy or usual care, and then followed them for months to eight months.                                 25% of participants were carriers of the SLCO1B1 star five genotype. The authors found that statin adherence was similar in both groups, but gene type guided therapy resulted in more new statin prescriptions and significantly lower LDL cholesterol at three months, and levels that were lower but no longer significantly different at eight months.                                 In individual's randomized to usual care who then crossed over to genotype informed therapy after the trial period ended, there was an additional decrease in LDL cholesterol. Overall, genotype informed statin therapy led to an increase in re-initiation of statins and decreases in LDL cholesterol, but did not appear to affect adherence.                                 The authors also examined the effects of commercial genetic testing for SLCO1B1 variants in an observational setting by looking at over 92000 individuals with data available in the EHR. They found the people who receive genetic testing results had a larger drop in LDL cholesterol compared to untested controls. Overall, the study indicates that carriers of the SLCO1B1 risk variant may benefit from genotype informed statin therapy, while for non-carriers receiving their results may has limited effects.                                 If you want to read more on this, Sony Tuteja and Dan Rader from UPenn wrote an editorial to accompany this article, which was published in the same issue.                                 We're staying on the topic of statins and LDL for our next paper. This article comes from Akinyemi Oni-Orisan, and Neil Risch and colleagues from the University of California and is entitled, "Characterization of Statin Low-Density Lipoprotein Cholesterol Dose-Response Utilizing Electronic Health Records in a Large Population-Based Cohort."                                 They were interested in understanding what determines variation in statin induced LDL reduction, particularly the genetic component, and they used a large EHR derived data set, the Kaiser Permanente Genetic Epidemiology research on adult health and aging cohort to address this important question. An EHR dataset does have intrinsic limitations, but also has some clear strengths, not only as a readily available and cost-effective data source for large sample sizes, but also because it reflects real world clinical care in diverse individuals, which is not always well represented within the selective constraints of a randomized trial.                                 There were over 33000 individuals who met their inclusion criteria. To account for differences in potency between different statins and doses, the authors generated a defined daily dose value, with one defined daily dose equal to 40 milligrams per day of Lovastatin. The slope of the dose response was similar across statin types and across different sex and race or ethnicity groups. But there were differences by statin type in the response independent of dose, as well as differences in absolute responses by sex, age, race, smoking, and diabetes.                                 Based on these differences, the authors revised the defined daily doses and they highlight how previously defined equivalencies between different statins may not be accurate. They found that individuals with East Asian ancestry had an enhanced response to therapy compared with individuals of European ancestry.                                 The authors identified related individuals within the data set and the estimated heritability of statin response using parent-offspring and sibling pairs. They found only modest heritability, indicating that non-genetic factors may be more important in determining variability in statin response. Overall, this large single cohort study adds to our knowledge on determinants of statin response and raises further questions on the relative effects of different statins and doses within patient subgroups.                                 Okay, so now let's talk about GWAS and Athero. Sander van der Lann, Paul de Bakker, Gerard Pasterkamp and coauthors from University Medical Center Utrecht published a paper entitled, "Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques."                                 Over the past decade, genome-wide association studies in large cohorts have been very successful in identifying cardiovascular risk loci. However, relating these to subclinical disease or two mechanisms has been more challenging. The authors were interested in understanding whether established GWAS loci for stroke and coronary disease are associated with characteristics of atherosclerotic plaque, the idea being that some of the risk loci may alter disease risk by determining the development and stability of plaque. They identified seven plaque characteristics to study and histological samples, including intraplaque fat, collagen content, smooth muscle cell percentage, macrophage percentage, calcification, intraplaque hemorrhage, and intraplaque vessel density.                                 They selected 61 known loci and examined association of those SNiPA with black phenotypes in over 1400 specimens from the athero express biobank study. Out of the 61 loci, 21 were associated with some black phenotype compared with zero of five negative control loci, which were chosen as established GWAS loci for bipolar disorder, which, presumably, should share limited mechanistic etiology with plaque. They used the software package VEGAS to run gene-based analyses. They also assessed SNiPA relationships with gene expression and methylation in multiple tissues derived from two independence Swedish biobanks, which included atherosclerotic arterial wall, internal mammary artery, liver, subcutaneous fat, skeletal muscle, visceral fat, and fasting whole blood.                                 One CAD locus on chromosome 7q22 that survived correction for multiple testing was associated with intraplaque fat, and was also an EQTL for expression of several genes across multiple tissues. In addition, it was also a methylation QTL.                                 The authors focused on this locus and looked at correlation of expression within the LDL receptor and noted associations with HDL and LDL cholesterol in the global lipids genetics contortion data, which suggests that this locus may have a role in the metabolism. At this locus, the HBP1 gene expressed foam cells may be an interesting candidate as a causal gene in determining plaque-lipid accumulation and cardiovascular risk.                                 So next up, we have a paper that is also about athero and is coauthored by many of the same group as did that previous study. So yeah, this group's productivity is kind of making the rest of us look bad this month. So Martin Siemelink, Sander van de Lann, and Gerard Pasterkamp and their colleagues published, "Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions."                                 Okay. So I think one of the few things we can all definitely agree on is that smoking is bad. But, does smoking exert any of its cardiovascular damage by altering within atherosclerotic plaques? That's the question this group set out to answer.                                 They carried out a two-stage epigenome-wide association study, or EWAS, with discovery and replication of differentially methylated loci with tobacco smoking within carotid arteriosclerotic plaques of a total of 664 patients undergoing carotid endarterectomy and enrolled in the arthero-expressed biobanks study. In discovery, they found 10 CpG loci within six genes that associated with smoking. Four of the CpG loci replicated. These four loci mapping within six genes showed reduced methylation in current smokers compared with former or never smokers.                                 However, there was no difference in specific plaque characteristics based on methylation at any of the four loci. There was also no significant difference in plaque gene expression at these loci based on smoking status. However, a SNiPA at a nearby locus located in the 3' UTR of the PLEKHGB4 Gene was associated with methylation at AHRR, and was a [inaudible 00:09:58] QTL for PLEKHGB4 of expression but not a AHRR expression. The authors speculate that PLEKHGB4 may co-regulate AHRR expression. The authors also examined blood methylation in a subset of the same subjects, and they were able to replicate previously identified CPG sites associated with smoking.                                 This is a really complex area, and it's hard to identify mechanisms and causality from these multiple layers of data, but the authors demonstrate the importance of using disease relevant tissues to start to understand how environmental factors interact with genetics and other underlying physiology to modify methylation and function within the vasculature.                                 Our final full-length research paper this issue from Brian Byrd and colleagues Michigan, is actually the subject of our interview today. So I won't go into too much detail on it right now, but keep listening for an interview with Brian about their paper, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension."                                 Our review article this month is about the "Dawn of Epitranscriptomic Medicine" from Konstantinos Stellos from Newcastle University and Aikaterini Gatsiou from Goethe-Universität Frankfurt. In this paper, they're taking us to the next level beyond just RNA, but towards RNA epigenetics. Given the large number of possible modifications that can and are made to RNA during RNA name metabolism, there's huge potential to gain a new biological and mechanistic understanding by studying the RNA epitranscriptome. I think we'll ignore this at our peril. So if you need to catch up on this new field, this comprehensive review will get you right up to speed.                                 Moving on, our research letters are short format papers that allow authors to present focused results. These are also a great avenue to submit findings from replication studies that might not necessitate a full-length paper. So if you have some data from a replication study that you've been procrastinating writing up, a short research letter is a great format to consider.                                 This month, Bertrand Favre, Luca Borradori and coauthors from Bern University Hospital published a letter entitled, "Desmoplakin Gene Variants and Risk for Arrhythmogenic Cardiomyopathy: Usefulness of a Functional Biochemical Assay." The desmoplakin is essential for the cell-cell adhesion complex's desmosomes. Mutations in this gene have been associated with a wide range of phenotypes, including some in skin and hair, but also in heart, which can manifest arrhythmogenic or dilated cardiomyopathy. This protein anchors intermediate filaments, so mutations that alter binding to intermediate filaments may pathogenicity.                                 The author selected seven reported amino acid altering mutations in desmoplakin, and they screened for effects on binding using a novel fluorescence binding assay. They found that three of the seven mutations had a clear impact on binding. This assay is a novel way to assess functional impact of desmoplakin variants, and may be useful to inform the severity of future phenotypes in individuals carrying a desmoplakin mutation.                                 Finally, if you want to stay up-to-date on the genetics of aortic disease and Marfan syndrome, you can find a letter from Christian Groth and colleagues and an author response from Norifumi Takeda and colleagues regarding their previously published paper on impact of pathogenic FBN1 variant types on the progression of aortic disease in patients with Marfan syndrome.                                 I am joined today by Dr. Brian Byrd from the University of Michigan, who is the senior author on a Manuscript published in this month's issue, entitled, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension."                                 So welcome Brian. Thanks so much for coming on the podcast. Brian Byrd:          Thank you for having me. Jane Ferguson: So before we get started, could you give a brief introduction of yourself to the listeners and maybe tell us a little bit about how you got into the field? Brian Byrd:          Absolutely. So I am a cardiologist and a physician scientist. I'm an assistant professor at the University of Michigan, where I have a laboratory engaged in clinical investigation. My background is that I did my Internal Medicine Residency at Vanderbilt University. And after I finished residency, I entered Nancy Brown's lab. She's the Chair of Medicine at Vanderbilt, as I know you're aware. And she had a laboratory focused, and still does have a laboratory focused, on the investigation of high blood pressure, with a lot of focus on understanding high blood pressure as it occurs in humans. And I got a Master of Science degree in clinical investigation while I was in her lab, and we did some work on a number of topics related to the renin-angiotensin-aldosterone system, which has been a long-standing interest of mine ever since then.                                 So, at the same time, I was learning how to take care of patients with very complex blood pressure problems, who required three, or four, or five, or six blood pressure medications, in some cases, to control. And it's with that background that I became very interested in the science that underlies treatment-resistant high blood pressure in people and what we might be able to do about that. Jane Ferguson: Wow. Nice. Yeah and I think that background of sort of the combination of clinical and experimental is really nice and really important. I think your paper actually exemplifies that really nicely, so using humans but also some basic science techniques and combining them to really have a very patient focused instead of mechanistic interrogation.                                 So as I mentioned, you just published this really nice manuscript using urine as a source of mRNA biomarkers, which has relevance to hypertension and potentially also to other diseases. But before we get sort of too much into the weeds on the specific details, for any of our listeners who didn't get a chance to read your paper yet, maybe you could briefly summarize what you did? Brian Byrd:          Okay, so the general overview of what we were interested in was that the patients who have treatment resistant high blood pressure tend to have a lot of activation of a receptor in the kidney called the mineralocorticoid receptor. And this receptor helps control salt in bladder in the body. Obviously the amount of salt in the blood stays very, very homeostatic, but we if eat more salt one day then the next and there needs to be a system to help regulate the homeostasis. And so, you waste more or less salt in the urine depending upon how much sodium you're taking in.                                 And one of the functions of the mineralocorticoid receptor is to control this salt and bladder regulation or to fine tune it anyway. And the reason we know that that's an important receptor in patients with treatment-resistant high blood pressure is because of a series of studies done by David Calhoun and Brian Williams and others, showing that mineralocorticoid receptor blockers, or antagonists, are very effective in the treatment of tough to control high blood pressure.                                 And so, we had some insight that there would be something interesting to study there, and one of the things that we knew was that the mineralocorticoid receptor is a ligand activated transcription factor. So when it gets activated by it's ligan which canonically is a steroid hormone from the adrenal gland aldosterone, the receptor, which is in the cytoplasm, ordinarily dimerizes and translocates to the nucleus, where it controls the regulation of a number of genes. We also were aware that cells secrete RNA, and others had the idea that it might be inside vesicles because there's a lot of ribonuclease and biofluids. And you would think it might be difficult to pass the RNA if it were sort of naked as it were.                                 And it turns out that that's right. If you, for example, introduced synthetic RNAs into biofluids, the RNAs will be gone very quickly in a matter of seconds. So, we had this idea that we might be able to look at RNA that was being secreted by cells probably in vesicles, and assay the activity of the receptor potentially. We weren't sure if that was going to be possible or not.                                 One of the things we did was we used part of the available data to look at the transcriptome of vesicles in the urine that had been isolated from 3300 milliliters of urine by ultracentrifugation [inaudible 00:18:57]. Jane Ferguson: So it's a big centrifusion. Brian Byrd:          Exactly. Jane Ferguson: Like you [inaudible 00:19:00] Brian Byrd:          It must have been some project. So that was the work of Kevin Miranda and colleagues, and we were able to compare that transcriptome to the transcriptome of human kidney cortex samples from the GTEx project, which a large consortium focused on human transcriptomics.                                 And that was sort of the first part of what we presented in this paper, and the second thing that we did was we looked within a crossover study in a collaboration with Scott Hummel, one of my close collaborators here at the University of Michigan. We looked at individuals who had been put on a low salt diet activating renin-angiotensin-aldosterone system and causing more activation of the mineralocorticoid receptor. And then, those same individuals underwent saline infusion, so salt loading, and we knew that that would suppress the renin-angiotensin-aldosterone system. And we measured the [inaudible 00:20:02] measures of the renin-angiotensin-aldosterone system, but we also took the urine samples that had been recently banked from that experiment and we centrifuged them to try to palette the cells. We took the supernatant and we extracted RNA after trying to enrich for extracellular vesicles.                                 And with that approach, we measure targets that we thought would be regulated my the mineralocorticoid receptor, as well as some things that we did not think would be regulated by mineralocorticoid receptor. So that's the general overview of what we undertook. Jane Ferguson: Great. Right. So it's very cool. I guess we can break it down into sort of the two different parts, because I think it was a really nice examples of using public data to sort of start addressing your question and then actually doing a human experiment. But so for the GTEx data and the urinary data, you looked at few different tissues, right? And was kidney the one that you were thinking upfront would sort of most likely to correlate, or were you also looking at bladder and other sort of tissues that could potentially be of relevance to urine? But what sort of the ... I guess sort of tell me more about those different tissues that you looked at and what you found and what surprised you or not. Brian Byrd:          Great question. So, the kidney was on our minds from the outset. We knew that Mark Knepper at the National Institute of Health had published in the [inaudible 00:21:25] National Academy of Sciences back in 2004 that there are urinary extracellular vesicles. And he had found proteins that are very characteristic of the aldosterone sensitive distal nephron, that part of the kidney that we're interested in, embedded in the vesicles.                                 So we became quite interested in the idea that it seemed that there was likely a population of vesicles in the urine that is of kidney origin. And that's not to say that there weren't also plenty of vesicles from other origins as well, and there could very well be RNA that is not vesicle enclosed, but is rather ribonucleic protein bound or even bound to other carriers potentially. That could be there as well, and it's possible that the origin of those things could be any number of tissues. I don't really think that we know yet where the possible tissue origins are.                                 But we were curious to know ... I guess the direct answer to your question is we thought from the outset that we probably would find some sort of signal related to the kidney. But we wanted to also consider the possibility that our findings were not very specific to the kidney. And so we thought that the brain would be an interesting negative control. If we say very high correlation with the brain, it would suggest that maybe what we're looking for is a signal that's not really coming from the kidney.                                 And we also wanted to look at the bladder just to try to understand whether or not the signals that we're detecting could be coming from the bladder. It's certainly true that some aspects of the system that we're interested in are present in the bladder, so I wondered whether that might even serve as a signal amplifier for what we were looking for since there's, presumably, quite a bit of bladder tissue right around the urine. It might be contributing vesicles.                                 So that's sort of the rationale for why we looked at those things. Jane Ferguson: And you found mostly enrichment for kidneys. So sort of I guess what you were hoping to find came true? That actually there was sort of evidence that even though there may be contribution from other tissues, that really kidney seem to be the predominant contributor to the expression of the genes in the urine. Brian Byrd:          I think there's a lot of truth to that. One of the things I would say is we found high correlation looking across all genes. But it occurred to us ... As soon as we thought that, we realized, wait a second, that could be driven by ubiquitously expressed genes. Housekeeping genes.                                 So we really wanted to stratify our analysis by things we thought would be expressed in the kidney as well as things that we thought would be ubiquitously expressed to make sure that we could see signals that correlate ... That the transcriptome of the kidney, per se, had a good correlation with those same in terms of the abundance of the gene counts or recounts. They said it was similar to what was in the vesicles.                                 And so, we looked in the literature, and we found that a group had already established a number, 55 genes actually, that were highly kidney enriched as well as over 8000 genes that were ubiquitously expressed. And so we started the analysis from this perspective of the stratification. We thought that was a very important aspect of the analysis. And it's definitely true that if you look at our findings with respect to the kidney enriched genes, as you might expect, they correlate quite well with what is in the urinary extracellular vesicles compared to the kidney cortex.                                 You look at the brain as you might expect the expression of those kidney enriched genes is not well correlated with what's happening in the urine. And then, with respect to the bladder, it's sort of somewhere in between. Jane Ferguson: Okay. Interesting. So I know that some people look at small non-coding RNAs in urine, but you were mostly focused on mRNAs. Is that right? Brian Byrd:          That's right. I thought of this as sort of frontier, something that I knew from some early publications was probably measurable. But I didn't know what it would signify, if anything, with respect to physiology. And I knew that there were quite a few papers about micro RNAs and I wanted to do something a little bit innovated, partly.                                 But the main reason that I was interested in the RNAs was because I could relatively easily tie those to the existing literature from animal models. Preclinical animal models and cell culture studies showing what happens when the mineralocorticoid receptor's activated. That was really the driving reason that I was interested in the RNA. Because if you think about what is the approximate event that might be a readout for activation of a new growth hormone receptor like the mineralocorticoid receptor, it's really the transcriptional events that happen when the receptors translocates to the nucleus and serves its ligan activated transcription factor role. Jane Ferguson: Right. So, [inaudible 00:26:43] sort of the first part of analysis, you saw these really nice correlations between expression and kidney and in urine. And then, a lot of the times when you tried to publish that kind of thing, people are like, "Okay, so what? So you didn't do any intervention. We don't really know what that means."                                 But I like that you took it to the next step and you did sort of a human intervention experimental model. So tell me more about that model and how that worked. Brian Byrd:          Right. Well, I'll just mention also that the work that was done in terms of RNA [inaudible 00:27:14] was done in collaboration with Mark Bertini in Italy as well as Dr. [inaudible 00:27:19]. They were fundamental to getting that work done.                                 With respect to the collaboration with Scott Hummel, one of my colleagues here at the University of Michigan, what we did in that setting was to look at whether or not we could identify within these urinary mRNA signals that are in the supernatant in the urine, whether we could identify changes in physiology. That was the question that was of greatest interest scientifically.                                 And for a very practical or blind perspective, the question was could we detect the activation of the receptor that might determine whether or not people should get a certain medication. Of course, we're not saying that that's an established fact yet, but this is sort of concept, that there's something here to explore further.                                 And so, what we found was that a number of genes that are regulated by the mineralocorticoid receptor, including genes encoding the subunits of the amiloride-sensitive epithelial sodium channel that regulates the salt that I was talking about earlier. We found that those genes changed with sodium loading in terms of their abundance in the expected direction.                                 We also found that several of the assays that we made changed ... I'm sorry. That they correlated with the serum aldosterone concentration. So the concentration of the ligan for the receptor whose readout we were looking for. And we also noticed an inverse correlation with urinary sodium excretion, which is what we would expect if we really identified a readout of the mineralocorticoid receptor's activity.                                 So this study supported the idea that we have identified a way to measure this nuclear hormone receptors activity in living humans. Jane Ferguson: Right. Which is really nice. So there's probably a huge amount of extra things you could do with this, some sort of different ways you could look at it. So how did you pick the time point? So, I suppose when you think about it, I mean the genes, they're transcribed and then that takes a little bit of time, and then it takes a little bit of time for that to sort of make its way into the urine and to be excreted.                                 So how did you decide on sort of what time points to use, and do you think you would see the same things or different things [inaudible 00:29:39] if you did repeated sampling or if you looked at different time points? Brian Byrd:          That's a fantastic question. So this was a study that had already been completed, and I had mentioned to Scott what we were working on. And he said, "You know, we have these samples from this study and it might be possible for us to collaborate."                                 So, we didn't get to pick the timeframes. Jane Ferguson: Right. Brian Byrd:          So, that's a great point. And what I would say is that, as you can imagine, we're very focused on exactly the questions you're asking now. What about sort of signal refinement? What about the chrono-biology of these signals, and how do we understand when we see what in the urine?                                 So, I'm actively pursuing those questions. Jane Ferguson: Right. So, I know as well, there was quite a lot of sort of technical challenges I think to doing this work. Sort of getting to be even able to amplify and get a signal from these RNAs that are really present, sort of pretty low abundance in urine compared to tissues or biofluids that we're used to working with.                                 So tell me maybe a little bit about that process and sort of how much optimization was required to get these essays to work? Brian Byrd:          Great question. So, I had known [inaudible 00:30:58] since 2014 when I took a course on isolation of extracellular vesicles in Heidelberg, Germany. And I had talked to him at a meeting in Washington DC, and I had mentioned what we were trying to do. And he said, "You know, if you were trying to do that, you might want to consider preamplification." You know, using something like 15 cycles of preamplification. And he was willing to share that protocol that he had with me, because they were interested in similar issues. So, I was able to use that protocol to evaluate these gene targets in the urine. And so that was immensely helpful.                                 And the other thing that we did was we used locked nucleic acid probes to try to increase the sensitivity and specificity of our assays. Finally, we just tried to use good logic in the design of the assays. So we were concerned that the RNA might be fragmented, so where it was possible to do so within the design constraints that I'll mention in a second, we made multiple assays per gene target just in case this was fragmented. Which makes the analysis a little more complicated, but I think it was probably the right thing to do, given the state of knowledge that we had then.                                 And one of the other things we did was we made sure that the primers either ... Within a primer, there was an intron or between the primers there was an intron, so that if we actually did try to amplify DNA, abundant amounts of DNA, with those primers just to make sure that our theorizing about the inability to amplify things was actually factual. And that turned out that we couldn't amplify anything at 40 cycles with those.                                 So, we spent a lot of time thinking about how not to get fooled, but also to have adequate signal detection. And have included in the supplement quite a bit of information about the technical merits of the assays and showing how close the technical replicates were. They tended to be very, very similar to one another. We didn't see a signal in every urine sample for every participant at both time points, and I think that was interesting to me about that there tended to be a very binary result, so that you'd either see three technical replicants for the QPCR assays, our QPCR assays that were extremely similar to each other, or you would see no CT value detected.                                 [inaudible 00:33:47] That these were valid assessments of very low copy numbers. Jane Ferguson: Right. And that's probably related to up front of what happens to urine right after it's collected and stored, or during that RNA extraction. But it seems like once you've got RNA, then downstream assays were sort of ... They held through, but I guess ... I mean, and you obviously didn't have necessarily a huge amount of control over how these urine samples were collected. So it's kind of nice that you were able to see something even though these were collected possibly in a way that was not optimized for preserving RNAs.                                 But do you think those ... Are there ways that you could make this even sort of more streamlined and better as far from the get go of how you collect the urine, whether you could be extracting stuff right away? Is that anything you sort of looked into of how this could be improved? Brian Byrd:          That's really been the focus of the labs work since we completed that project, is sort of understanding how would we do this in a prospective study in the best possible way so that the results are highly repeatable, that we get a CT value in everybody so that we're really ... I mean, as you can imagine, that actually has something to do with the input volume of urine that you use. So if you have too little input volume, then you won't be able to detect the targets that you might be interested in every person.                                 However, if you have more, then you can do more with that. But then you have to think about how you're going to deal with the larger volumes of urine. There are lots of questions that we've been interested in related to extract the RNA and the stability of the RNA. And so we have done some experiments of that type, and we continue to work in that area. And I do think that those questions you're asking are the right questions with respect to next steps. Jane Ferguson: All right. So you looked at sort of specific targets, which I think made a lot of sense. Sort of this proof of principle. But do you think this would work on a transcriptome wide level? I mean, could you look at all the genes, or do you think that's just sort beyond the possibility right now given sort of the RNA fragmentation and how you have to sort of amplify it before being able to detect anything? Brian Byrd:          I think it's possible. So the group that had preceded our work with 3300 mils of urine, isolating the vesicles from there, eight have showed that that's something that can be done. The question that's of interest to me is does it actually require such large volumes of urine? And I think the answer to that question is going to be no from what we're overseeing so far.                                 And so, we're thinking along exactly the lines that you are. And certainly some of the feedback we've gotten as we've discussed this project with people is, "Hey, could you look at everything rather than picking targets at [inaudible 00:36:41]."                                 I think there's advantages and disadvantages. I think we chose based on prior knowledge in a way that was rational. But at the same time, it may turn out that there are many things about activation of the mineralocorticoid receptor in humans, especially in the living in-tact human, that don't exactly mirror what's found in rabbits, rats, mice or cells, which are really the systems that have been evaluated the most thoroughly in the past.                                 So I'm very interested in exactly what you're proposing. Jane Ferguson: Yeah. I mean, I think it's exciting because it's obviously relevant for hypertension, but potentially a lot of other conditions, to be able to look at that sort of dynamic change. So I think it's really exciting. It's very cool. Brian Byrd:          And I appreciate your asking about this study. We were excited to do this work and very, very excited to see where we can in the future with this. And I agree with the point you were making, that here we've gone from a rather specific application driven question and we've, I think, made some insights that are probably useful outside the application that we had in mind. And it may turn out that the application where this is the most important is not even the one that we considered in the first place at all.                                 And so I'm pleased by that. I'm pleased by the fact that I think in a sense we're working in what Donald Stokes described as pasture's quadrant, which is a sense that the work is driven both by curiosity and by an intent to use the results. Jane Ferguson: Right. Brian Byrd:          And so that's really what gets me out of bed in the morning, is working that exact space. So that's what we were glad to have done and continue to do. Jane Ferguson: Yeah. No, I think it's grea.t and I feel like a lot of people will read this paper and be like, "Hey, I have urine stored in the freezer. What can I do with this now?" Brian Byrd:          Contact me. Let's talk. We'll see what we can do. But we certainly tried to describe the methods in such a way that people could easily follow in our footsteps if they want to apply these methods. Jane Ferguson: Yeah. Now having read through them, I think that ... Really thorough. I really liked the sort of attention to detail. It was definitely one of those ones where I was like, "Oh yeah. I can see exactly how I could do this if I wanted to. So I think that was great. Brian Byrd:          Thank you. Jane Ferguson: So yeah. Congratulations on the paper. Really nice work and thanks so much for talking to me. Brian Byrd:          Thank you. It was a delight. Jane Ferguson: That's it from me for September. If you haven't had enough yet, you can access all the papers online and you can choose to digest the papers in video format. Available on our website or the Circulation YouTube channel. Thank you for listening and subscribing. I look forward to bringing you more next month.  

Jane Ferguson: Hello. Welcome to episode 19 of Getting Personal: Omics of the Heart, the issue from August 2018. I am Jane Ferguson, and this podcast is brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Council on Genomic and Precision Medicine. Before I dive into the papers from this month, a reminder that early bird registration for AHA Scientific Sessions runs until September 4th, so go register now if you haven't already to take advantage of reduced rates. The meeting will be held in Chicago from November 10th through 12th, and it's the first year of the new three-day meeting format. It's already promising to be a really great meeting, and I'm hoping to see a lot of you there.     The August issue has a number of really interesting papers. First up, Gardar Sveinbjornsson, Eva Olafsdottir, Kari Stefansson, and colleagues from deCODE genetics-Amgen report that variants in NKX2-5 and FLNC cause dilated cardiomyopathy and sudden cardiac death. This team leveraged available DNA samples from the Icelandic population to carry out a genome-wide association study in 424 cases of dilated cardiomyopathy and over 337,000 controls. They applied whole genome sequencing to all of these samples, allowing them to identify common and rare variants. In total, they tested over 32 million variants.     They found two variants that were significantly associated with DCM at genome-wide significance, a missense variant in NKX2-5 and a frameshift in FLNC, both associated with heart failure and sudden cardiac death. Further, the NKX2-5 variant was associated with atrioventricular block and atrial septal defect. Although these variants are rare and not documented in other populations, they are significant contributors to familial DCM in Iceland. Because of the unique population structure of Iceland and known genealogy, the researchers were able to trace the NKX2-5 variant back to a common ancestor born in 1865. They traced the FLNC variants to a common ancestor born in 1595.     While the specific variants identified in this study may not be present in other populations, they are located in genes with known relevance for cardiac function. NKX2-5 encodes a cardiac transcription factor, which is required for embryonic cardiac development, and other variants in this gene have been associated with cardiac dysfunction in other populations. FLNC encodes filamin-C, a muscle cross-linking protein. Variants in FLNC have previously been ascribed to associate with myofibrillar myopathy, muscular dystrophy, and cardiomyopathy. This study adds to our knowledge of the genetics of dilated cardiomyopathy and supports screening for NKX2-5 and FLNC variants, particularly in the Icelandic population, which would allow for early intervention and monitoring in carriers.     Staying with the topic of dilated cardiomyopathy, Inken Huttner, Louis Wang, Diane Fatkin, and colleagues from the Victor Chang Cardiac Research Institute in Australia report that an A-band titin truncation in zebrafish causes dilated cardiomyopathy and hemodynamic stress intolerance. We actually talked to Dr. Wang about this research last year when he was presenting this as a finalist for the FGTB Young Investigator Award. You can go back in the archives to episode 10 from November 2017 if you'd like to hear more.     Titin mutations are responsible for a large number of cases of dilated cardiomyopathy, but there are also individuals with titin mutations that remain asymptomatic. This group used zebrafish as a model of human titin mutations and generated fish with a truncating variant in the A-band of titin, as has been identified in families with DCM. They found that homozygous mutants had a severe cardiac phenotype with premature death, but that heterozygous carriers survived into adulthood and developed spontaneous DCM. Prior to onset of DCM, the heterozygous fish had reduced baseline ventricular systolic function and reduced contractile response to hemodynamic stress, as well as ventricular diastolic dysfunction.     Overall, the mutant fish displayed impaired ability to mount stress responses, which may have contributed to development of disease. Extrapolating this to humans, this could suggest that hemodynamic stress may be a factor that contributes to timing and severity of disease in individuals with titin variants. Hemodynamic stress can be exerted by exercise, pregnancy, and other diseases contributing to ventricular volume overload. Modifying these hemodynamic stressors in at-risk subjects could potentially help to modulate the severity of DCM phenotypes.     Moving on to the topic of coronary artery disease, Vinicius Tragante, Daiane Hemerich, Folkert Asselbergs, and colleagues from University Medical Center Utrecht in the Netherlands report on druggability of coronary artery disease risk loci. This group was interested in using results from genome-wide association studies for CAD to identify new targets that may be amenable for drug repurposing. They used results from published GWAS for CAD and created a pipeline to integrate these loci with data on drug-gene interactions, chemical interactions, and potential side effects. They also calculated a druggability score based on the gene products to prioritize targets that are accessible and localized to increase the chance of a drug being able to find the target without affecting core systemic processes or housekeeping genes.     Their pipelines allowed them to identify three possible drug-gene pairs, including pentolinium to target CHRNB4, adenosine triphosphate to target ACSS2, and riociguat to target GUCY1A3. They also identified three proteins to be prioritized for drug development, including leiomodin 1, huntingtin-interacting protein 1, and protein phosphatase 2, regulatory subunit b-double prime, alpha). While these predictions were all made in silico and need to be extensively tested in clinical trials, the pipeline did identify many current therapies for CAD and myocardial infarction, including statins, PCSK9 inhibitors, and angiotensin II receptor blockers. These positive controls support that this method can successfully discover effective CAD therapies.     Staying on the topic of drugs, Kishan Parikh, Michael Bristow, and colleagues from Duke University report on dose response of beta-blockers in adrenergic receptor polymorphism genotypes. Two clinical trials have reported pharmacogenomic interactions between beta-blockers and beta-1 adrenergic receptor genotype in the setting of heart failure with reduced ejection fraction. In a retrospective analysis in almost 2,000 subjects from the BEST and HF-ACTION studies, the authors analyzed whether genotype at the Arg389Gly polymorphism in beta-1 adrenergic receptor, or an indel in the alpha-2C adrenergic receptor interacted with drug dose to affect mortality and hospitalization.     They found that ADRB1 genotype affected mortality in response to drug dose with less all-cause mortality in high versus no or low-dose beta-blockers in individuals homozygous for arginine at position 389, but not in individuals carrying a glycine at that position. In individuals on high-dose beta-blockers, genotype did not affect outcomes, but there was a significant difference by genotype in all-cause mortality in individuals on no or low-dose beta-blockers. These data support the guideline recommendations to use high-target doses of beta-blockers in HFrEF.     Switching gears towards precision medicine and genotype-guided approaches, Laney Jones, Michael Murray, and colleagues from Geisinger were interested in the patient's perspective. In their paper, Healthcare Utilization and Patients’ Perspectives After Receiving a Positive Genetic Test for Familial Hypercholesterolemia, they explored the impact of providing genotype test results for familial hypercholesterolemia to subjects participating in the MyCode Community Health Initiative. In MyCode, exome sequencing is conducted in participants, and results are returned for pathogenic and likely pathogenic variants in genes representing actionable conditions based on American College of Medical Genetics secondary findings and recommendations.     It is estimated that 3.5% of MyCode participants will be carriers of such variants, and this number may increase as more variants are discovered. In this pilot study, the authors screened for individuals with mutations in LDLR, APOB, or PCSK9, consistent with FH. They identified 28 individuals, of which 23 were eligible for inclusion in the study. Only five of the 23 subjects had previously been diagnosed with FH. Receipt of genetic test results led to change in medications in 39% of individuals. 96% of the subjects had previous LDL measurements, but only four subjects had ever met LDL goals. After genetic test results, three individuals met their LDL goals.     Seven individuals consented to participate in interviews about their experience. Almost all of these subjects already had a personal or family history of high cholesterol or heart disease, and all subjects felt that they were being adequately treated. Only three of the seven subjects mentioned using diet and exercise to control their high cholesterol, with most individuals being relatively unconcerned because they felt their medication was effective in controlling disease risk.     While the numbers studied here are too small for any statistical testing or inference, the paper describes the results from the interviews, including some excerpts from patients, which really highlight the complexities of returning results and of helping patients understand what their results mean. Given increasing genetic testing and returning of results, studies like this are really important to help us figure out the most effective ways to communicate results and support patients and their care providers.     Also from a patient-centric perspective, we have an article from Susan Christian, Joseph Atallah, and colleagues from the University of Alberta in Canada on when to offer predictive genetic testing to children at risk of an inherited arrhythmia or cardiomyopathy, the family perspective. This article considers the timing of cascade testing to predict inherited arrhythmias and cardiomyopathy in children of affected individuals. European and North American guidelines differ on when or if they recommend genetic testing in children.     In this study, surveys were circulated to foundations and patient groups to solicit familial perspectives on when genetic testing should be offered to children. In total, 213 individuals responded. In the case of long QT syndrome, 92% of respondents thought testing should be offered before the age of five, while 77% of respondents thought genetic testing should be offered before the age of 10 for hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy.     Overall, the potential benefits of genetic testing, including guiding therapies, sport participation, and decreasing worry were ranked more highly than potential risks of discrimination or increasing worry that could occur from genetic testing. Overall, the responses indicated that families would welcome the option of genetic testing for at-risk children from a young age and support initiating early discussions with families to explore costs and benefits of early genetic testing.     Finally in this issue, we have a review from Paul Franks and Nicholas Timpson from Lund University and the University of Bristol entitled Genotype-Based Recall in Complex Cardiometabolic Traits. This review looks at the increasing practice of selecting samples or individuals from larger cohorts or biobanks based on their genotype to carry out additional studies. The article focuses on examples of such genotype-based recall studies in cardiometabolic disease, highlights approaches and new methods, and discusses the ways these types of studies can be used to extend and supplement randomized trials and large population-based studies.     As always, you can find all the articles, accompanying editorials, and video summaries online. Our website recently underwent some redesigns and has moved. You should be redirected if you have the older site bookmarked, but you can also find us directly at ahajournals.org/journal/circgen. Also, thanks to everyone who participated in the Twitter poll last month. You were pretty evenly split on what you want to hear in the podcast, but please continue to leave suggestions and feedback on what we're doing and where we can improve things. That's it for the August issue of Circulation: Genomic and Precision Medicine. Thanks for listening, and tune in next month for more.    

Jane:                                     Hi, everyone. Welcome to Episode 18 of Getting Personal: Omics of the Heart. I'm Jane Ferguson, and this podcast is brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Counsel on Genomic and Precision Medicine. It is July 2018, which means that the best possible place to be listening to this episode is at the beach, but failing that I can also recommend listening on planes, during your commute, while exercising or while drinking a nice cup of tea.                                                 So before I get into the papers we published this month, I want to ask for your help. If you're listening to this right now, hi, that means you, we're a year and a half into podcasting and I would love to know what content you like and where we could improve things. We have a poll up on Twitter this week, and I would really appreciate your input. If you're listening to this a little bit later and miss the active voting part of the poll, you can still leave suggestions.                                                 Okay, so what I would like you to do right now is to go to Twitter. You can find us as Circ_Gen and locate the poll. If you don't already follow us on Twitter, go do that now too. We want you to let us know what content we should focus on and what is most useful to you, so go ahead and pick your favorites from the options and also please reply or tweet at us with other thoughts and suggestions.                                                 Options include giving summaries of the recent articles like I'm about to do later this episode, conducting interviews with authors of recently published papers, interviews with people working in cardiovascular genomics, broader topics. For example, to get their insight on career paths and lessons learned along the way.                                                 And something we have not done yet on the podcast but are considering, would be to record podcasts that focus on particular topics in genomics and precision medicine. These could give some background on an emerging field or technology and we could talk to experts who are leading particular innovations in the field. So, if that sounds good to you, let me know! If you're not on Twitter, I don't want to exclude you, so you can email me at jane.f.ferguson@vanderbilt.edu and give me your thoughts that way. I'm looking forward to hearing from you.                                                 Okay, so on to the July 2018 issue of Circ.: Genomic and Precision Medicine. First up is a PhWAS from Abrahim Rao, Eric Ingelsson, and colleagues from Stanford. The discovery of the PCSK9 gene as a regulator of cholesterol levels has led to a new avenue of LDL lowering therapies through PCSK9 inhibition. However, some studies suggest that long term use of PCSK9 inhibitors could have adverse consequences. Because of the long follow-up time required, it will take many more years to address this question through clinical studies. However, genetic approaches offer a fast and convenient alternative to address the issue.                                                 In this paper, entitled: "Large Scale  Phenome-Wide Association Study of PCSK9 Variants Demonstrates Protection Against Ischemic Stroke," the authors use genetic and phenotype data from over 300,000 individuals in the UK BioBank to address whether genetic loss of function variants in PCSK9 are associated with phenotypes including coronary heart disease, stroke, type II diabetes, cataracts, heart failure, atrial fibrillation, epilepsy, and cognitive function.                                                 The missense variant RS11591147 was associated with protection against coronary heart disease and ischemic stroke. This SNP also associated with type II diabetes after adjustment for lipid medication status. Overall, this study recapitulated the associations between PCSK9 and coronary disease, and revealed an association with stroke.                                                 Previous studies suggested use of LDL lowering therapies may increase risk of cataracts, epilepsy, and cognitive dysfunction, but there was no evidence of association in this study. Overall, this study provides some reassurance that the primary effect of PCSK9 is on lipids and lipid related diseases, and that any effects on other phenotypes appear to be modest at best. While a PhWAS can't recapitulate a clinical trial, what this study indicates is that PCSK9 inhibition is an effective strategy for CVD prevention, which may confer protection against ischemic stroke and does not appear to convey increased risk for cognitive side effects.                                                 Next up we have a manuscript form Jason Cowan, Ray Hershberger, and colleagues from Ohio State University College of Medicine. Their paper, "Multigenic Disease and Bilineal Inheritance in Dilated Cardiomyopathy Is Illustrated in Non-segregating LMNA Pedigrees," explored pedigrees of apparent LMNA related cardiomyopathy identifying family members who manifested disease, despite not carrying the purported causal LMNA variant. Of 19 pedigrees studies, six of them had family members with dilated cardiomyopathy who did not carry the family's LMNA mutation. In five of those six pedigrees, the authors identified at least one additional rare variant in a known DCM gene that was a plausible candidate for disease causation.                                                 Presence of additional variants was associated with more severe disease phenotype in those individuals. Overall, what this study tells us is that in DCM, there is evidence for multi-gene causality and bilineal inheritance may be more common than previously suspected. Future larger studies should consider multi-genic causes and will be required to fully understand the genetic architecture of DCM.                                                 Yukiko Nakano, Yasuki Kihara, and colleagues from Hiroshima University published a manuscript detailing how HCN4 gene polymorphisms are associated with tachycardia inducted cardiomyopathy in patients with atrial fibrillation. Tachycardia induced cardiomyopathy is common in subjects with atrial fibrillation, but the pathophysiology is poorly understood. Recent studies have implicated the cardiac hyperpolarization activated cyclic nucleotide gated channel gene, or HCN4, in atrial fibrillation and ventricular function.                                                 In this paper, the authors enrolled almost 3,000 Japanese subjects with atrial fibrillation, both with and without tachycardia-induced cardiomyopathy, as well as non-AF controls. They compared frequency of variants in HCN4 in AF subjects with or without tachycardia-induced cardiomyopathy, and found a SNP, RS7164883, that may be a novel marker of tachycardia-induced cardiomyopathy in atrial fibrillation.                                                 Xinyu Yang, Fuli Yu, and coauthors from Tianjin University were interested in finding causal genes for intracranial aneurysms, and report their results in a manuscript entitled, "Rho Guanine Nucleotide Exchange Factor ARHGEF17 Is a Risk Gene for Intracranial Aneurysms." They sequenced the genomes of 20 Chinese intracranial aneurysm patients to search for potentially deleterious, rare, and low frequency variants. They found a coding variant in the ARHGEF17 gene which was associated with associated with increased risk in the discovery sample, and which they replicated in a sample of Japanese IA and in a larger Chinese sample.                                                 They expanded this to other published studies, including individuals of European-American and French-Canadian origin and found a significantly increased mutation burden in ARHGEF17 in IA patients across all samples. They were interested in further functional characterization of this gene and found that Zebra fish ARHGEF17 was highly expressed in blood vessels in the brain. They used morpholinos to knock down ARHGEF17 in Zebra fish, and found that ARHGEF17 deficient Zebra fish developed endothelial lesions on cerebral blood vessels, and showed evidence of bleeding consistent with defects in the vessel. This study implicates ARHGEF17 as a cerebro-vascular disease gene which may impact disease risk through effects on endothelial function and blood vessel stability.                                                 Sumeet Khetarpal, Paul Babb, Dan Rader, Ben Voight, and colleagues from the University of Pennsylvania used targeted resequencing to look at determinants of extreme HDL cholesterol in their aptly titled manuscript, "Multiplexed Targeted Resequencing Identifies Coding and Regulatory Variation Underlying Phenotypic Extremes of HDL Cholesterol in Humans." Stay tuned because we're gonna hear more about this paper from the first author Dr. Sumeet Khetarpal later this episode.                                                 Rounding out this issue we have a Perspective article from Chris Haggerty, Cynthia James, and coauthors from Geisinger and Johns Hopkins Medical Center entitled, "Managing Secondary Genomic Findings Associated With Arrhythmogenic Right Ventricular Cardiomyopathy: Case Studies and Proposal for Clinical Surveillance." In this paper the authors discuss the challenges for returning findings from clinical sequencing for arrhythmogenic right ventricular cardiomyopathy, presenting case studies exemplifying these challenges. They also propose a management approach for returning clinical genomic findings, and discuss new innovations in the light of precision medicine.                                                 We also published a review article by Pradeep Natarajan, Siddhartha Jaiswal, and Sekar Kathiresan from MGH on "Clonal Hematopoiesis Somatic Mutations in Blood Cells and Atherosclerosis", which discusses recent advances in our knowledge on the role of somatic mutations in cardiovascular disease risk.                                                 Finally, we have an update on some pharmacogenomics research into CYP2C19 Genotype-Guided Antiplatelet Therapy by Craig Lee and colleagues which we published a few months ago. Dr. Lee was also featured on Podcast episode 15 in April of this year.                                                 Jernice Aw and colleagues from Khoo Teck Puat Hospital, Singapore shared from complimentary data from their sample of 247 Asian subjects which found the risk for major adverse cardiovascular events was over 30-fold greater for poor metabolizers, as defined by CYP2C19 genotype on clopidogrel, as compared to those with no loss of function allele.                                                 You can read that letter and the response from Dr. Lee and colleagues online now. And, as usual, all of the original research articles come with an editorial to help give some more background and perspective to each paper. Go to circgenetics.ahajournals.org to find all the papers and to access video summaries and more.                                                 Our interview is with Dr. Sumeet Khetarpal who recently completed his MD-PhD training at the University of Pennsylvania, and is currently a resident in Internal Medicine at Massachusets General Hospital. Sumeet kindly took some time out from his busy residency schedule to talk to me about his recently published paper, and to explain how molecular inversion probe target capture actually works.                                                 So I am here with Dr. Sumeet Khetarpal who is co-first author on a manuscript entitled, "Multiplexed Targeted Resequencing Identifies Coding and Regulatory Variation Underlying Phenotypic Extremes of High-Density Lipoprotein Cholesterol in Humans."                                                 Welcome Sumeet, thanks for taking the time to talk to me. Dr. Khetarpal:                    Thank you so much Dr. Ferguson, it's really a pleasure to talk to you today. Jane:                                     Before we get started, maybe you could give a brief introduction on yourself and then how you started working on this paper. Dr. Khetarpal:                    Sure, so this work actually was a collaboration that came out at the University of Pennsylvania that I was involved with through my PhD thesis lab, my mentor was Dan Rader, and also a lab that is a somewhat newer lab at Penn, Benjamin Voight's lab which is a strong sort of computational genomic lab.                                                 This work actually highlights the fun of collaborating within your institution. We had, for some time, been interested in developing a way to sequence candidate genes. Both known genes and also new genes that have come out of genome-wide association studies that underlie the extremes of HDL cholesterol, namely very high cholesterol versus low HDL cholesterol. We've been looking for a cost-effective and scalable way to do this.                                                 Independently, Ben, who is very interested in capturing the non-coding genome, was interested in developing a method to better understand the non-coding variation, both common and rare variation that may be present at all of these new loci that have come out for complex traits such as HDL.                                                 We, at some Penn event several years ago, were talking about our common interest and Ben had actually identified this work that had come out of J. Shendure's lab at the University of Washington. A paper by the first author, Brian O'Rouke, in Science in 2012 in which they had developed an approach that involved molecular inversion probes, or MIPs, to capture regions of the genome related to target the gene that they were interested in studying for autism-spectrum disorders.                                                 They had applied this largely to coding regions of, I think, almost 50 genes and almost 2,500 patients with the feedback to do deep, targeted sequencing. So our thought was, well, we could try to apply this approach and adapt it to capture non-coding regions, and also see if we can expand the utility of this approach to study the phenotypic extremes of a complex trait such as HDL cholesterol. Jane:                                     Yeah, that's really cool. I love how you saw this method in a totally different application and then realized that there was expertise at Penn that you could bring together to apply this in a different way.                                                 I'd love to hear more about this MIP, the molecular inversion probe. How does it work? How difficult is it to actually do? Is it very different from normal library preparation for sequencing or is it something that's actually relatively easy to apply? Dr. Khetarpal:                    These MIP probes are oligonucleotide probes that capture your region of interest by flanking them and capturing by gap filling. There's a method to capture parts of the genome in a library-free way. They do ultimately involve barcoding the way traditional library-based target capture does and then deep sequencing.                                                 But the most impressive feature about them is just that they're very scalable. I think in the original paper by O'Rouke and colleagues they were able to sequence their set of genes and their set of samples at about a sample preparation cost of $1 per sample, and we were actually able to do about the same for our study.                                                 The main utility of the approach is just the economic scalability, and the ability to customize your panel to capture several regions of the genome that are adjacent to each other. Jane:                                     Right, so how many genes or regions can you multiplex at the same time? Is it just one prep, like you just design all of your oligos, you put them all together in one reaction, or are you doing separate reactions for each region? Dr. Khetarpal:                    We're actually doing all of our oligos together. In our case, I think it ended up being around the order of almost 600 oligos together to capture our ultimately 50kB of genomic territory that we wanted to capture. Really, our study was kind of a pilot experiment where we picked a few genes or regions of high interest to us, both known genes that effect HDL and also those that have been implicated in genome-wide association studies that were of high interest to our labs.                                                 I think that this approach could actually be expanded to capture much more genomic territory in a single capture reaction. We sort of touched the surface probably of what we could do. Jane:                                     Wow, that's cool! And then for sequencing it, I guess it's really just a function of how many samples you wanna multiplex and how much you want to sequence from each region. So I suppose the way you did it, you had about 50kB and then you had over 1,500 participants and you were able to do those on a single HiSeq run, right? Dr. Khetarpal:                    Right. Jane:                                     So I suppose if you'd done more genetic regions, you would've had fewer people and vice versa so you can balance that out depending on if you're having more samples or more genomic regions to sequence. Dr. Khetarpal:                    Exactly, in certain ways the design of our experiment we had a limited sample size that did afford us some luxury in terms of knowing that we would have deep coverage of the region that we were targeting. I think that's always a critical question in sort of targeted or just sequencing in general. The balance between the number of regions that you want to sequence and the number of samples you want to sequence is going to dictate what your sequencing depth with be. Jane:                                     Right, okay so I guess if we go on to what you actually found, how'd you pick this? You picked seven regions which encompasses eight candidate genes for HDL, so how did you select those? Dr. Khetarpal:                    The population that we were studying, the samples we were looking to sequence were largely individuals which fall into two bins if you will. One was extremely high HDL cholesterol which we're defining as the greater than the 95th percentile, but really there was a range within that population that spanned individuals with probably greater than the 99th percentile of HDL.                                                 We were hoping as a proof of principle effort to identify variation in genes that were known causes of high HDL cholesterol in prior studies of Mendelian genes for HDL. So genes such as LIP gene which encodes endothelial lipase or CETP or SCARB1, these 3 genes are, at this point, well-known genes that loss of function mutations are associated with extremely high HDL. We thought that capturing some of those genes would potentially both provide a level of validation for the approach, hypothesizing that individuals with high HDL would be enriched with these genes, but also may allow us to find new variants in these genes or also non-coding variants which has not previously been studied before.                                                 Some of the genes came out from that line of thinking, then some of the other genes happened to be genes that in the Rader laboratory we had a vested interest in understanding the genetic variation that might link the genes to HDL, which may not have necessarily come out before.                                                 For example, the gene GALNT2 is one of the first g-loss implicated novel genes for HDL, novel as in the earliest g-loss study for plasma lipids had identified that gene as associated with HDL but it never had come out before as being so. Our laboratory was very interested in better understanding the genetic relationship between genes such as GALNT2 and several of the others such as CCDC92 and ZNF664 with HDL.                                                 It ended up being a hodge-podge or a sampling of genes that had at some level been implicated with HDL, but really it's just a proof of principle that this method could work for both identifying variation in known genes and also less studied ones. Jane:                                     You validated the MIP genotyping by exome genotyping, and then saw concordance of over 90%, is that lower than you were expecting? Was it about what you were expecting based on these two different methods of genotyping? Dr. Khetarpal:                    Yes, I think we were expecting somewhere on the order of 90 plus percent. It's hard to know why we just hit that, we likely would've benefited from being able to genotype all of the individuals by the exome chip that we had sequenced as well, where we were able to validate in about two-thirds of those individuals.                                                 It's hard to know exactly what the cause of the about 10% discordance rate might be, whether it's just in certain samples the genotyping quality was perhaps on the border of being valid or the sequencing quality. Jane:                                     Right, I'm wondering sort of with the MIP, what's the gold standard? Is the XM chip genotyping still the gold standard and the MIP maybe is more error-prone, or perhaps the other way around? Or is it you can't tell at this point which is the true genotype and which is an error potentially for those discordant ones? Dr. Khetarpal:                    Certainly whenever there's a new sequencing methodology that is proposed I think it's critical to have some sort of validation. We happened to cover regions that would span the genome enough that we had XM chip genotyping in a large subset, that that might be the best approach. But if you had a limited number of regions or variance that you were interested in one could imagine also doing Sanger sequencing as the tried and tested validation approach. Of course it becomes not so scalable at a certain point.                                                 Certainly we would say that the MIPs, while the method has been developed and expanded by the Shendure lab, our hope is that through our studies maybe it will be applied further. It's still very much a new approach and so validation is key. Jane:                                     Very important. What do you think was the most exciting finding that came out of this, after you analyzed the data, what were you most excited about seeing? Dr. Khetarpal:                    The critical finding for us, which I think implies the utility of the approach, was just the validation of four of the loci that we had studied. Validation in our cohort of known genome-wide significant associations for HDL that had been published previously in almost 200,000 individuals in terms of sample size, in our experiment involving just about 1,500 people we were able to find consistent associations of those same variants that segregated with low versus high HDL. Directionally consistent with the large genome-wide association studies.                                                 I think the value of this finding is really just to emphasize the utility of the case control design in these phenotypic extremes, in addition to the overarching goal of our study, which was in a way that perhaps provides the most validation of the approach in terms of concordance with prior known studies. Jane:                                     So if somebody was listening to this and was trying to decide should they use MIP for a study they have in mind, should they use another technique? Based on your experience, what would you recommend? Dr. Khetarpal:                    I think in our current stage it's a very exciting time because we're just seeing whole genome sequencing really take off and being used at scale to ask critical questions about non-coding variation as it relates to both disease and complex traits. I don't think we're quite there yet with being able to apply that approach in a cost effective manner. The ability to annotate and analyze that data is still at it's infancy. The utility of the MIPs is that it provides a very cheap alternative.                                                 I can say from my experiences actually doing the capture and preparation from sample to sequencer stage that it's a very easy to use methodology that is very fast and cheap. That if one is really interested in a handful, or more than a handful, of candidate genes and their non-coding regions as it relates to a trait or disease of interest, it may not be the era for going full on with whole genome sequencing, especially at the current cost. That's where I think the MIPs really come in to be very useful. Jane:                                     It sounds great, is there anything else that you'd like to mention? Dr. Khetarpal:                    Just to say that we recognize it's a relatively small study as our pioneer approach with this method but that the Rader lab and Voight labs are actively pursuing larger applications of this to study, not only HDL, but other complex traits, such as diabetes, in much larger populations. I can't overemphasize how easy of a method it is to apply, but also that I think a bigger take home of this study for me as a very recent graduate student working in a very collaborative institution the ability of two laboratories to come together with different sets of expertise to try to tackle a problem that I think goes beyond the individual science. For any human geneticist how to find the variation you're interested in and not break the bank is kind of at the core of what we do, and so I think it was very fun to be part of this collaboration and our hope is that the outcome of it is a method that can be useful for many people, both in our field and beyond. Jane:                                     I think it's great and I'm hoping this will inspire a lot of other people to try this method and see if it can work for them. So, congratulations on the study, it's really nice work. Dr. Khetarpal:    Thank you so much!                                                                                                                                       Jane:                                     That's all I have for you for July, thanks for listening. Send me your thoughts on the podcast via Twitter or email, or leave us a review in Itunes. I look forward to talking to you next month.  

Jane Ferguson:                 Hello, welcome to Getting Personal: Omics of the Heart. It is June 2018, and this is podcast episode 17. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center, and a proponent of precision medicine, genomics, and finding ways to prevent and treat heart disease. Jane Ferguson:                 This podcast is brought to you by Circulation: Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. Jane Ferguson:                 For our interview this month, early career member, Jennie Lin talked to Beth McNally about science and careers in genomic medicine. We'll have more on that later but first I want to tell you about the cool papers we published in the journal this month. Jane Ferguson:                 First up, Orlando Gutierrez, Marguerite Irvin, Jeffrey Kopp, Cheryl Winkler, and colleagues from the University of Alabama at Birmingham, and the NIH, published an article entitled APOL1 Nephropathy Risk Variants and Incident Cardiovascular Disease Events in Community-Dwelling Black Adults. This study was conducted in over 10 thousand participants of the Reasons for Geographic and Racial Differences in Stroke, or, REGARDS Study. They examined associations between APOL1 variants and incident coronary heart disease, ischemic stroke, or composite CVD outcome. Because there are coding variants in the APOL1 Gene that are only found in individuals of African ancestry, these are hypothesized to contribute to the disparities in cardiovascular and renal disease in African Americans. Jane Ferguson:                 The authors found that carrying the risk variants was associated with increased risk of ischemic stroke, but only in individuals who did not have diabetes, or chronic kidney disease. They hypothesize that because diabetes and kidney disease already increase CVD risk, the variant does not have an additional effect on risk in individuals with existing comorbidities. But, it contributes to small vessel occlusion and stroke in individuals without diabetes. Jane Ferguson:                 They also found that the magnitude and strength of the association became stronger in a model adjusted for African ancestry, suggesting an independent effect of the APOL1 risk variants. Jane Ferguson:                 While future work is needed to study this more, this is an important step in understanding the complex relationship between APOL1 and disease. Jane Ferguson:                 Next up, Daniela Zanetti, Erik Ingelsson, and colleagues from Stanford, published a paper on Birthweight, Type 2 Diabetes, and Cardiovascular Disease: Addressing the Barker Hypothesis with Mendelian Randomization. The Barker Hypothesis considers that low birthweight as a result of intrauterine growth restriction, causes a higher future risk of hypertension, type 2 diabetes, and cardiovascular disease. However, observational studies have been unable to establish causality or mechanisms. Jane Ferguson:                 In this paper, the authors used Mendelian Randomization as a tool to address causality. They used data from the UK Biobank, and included over 237,000 participants who knew their weight at birth. They constructed genetic predictors of birthweight from published genome wide association studies, and then looked for genetic associations with multiple outcomes, including CAD, stroke, hypertension, obesity, dyslipidemia, dysregulated glucose and insulin metabolism, and diabetes. Jane Ferguson:                 The Mendelian randomization analysis indicated that higher birthweight is protective against CAD type 2 diabetes, LDL cholesterol, and high 2 hour glucose from oral tolerance test. But, higher birthweight was associated with higher adult BMI. This suggests that the association between low birthweight and higher disease risk is independent of effects on BMI later in life. While the study was limited to a well nourished population of European ancestry, and would need to be confirmed in other samples, and through non-genetic studies, it suggests that improving prenatal nutrition may be protective against future cardiometabolic disease risk. Jane Ferguson:                 Laura Muino-Mosquera, Julie De Backer, and co-authors from Ghent University Hospital, delved into the complexities of interpreting genetic variants, as published in their manuscript, Tailoring the ACMG and AMP Guidelines for the Interpretation of Sequenced Variants in the FBN1 Gene for Marfan Syndrome: Proposal for a Disease- and Gene-Specific Guideline. Jane Ferguson:                 With a large number of variants being uncovered through widespread sequencing efforts, a crucial challenge arises in their interpretation. The American College of Medical Genetics and Genomics, and the Association for Molecular Pathology put forward variant interpretation guidelines in 2015, but these were not tailored to individual genes. Because some genes have unique characteristics, the guidelines may not always allow for uniform interpretation. Jane Ferguson:                 In their manuscript, the authors focused on variants in fibrillin-1 that cause Marfan Syndrome, and reclassified 713 variants using the guidelines, comparing those classifications to previous in-depth methods which had indicated these variants' causal or uncertain significance. They find 86.4% agreement between the two methods. Jane Ferguson:                 Applying the ACMG, AMP guidelines without considering additional evidence may thus miss causal mutations. And it suggests that adopting gene specific guidelines may be helpful to improve clinical decision making and accurate variant interpretation. Jane Ferguson:                 Delving deeper into FBN1 and Marfan Syndrome, Norifumi Takeda, Ryo Inuzuka, Sonoko Maemura, Issei Komuro, and colleagues from the University of Tokyo examined the Impact of Pathogenic FBN1 Variant Types on the Progression of Aortic Disease in Patients With Marfan Syndrome. They evaluated 248 patients with pathogenic, or likely pathogenic, FBN1 variants, and examined the effect of variant subtype on severe aortopathy, including aortic root replacement, type A dissections, and related death. They found that the cumulative aortic event risk was higher in individuals with haploinsufficient type variants, compared with dominant negative variants. Jane Ferguson:                 Within individuals with dominant negative variants, those that affected Cysteine residues, or caused in-frame deletions, were associated with higher risk compared with other dominant negative mutations, and were comparable to the risk of the haploinsufficient variants. These results highlight the heterogeneity and risk of the FBN1 variants, and suggest that individuals with haploinsufficient variants, and those carrying dominant negative variants affecting Cysteine residues or in-frame Deletions, may need more careful monitoring for development of aortic root aneurysms. Jane Ferguson:                 Lydia Hellwig, William Klein, and colleagues from the NIH, investigated the Ability of Patients to Distinguish Among Cardiac Genomic Variant Subclassifications. In this study, they analyzed whether different subclassifications of variants of uncertain significance were associated with different degrees of concern amongst recipients of genetic test results. 289 subjects were recruited from the NIH ClinSeq Study, and were presented with three categories of variants, including variants of uncertain significance, possibly pathogenic, and likely pathogenic variants. Participants were better able to distinguish between the categories when presented with all three. Whereas, a result of possibly pathogenic given on its own, produced as much worry as a result of likely pathogenic. The authors conclude that multiple categories are helpful for subjects to distinguish pathogenicity subclassification, and that subjects receiving only a single uncertain result, may benefit from interventions to address their worry and to calibrate their risk perceptions.  Jane Ferguson:                 Erik Ingelsson and Mark McCarthy from Stanford, published a really nice review article entitled Human Genetics of Obesity and Type 2 Diabetes: Past, Present, and Future. Over the past decade, we've had a lot of excitement, optimism, and also disappointment in what genome-wide association studies can deliver. Doctors Ingelsson and McCarthy do a great job laying out the history and the successes in the field of genetic interrogation of obesity and diabetes, as well as acknowledging where reality may not live up to the hype, what challenges remain, and what the future may hold. They also have a figure that uses an analogy of a ski resort to emphasize the importance of taking a longitudinal perspective. And I would argue that any paper that manages to connect apres-ski with genomics is worth reading, for that alone. Jane Ferguson:                 Robert Roberts wrote a perspective on the 1986 A.J. Buer program, pivotal to current management and research of heart disease. Highlighting how the decision by the AHA in 1986 to establish centers to train cardiologists and scientists in molecular biology, has led to huge advances in knowledge and treatment of heart disease. Jane Ferguson:                 Finally, rounding out this issue, Kiran Musunuru and colleagues, representing the AHA Council on Genomic and Precision Medicine, Council on Cardiovascular Disease in the Young, Council on Cardiovascular and Stroke Nursing, Council on Cardiovascular Radiology and Intervention, Council on Peripheral Vascular Disease, Council on Quality of Care and Outcomes Research, and the Stroke Council, published a scientific statement on Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine. Jane Ferguson:                 This paper lays out the field of cardiovascular research in the post genomic era, highlights current practices in research and treatment, and outlines vision for interdisciplinary, translational research and clinical practice, that could improve how we understand disease, and how we use those understandings to help patients. Jane Ferguson:                 Our guest interviewer today is Dr. Jennie Lin, an Assistant Professor at Northwestern Universities Feinberg School of Medicine, and the incoming Vice Chair of the Early Career Committee of the AHA Council on Genomic and Precision Medicine. As an aside, Jennie is a great person to follow on Twitter for insights into genomics and kidney disease, and as a bonus, she also posts the occasional dog photo. So she's well worth following just for that. You can find her on Twitter @jenniejlin. As you'll hear, Jennie talked to Dr. Beth McNally about her view on genomic medicine, and Beth also shared some really great practical tips for early career investigators building their independent labs. So make sure you listen all the way to the end. Take it away Jennie. Dr. Lin:                                  Thank you for tuning in to this edition of Getting Personal: Omics of the Heart, a podcast by the Genomic and Precision Medicine Council of the American Heart Association, and by Circulation: Genomic and Precision Medicine. Today I am joined by Dr. Elizabeth McNally, the Elizabeth J Ward Professor of Genetic Medicine, and director of the Center for Genetic Medicine at Northwestern University. Beth, thank you for taking time to chat with all of us. Dr. McNally:                       Happy to be here. Dr. Lin:                                  As a successful physician scientist, you have been interviewed in the past about your life, your scientific interests, and advice for budding investigators. I don't want to rehash everything you have already stated beautifully in an interview with Circ Res, for example. But instead wanted to focus more on your views of genetic medicine and genome science today. Dr. Lin:                                  So you mentioned in that prior Circ Res interview that you started your laboratory science training and career during college, when you participated in a project focused on genetic variation among children with muscular diseases. What have you found to be most interesting about the process of identifying functional genetic variants back then, and also that on-going work now. Dr. McNally:                       Well, I think over the years I've been doing this is the tools have gotten so much better, to be able to actually define the variants much more comprehensibly than we ever could in the past. And then also to be able to study them, and very much to be able to study them in context. And so I look at the revolutions in science that will cause people to look back on this era as the era of genetics. It began obviously with PCR, we couldn't have gotten anywhere without that. Dr. Lin:                                  Right. Dr. McNally:                       And then you leap forward to things like next generation sequencing, and IPS cells, and now CRISPR/Cas gene editing. And to realize that the last three happened within a decade of each other, is going to be so meaningful when you think about the next few decades, and what will happen. So being able to take an IPS cell and actually study a mutation or a variant in context of that patient, the rest of their genome, is really important to be able to do. Dr. Lin:                                  Okay, Great. And so, where do you envision ... with taking say for example, this next gen. technology, CRISPR/Cas9, studying variants in an IPS cell, for example. How do you envision this really revolutionizing the study of human genetics for patients? And how far do you think we've come in fulfilling that vision, and what do you think should be our focus going forward? Dr. McNally:                       I think broadly thinking about human genetics we're really very much still at the beginning, which I know is hard to say and hard to hear. But, we've spent a lot of the last 15 years very focused on that fraction of the genome that has high frequency, or common variation, through a lot of the GWA studies. With those common variants, we had a lot of associations, but relatively small effects of a lot of those, causing a lot of people to focus on the missing heritability and where we might find that hiding. And of course, now that we have deep sequencing, and we have deep sequencing where we've really sampled so much more of the genome, and from so many more people, I think we're just at the beginning of really appreciating that rare variation. And beginning again to really appreciate that 80-85% of the variation that's in each of our genomes is really characterized as rare. Dr. McNally:                       And so we really each are quite unique, and that when we understand a variant we do have to understand it in the context of all that other variation. So computationally that's very challenging to do. Obviously requires larger and larger data sets. But even in doing that, you are not going to find exact replicates of the combinations that you see in any one individual. While I know everybody would love that we're going to have the computational answer to all of this, it's still going to come down to a physician and a patient and making what you think is that best decision for the patient, based hopefully on some genetic data that helps inform those decisions. Dr. Lin:                                  Right, right. So it kind of gets into this whole concept of precision medicine, which has gained a lot of popularity and buzz in recent years, and Obama has really brought it to the forefront in the public arena. You mention rare variants in ... finding rare variants in each patient, for example. And moving a little bit away from some of the common variants that we find in GWAs. What does it mean for a patient to have a rare variant and come see you in your cardiomyopathy clinic, is it going to be precision for that patient, or suing rare variants among many different individual patients to try to find function for a gene? Dr. McNally:                       It's a great question. So I think the first way we approach it is, it depends who's asking the question. So if it's somebody who comes to me who has cardiomyopathy, or has a family history of cardiomyopathy and sudden death, that's a very different question to ask what's going on with their rare variants, for example in cardiomyopathy genes. Now if you translate that over to, I have a big population of people, I don't particularly know what their phenotype is, and I see rare variants for cardiomyopathy, those are two fundamentally different questions. So we very much know a lot about how to interpret rare variants for cardiomyopathy in the context of a patient or a family who has disease, and I do emphasize the latter part of that, the family, working with families and seeing how variants segregate within families. We interpret that very differently, and I think it's appropriate to interpret that very differently in that context. And that's completely different than again, going against what is the regular population, notice I'm not calling it normal population- Dr. Lin:                                  Right. Dr. McNally:                       ... but the general population that's out there. The first step in doing that is the list of the ACMG, American College of Medical Genetics, actionable genes. So this is an interesting question in and of itself. It's 59 genes, of course that list is too small, and it should be bigger than that, and ultimately that will happen. But to take a population based approach to those actionable genes, and looking across the population, finding someone who's got variants in, lets say our favorite genes MYH7, MYBPC3. Knowing what that risk means on a population level is very different than knowing what that means in the context of a patient who comes to you, who has that variant, runs in their family, and has clear disease. Those again, really two different questions, and we have to come up with what's the best practices on that, how to answer either of those questions. Dr. McNally:                       I think the first step working with patients and families who have known disease and have clear variants that segregate with disease, I think its very powerful. I think we've probably got close to a good decade of doing that already. It's incredibly useful for those patients and families. It helps us reduce their risk. It helps us treat them early, it helps us manage their arrhythmias. There's no question that that information is incredibly valuable, but we're still learning how to process that across the population, and how to answer that question for people who are coming who don't already have disease. Dr. Lin:                                  Right, right. That makes sense. And I guess that kind of plays into a follow up question about whether or not we need to test, or think about every variant of unknown significance in lab, and ... the- Dr. McNally:                       It's a great ... You know again, you always have to very carefully consider the context in which the question's being asked. So again, if you're talking about a relatively normal population, well, walking, healthy person, and you're seeing variants of uncertain significance, that's a very different question than somebody who's coming in to you with cardiomyopathy and has a highly suspicious variant of uncertain significance that falls right within the head domain of MYH7. We know a lot about that, and we can do a lot of interpretation in that case. Dr. McNally:                       However, I would say that to put too much value on what we do in the research lab ... Just putting a regulatory hat on for a second and thinking about it, there's nothing from a regulatory standpoint that really validates what we do in the research lab, to say that we can really fairly adjudicate a VUS or not. We can't do that, that's over-valuing what we do in research lab. Dr. McNally:                       So I think, how do we consider variants among certain significance? I think it's really important to recognize that it's exactly that, it's a variant of uncertain significance. And so when you're a clinician taking that to a patient, you have to approach it from the standpoint of saying, this is a variant of uncertain significance. Which means we don't know whether it's pathogenic, but we also don't know that its benign. Because I think right now what we've seen, a lot of clinicians, and even researchers, fall into the path of this believing that variant of uncertain significance is the equivalent of benign. That's not true. It is simply ... That is a rare variant, and we don't know whether it's pathogenic or non-pathogenic. And hopefully overtime we will learn more to better assess that, and better provide the interpretation of what that means in the context of that patient. Dr. McNally:                       It's a good conversation to have. It's important to recognize they're not necessarily pathogenic, but they're also not necessarily benign. Dr. Lin:                                  Mm-hmm (affirmative). So do you see a role, for example, when you see this variant of uncertain significance, is there a role to go back into lab, for example, and try to knock that mutation to IPSC's and test to see if its pathogenic? Or is that going a step too far? Dr. McNally:                       In some cases, that is the right thing to do. Because genetics is so powerful, genetics doesn't only give you the association of a gene with an outcome, and GWAs was fabulous at doing that ... giving us a lot of variants, and often nearby genes, sometimes far away genes, but linking genes to phenotypes, and that's very powerful. But specific variants can actually tell you a lot about mechanism, about how a gene and protein actually function, and how it functions when it's broken. And so, particularly where you can gain a lot from the research front in understanding mechanism, then I think it's really powerful to take those things to the laboratory and to use that to learn about mechanism. Dr. McNally:                       Sometimes you can do it to help adjudicate whether something's pathogenic or not, but again, I think we want to be cautious in doing that. Because what we do in the res ... I always like to say, "What we do in the research lab isn't exactly CLIA certified." Dr. Lin:                                  Right. Dr. McNally:                       There isn't anything magical about what we do, but we definitely ... It is so powerful what's available out there in terms of the genetic variants, and teaching us about how genes and proteins interact. And so I think it is such a rich resource of information right now. The things I bring back to the laboratory, and get my students and trainees excited about working on, is usually where I think we can gain something new about mechanism. Dr. Lin:                                  Right, right, right. Since you are a role model physician scientist, and you think about questions in lab that will ultimately benefit your patients, and you are a genetic cardiologist. What are your thoughts on doing genome editing as a possible therapy for your patients? It's a little bit of a loaded question [crosstalk 00:21:51], it's a little bit controversial. Dr. McNally:                       So I think, no doubt CRISPR/Cas9 gene editing is transforming what we do in the research setting. It's a fantastic tool. Is it a perfect tool? No. Anybody who has been using it a lot in the lab knows that it is much better than anything we've had before, but still quite limited in fidelity and efficiency. And so imagining that we are going to do that in patients is still pretty daunting to me. We do enough gene editing in cells to know that you have to select through an awful lot of cells before you get the one that has the exact variant you are trying to make. So that's not something we can tolerate in the human setting. But we're not there yet, we know that. Dr. McNally:                       Many of the disorders I see clinically are things that are autosomal dominant due to very precise single base-pair changes. And so envisioning how we're going to correct only one copy of an allele and do in a very precise manner, we don't have those tools available yet. Now on the other hand, if you look at a disease like one of the diseases I spend a lot of time on, Duchenne muscular dystrophy, where the majority of mutations are deletions. It's X-linked, it's male, so there's only one copy of the gene, and we know a whole lot about the structure and function of the gene. We know that if we take out this other part we can skip around that mutation and make an internally truncated protein. That's actually a very good use of gene editing, because it only requires making deletions. They don't need to be very precise, and there's only one copy of it that you have to do the gene editing on. Dr. McNally:                       So I see that being something in the near term that will happen, simply because the genetics positions it well to be something where that could be successful. The hard part is still how are we going to get the guides, and how are we going to get the Cas9 in safely into all the cells that need to be treated? And ultimately that lands us back at looking at what our delivery vehicles are. Which at this point in time is still viral delivery, and still has a lot of issues around can we make enough of it? Are people immune to it? So all those questions that come with viral delivery. So still lots of hurdles, but you can see some paths where it makes sense to go forward. Dr. Lin:                                  Very interesting. Okay great. Well thank you for providing your thought on human genetics and genome science. We're going to switch gears for the last portion of this podcast, and talk about your thoughts on career development issues for young investigators. At a recent AHA Scientific Sessions meeting, you participated on a panel that was assembled to provide advice to early career scientists. When you were starting out, what were some of the biggest challenges you faced when you were transitioning to independence and building your own lab, and what's your advice to those facing the same challenges today? Dr. McNally:                       Well, even though I did it quite a few years ago, many of the things are still the same. Transitioning to independence, I think is easier if you pick up and move and start in a new place. I think it's much easier to establish your independence when you're not in the same place as your mentor. That said, we have many more people who now stay in the same place as where their mentors were and we have many more approaches towards doing that. So I think people are much more open to both possibilities as being ways of doing that. But at some level it still comes down to starting your own lab, and you hopefully have been given some start-up resources and you have to think about how to wisely spend them, and how to really get things going. I don't think this is changed either. Dr. McNally:                       I usually tell people, don't just start in one area, if you can, start in two areas because things don't work, and sometimes things do work. In reality when you look at people who are successful, they're often working in more than one area. And so the sooner you start getting comfortable working in more than one area, that's a good thing. Now ideally, they should be areas that have some relationship to each other, and then feed each other in terms of information so that they grow off each other. But what does that practically mean? I always say, "Well if you can hire two people and start them on two different paths, that's a really good way to get going." And practical things like look at all different kinds of private foundations and things like that for getting some good pilot start up money to help develop new projects in the lab. And always be looking at how can these projects help me develop a bigger data package, that's going to put me in a good competitive position for example bigger grants and federal funding, and things along those lines. Dr. McNally:                       Very much a stepwise process. People want to shoot for the moon and get the biggest things first, but sometimes just focusing on the smaller steps which are definitely achievable and building your path towards those bigger steps is the smarter way of doing it. Dr. Lin:                                  That's great advice. You also mentioned recently that young investigators should try to have as many mentors as possible. What advice would you have for, in particular, early career genomics investigators, for finding these mentors passed the postdoc phase? Some of us get introduced at the postdoc phase to maybe some other collaborating labs, but those are really collaborations of our mentors per se. Dr. McNally:                       Well I think especially in the field of genetics and genomics, collaboration is key, and I will say one of the things that has changed over since I started doing this is there is a lot more understanding of the need to collaborate. Not so many years ago, it wasn't really an independent investigator went and started a lab, and it would be your trainees and the papers would have only those people on it. Dr. McNally:                       I think these days, the best science is where you've tackled a problem from multiple different directions, one or two of those being genetics, genomics directions. And then sometimes there's other ways that you've approached that scientific problem. And by necessity, that usually involves collaborating with other people. And your role is sometimes to be the coordinator of all those collaborators, and that's where again you might be in a senior author position then doing that. But your role sometimes is to be the good collaborator. And so when I look at people being successful right now, seven, eight years in to running their own lab, I like to see that they've been the organizer of some of those, that they've collaborated with people who are even senior to them, and that they've established those good collaborations, but that they've taken the leading role in doing that. But also that they've had middle author contributions, that they've been a good collaborator as well. Dr. McNally:                       And so, part of that is not being afraid to collaborate, and to recognize the value of doing that. And what's so great about doing that is you can collaborate with people at your same institution where you are, but you can also collaborate with people all over the world, and I think that's what we do. You go to where you need somebody who is using a technique or an approach that really helps answer the question you want to have answered. And so that's reaching out to people and really establishing again that network and good collaborators which you can do by a whole bunch of ways. You can do it by meeting somebody at a meeting, scientific meeting. You can do it through emails, phone calls, Skype, all sorts of different ways that you can reach out and collaborate with people. Dr. McNally:                       It is easier than ever to share data and share ideas, but that negotiation of how to establish the terms of the collaboration and how to make it be successful is a critically important part of being a scientist. And what we now know when we look at the promotion process, is people who do that effectively, that's a really important mark of being a successful scientist, and marks them as somebody who should be promoted through the process. So great. Dr. Lin:                                  Yeah. No I agree. Certainly with the direction science is moving, it's definitely very difficult to work in a siloed manner. Dr. McNally:                       Yeah. Well you won't get very far. You'll be able to have some really good first ideas, and show some proof of principle approaches. But to really, really address an important scientific problem, we know that you have to see those signals using multiple different methods. And once you have five different ways showing you that that's the right answer, then you're much More confident that you've gotten to the right answer. Dr. Lin:                                  Right. Alright, so I think we're going to wrap up. Do you have any other final thoughts for any other young investigators or genomics researchers listening to this podcast? Dr. McNally:                       It's a great time to be doing genetics and genomics, and particularly human genetics, where we now finally have all this information on humans, and we'll have even more of it in the future. So I think humans are coming close to becoming a real experimental system. Dr. Lin:                                  Excellent. Alright well thank you so much for your time. It was a pleasure having you on this podcast. Dr. McNally:                       Great. Thank you for doing this. Jane Ferguson:                 As a reminder, all of our original research articles come with an accompanying editorial, and these are really nice to help give some more background and perspective to each paper. To read all of these papers, and the accompanying commentaries, log on to circgenetics.ahajournals.org. Or, you can access video summaries of all our original articles from the circgen website, or directly from our YouTube channel, Circulation Journal. And lastly, follow us on Twitter @circ_gen, or on Facebook, to get new content directly in your feed. Jane Ferguson:                 Okay, that is it from us for June. Thank you for listening, and come back for more next month.  

Jane Ferguson:                 Hi, everyone. Welcome to Getting Personal: Omics of the Heart. This is podcast episode 16 from May 2018. I'm Jane Ferguson from Vanderbilt University Medical Center and this podcast is brought to you by Circulation Genomic and Precision Medicine and the AHA Council on Genomic and Precision Medicine. Jane Ferguson:                 This month we talked to Dr. Caitrin McDonough from the University of Florida. We briefly mentioned her paper in last month's episode Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients From the PEAR Study, but we wanted to go into it in more depth this month. Caitrin shared with us that this manuscript actually resulted from student course work and was a collaborative effort between students and instructors. The manuscript highlights has successful as approach can be both in increasing student engagement and as an effective way to do high quality research. You can hear her talk more about her innovative approach to student learning and the study findings later in this episode. Jane Ferguson:                 Of course, we have a great lineup of papers in Circulation Genomic and Precision Medicine this month. First up, a paper entitled, "SCN5A Variant Functional Perturbation and Clinical Presentation Variants of a Certain Significance" by Brett Kroncke, Andrew Glazer, and Dan M. Roden and colleagues from Vanderbilt University Medical Center. They were interested in investigating the functional significance of variants in the cardiac sodium channel in particular to see if they could explain why some variant carriers present with cardiac arrhythmias while others remain asymptomatic. Through a comprehensive literature search, they identified 1712 SCN5A variants and characterized the carriers by disease presentation. Variants associated with disease were more likely to fall in transmembrane domains consistent with the importance of these domains for channel function. Jane Ferguson:                 Using American College of Medical Genetics Criteria for variant classification, they found that variants classified as more pathogenic were also more penetrant. Penetrance was also associated with electrophysiological parameters. This approach highlights how modeling the penetrance of different variants can help define disease risk for individuals who carry potentially pathogenic variants. Jane Ferguson:                 Next we have a paper from Vincenzo Macri, Jennifer Brody, Patrick Ellinor, Nona Sotoodehnia and colleagues from the University of Washington and Massachusets General Hospital. This is also related to sodium channels and the paper is entitled, "Common Coding Variants in SCN10A Are Associated With the Nav1.8 Late Current and Cardiac Conduction". They were interested in SCN10A and sequenced this gene in over 3600 individuals from the CHARGE consortium to identify variants associated with cardiac conduction. They were able to replicate associations between variants and PR and the QRS intervals in a sample of almost 21,000 individuals from the CHARGE Exome sample. They identified several missense variants have clustered into distinct haplotypes and they showed that these haplotypes were associated with late sodium current. Jane Ferguson:                 Continuing the cardiac conduction theme, Honghuang Lin,  Aaron Isaacs and colleagues published a manuscript entitled, "Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval". They conducted a meta-analyses of PR interval in over 93000 individuals which included over 9000 individuals of African ancestry. They identified 31 loci, 11 of which have not been reported before. We see SCN5A come up again as a gene of interest in this study but their analyses also implicated a novel locus, MYH6. Jane Ferguson:                 Next up moving from the heart to the vasculature, Janne Pott, Markus Scholz and colleagues from the University of Leipzig published a manuscript entitled, "Genetic Regulation of PCSK9 Plasma Levels and Its Impact on Atherosclerotic Vascular Disease Phenotypes". They were interested in whether circulating PCSK9 can be used as a diagnostic or predictive biomarker. To address this, they conducted a GWAS of plasma PCSK9 in over 3000 individuals from the LIFE-Heart study. They found that several independent variants within the PCSK9 gene were associated with plasma PCSK9 as well as some suggestive variants in another gene locus FBXL18. They used Mendelian randomization to probe causality and the data suggest that PCSK9 variants have a causal role in the presence and severity of atherosclerosis. Jane Ferguson:                 Moving on to another biomarker, Lisanne Blauw, Ko Willems van Dijk and colleagues from the  Einthoven Laboratory for Experimental Vascular Medicine report on CETP in their manuscript Cholesteryl Ester Transfer Protein Concentration A Genome-Wide Association Study Followed by Mendelian Randomization on Coronary Artery Disease. They aimed to assess potential causal effects of circulating CDP on cardiovascular disease through GWAS and Mendelian randomization. Jane Ferguson:                 In a study of over 4000 individuals from the Netherlands Epidemiology of Obesity Study, they identified three variants in CTP that associated with plasma levels of CETP and explained over 16% in the total variation in CDP levels. Genetically predicted in CETP was associated with reduced HDL and LDL cholesterol suggesting that CETP may be causally associated with coronary disease. Jane Ferguson:                 Rounding out the table of contents we also have a clinical case perspective from Nosheen Reza, Anjali The Importance of Timely Genetic Evaluation in family members in cases of cardiac disfunction and cardiomyopathy. We have a report from Adrianna Vlachos, Jeffrey Lipton and colleagues on the Diamond Blackfan Anemia Registry and we have a clinical case from Yukihiro Saito, Hiroshi Ito and colleagues on TRP and poor mutations in patients with ventricular non-compaction and cardiac conduction disease. Jane Ferguson:                 To read all of these papers and the accompanying commentaries, log on to circgenetics.aha.journals.org and if you're a visual learner or you need a work related excuse to spend time on YouTube, you can also access video summaries of all our articles from the CircGen website or directly from our YouTube channel Circulation Journal. Lastly, follow us on Twitter at circ_gen or on Facebook to get new content directly in your feed. Jane Ferguson:                 I'm joined today by Caitrin McDonough from the University of Florida and Caitrin is an Assistant Professor in the Department of Pharmacotherapy and Translational research in the College of Pharmacy and she's the first author on a recently published manuscript entitled, "Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients From the PEAR Study". This was published in the April 2018 issue of Circulation Genomic and Precision Medicine. Welcome, Caitrin. Caitrin M.:                           Thank you. Jane Ferguson:                 For listeners who haven't had a chance to read the paper yet, I wonder could you give us a brief overview of what prompted you to do this study? Caitrin M.:                           Sure so this looks at plasma renin activity and just initially a GWAS but it was done in a hypertensive population from the pharmogenomic evaluation of antihypertensive responses study. Particularly, since our group here at the University of Florida is more interested in pharmacogenomics we wanted to address plasma renin since it can influence blood pressure response to antihypertensive medication particularly if you use it as something to predict but also to correlate it with that as there have been also prior data from our group that shows if you have different levels of plasma renin that would predict if you would respond better to certain types of antihypertensive medications such as a beta-blocker or a diuretic. Caitrin M.:                           We used both a GWAS approach as well as a prioritization through blood pressure response to focus in on signals and then furthered by using prioritization using data from RNA seq and looking at eQTLs and then finally looking at more of just a traditional net replication of the original plasma renin activity signal. Caitrin M.:                           Overall, one of the interesting things and why we were initially doing this study was really in connection with a graduate course that myself and another faculty member here who's also an author on the paper, Yan Gong [inaudible 00:09:12]. We often have the students analyze data from the PEAR study as we have a lot of data from that study and it helped us analyze additional papers but we didn't necessarily know if this was going to be an interesting phenotype but through that course work which turned out that it really did have some interesting signals so we wanted to follow up more on. Jane Ferguson:                 Yeah, I love that approach so I think that's a really smart way to do it. To actually get your students to analyze your data and get them really involved in the process. How much then did the students ... how much were then they able to get involved when it started transpiring that their results would actually be something that could be put together for a manuscript? Caitrin M.:                           Overall, they are fairly involved. During the course work, what we usually do is give them just directly types data since a lot of them have not done this type of genetic analysis before and we split it up where each student gets about four to five chromosomes of data and then different phenotypes in the different race groups as we have both whites and African Americans. They get a certain race group, certain number of chromosomes and so they're able to conduct the analysis just using the Uplink software which is fairly user-friendly and straightforward. Then they get experience making Manhattan plots and using LocusZoom. Caitrin M.:                           After they have the basic techniques, then we teach them how to start following up top signals and determine what is a good signal. They're looking at the LD or SNP function or possibly gene function or looking at their genotype, phenotype relationships and making sure that it's not just one person who's driving the whole signal. Then selecting what top reasons and top SNPs may need a follow up. That part they all do there in the class and learn more of the basics. Caitrin M.:                           After the class, the students who want to continue to participate we get together and redistribute data where they would then move on to working on the imputed data sets and we teach them how to do that. Then we give them ... operate it somewhat similar to a consortia level meta-analysis type thing. I write up an analysis plan, each student does some part of the analysis. They have to bring it all back to me. I sort through it. We meet and go through it. Then we set our next steps to follow up. Then different students get different SNPs to investigate the function of or different subanalyses to do. Caitrin M.:                           One of our graduate students who is on this particular project, her dissertation project was very focused on our RNA seq data so that was how we were able to bring in the eQTL analysis using the RNA seq data as she had done a lot of the groundwork with that already. In one of our discussions that was one of the ways that we were able to incorporate the prioritization since she was intimately familiar with that data set. Jane Ferguson:                 Yeah and I think that's great. I can imagine that, that's a much more compelling way for students to learn about how to analyze data when they see the natural follow through. Do you find that some of the students maybe get more excited about research or are more likely to pursue future research opportunities by having had this hands on experience with the publication process and completing a project really did to this very end? Caitrin M.:                           They do, yeah. I see some of the students that end up sticking with it more are the students who I work more closely with and see more closely some of the students who are from other departments still stay involved but sometimes don't stay quite as involved. But, all of them really do continue to follow up and ask if they can still help or if there's anything they need to do until we get it to publication which is really nice. Jane Ferguson:                 Yeah, right. I think that's fantastic and I'm sure every study has its challenges. I'm interested what were the challenges you encountered in doing this study and which one of them may be unique to the way you have a lot of different people analyzing different aspects of the data versus the regular challenges that would come up in a study like this. Caitrin M.:                           Yeah so some of it I think is just keeping everyone on track and keeping it organized, making sure I think some of our challenges with this study was just me making I think on a lot of other studies, while I had certainly hands on the data it was more of an oversight rule for some pieces of it and just making sure everything looked the way that I thought it did, double checking. Some of it I think the teaching aspect of it just making sure everything was also done correctly and then keeping everything organized made the study a little bit more challenging. Caitrin M.:                           I think part of it too was with the PEAR study, it is a very rich data set. Determining what we wanted for our prioritization scheme and how to work through the different types of data sets that we had and put it all together as initially we just assign each student a different piece and we had a vague plan but it was a little bit more tricky as to work through how it was all coming together then when everyone came back together since a lot of people were doing as opposed to just one person doing it. Jane Ferguson:                 Right, so yeah and I think you're touching on the part that all of us have when we're writing papers that you sometimes end up with a lot of data at the beginning, you're trying to sift through it and then sometimes at a certain point you see something and you're like, "Okay, yes. This is interesting." Then you start following it up. Jane Ferguson:                 I wonder at what point did that happen? I suppose you probably ... You ran the GWAS for plasma renin activity and then find a number of suggested SNPs that were significant you associated but then ... Describe your strategy and you did so the second screening stuff to look at the pharmacological aspect defining [crosstalk 00:15:12]? Caitrin M.:                           Yeah, our initial plan going in was the first two steps, to do the GWAS for plasma renin activity and then to do the prioritization through blood pressure responses. I was very familiar with what our lab was familiar with but then after we got there, I think we were then troubled with what we did next and where to go. When we decided to bring in the RNA seq data, I think that was when it really started coming together as our top signal, the SNN-TXNDC11 gene region really stuck out then and it showed up. That seemed like a much stronger signal and it gave us a little bit more focus and also brought it much more of a functional aspect where we would maybe start to believe that signal more. That I think was really when we did that more of a turning point for the study and helped us focus more on where then to go with the results. Jane Ferguson:                 As far as the data you had I think over 700 people for your GWAS. Then you had a pretty large number of ... Was it the same subjects or different subjects where you also had the RNA seq data to do the QTL analysis? Caitrin M.:                           The same subject so not everyone has RNA seq. We have RNA seq data on 50 individuals and they were selected from whites and at the extremes of the blood pressure response so that it has a slightly interesting selection process. It's the main data analysis there was a best responder, worse responder to thiazide diuretics. Caitrin M.:                           When we do the eQTL analysis, we aren't always sure what we're going to get since we're missing the middle of blood pressure response. But, when we're just looking strictly at eQTL analysis sometimes we get lucky and sometimes it looks weird. Jane Ferguson:                 In your case as well you had the added issue of subjects were randomized to drug treatment so it was some where responders were ... I guess some people got the drug that worked for them and some people did not get the drug that worked for them. Caitrin M.:                           Yeah. Jane Ferguson:                 Did you I guess were incorporating both groups so good responders to either and some of that was because of their gene. They got the right drug for their genotype. Caitrin M.:                           Exactly, yeah. Jane Ferguson:                 It's good and then you were able to replicate this. After you were able to prioritize your gene region based on the GWAS and the drug response and the eQTL data, you actually ended up being able to go to a second sample to replicate the association right? Caitrin M.:                           Yes, it was in a lot of the same investigators, we have a second study PEAR-2, which has a very similar design to the PEAR study but used different drugs but also collected baseline plasma renin activity. We were able to use that phenotype again. We did have slight differences in GWAS to imputation panels at that point in time for when we were conducting this study so we ended up using a proxy to replicate but we did see the same signal in the second population which was very nice to see. Jane Ferguson:                 What is known about this gene region or either of these two genes? Caitrin M.:                           Overall, that was I think one of our harder points when we started trying to make the connections back to our phenotype. This was one of the areas where we did also have help from our students and the students as that was part of their initial training where they really looked to see what function was of various different genes and how to follow them up. That was one area where they came in, was to help look up some of the function of these ... there have been some connections with the various genes, the other phenotypes and with SNN and to atherosclerosis and other inflammatory cytokines such as TNF-alpha. Then there have been data also from [inaudible 00:19:37] that really show that there is an eQTL in this region that which supports what we saw in our own data. However, there really wasn't any direct connections with renin and the renin angiotensin aldosterone system and blood pressure regulation that we could find in the literature. Caitrin M.:                           We're not exactly sure how it connects but based off of our functional data and levels of evidence and then we saw some of that in publicly available data, we're still very interested in the region. Jane Ferguson:                 I think the data is compelling enough that it looks like you've identified the new region that probably is the mechanistically related that will require a whole bunch of basic mechanistic research to figure out what exactly the genes in this region are doing and how this ultimately connect back to blood pressure and response to drug therapy. Caitrin M.:                           Exactly. Jane Ferguson:                 I could see this ... I mean obviously there's a whole lot of potential functional work there and then probably also the clinical work, I wonder what you think about how this would affect any pharmacogenetic therapeutic ... You know at present I think you can look at plasma renin activity and use that as a predictor of drug response to help guide therapies. Would you think that a genotype guided therapy may end up being more effective than the plasma renin activity measurement in this case? Caitrin M.:                           In this case since this is so connected with a phenotype that you could use with plasma renin, I think if you're able to draw a plasma renin you may just want to do that. I think our overall goal would be if someone had preexisting genetic data and you weren't wanting to do an additional test or if you're contemplating response to a lot of different drugs that perhaps you could use a genetic data. One of the issues that was brought up on review and that are a lot of group considers quite a lot is that we have a lot of signals and that our group has certainly published a lot in this area and there's a lot of signals that we have to a lot of different drugs and how do you incorporate all of them together, is there overlap between them or where do they all fall? Caitrin M.:                           That is certainly something that we're still working on as more I think ultimate goal would be more to delve more of a SNP score or gene score and some type of risk score that would help you determine what drug you would best respond to. We've done that a little bit in some of our prior publications but we haven't yet taken all of our data together and help to build something that would if you had a lot of data on an individual and various different alleles at various different genes, how that would respond. Caitrin M.:                           Overall, when we look at blood pressure response as a pharmacogenetic signal, certainly we see larger affect sizes than you would in disease genetics but we're not seeing affect sizes like you would with more of an adverse drug event. We're in between there and we're often times it's not necessarily just going to be one SNP or one gene that would tell your whole story but a combination of quite a few of them. Jane Ferguson:                 I wonder are there more similar stories like this from the same data set? You know you've been through this process from start to finish and building in the functional work and do you think that next year's class will be able to do this again with the same data set? That maybe pick one of the next priority candidate down the list and maybe find another interesting story like this? Caitrin M.:                           Yeah, so we actually just finished our class this year and they looked at potassium. We just got done grading final papers and submitting grades so we will over the summer be working with them a little bit more. I think some of our new graduate students too are starting to work on trying to make more connections between a lot of our different phenotypes and as you start to layer those together what it exactly means for a patient or implementation perspective. Jane Ferguson:                 Yeah, interesting. We'll have to look for that story whenever you guys get done with it. Otherwise, are you planning on following up this specific SNP region in any other way or any other studies? Where's next for you guys overall? Caitrin M.:                           I think one of the things we would like to do is look at this more in PEAR-2. We really just brought the PEAR-2 data set in here as replication of the top region in that last stage but we have that data set and we can certainly look at that data set. Caitrin M.:                           The other thing that I would like to do is as we started this project in conjunction with the class that was a couple of years ago at this point in time, we used [TAP/MAP 3 00:24:35] imputed data since that was what we had in the lab and what we were using at that point in time. At this point in time, we have now imputed both PEAR and PEAR-2 2000 genomes phase three data. It'd be interesting to see if we are able to see any additional signals or if these regions become stronger or exactly what would happen using a more imputation panel that has more coverage and where we would have the same panel between both PEAR and PEAR-2. Jane Ferguson:                 Right because you may or may not have identified the causal SNPs in the previous access but- Caitrin M.:                           Yeah. Jane Ferguson:                 -yeah so it'd be nice to see if you can actually get that out. That potentially could end being a drugable target maybe suitable for something more specific but who knows. Is there anything else that we haven't covered yet that you'd like to mention? Caitrin M.:                           Overall, I think that just this type of model of utilizing more of a real world analysis and data in a class project really certainly engages our students a lot and I think they all enjoy actually being able to work with data that came out of this study and have a lot more hands-on experience and really project-based analysis experience. We've been very happy with this model and have used it multiple times. We have an HDL paper, the renin paper, our glucose response paper and now we're working on the potassium project. It's been a good model for us here with our pharmacogenomics class. Jane Ferguson:                 Yeah, I mean I think it's a really smart and intuitive way to think about education. It's mutually beneficial it sounds like, so it's helping you guys get your data analyzed. It's really helping the students learn so I think it's a win-win situation. I think it's a model that a lot of other people would really be interested in adopting. Caitrin M.:                           Yeah. Jane Ferguson:                 Okay well thanks so much for talking to me and talking about your model and your research. It's been great. Caitrin M.:                           Yes, thank you very much for having me. Jane Ferguson:                 That's it from us for May. Thank you for listening and come back for more next month.  

Jane Ferguson:                 Hello, welcome to Getting Personal: Omics of the Heart. This is podcast Episode 15 from April 2018. I'm Jane Ferguson, an Assistant Professor of Medicine at Vanderbilt University Medical Center, and this podcast is brought to you by Circulation Genomic and Precision Medicine and the AHA Council on Genomic and Precision Medicine.                                                 As usual, we have a great lineup of papers in Circ Genomic and Precision Medicine this month. The first is actually the subject of our interview this month. Sony Tuteja talked to Craig Lee from the University of North Carolina about his manuscript entitled, "Clinical Outcomes and Sustainability of Using CYP2C19 Genotype Guided Antiplatelet Therapy After Percutaneous Coronary Intervention." This manuscript investigated the use of pharmacogenomics to improve treatment after PCI, and you can hear a lot more about it directly from the first author later in the podcast.                                                 Our next manuscript also used pharmacogenomics approaches to look for snips associated with plasma renin activity and to assess the effect of top snips with blood pressure response to atenolol and hydrochlorothiazide. The first and last authors are Caitrin McDonough and Julie Johnson from the University of Florida. And their manuscript is entitled, "Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients from the Pharmacogenomic Evaluation of Antihypertensive Response," or PEAR study. They find that snips in the SNNTXNDC11 gene region associate with higher baseline plasma renin activity in their sample of over 700 subjects and with a smaller systolic blood pressure reduction to hydrochlorothiazide. Variation in the region may act through modulation of TXNDC11 gene expression. They also identified several other candidate genes of interest. These new candidates may allow for precision medicine approach to selection of hypertensive treatment and further study the mechanisms may reveal novel biology on blood pressure response to pharmacological treatment.                                                 Next up is a manuscript by Deirdre Tobias and colleagues entitled, "Circulating Branch Chain Amino Acids and Incident Cardiovascular Disease in a Prospective Cohort of U.S. Women." I actually had the chance to talk to Deirdre about her research last month. So check out the March podcast, Episode 14, to hear more from Dr. Tobias about this study.                                                 A study of hypertrophic cardiomyopathy from Hannah [inaudible 00:02:36] and Michelle Michels and colleagues from the Erasmus Medical Center in the Netherlands assessed the effects of genetic screening in family members of patients with a known hypertrophic cardiomyopathy mutation. In their manuscript entitled, "Outcomes of Contemporary Family Screening and Hypertrophic Cardiomyopathy," they described their study which assessed cascade screening in 777 relatives of 209 probans between 1985 and 2016. Genetic and clinical screening resulted in a diagnosis of HCM in 30% of family members at the time of testing. An additional 16% of family members developed HCM over seven years of follow up. Of the 43% of family members who were genotype positive, 37% were ultimately diagnosed with HCM. There was no difference in survival between genotype positive and genotype negative family members or with relatives who did not undergo genetic testing.                                                 There are genetic considerations that are unique to the ancestral composition of the Netherlands with a high proportion of individuals with a founder mutation, so the proportion of probans with identified mutations is higher than in other reported studies. This paper demonstrates the potential benefit of genetic screening in family members, which can identify individuals who should undergo intensive screening, and at the same time reduce concerns for family members who are genotype negative. However, the classification of the pathogenicity of variants and understanding variable penetrance remains a challenge.                                                 A manuscript entitled, "Exome Sequencing in Children with Pulmonary Arterial Hypertension Demonstrates Differences Compared to Adults." From Na Zhu, Claudia Gonzaga-Jauregui, Carrie Welch, Wendy Chung, and colleagues from Columbia University, ask the question whether there were differences in the genetic mutations responsible for early onset pulmonary arterial hypertension, or PAH, in a pediatric sample compared with adult onset disease. While some mutations, particularly in BMPR2 appear to be similar in the pediatric and adult samples there were significantly more mutations in TBX4 in the children compared with adults.                                                 Further, children were more likely to have de novo mutations identified through exam sequencing that were predicted missense variants. Given the additional complications associated with pediatric onset of PAH, understanding the genetic differences in this population is an important step towards identifying novel genes and mechanisms which could guide future therapeutic development.                                                 Our next manuscript authored by Iisan Kadhen, Carolyn Macdonald, Mark Lindsay, and colleagues from Harvard Medical School is entitled, "Prospective Cardiovascular Genetics Evaluation in Spontaneous Coronary Artery Dissection," or SCAD. They genotyped individuals with SCAD to find out the genetic contribution to the disease. Of the patients for whom genetic testing was performed, six of them were 8.2%. Identifiable mutations in genes known to be involved in vascular disease, including COL3A1, LMX1B, PKD1, and SMAD3. These individuals were significantly younger at the time of their first SCAD event compared to patients with no identifiable mutation. Given the relatively higher rate of mutations identified in this sample, there may be a rationale to conduct genetic testing in all individuals presenting with SCAD, particularly in younger individuals.                                                 Shiu Lun Au Yeung, Maria-Carolina Borges, and Debbie Lawlor, from the University of Hong Kong and the University of Bristol, set out to find out if reduced lung function is causal in coronary artery disease. As reported in their manuscript, entitled "The Association of Genetic Instrumental Variables for Lung Function on Coronary Artery Disease Risk, A 2-Sample Mendelian Randomization Study," they used a Mendelian Randomization approach to assess causal relationships between two measures of lung function. Forced expiratory volume in one second, and forced vital capacity on CAD. Genetic predictors of increased forced expiratory volume were associated with lower risk of CAD. While there was a similar association with forced vital capacity, this was attenuated in sensitivity analyses. Overall, the data suggests that higher forced expiratory volume may independently protect against CAD. However, the mechanisms remain unclear.                                                 Finally, the April issue also contains a white paper from Kiran Musunuru, Xiao-zhong Luo, and colleagues entitled, "Functional Assays to Screen and Dissect Genomic Hits, Doubling Down on the National Investment in Genomic Research." This paper lays out strategies to followup on findings from high-throughput genomic analyses, including the use of novel technologies, assays, and model systems that can help to effectively translate big data findings and capitalize on previous investment in genomic discovery.                                                 To see the latest issue of Circulation Genomic and Precision Medicine, and to access all the papers we talked about and to browse previous issues, go to "circgenetics.ahajournals.org." Sony Tuteja:                       Hello, my name is Sony Tuteja, I'm an assistant Professor of Medicine at the University of Pennsylvania in Philadelphia, I'm also an early career member of the American Heart Association Council on Genomic and Precision Medicine. Today I'm joined by Dr. Craig Lee, an associate Professor of Pharmacy at the University of North Carolina School of Pharmacy. Dr. Lee is a first author of an article published in April 2018 issue of Circulation Genomic and Precision Medicine entitled, "Clinical Outcomes and Sustainability of Using CYP2C19 Genotype Guided Anti-Platelet Therapy After Percutaneous Coronary Intervention." Welcome Dr. Lee, and thank you for joining me today. Craig Lee:                            Thanks for having me. Sony Tuteja:                       First let me just say congratulations on spearheading such impactful work on the implementation of CYP2C19 pharmacogenetic testing. Craig Lee:                            Thanks, this has been a very complicated project, but a lot of fun. Sony Tuteja:                       Great. So I think some of our listeners may have not had time to read your paper yet so I was wondering if you could provide a brief overview of the paper and what the study was about. Craig Lee:                            Sure. Although it's been widely described that loss of function polymorphisms in the drug metabolizing enzyme, CYP2C19, which is responsible for the bio-activation of the antiplatelet drug clopidogrel, impairs its effectiveness, there remains considerable debate and uncertainties surrounding whether CYP2C19 genetic testing should be used clinically for guiding antiplatelet therapy in percutaneous coronary intervention, or PCI patients. As the evidence base is expanded, an increasing number of institutions are seeking to implement CYP2C19 genetic testing despite limited data on the use and impact of using this genetic testing to guide antiplatelet therapy selection following PCI in real world clinical settings.                                                 UNC was an early adopter for CYP2C19 genotype-guided antiplatelet therapy in high-risk PCI patients. Our algorithm recommends that patients carrying one or two loss of function alleles in CYP2C19 be prescribed an alternative antiplatelet therapy such as prasugrel or ticagrelor. Our algorithm was implemented back in the summer of 2012, under our then-director of the Catheterization Laboratory, and now Chief of Cardiology, Dr. Rick Stouffer. We conducted the study to better understand the feasibility, sustainability, and clinical impact of using CYP2C19 genetic testing to optimize antiplatelet therapy selection in PCI patients in real-world clinical practice.                                                 Basically what we did was following the implementation of our algorithm in the summer of 2012, we've been retrospectively collecting data from all patients that come through our Cath lab that undergo a PCI. We collect information on their clinical characteristics, whether or not they underwent CYP2C19 genetic testing, what antiplatelet therapy they were prescribed when they were in the hospital at discharge and over the course of followup, and more recently we've been assessing clinical outcomes, both ischemic outcomes and bleeding outcomes. The data presented in our paper described the algorithm's use at our institution over the first two years following its implementation from 2012 to 2014 with one year of followup data. Since we do about 600 PCI procedures per year on our Cath lab, the study population is just under 1200 patients.                                                 Our main findings were that CYP2C19 genotypes were frequently ordered, efficiently returned, and routinely used to guide antiplatelet therapy selection after PCI over this two year period. However, we also observed that the frequency of genotype testing and frequency of using alternative therapy such as prasugrel or ticagrelor in the patients that carried CYP2C19 loss of function alleles fluctuated over time. We also observed that use of clopidogrel in patients that were tested, but carried either one or two copies of a CYP2C19 loss of function allele was associated with a significantly higher risk of experiencing a major ischemic cardiovascular event compared to use of alternative therapy. These risks were particularly evident in the highest risk patients, and largely driven by patients who carry only one copy of the loss of function allele, the so-called intermediate metabolizers.                                                 Our primary takeaway from this analysis is that implementing a genotype-guided antiplatelet therapy algorithm is feasible, sustainable, and associated with better clinical outcomes in a real-world clinical settling, but challenging to maintain at a consistently high level over time. Sony Tuteja:                       Great. I know it's always challenging to implement new work flow and new testing into the clinical setting. Can you describe how the algorithm was incorporated in the cardiologist workflow to minimize disruption? Craig Lee:                            Absolutely. This algorithm was spearheaded by our interventional cardiologists with the support of our clinical pharmacy specialists and pathology laboratory. They key element to our success is that we have the capacity to do the genotype testing in our molecular pathology lab on site. Dr. Karen Weck is the director of that laboratory and is a coauthor on our paper. Since the prescribing decision for antiplatelet occurs in a highly specialized clinical setting, we have all the pieces in place to do this in-house at UNC, which seems to make things very efficient.                                                 There really wasn't very much disruption in the workflow given that the testing is done on-site and the test seems to be treated like another laboratory test that's done, which is really the ultimate goal of pharmacogenomics. We don't currently actually have clinical decision support built into our electronic health record, so the reason we could actually get this off the ground was because of the substantial collaboration between our physicians, pharmacists, and pathology lab.                                                 But one of the things we learned through this experience, which is described in the paper, is that there are fluctuations in the use of the genetic testing to guide prescribing over time that we believe could be remedied by developing more automated clinical decision support, to help make things a little bit more efficient for the clinicians. But at the start of it, it was really just a will to do it, which was really exciting to observe. Sony Tuteja:                       Absolutely. That's exciting that everybody was on board with this project. What do you think were the most challenging aspects of the implementation? Craig Lee:                            That's a great question, and one that often comes up. I think that the education on the front end is really, really important. It needs to recur as the implementation spans over a period of time. For example, there's turnover in the interventional cardiology fellows every summer as well as occasional turnover of attending physicians and clinical pharmacy specialists. As individuals come and go into the clinical environment, it is important that they understand how the algorithm works, and how it can be applied in practice. And this is accomplished by recurring education and communication.                                                 The other thing that's been a challenge is turnaround time. Even though our molecular pathology lab typically turns tests around within one day of a PCI procedure, if the test result isn't available or the antiplatelet therapy isn't changed in response to the genetic test before the patient is discharged from the hospital, we found that it can be challenging to followup on the result before the next encounter. Typically, if a change in medication needs to occur after discharge and prior to the first followup clinic visit, the communication piece has proven to be very important. It's not an insurmountable barrier, but one we observe that created one additional challenge. Other institutions around the country that are doing this have expressed similar things. Sony Tuteja:                       You showed in your study that during the middle of the implementation there was a decline in testing. What do you think were the major reasons that led to decrease in testing? Craig Lee:                            Yeah, that's a great question. We're not sure. We didn't collect information prospectively, and more specifically, we did not survey the physicians in terms of why they ordered the test. But we believe, just based on anecdotal experience and talking about this with everyone, there was this big surge of momentum, with the initial implementation, and as the practice evolved there was just sort-of a settling of individuals in terms of, I think, the practice patterns.                                                 Overall, the test was ordered and over 70% of PCI patients, an alternative therapy was prescribed and approximately 70% a loss of function allele carriers. These numbers exceeded 80% early on which was higher than we expected. They dropped down to about 60%, which is still a pretty high utilization rate when you compare to other institutions that have implemented. After some educational efforts, the testing rates and use of alternative therapy and loss of function allele carriers began to increase again over the last six months. Sony Tuteja:                       Yeah I was just gonna ask, since the study is completed, have you taken any further steps to maintain the frequency of the testing at the high level that you initially started with? Craig Lee:                            Yeah, so again recurring education has been really important particularly with interventional cardiology fellows, since they're the ones that really execute this in terms of ordering the tests and working with the clinical pharmacy specialists. And as I mentioned, we're in the process of developing clinical decision support to help make this a little bit easier on the prescribers. When a test result is available, we believe this will make it a little easier for the result to be more readily available for the clinical decision. Sony Tuteja:                       Yeah I think the CDS tools will be key to have more compliance with the results in adherence to the test results. I'm just curious, who pays for the genotype tests at your center and are you billing for these tests? Craig Lee:                            Yes. We're billing for these tests as part of routine clinical care. Sony Tuteja:                       Great, and you've had good success with reimbursement? Craig Lee:                            As far as we can tell, yes. Sony Tuteja:                       That's great to hear. I think that will really incentivize other centers to pursue similar lines of testing. So what do you think are the broader implications for implementing genetically guided care for other drugs? Craig Lee:                            Yeah, I think that it's interdisciplinary collaboration. Communication is really important among physicians, clinical pathologists, and clinical pharmacists. We found that this has been essential to success of the program here at UNC with this one gene drug pair. And again, this is fueled by a spirit of collaboration and will for our clinicians to work together to optimize patient care. And really, I think clinical pharmacists are uniquely positioned to help make this happen. Clinical pharmacists are uniquely positioned to interpret pharmacogenomic test results, provide medication recommendations, as well as counsel patients on how to interpret the tests and why the prescribing decision is being made. Our clinical pharmacists at UNC are fantastic and have really embraced this. They've shown that pharmacogenomics can be an important part of medication therapy management.                                                 Although implementation of pharmacogenomics testing is clearly a challenge, it is now part of the routine in our Cath lab and in our cardiology services. And again, that's been really exciting to observe. I also think this experience provides a foundation in an example for other pharmacogenomic implementations to occur at our institution. Sony Tuteja:                       That's great, it's so nice to hear about the team working together to get this accomplished. What has been the patient response to the testing? How have they responded to receiving genetic test results? Craig Lee:                            We think it has been overall positive. And again, it's now part of the workup in terms of providing the best possible care for the patient given the evidence that we have. And so again, since it's part of the clinical work flow, there's not a separate research consent that's done. The testing is part of the consent to the procedure. Sony Tuteja:                       Well great, that's all the questions I have for you today. Do you have any final thoughts you wanna share with our listeners? Craig Lee:                            No, other than just a thank you again for having me in for talking about our paper. And I guess, I would just urge those that are out there that are either planning to do this or doing this, to collect data. It's really important to evaluate the practice, evaluate the frequency of testing, the frequency of prescribing decisions being altered by the testing, and trying to understand what the barriers are. And if possible, evaluate clinical outcomes.                                                 You know, we started this study under the umbrella of continuous quality improvement and it really has taught us a lot. I think it has helped optimize how the algorithm is used, and as other centers around the country have been doing this, it provided a basis to collaborate and really evaluate the impact on clinical outcomes, which is really the question that is on everybody's minds. And as the evidence base expands, I think there will be a lot more comfort with doing these things, but we should always strive to generate the evidence we need to assure that we're making the right decisions in practice. Sony Tuteja:                       Absolutely, I think that outcomes piece will be critical to getting this in the mainstream. Well I'd like to thank you for your time today, it was a pleasure speaking to you and once again, congratulations. Craig Lee:                            Thanks. Jane Ferguson:                 That's all for this month. As a reminder you can follow us on Twitter, @Circ_Gen or connect with us on Facebook. Thanks for listening, and I look forward to bringing you more on genomics and precision medicine of the heart next month.  

Jane Ferguson:                 Hello, welcome to Getting Personal: Omics of the Heart, episode 14 from March, 2018. I'm Jane Ferguson, and this podcast is brought to you by Circulation Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. This month I talk to Deirdre Tobias about her research on branch gene amino acids and incident cardiovascular disease in women, and I got the chance to talk to Kiran Musunuru, the new editor in chief of Circulation Genomic and Precision Medicine, about his take of the publishing process and new directions the journal has been taking.                                                 I'm joined today by Dr. Deirdre Tobias who is an instructor in medicine at the Brigham and Women's Hospital in Boston. Dr. Tobias is the first author of a paper entitled Circulating Branch Chain Amino Acids and CBD Risk in Women that is published this month in Circulation Genomic and Precision Medicine. Deirdre is also presenting this work at the lifestyle sessions in New Orleans this month, where she is receiving the Scott Grundy fellowship award for excellence in metabolism research. Deirdre, thank you so much for joining us, and congratulations on your manuscript and your upcoming award. Deirdre Tobias:                 You're very welcome, and thank you. Jane Ferguson:                 Could you tell us a little bit more about your background, and what led you to this specific research focus? Deirdre Tobias:                 Sure. I am an epidemiologist, and I investigate risk factors for type two diabetes and other obesity related chronic diseases. Most recently I've been interested in looking at the mechanisms linking obesity with many of it's associated risk factors through metabolomics. Metabolomics is a field that's relatively new, and it identifies, or seeks to identify small circulating molecules throughout the blood, or urine, or other specimen samples, and then relate those levels to risk of disease.                                                 Type two diabetes has had large successes with finding markers that are novel, and these are often consistently identified across studies, which is very reassuring, and not always the case for many risk factors of chronic diseases. Branch chain amino acids in particular have been consistently associated with diabetes risk across study populations, and tissue type samples, and methodologies for measuring metabolites. This is reassuring that these metabolite markers might really be picking up on an important signal in diabetes risk. Jane Ferguson:                 For any of our listeners who haven't had a chance to read your paper yet, I wondered. Can you give us sort of a brief overview of what you did, and a summary of your findings? Deirdre Tobias:                 Sure. Metabolomic studies, as I mentioned, have been successful in the field of type two diabetes, but less so for cardiovascular disease endpoints. With branch chain amino acids being a risk factor for type two diabetes we then thought to establish, or to examine whether they were also associated with incidents of cardiovascular disease risk. In our study we had branch chain amino acids measured on over 27,000 women from their baseline blood samples, and these women were participants in the women's health study in the US.                                                 This cohort already has over 18 years of mean follow up with a number of CBD and diabetes cases already accrued, so we used these baseline measures of branch chain amino acids measured from plasma samples to then relate these to incident CBD risk. We had over 22,000 MI, stroke, and revascularization events in these women. What we then did was analyze the relationship between branch chain amino acids levels with incident in CBD. Jane Ferguson:                 That's a really amazing data set. I mean, that's a huge number of subject, so that's really, really powerful. Deirdre Tobias:                 Yeah. For metabolomics most of the prior evidence has come from smaller case control studies, so this is really an unprecedented number of women participants in general that have had metabolomics with this much follow up. It was definitely a rich resource to be able to address this question and with a substantial amount of statistical power. Jane Ferguson:                 Right. I know you ran a large number of different models, and you looked at a lot of different covariances, so what were the primary findings? Deirdre Tobias:                 The main results indicated that even adjusting for the traditional CBD risk factors, including behavioral, and lifestyle, smoking status, family history, race and ethnicity, even body mass index which is a strong predictor of branch chain amino acids levels, we observed a striking association indicating that higher levels of branch chain amino acids were associated with a greater risk of MI stroke or revascularization during follow up. Jane Ferguson:                 Yeah, and I thought it was really interesting that you saw this in the whole sample, and then you also saw this sort of same association, in sort of like attenuated strengths in individuals without type two diabetes. Then, when I was looking I suppose you had adjusted for a number of different biomarkers, and then when you adjusted for the biomarkers as pre diabetic risks, so hemoglobin A1C or insulin resistance, the association went away. I wonder, even in your subjects who didn't have diabetes yet, were the association between the branch chain amino acids and CBD events was significant, but do you think that this was primarily driven by the pre-diabetes level, where these women are probably on track to developing diabetes, and just haven't hit that threshold for diagnosis yet? Deirdre Tobias:                 I suspect that could be the case. We do know that diabetes is a risk factor for CBD, and as I mentioned with the strong, consistent evidence indicating branch chain amino acids as a risk factor for type two diabetes we wanted to disentangle any association that we would see with branch chain and CBD to be able to show if that was independent of intermediate type two diabetes or not. When we did stratify by diabetes, clearly the majority of that risk seemed to be driven through type two diabetes.                                                 The women who had diabetes prior to their CBD event, clearly we saw the relationship much stronger for them. The residual is still there among those without type two diabetes, could be some clinical diabetes or pre-diabetes. It's hard to really say for sure, but we do have additional models where we adjusted for biomarkers that were measured in the same baseline blood samples as the branch chain amino acids.                                                 When we adjust for these markers that are more related to insulin resistance and glycemic control we see that the relationship between branch chain amino acids and CBD becomes attenuated. We can interpret this as being that the branch chain amino acids may be mediating the relationship with CBD through these markers of insulin resistance and glucose metabolism. If we similarly adjust for cholesterol, LDL or HDL, the relationship between branch chain amino acids and CBD didn't budge.                                                 That would indicate that perhaps branch chain amino acids and CBD risk is being mediated largely through this diabetic pathway rather than other more traditional CB pathways such dyslipidemia or inflammation. Jane Ferguson:                 Right, so it's an entirely independent pathway, I guess, that probably adds to the risk rather than being complimentary with traditional risk factors like LDL cholesterol. Deirdre Tobias:                 Yeah. The common soil hypothesis which has been around for many years suggests that there's a common set of risk factors, or cardio metabolic dysfunction, that leads to both diabetes and CBD. This suggests that branch chain amino acids and impaired branch chain amino acid metabolism could be one pattern or marker of this common predisposition to both type two diabetes and CBD. Jane Ferguson:                 Right. It's really interesting stuff, and I think this field, it's so challenging following up these markers when you're trying to find out, is a biomarker, when it's associated with a disease is it actually causal, is it a bystander? Are branch chain amino acids increased by insulin resistance, but don't actually themselves contribute to disease, or are they also individually contributing to disease. I know there's been some papers trying to address this through Mandelian randomization approach.                                                 It's indicated that the genetic predictors of branch chain amino acids aren't necessarily causal for diabetes, but that's sort of a consequence for insulin resistance. I wonder how that fits into your findings with, then, the additional associations with cardiovascular disease where we think of this pathway where we get this increased diabetic risk, and then perhaps as a consequence of the increased diabetic risk you have increased branch chain amino acids. Are these, then, themselves increasing oxidative stress or some other mechanism that's then leading to pro-atherogenic, pro-cardiovascular risk, or is it still just, well, it's a bystander, and they're there?                                                 They're a biomarker, but they're maybe not great targets for therapeutic interventions. I don't know what you think of this. Deirdre Tobias:                 Yeah. No, that's a completely fair interpretation of the data, and the literature overall. I think with observational epi, disentangling not only the causality but the temporality, so which biomarker is really, if it is causal, occurring first on this pathophysiology from say obesity or lifestyle to ultimately CBD? I think that it's difficult to really determine from one single study what that directionality is. Looking to the other literature we do see that there is the Mandelian Randomization. I think there have been more than one now, but one did indicate that genetic predictors of circulating branch chain amino acid levels were associated with type two diabetes risk, which supports there being a causal relationship between branch chain and diabetes.                                                 I haven't seen that also done for CBD, but that could be a next step. I think another next step for branch chain amino acids and metabolomics in general is to establish whether or not these are modifiable. If they're just along for the ride, or they're even just a strong biomarker, what does that mean clinically? I think it's still a very open question for many of these metabolomic studies, and even when we have these metabolites that really rise to the top as strong biomarkers, what do they mean?                                                 It could even be that we know they're causal, but that they're not entirely modifiable. Maybe they are just very strongly genetically determined. I think the next step might be to then identify what modifies levels of branch chain amino acids, whether it's lifestyle, or pharmacologic therapies, I think is still unknown, but if we can identify what can modify branch chain amino acids and then answer that next step of, "Well, does the modifying branch chain amino acids then confer a lower risk in disease," that would be an ultimate question to answer.                                                 I think these large scale epidemiological studies are very important as that first step in telling us whether we're even going in the right direction, and then subsequent studies will only strengthen these results, especially when it comes to the causality point. Jane Ferguson:                 Right. Right. I know in your current study, you're limited somewhat by the data, but I wonder. Were you able to look at whether dietary factors, or physical activity and exercise levels were even associated with branch chain amino acids. Obviously protein intake, or carbohydrate, sort of a prudent versus a western diet, were you able to look at that, or is that something that you may be able to look at in the future? Deirdre Tobias:                 Right. In the future we are hoping to disentangle what the determinants are for branch chain amino acids in this cohort, so looking at the role of physical activity, or dietary patterns, or specific foods and nutrients might play. But for this analysis here, we adjusted for all of those factors, and when we do compare, the first model where we only adjust for age, with the second model where we include adjusting for all the more traditional CBD factors as well as the behavioral, lifestyle, dietary patterns or et cetera, we see that there is quite an attenuation.                                                 This does suggest that there is some room for modifiability, because these other potential confounders are impacting the association that we see. If there was no effect in our results when we adjusted for all of these behavioral factors then they might not be that strong determinant of branch chain amino acids, but we do see some attenuation. It is possible that many of these factors, or maybe collectively they impact branch chain amino acid levels. But that's another next step, and I think that's something that we can address very well with the data that we have in our current data set, the women's health study. Jane Ferguson:                 Right. I mean, given the large number of subjects, even with messy dietary or exercise data, I think you'll have a lot of power to at least get you in the right direction to then define interventional trials that could specifically address that issue. Deirdre Tobias:                 Right. Another thing to keep in mind about branch chain amino acids is that they're essential amino acids, meaning that they're derived from diet and not synthesized within our bodies, but surprisingly the correlation between dietary intake and circulating levels is quite low. This, to me, tells the message that metabolism of branch chain amino acids, more so than their dietary intake, is what's driving these elevated levels, and what leads to this impaired ability to break down branch chain amino acids leaving these higher circulating levels, I think that's the risk factor that might predispose to these other cardio metabolic conditions down the road.                                                 Really I think the next steps would be to determine why certain people have more impaired metabolism of branch chain than others. Body mass index is highly correlated with branch chain amino acid levels, that's, you know, an obvious next direction would then be to look at lifestyle factors and anthropometrics to see where those lead us. Jane Ferguson:                 Right. Right, and I wonder, is there some genetic [inaudible 00:16:05] where you could maybe find the people who don't fit the profile, like say somebody who has really dysregulated glucose and insulin homeostasis but actually has very low branch chain amino acids, or the converse, where they have very high branch chain amino acids but actually their insulin levels seem fine, and see. Is there something special about those groups of people, if they even exist? I'm sure there's probably some disconnect sometimes. It's not obviously perfectly predicted. Deirdre Tobias:                 Right. Sometimes looking at those discordant phenotypes can be really informative, and I think that could be interesting to look at as well. I think the genetic predictors, the few snips that have been associated with circulating branch chain amino acid levels from some of the Mandelian Randomization studies indicate that heritability might not be that strong, but certainly there are genetic factors that influence levels. But a lot of it is likely to be more of the modifiable, or environmental risk factors. Jane Ferguson:                 Right. Right. Deirdre Tobias:                 Which I think is an important message for prevention, or motivation towards prevention, because if we can modify this important risk factor, then we can ultimately reduce risk. It's certainly a lead worth investigating. Jane Ferguson:                 Yes, absolutely. Yeah, what's next for you. Are you going to keep working on some branch chain amino acids? Are there other metabolites that you're interested in as well? Deirdre Tobias:                 The overall metabolome is something I'm still very interested in. Branch chain amino acids have risen pretty quickly to be among my favorite metabolites, if I'm allowed to have a favorite metabolite, but I think that although an overall metabolomic pattern identifying what the overall pattern or profile of metabolites looks like for individuals who go on to develop certain diseases, and using those patterns as predictors, or again looking to see what we can modify about them I think is also really interesting. But branch chain amino acids clearly have an important role either as a predictor, a bystander along for the ride, or possibly even causal, yet to be determined.                                                 Yeah, next steps would be to, like I said, identify, what are the determinants of higher levels, and whether or not these can then be modified to reduce risk. Jane Ferguson:                 Important work. Is there anything else you want to add that I haven't asked you about yet? Deirdre Tobias:                 The other findings in the paper were that it seemed fairly consistent across the three branch chain amino acids that we investigated, so isoleucine, leucine, and valine, which share a similar catabolic pathway. Again, maybe the overall breakdown of this metabolite type rather than any one metabolite might be what's relevant to [inaudible 00:19:01]. Jane Ferguson:                 Right. Yeah, so a defect, if there is one, is a stream of all of the branch chain amino acid processing. Deirdre Tobias:                 Mm-hmm (affirmative). Yeah. Jane Ferguson:                 Yeah, really interesting. Well, thank you again for joining this, and for talking about your work. Congratulations again on it. It's a really interesting paper, and your presentation and award at EPI Lifestyle, it's great stuff. Deirdre Tobias:                 Great. Well, thank you very much. I appreciated talking to you. Jane Ferguson:                 Thanks. As many of you may know, Dr. Kiran Musunuru is an associate professor of medicine at The University of Pennsylvania, Perelman School of Medicine. More pertinent for this conversation, he assumed the role of editor in chief of Circulation Genomic and Precision Medicine this year. Welcome Kiran, and congratulations on your appointment as editor in chief. That's a fantastic achievement. Kiran Musunuru:              Thank you. Jane Ferguson:                 With great power comes great responsibility. I know you've been making a lot of changes to the types of content available on the journal website, and finding new ways to ensure the journal is publishing best science and keeping up with changing technologies and capabilities. I'd love to hear about some of the initiatives that you've been putting in place and what your vision is for the journal going forward. Kiran Musunuru:              Sure. I think it's not just about publishing the best science, although I think that's obviously the core mission, but I think also publicizing the good science that we're publishing. With that in mind, the name change of the journal to Circulation Genomic and Precision Medicine really indicates our desire to go beyond what can seem like the very limited scope of cardiovascular genetics, and really take advantage of the rich work, and the energy that's now being infused into whatever you want to call it, Omics, or precision medicine, or so forth. It really is much more than just cardiovascular genetics.                                                 We're casting a wider net. We want to publish a more diverse group of articles. In a sense, we want to be a player in the field. We have a nice opportunity where there is this thing called precision medicine, but everyone is hard pressed to define exactly what that means. I think what that signifies is that it's just so new, and still in the process of early evolution, that the journal I think will have a part to play in helping to define the field over the next few years. I think that's very exciting. It's a very exciting opportunity for any journal, or any journal editor, to be able to contribute in that way.                                                 But as I said, it's not just about publishing the best science. It's also about really trying to make maximum possible impact with that science. With that in mind we're working very hard to introduce elements in the publication process to really expand the reach of the work that is published. The way I like to think of it is, traditional journals a paper is published on the printed page. It gets mailed out to it's subscribers. Some people read it. Some people don't, but within a few weeks after the issue is published basically that's it.                                                 No one really, certainly is not going to casually pick up an issue and look at it, and only a very limited number of people are going to come across the paper on PubMed or whatnot, and actually go track the paper down. I think it should not be the end of it. I think that should just be the beginning. I think the day that it's published online, or in the formal journal, is really just the beginning of the opportunity to make that work known, and really try to make an impact on the field.                                                 Some of the things that we are doing in that spirit include this podcast series, that chain. You've taken the leadership, and have been doing a wonderful job with in terms of promoting some of the science that we're publishing, as well as just general issues in the field that I think that will be of broad interest to the same people who are interested in the content of the journal, and interested in the science that's encompassed by the Genomic and Precision Medicine Council, The American Heart Association.                                                 One element beyond that is what we call our calling, I think of as video summaries. Some journals have been experimenting with this in a sort of exploratory way inviting authors to make their own videos and submit them so that they can be placed on the journal website. Of course that demands a lot of authors 'cause there's a lot of inconsistency in the tone and the quality of those videos because they are coming from very diverse people rather than being centrally produced with the journal.                                                 Some of the very high profile journals have a substantial enough budget that they can actually internally produce, with high production values, very nice videos, but again, they tend to focus on just one or two key articles in each issue. Our ambition is to have a video summary for every original research article that's published in the journal bar none. We think that plays a very useful purpose.                                                 We think that getting someone to actually download a PDF, and read through it carefully, in this day and age is a harder sell than it has been in the past, and if we want to take full advantage of social media, and the fact that everything is out there on the internet, and can be accessed through devices, through smart phones, et cetera ... We felt the best way to introduce a paper and the content of that paper to the casual viewer, or listener, or reader, if you will, maybe not someone who is super specialized in the topic that's covered by a given paper, but still nevertheless has something the learn from the paper, can get something useful out of it.                                                 We feel that generating a video summary that goes through the high points of the paper, that can actually within the video show the key figures of the paper, and then in, not exactly layman's terms, or lay people's terms, but rather, in a non-specialist sense, so still speaking to the science, but without a lot of jargon, without a lot of specialized vocabulary that's really specific to the specialists in the area that's covered by the paper, but really more broadly speaking to scientists, and even more than that, clinical practitioners, really explain in a very straightforward and simple way exactly what the key message of the paper is and why it is important for genomic and precision medicine.                                                 We have started doing this internally. Starting with the January issue we have had a video accompany every single original research article as well as a scientific statement that we published in the January issue. They are linkable, or linked to, from the website, but they are physically, well, not that anything digital is really physical, but let me put it this way, they're hosted by a YouTube channel under the umbrella of the Circulation Journal. They can be found there because they are on a YouTube channel they are essentially a permanent part of YouTube, so anyone searching YouTube can find them.                                                 Then something we've started doing with the transition internal leadership and the new name of the journal is using Twitter to make people aware of these articles that we are publishing, but one very nice thing we can do since we have video summaries available on YouTube is we can actually link within a Tweet directly to that video, and people can actually watch the video directly within Twitter on their devices, on their smartphones, on their computers, wherever they are, however they're accessing it.                                                 We've been finding that people are watching these videos, regardless of what channel they use to get to the videos. They are watching. I think that's a nice thing, because it is expanding the reach of the journal to an audience that might not necessarily or naturally go to the journal website to see what the latest articles that have been published are. It's a different way of reaching the intended audience. Jane Ferguson:                 Yeah, I think it's fantastic. I mean, it's much easier to watch a video for a few minutes when you're, I don't know, waiting for the bus or something, rather than take out your PDF and try to read through these dense method sections. It's really fantastic, I think, even for people who are, if it's our field, or if it's something outside of our field, or people who don't typically read scientific articles but are interested in science [inaudible 00:28:24] and learning more. I think it's really nice to offer that sort of alternative format for people to discover a new science.                                                 I wonder, what do you think is the value of commentating an interactivity in scientific publications? I know in some places they allow commenting, whether anonymous, or named. For a lot of people they get a lot of their science on Twitter, and they have Twitter conversations. Do you think that's an important role that needs to grow more in our dissemination, our discussion of science? Do you think there's an ideal forum for this kind of discussion, or is it still something that's evolving, and we'll find our place, whether it's the comments section of the YouTube videos, or on Twitter, or elsewhere? Kiran Musunuru:              Sure. No, that's a great question. It strikes me that a lot of groups, a lot of organizations, have been hitting upon the same question, and attempting to answer it by generating a forum that's, if not exactly proprietary, is very much under their thumbs, with the intent of fostering conversations about papers published in journals, about content from publishers and so forth. Because everyone is trying to do their own thing it ends up being quite fragmented.                                                 There's not a lot of uptake for any one particular publisher's website, or any one particular mechanism. What has sort of naturally, spontaneously occurred, is a lot of those conversations have just happened on Twitter, which is not intended specifically for scientific discourse, but has cast such a wide net, and has so prevalent a footprint in our society that it serves that purpose just as well as it serves 100 other purposes.                                                 I think it's becoming clear that, increasingly, conversations, discussions, debates, controversies even, are unfolding on Twitter. That's not to say that everyone's on Twitter, or even a large segment of our intended audience is on Twitter, but I think a growing proportion of our audience is on Twitter, and Twitter I think skews younger. But we're a young discipline, and I feel like a lot of the practitioners, a lot of the investigators in our field are of a younger generation who is more ready to embrace Twitter, and is already out on Twitter, on Facebook, on other social media outlets.                                                 I think this is going to be absolutely critical going forward. Twitter, it's not happenstance of course, but it turns out that it lends itself nicely to communication about scientific articles because you can link directly to a paper through Twitter right there in the Tweet, so people don't have to look very far. You can send out your Tweet describing the paper in very brief terms, but then within that Tweet you actually see a box with a description of the paper, with a link to the paper. You can link on it. It takes you directly to the journal's website.                                                 You don't have to actually work to find the paper. The same is true of other elements that we've already discussed. If you want to listen to this month's podcast for Circulation Genomic and Precision Medicine, spearheaded by Jane Ferguson, then the Tweet that goes out, and then is retweeted among our network, allows you to click right there and go to the podcast. Again, you don't have to track it down. You don't have to find it. It's just kind of put there, out there, and people will immediately be notified about it because it will be on their feeds, and then they'll see it.                                                 Then, as you say, when you're waiting for the elevator, or you have a little bit of down time, you can go ahead and just click on it and immediately start consuming it, if you will. The same, of course, is true of our videos. Our videos are five to ten minutes, ten minutes maximum. They're intended to be bite sized pieces that you can kind of catch on the run as you described. It's not a matter of you having to download a PDF and read through very dense language and through method sections and try to figure out what's going on.                                                 Then people can access these on Twitter, through other channels. Then a lot of the conversation can happen on Twitter, and on the other channels. I think we're seeing more and more of this happening, among at least that portion of the scientific community that is Twitter savvy. Jane Ferguson:                 Yes. And I will use this opportunity to plug everybody to follow us on Twitter. You can follow us at @circ_gen, and you can tweet at us and tell us what you think of the journal, of the council, of the podcast, of science in general. We would love to hear your thoughts on that. As we're talking about this, how we're able to access so much information so quickly at our fingertips, the publication process has in some ways still lagged behind, where you submit your manuscript, and it goes out for review, and sometimes you don't hear back for a very long time. I'm wondering how you at the journal are dealing with that aspect of the publication process, and the turnaround time? Kiran Musunuru:              Sure. I mean, I think it's becoming increasingly less acceptable for what has happened in the past, and it has been highly prevalent in the past to continue to occur. What I mean by that is, a very long, drawn out, peer reviewed process and time to publication of the final project. I mean, it's so unacceptable these days when there's so many avenues through which you can communicate your science.                                                 We're seeing things like pre-print servers that are really getting messages out. Then to have to go through a formal review process, and take many months, even years, to actually get your work actually formally published in a journal with the imprimatur of high quality peer reviewed process is just too long. It's impeding communication among scientists. That's a disservice to the scientific process, especially in a day and age where there is such a rapid evolution of technologies. There's such rapid advances in a field, to think that the journals are having to play catch up with what's actually going on on the ground is really quite frustrating.                                                 It's part and parcel of the publication process as it is, and it's not going to change overnight, but in my own role as editor of a journal I'm doing what I can to remedy it. I've committed, and the journal's editorial staff has committed to really trying to streamline the review process. Now, we're not going to work miracles, but I'm happy to say that, whereas in prior years it would have taken on the order of three, four, five weeks for a paper to be reviewed, we've really worked hard to streamline that to make it much more quick, nimble, and we hope less cumbersome to authors.                                                 For example, I will say in the month of January our average time from submission to first decision was under one week. Part of that is, we've accelerated the review process, engaged high quality reviewers who we know are responsive, and who will turn around papers relatively quickly. We've engineered things so that there's not much delay to any step in the process. Even those papers that are sent out for review we've accelerated the process and decreased the time on that basis alone, but something else we've introduced is a very rapid triage process.                                                 Rather than have a paper sit around, sit around, and then be assigned to somebody to look at, and then have to wait for a weekly conference call among the editors to decide the disposition of that paper, you can see how things can get drawn out. Even before the decision is made to send something for review you might have a paper sitting around for a week or two. That happens, I know from my own personal experience at quite a few journals. We're committed to making the decision, ideally within 24 hours, but certainly within 48 hours.                                                 Our editorial staff is extremely responsive. When a paper is submitted, there's a whole lot of eyeballs among the editorial staff that look at that manuscript from the get go, quite a few opinions, not just one, or two, or three opinions, but more like six or seven opinions within 24 to 48 hours. That's useful in two ways: One, it allows us to make a very informed but rapid decision as to the disposition of a paper.                                                 I think the optimal scenario is where we can forecast whether a paper is not going to fare well in the review process, and is ultimately going to get rejected, without actually having to go through the full length peer review process. If we can predict that outcome occurring, but be able to do that within the first 24 to 48 hours, then we can just make that decision and spare the authors a long delay for what ultimately is likely to be a negative outcome.                                                 Conversely, if we are fairly confident that a paper will ultimately get accepted, we'll need some revisions. Every paper can be improved, and that's what the peer review process at it's best is all about is improving the quality of a paper. But if we can forecast very early, this paper is very likely to be accepted. This is what we should send out for review. Then that allows us to really save everybody time.                                                 It saves author's time, 'cause they're not going through a long, drawn out process before ultimately having a negative outcome, but it also spares reviewers' time. We can focus reviewers' efforts on those papers that are extremely likely to ultimately be accepted, and that's the most constructive use of reviewers' time, I think.                                                 There's a secondary purpose, however, and that is when we do reject a paper without review because we've garnered so many opinions about the paper in a very short time, we're actually in a position where we can offer useful feedback to the authors as to why the paper was felt not to be of high enough priority for the journal. Most journals, and I'm speaking from my own experience as a scientist, as an investigator, as an author, you send the paper, and then it takes them how many days, or weeks to make a decision. Then often they will decide that it's just not for them, and they will reject without review.                                                 That's okay, but it can be very frustrating when the decision is made, and then you get the letter back saying, essentially in effect, "We don't like this paper," without any explanation why. What we have been doing, which I think has been well received by authors, is offering fairly detailed feedback. If you want to think of it as a triage review you can think of it that way, but corporate feedback from not just one or two peer reviewers, but actually six or seven editors who have looked through the paper.                                                 We've actually gotten feedback from a few of the authors, that even though we are not publishing the paper, it's been useful in helping them to revise the paper and then go on to the next journal for submission. Jane Ferguson:                 Yeah. I think that's fantastic on all fronts. I think making the process faster is better for everybody, and also making it constructive, so that yes, you're not just sending out form rejection letters, but you're actually helping scientists and authors to identify what could be improved in their papers and what sort of things they might not have thought about. I think that's really fantastic. Is there anything else new with the journal, or anything else that we can look to in the next few months coming out? Kiran Musunuru:              Well, I think we've hit the high points. I think the idea that we want to be friendly to authors, that we want to streamline the review process, that we want to work hard to publicize their work and maximize it's impact in the community. I think by broadening the scope of the journal we're hoping to get substantially more submissions, and more diverse papers. We're very interested in publishing in the area that broadly falls within genomic and precision medicine. We're working hard to generate high value, non-original research articles.                                                 What I mean by that is scientific statements from The American Heart Association, working closely with the Council on Genomic and Precision Medicine to generate scientific statements that are of value to the community. Of course, we would continue to want to publish state of the art reviews, but also partner with other organizations, and publish white papers. For example, we have a couple of white papers on which we're working with The National Heart, Lung, and Blood Institute. That should be coming out in calendar year 2018. Jane Ferguson:                 Okay. Kiran Musunuru:              Beyond things you would normally associate with publishers, we're also working hard to increase our presence at meetings. Part of that is what you might expect editors of journals to do, which is being there in person, and attending talks, and attending poster sessions, and pressing the flesh, and inviting promising presentations to be submissions to the journal. Of course, that's part and parcel of what any good, proactive journal is going to do.                                                 But I think going beyond that, and doing more, and actually being involved in contributing educational activities at conferences. As you well know, the Council on Genomic and Precision Medicine in partnership with the journal has been organizing boot camps and workshops at various American Heart Association meetings that have been extremely well received. And we've now started to organize similar sorts of boot camps and workshops at non American Heart Association meetings.                                                 We'll be doing quite a lot of that, at least three or four national or international meetings in calendar year 2018. I think this is all part of a big strategy to not just be a place where papers are published, read for a few weeks, and then never really thought much of again, but really to make it more of a living piece of work that can inform the community, that has a reach beyond the printed page, whether it's through videos, or podcasts, or forming the basis for educational activities, workshops, boot camps, maybe eventually journal clubs, things of that sort. That's what we would really like to do with the journal going forward. Jane Ferguson:                 That's fantastic. I think it's really great. You're doing some great new initiatives. Congratulations again on your appointment as editor, and on all of the wonderful work you're doing. Kiran Musunuru:              Thank you, Jane. Jane Ferguson:                 That's all for this month. As a reminder, you can follow us on Twitter @circ_gen, and you can also now connect with us on Facebook. Find us under Circulation: Genomic and Precision Medicine, and hit like or follow to get the latest in your news feed. Thanks for listening.  

Transcript of the February Podcast, “Getting Personal: Omics of the Heart”, Episode 13   Hosted by Jane Ferguson   Assistant Professor at Vanderbilt University Medical Center & Associate Editor of the Circulation: Precision and Genomic Medicine journal of the American Heart Association Jane Ferguson:             Hello. This is episode 13 of Getting Personal: Omics of the Heart. It's February 2018. I'm Jane Ferguson, an assistant professor at Vanderbilt University Medical Center, an associate editor at Circulation: Precision and Genomic Medicine, and an occasional podcast host. This month, I talked to Kiran Musunuru and Svati Shah about how they spearheaded name changes for Circulation Cardiovascular Genetics and for the AHA Council on Functional Genomics and Translational Biology, and Andrew Landstrom talked to Kaytlyn Gerbin and Brock Roberts from the Allen Institute about some extremely cool work they are doing with CRISPR and IPS cells to create fluorescently tagged maps of live cells, which allowed them to image and better understand the structure and function of individual cells.                                     I'm delighted to have two guests on the podcast today, Dr. Svati Shah is the current chair of the AHA Council on Genomic and Precision Medicine formerly called the Council on Functional Genomics and Translational Biology. She is an associate professor of medicine at Duke University Medical Center. Dr. Kiran Musunuru is editor in chief of Circulation Genomic and Precision Medicine formerly named Circulation Cardiovascular Genetics, and he's an associate professor of medicine at the University of Pennsylvania Perleman School of Medicine.                                     Dr. Shah and Dr. Musunuru were kind enough to take time out of their busy schedules to join me for a joint discussion on the recent enhancement of name changes for our council and our journal. With tight schedules and last-minute flight cancellations we didn't have ideal settings for recording, so apologies in advance for a little more background than usual.                                     My instruction highlighted a number of name changes and astute listeners will have noticed that the new names for both the journal and the council are very nicely aligned, so I know this was not a coincidence, and I'd love to hear from both of you, what prompted the decision to change the respective names of the council and the journal, and how did you come together to streamline these name changes? Svati Shah:                   Well, maybe I'll take a first start, you know, we, we're really lucky in our council, we have a very, you know, certainly one of the smaller councils [inaudible 00:02:26] we have a very collegial spirit that wants to get things done. So, these conversations actually started probably three years ago, umm, when Jen Howell was chair of the FGTB council. And we realized that not only was our constituency broadening in expertise and breadth and depth, but also, umm, the desire to kind of move beyond the really wonderful work the council is doing around technology platform, genomics, genetics and you know important advances in many of our council members have made in the translational biology field and really thinking about the fact that we have this amazing expertise that can come together across a wealth of disciplines to really translate what's being done in the omic space, and apply it in this new world of precision medicine.                                     And so, umm, that is what stirred really thinking about a name change so that not only would it reflect this expanding constituency in expertise and hopefully draw even more people, across the, you know, wide expertise. But also to harmonize more with people who are in other councils, including clinical cardiology, and people that, really, in the end we are actually quite allied with scientifically, but perhaps those councils didn't recognize really what our council was about because of our previous name. So in that context, you know, it's been wonderful. Kiran has been a wonderful partner in all of this, he's been a real leader in the council and over the past two years we have had many conversations across council leadership and the entire council, and thinking about what this name change would be. And actually, it was almost a consensus amongst council leadership to choose Genomic and Precision Medicine as the name, really to reflect our core beliefs and our core science in genetics and genomics, but also to reflect the expanding expertise of all the different omics platforms, our expertise in clinical genetics with more genetic counselors joining our council, and our expanding expertise in computational biology. And this really allied nicely also with the American Heart Association building a very important institute, the Precision Medicine Cardiovascular Institute. So, I'll let Kiran go from here but again, Kiran has really been a great partner in this and he can kind of expand on that story and how that led to the journal name change. Kiran Musunuru:         Sure, so, with respect to the journal, I think these changes have been growing for a while. I think a lot of the same considerations came into play, the feeling that the journal with the name Circulation Cardiovascular Genetics was perhaps too narrowly defined given how the field, how the science was evolving. And the other consideration is that the Functional Genomics and Translational Biology Council has had a journal, a companion journal if you will, all of this time with a fairly distinct name, Circulation Cardiovascular Genetics, and so it wasn't necessarily obvious to those who are not on the inside so to speak that there was supposed to be a very tight connection between council and journal, that the journal really was the journal of the council and so in the process about deliberating about a council name change, it became natural to think that, "Wow, wouldn't it be nice if the journal could execute a similar name change", and separately, even though this predates my tenure as editor of the journal there had been conversations going on separately or independently that perhaps the journal would benefit from signaling that it was not just about cardiovascular genetics in the very narrow sense, but was really about a much larger area of science. And so there had already been contemplation for quite a while about a name change and so when I assumed the editorship I didn't really have to do much to convince anyone that this would be a useful thing.                                     The scientific publishing committee of the American Heart Association and all the various people involved publishing the journal were already sort of primed for a name change and then it just ended up being a nice convergence of opportunities, Svati with her work in the council and really showing the leadership to lead the transition from Functional Genomics and Transitional Biology to Genomic and Precision Medicine.                                     That really laid the groundwork, and because it was such a deliberative process, such an inclusive process, involving dozens of people on the leadership committee of the council as well as general membership of the council, it was really a no-brainer. The hard part had already been done, the thinking had already been done and I was straightforward to say that we should change the name of the journal to match, Circulation Genomic and Precision Medicine. Jane Ferguson:             Have there been any logistical difficulties in getting this name change through, or has it all happened very organically? Svati Shah:                   The American Heart Association has been a real partner in the name change, sometimes things require many layers of approval and in fact, it has been a relatively seamless process. We came up with a consensus around the name change and later applied formally for that change in the council name, and that was pretty quickly approved by the Scientific Advisory Committee, within a few months really. Our name change became official and we are in the exciting time now of advertising and kind of marketing the name change and appeal to a broader constituency and really reach out to group that perhaps wouldn't have realized that this council is a great home for them again thinking of genetic counselors and computational biologists. So, it really, you know, has been a surprisingly seamless and fun process. Kiran Musunuru:         As I mentioned before it was already kind of in the air that a change was imminent and so when I posed the name change to the Circulation Genomic and Precision Medicine it ended up being a very smooth transition. It was timed so that the volume change, that is changing from the volume associated with the calendar year 2017 to the volume associated with the calendar year 2018, January first ended up being a very logical transition time and so that's when the change occurred.                                     And happily, the council name change ended up occurring almost in lockstep; whereas, you know within a few weeks of the journal announcing its name change the council was able to announce its name change as well. I think that has had a reinforcing effect across the American Heart Association and its membership. It really signals that the council and the journal are tightly tied together, are partners in moving in lockstep. Jane Ferguson:             Svati, this question's probably more for you, so what does the name change mean specifically for existing FGTB council members, and what if anything will change, and then what might it mean for potential new members who are trying to decide what council to join? Svati Shah:                   That's a great question, Jane, you know I am a pragmatic person and I think our council also reflects that pragmatism. We get a lot of things done and we, I think, spiritually all agree that we shouldn't just change the name just for the sake of changing the name. And so we really, actually the name change followed [inaudible 00:10:18] were involved in, these discussions are a year and a half of really thinking about what direction we wanted the council to go and then what the sort of short and long term goals of our council are and then how does the name change effect the long term goals.                                     So, we have a lot of great initiatives in the short and long term, which again will capitalize on our broadening expertise in these different clinical genetics and precision medicine and really, translating genomic and omic findings into, into important patient care. And so, we have several things coming down the pipe that are sort of proof of principle examples of what the name change reflects.                                      So, one example is that we are now working on developing a certificate in medical genomics with the idea that we really need more genetics education. Our council has been very much embedded in genetics and genomics education, Kiran being a key example of that. And now we are expanding that into thinking about how genomics is applied to clinical medicine but making it at the level that is digestible and understandable and is easily applied by a general cardiologist and even primary care doctors will be able to use that resource. And the idea is this will be your self-sustaining certificate that's given through the American Heart Association, so we have a group that's been working on that certificate and hopefully that will be coming out soon.                                     Another key component of what we're doing is trying to reach out more and partnering with other associations including the American College of Medical Genetics and the National Society of Genetic Counselors, again really thinking about how we transition our important scientific discovery work into translation implementation science around patient care.                                     To give you some examples of what that means in terms of what the name change is reflecting, I think with the right use, for the second part of your question, which I think is a really important part of your question is, we want to attract more people in the computational biology field, in the precision medicine space, in the clinical genetic space and again reaching out to genetic counselors through some of these societies, because we, just the wave of precision medicine is here, is going to expand even more and the expertise within our council that was already there but that now we can expand. I think it will be leveraged to really make important contributions to making sure that those efforts in precision medicine are done well, or done responsibly and are done with the patient in mind because in the end the American Heart Association is at the forefront of patient advocacy group.                                     This is a really exciting time, I think that, you know, however you want to define precision medicine the bottom line is precision medicine is here and we can't have, it's not going to be a single faction of individuals or a single expertise that is really, is going to be able to leverage fundamental scientific discoveries whether its genetics, genomics, metabolomics, proteomics, and really translate them responsibly into patient care, so it's going to involve an interdisciplinary and multi-disciplinary effort.                                     I feel really proud that I'm part of the AHA and that we sort of have this perfect storm between Kiran's leadership in the journal, our council changing, you know, its goals and its name aligning with the Institute for Precision Cardiovascular Medicine within the AHA. And I think that, you know, it's not all rainbows and sunshine. We have a lot of work that is cut out for us in the next few years to figure out ways that we can tangibly and concretely, and again responsibly, work together across each of these three components of this perfect storm to make sure that it’s not just a glitzy name change and that there is actually substance and behind all of it, so, you know, it will be, there will be challenges, there will be obstacles, but I think that the amazing people within each of those three components, I feel very confident that we are going to be able to do it well. Jane Ferguson:             Yeah, I agree, as a member of the council, if anybody can do it I think this group of people can do it, so it's very exciting to see, so thank you both for joining, and congratulations again on the new names. It's really exciting to see these, you know, new directions for the council and the journal working together. And I really look forward to seeing all the great initiative that will be coming out in the next few years. Svati Shah:                   Thank you, Jane. Kiran Musunuru:         Thank you, Jane. Andrew Landstrom:     My name is Andrew Landstrom, and I'm an assistant professor in the department of pediatrics section of cardiology at Baylor College of Medicine. I'm a member of the early career committee of the American Heart Association Council on Genomic and Precision Medicine, previously the Council on Functional Genomics and Translational Biology, and I'm joined today by Brock Roberts and Kaytlyn Gerbin, who are scientists on the stem cell and gene editing team at the Allen Institute.  Here to discuss a little bit more about CRISPR editing and what they have done for live cell imaging using fluorescent proteins.                                     So, Brock and Kaytlyn, I'm hoping you can discuss a little bit about what the Allen Institute is and your overall research mission and goals.  Kaytlyn Gerbin:           Yeah, great, so this is Kaytlyn and thanks Andrew for having us on, and we're really excited to share a little bit of the information about what the institute is doing, because we're building a bunch of tools that we think would be really useful for the research community. So, we're excited to get the word out there. And so, the Allen Institute is a non-profit research institute, and we're based in Seattle, Washington, and, essentially what we're trying to do is better understand the cell.                                     We want to understand the various states the cell can take based on structural organization of how different organelles work together. And so, we're doing this, essentially by live cell imaging and also combining that with predictive modeling so that we can build tools to be able to understand structure-function relationships and how cells behave in a healthy state or in a diseased state. So, you can kind of think of this as, we like to say sometimes like a Google Earth for the cell, so if you kind of think about it in that context, a lot of times, you know you could look at the cell at a really high level just like you could look at the Earth at a very high level. Then you could zoom in further and you could look at an individual pathway maybe that you're interested, or perhaps, as an analogy, like a different highway within a part of a city.                                     But you don't really understand how all that works together and how the city functions together until you start to put in things with spatial organization, or maybe temporal dynamics, or how different parts of the structures, or different structures and organelles work together to form the unit that is the cell.                                     And so, essentially, we're trying to generate a bunch of data so that we can build predictive models to help us understand that better. And, we're doing this with human induced pluripotent stem cells, and the first cell state or cell type that we're studying is cardiomyocytes after differentiation.                                     And so, yeah, as we're kind of generating this data we are a non-profit institute, and all of our lines and our plasmids, protocols, data, pretty much everything that we make is becoming publicly available as it passes QC. And so, yeah, we're excited about that, I don't know if, Brock, you have anything else to add. Brock Roberts:             Yeah, just I think an important concept that we're often working with is scale. And, biology exists at certain scales, and that's certainly true for cells and the Google Earth analogy holds.                                     You know, at some level if we want to understand the cell at the scale of its entirety, but we have to kind of cut that down and understand cells at the level of its parts.  And, they're working together as we know, and can infer, but we try to find a way to look at the part one by one and then put it all together in a model that's predictive. And the predictive part is going to be really important. Much like Google Earth can allow us to, you know, look at a traffic pattern in the city or something like that once the data is filled in. We hope to fill in enough data by looking at the cells constitutive parts to make the predictive model. Andrew Landstrom:     And not only looking at, sort of, constitutive parts, you're doing this in a physiologic live cell, so really it's Google Earth, but it's Google Earth in real time as cars are driving down the freeway and people are walking down the street. Brock Roberts:             Right- Kaytlyn Gerbin:           Yeah, exactly. Brock Roberts:             Yeah, that, that's where the dynamics of the cell can really come to life if you've prioritized looking at live cells, which are obviously incredibly dynamic. Andrew Landstrom:     And so, you know to be able to accomplish this, you all have come up with some pretty novel methods. Would you talk a little bit more about your CISPR editing approach, and how you've applied this to different lines and to get, sort of, different markers into cells? Brock Roberts:             Right, sure, the, we should say that we owe a lot to the development of CRISPR-Cas9 editing, which preceded us by a few years, but we've tried to kind of scale it up in some important ways.  And, really the important thing to appreciate about this process is it's a way to make a very precise, precisely guided DNA break in the genome of a cell. And we do this in human induced pluripotent stem cells, and so we can quite precisely choose a position or location in the human genome and trigger DNA damage, trigger breaks in the DNA molecules that make up the chromosomes.                                      And we can do this with, kind of a highly specifically guided RNA molecule that we complex with this Cas9 nucleus molecule, and these are, very famous molecules now, over the last few years they've become very well known.                                     And the upshot of this is we can, sort of trick the cell into repairing that DNA break using the processes that are always at play in living cells to resolve breaks in DNA, but we can sort of trick that process to add something additional at a specific site. And the additional sequence that we use is a tag sequence that corresponds to a fluorescent protein after the DNA is expressed and translated. And so, what we can effectively do is tag proteins that are produced in a highly endogenous, natural fashion within cells.                                     And the proteins that we can tag in this way, using this method, correspond to some of the most canonically recognized structures and organelles within the cell. And so, at this level we try to choose proteins, tag them in this manner, and take advantage of the fact that they will localize predictably to some of the dozens or hundreds of structures that make up cells. Kaytlyn Gerbin:           Yeah, and a key thing I think to add that Brock kind of mentioned was that this isn't any over expression, we're doing all this endogenously. So it’s really like, pretty, I think that's a big advancement over what has typically been done in the past with a lot of fluorescent tagging of proteins within the cell. Brock Roberts:             Right, but what's important to appreciate is that we're using the cells endogenous copies of each protein, expressed from the genome. We've done it in about 30 different genes so far. And we have a high success rate in accomplishing this process, all the way through to completion, which is to say that we know that we can introduce a tag onto at least one copy of each gene that is, that encodes a protein that can be tagged this way, and then we can monitor the cells over several months and ensure that this doesn't have a negative consequence on their growth or on their ability to differentiate or something like that. Our quality control process. We have a high success rate so far. Andrew Landstrom:     And that's really, in my eyes, one of the key, key sort of, innovative factors of your work, in that these are endogenous proteins that are able to be expressed and then to be imaged in real time without really disrupting the underlying cellular physiology. Kaytlyn Gerbin:           Yeah, and we do care a lot about what you just said, that it doesn't have any negative effect on cell behavior because we are using these as a surrogate for understanding cell behavior in, hopefully, a normal context. And we do an extensive amount of quality control work and all of that QC data is available on our website, and then you can actually access all of our cells through Coriell and all of the QC data for all those cell lines is made available, and we've also done a pretty extensive job outlining the QC that goes into this process so that, hopefully, people will take a look at that when they look at our cells and understand what we've done, but we also hope that this will kind of help set a standard for things that other people should be looking at when they're doing editing on their own. Brock Roberts:             And we really hope that people take these cells and do experiments that we don't have the bandwidth to do, and test them in ever expanding ways and let us know and report on it. Let us know how the cells perform and their unique assets. Andrew Landstrom:     Yeah, and I think all that sort of transparency with the quality control really makes it user accessible and just sort of invites that degree of collaboration, that's great. Kaytlyn Gerbin:           Yeah. Brock Roberts:             Yeah, we hope so. Yeah, we think so, too. Andrew Landstrom:     So how many cell lines do you have available? Kaytlyn Gerbin:           Yeah, so, currently, and again you can access all these lines on the website, but we have 16 lines that are released that have gone through the full QC process. Those are available now, and we have another six that are listed as in progress, which means that they will be released very soon.                                     Just to give you a few examples, so again, we're tagging proteins to label organelles in the cells. So, a lot of times, you know there's a lot of different kinds of proteins you could use to tag an organelle, so we've chosen a subset of those. So, we've tagged, for example, Tom20 to label mitochondria, Lamin-B1 for the nuclear envelope, alpha tubulin to look at micro tubules, and we also have started doing a lot more endosomal trafficking pathways, so like the endosome, lysosome, peroxisome, for example, and then a few other epithelial markers such as tight junctions, desmosomes, and actin.                                      And so, there's a kind of a bunch of structures. Those are just some examples of what we've been starting with tagging, but one of the reasons why we chose to use induced pluripotent stem cells for this whole model is because they do have the ability to differentiate into many cell types. And, I mentioned earlier that we chose to start with cardiomyocytes as a key cell type to look at, and so all of our cell line, as part of the QC process go through a cardiomyocyte differentiation protocol. And that kind of helps us ensure that the cells are pluripotent and that they can become a defined cell type and that the structure that we've labeled still is present in that differentiated cell. But it also means that we can start looking at some really interesting things in terms of how these structures change during differentiation and change from the stem cell state to the cardiomyocyte state. And so, one thing that we really started doing towards the end of last year, and we have lines coming out, hopefully soon on some cardiac specific tags. And so, to give you a few examples of things that we're working on, we have cardiac troponin I 1, and this I think will be available, I think it's passed QC and will be available pretty soon. And then we also have, we're working on sarcomeric alpha-actinin, titin, some gap junctions so that connexin 43, and then also starting to do a few signaling pathways and one that is of particular interest for the cardiomyocyte field would be beta-catenin for Wnt signaling.                                     So, we are kind of expanding on that list as well. So, we're really excited to start looking at these cardiac structures in the cells. Brock Roberts:             One way to summarize kind of, our strategy and one thing unites all of the different gene and protein targets that we have produced and focused on so far is to really think about the product gene or the protein as a reporter for an organelle or a structure in the cell. So, there are of course an extraordinary number of genes and proteins using this method, and there are many different justifications that would fly for why you would target a particular molecule, a particular gene, a protein of interest, but, what we really try to focus on are proteins that serve as a reporter for a structure.  Andrew Landstrom:     So, have you tagged any ion channels? Brock Roberts:             We have several targeting experiments that are, that take advantage of tagging the transporter molecule. One that is available is a transporter in the mitochondria, a transporter to the outer membrane, Tom20. And we're also making connexin 43 available for gap junctions. These proteins that function as trans-membrane transporter molecules accommodate the approach quite well.                                     Another that is a bit further behind, but we hope to make available before too long would be marker of the sarcoplasmic reticulum and cardiomyocytes. This is a serca protein. Andrew Landstrom:     So, with all these cell lines at your disposal, you've spoken to, sort of, the dynamic changes that occur both in differentiation of cardiac myocytes and cellular development and cell physiology, what are some other thoughts that you have that these lines might be able to show us? What are some fields that might be immediately informed by these models? Kaytlyn Gerbin:           I mean, I guess just kind of on a big pictures I think that having the ability to study live cells and look at different structures in the cell will help us better understand structure-function relationships. So I think that in cardiomyocytes that, you know, makes a lot of sense, but I think even just in the stem cell field, being able to understand how localization of a particular organelle corresponds to a different state that the cell might take.                                     And so we kind of are thinking about a lot of these different stages and states that the cell can pass through and how do we characterize that based on just kind of at a healthy or just kind of quiescent state, and then comparing that to different protivations, so looking at disease or maybe change in time, change in mutations, drug response, response to stress and how are the structures changing and how does that kind of dynamic integration effect how the cell behaves as a whole?                                     And I think that that's one thing that we're really trying to do at the institute that is out of the scope that a lot of federally funded academic labs can do. A lot of times people are focusing on specific pathways or a specific molecule or a specific protein and don't necessarily have the bandwidth to look at the cell on a systems level. And so, kind of as Brock mentioned, with doing these different proteins as tagging the organelles we're hoping that being able to integrate that and generate enough data where that starts to become predictive I think can be really, really powerful. So... Brock Roberts:             Yeah, and there's another thing to add that's is kind of a larger thought that we are very preoccupied with and interested in, which is to take kind of a post genomic view of biology and cell biology in particular. Genomics has been so explosively successful in allowing us to document and document the state of cells at the level of which genes, which of the many, many, hundreds and thousands of genes are active in a particular cellular state, in a particular cell type or particular state that that cell's in.                                     We can easily get lists of genes that we know are functioning and turned on. What we want to do is take that to the next level and start defining a cellular state as a combination, a particular combination of dynamic behavior of those molecules which we can actually see. So we want to be able to see the parts work together. Not just have a list of the parts, and define states in that way. Kaytlyn Gerbin:           Yeah, and I think you kind of asked about what kinds of communities might find these tools useful and I think lot of the disease, we're thinking about how this might apply to disease modeling or drug screens or even developmental biology and kind of studying things like that, so I think a lot of our, we have some collaborations, and we've also been really trying to expand what kinds of groups and communities are using the cell lines.                                     There's been a lot of, kind of positive feedback on people taking, you know, a highly defined cell type that has a lot of QC done, and then having the right tools to be able to start to look at things like that. So, I think we kind of mentioned some of the tools we have, but I just to kind of restate that, all of the cell lines that we listed, along with many more, are available at Coriell.                                      And then, in addition to that you can get the plasmids that we've used, which have gone through also an extensive QC, so if people are working on patient derived, on their own patient derived IPS lines, you know, you could get the plasmids for whatever reporter and then put those in to your own cells. And we do have protocols available that describe our whole process in a lot of detail for how to do that and kind of different QC steps along the way. Brock Roberts:             Yeah, we describe each targeting experiment in enough detail for it to be, we hope, recapitulated in any human cell line or cell type without too much strain on behalf of the person that's doing that work. So we hope to kind of inspire people to try this, even if they might not be familiar with it. Kaytlyn Gerbin:           Yeah, and another thing is that our data is also available, so all of our imaging data that we're doing, and then, you can actually find that we have a website called the Allen Cell Explorer. And from there you can go through and look at all of the imaging, no, pretty much all of the images that have gone through our pipeline are now on the website. So you can go through and actually look at individual cells that were imaged during what, you know, as live cells, and then look at different structural tags that are in there.                                     Another thing that you can see on that is the predictive modeling, and so what we're able to start doing is predict the structure of, let's say, mitochondria based on the nuclear shape and another organelle that's in there. So, we're able to start doing a lot of that. So that, I think, will be really useful to people.                                     We going to add about the label free...? Brock Roberts:             Yeah, and some of the more interesting results that have emerged recently are, are the ability to infer through machine learning approaches and neural network approaches the status and state and sub-cellular localization of certain organelles in the cell and structures in the cell that are actually unlabeled. Those can be inferred from the sort of sophisticated analysis of bright field, you know, images that are not displaying any particularly obvious properties, any tags or anything like that.                                     But because the work has been done in the background to train these models and deep learning approaches with individual cell lines that do have these very specific reporters of distinct structures and organelles, because that data set exists, our modeling team and imaging team is able to appear actually quite deeply into the state of cells that are actually not labeled. Andrew Landstrom:     Wow. Brock Roberts:             So, it's pretty, pretty interesting. Kaytlyn Gerbin:           Yeah. Yeah, we don't have that up on our website yet, but that's in the works to get that actual predictive model. So essentially what that would mean then is that you could take a bright field image in your own lab and then put it into this model, and then get information about maybe where the nucleus is or where the mitochondria are or where the actin is predicted to be.                                     And all that is actually trained off of thousands and thousands of images that have come through the imaging and then the modeling pipeline. So, I think that that tool itself, once that is out and fully QCed I think could be, have a big impact right away. At least we're hoping that it will. Brock Roberts:             Hoping. And those computational algorithms are among the publicly available tools that we have that can be found through our website, and our publications that are coming out. Andrew Landstrom:     That's absolutely fascinating. Are you able to provide a specific example of how you've used, sort of, artificial intelligent, deep learning predictive modeling to infer a physiologic sale or response that was not directly observed? Brock Roberts:             Well, I think the response is, we're really hoping to go in that direction. To use this to, I guess, if you will, take shortcuts toward a response in the form of a state change after we alter the environment in some way, or perhaps alter the genome to mimic a disease, mutation, or something like that. Right now, we are building the relationships. So, we can, we know, and I guess one example we can give is progress through the cell cycle. Kaytlyn Gerbin:           Yep. Brock Roberts:             That would be one kind of clear example that we, we haven't done a lot yet to manipulate the cellular environment or trigger cells to go through different states, but obviously cells that are in culture and proliferating alter their state by progressing through cell cycle. So that's one example that we can detect. We can clearly look at how the morphology of cells and different cell cycle states that emerge that are their chromosomes are compacted or dispersed as they undergo synthesis or undergo division, progress through metaphase and so forth.                                     We can look at those cues and connect the state of the cell with respect to the cell cycle, to the state of some of the organelles, with the state of the mitochondria, for example. And we're hoping that same approach will hold up when we trigger, in some cases, more subtle changes to the physiology of cells. Andrew Landstrom:     That's particularly fascinating. I think the, you know, the ability to leverage that in the setting of, like you were mentioning, patient derived IPSCs from heritable diseases. You know, these sort of monogenic disease models that impart a biophysical defect in the cell could then be modeled and not only directly observed, but perhaps indirect cellular physiology might be inferred in a way that we really haven't been able to do so previously. Brock Roberts:             Absolutely. Yeah, there would be, in some cases there are monogenic disease mutations and pathologies that we know ought to have an effect, and we're really excited to see if that holds up, and how that holds up and what their phenotype is when looked at in this sophisticated way. And then there are other, more mysterious mutations that would be really excited to see a phenotype in. Kaytlyn Gerbin:           Our goal at the institute is to build the tools and provide the resources to the community to be asking these kinds of really detailed, very interesting questions. I mean, I think there's definitely interest in doing some of that work here, but our main focus is to design the tools and the methods and make that all available to the public as soon as it passes our QC. So, that's the, those are the kind of thing that I think the community will have a big impact on, testing these kinds of things in their own systems given you know, new tools and ways to do it, so. Andrew Landstrom:     Right. Brock Roberts:             Our whole, our whole ethos is to cooperate and to facilitate. And rather than compete with other investigators, we want to make things possible and that are shared and open. For example, our list of genes that we went with to target, that was on open collaboration. We asked as many specialists in the academic community as we could to develop a consensus of what would be the most useful markers for different organelles. And we chose those proteins and genes. So, we're really trying to be collaborators, as best as we can. Andrew Landstrom:     Are there specific examples of collaborations that you've felt were particularly productive or yielded some new exciting insight? Kaytlyn Gerbin:           Mm-hmm (affirmative), yeah. I could give you a few examples. So, Doctor Ben Freedman, who is at the University of Washington, he is working on kidney research. And so, he has a few of our cell lines, he actually, it's convenient because we are located right across the street from each other, so we'll see them fairly often, but, yeah. So, he works on kidney research with the different cell lines and he really wanted to get the cells into a 3D context. So, he is working on a lot of different tissue engineering to study developmented disease.                                     And so, he's also starting to make his own, their own mutations in the cell line, and so that's been, at least so far, that's been one collaboration that's I think has really been very powerful. And it's cool because we don't have the bandwidth right now to be looking at kidney organoids, but I think it's showed, kind of, the power of these kinds of cells and tools that, you know, when you have that you can do the live cell imaging with different structure within the same kind of organoid and you can get a lot of information, and so ... Andrew Landstrom:     Yeah. Kaytlyn Gerbin:           That, that's been fun to see develop. Another one that I know, Chris Chen at at Boston University is using our lines and is making cardiomyocytes with them as well and looking at the effects of patterning. And patterning is something that we also planning to do here, but that collaboration has been great to kind of get things going.                                     And we've also been working closely with a group at the University of Washington, Georg Seelig's lab, who's developed a new way of doing single cell RNA sequencing. And so, that's been fun, we've been looking at that with stem cells and then cardiomyocytes to, kind of help, help us figure out what the different states that the cells are in. And then that is going to help and form, kind of, what future tags we might do or when, when to do imaging or kind of what protivations we want to put the cells through. Andrew Landstrom:     That sounds like you're spanning the gamut really of downstream experimentation on these lines. Brock Roberts:             Yeah, and we've also had a lot of people buy the cell lines. Kaytlyn Gerbin:           Yeah. Brock Roberts:             Acquire them through the Coriell, we hope that each case of their productive application toward different research questions could be defined as a mini collaboration. Maybe we'll hear from some of these people. And in some cases we have, and there may be more things that spring out of that. Kaytlyn Gerbin:           Yeah, I think like, because the lines are available through Coriell it's, it's a little early to start seeing publications from the stuff, because we're a pretty new institute, but we do keep track of where the lines are going and, I mean it's exciting to see, I mean, pretty much all throughout the world there's people ordering the lines and starting to do research in a lot of different kinds of systems. Brock Roberts:             Right. Kaytlyn Gerbin:           So, we don't always necessarily directly collaborate with the people that are using the lines, but a lot of times we do hear from them or we'll run into people at conferences or something who have been using our lines. So that's really fun to see that its, our, you know, the work that we're doing here is actually producing things that people in the community are finding informative and useful. So, that's always fun. Brock Roberts:             It's still so early in this project. I mean we're just at the beginning of a lot of collaborative potential. So, we really hope to see this take off. Andrew Landstrom:     Yeah, and if people listening want to collaborate or want to learn more, how can they learn more and how can they get ahold of you all? Brock Roberts:             Oh, hold on, I think, first of all, we really want to funnel people to our website. We think it's a really great resource and at that allencell.org you can contact us through that link. We look forward to hearing from you. Kaytlyn Gerbin:           Yeah, so you can start with the website there. And as we mentioned before you can find all of our cell lines, plasmoids, protocols, etc. on this site. And we've also started to do a few more instructional videos, and so those are coming up on the website, too. So, some things, you know, especially as more groups are starting to use the lines, we do have the detailed protocols, but I think groups that maybe haven't done stem cell culture before or haven't worked with these kinds of IPS lines before, we're trying to provide as much content for people to make it easy for them to do the research. So we're starting to do more, sort of instructional videos. Brock Roberts:             Yeah, and we seek this out. We want to hear from people. It's not a bother. We're trying to get as much, we're trying to get the, we're trying to branch out and communicate as extensively as we can. Kaytlyn Gerbin:           Actually, one thing I just thought of that I want to add in her is that we have started to work with a few stem cell cores. And so, right now, I mean- Brock Roberts:             These are core facilities at universities. Kaytlyn Gerbin:           Yeah, stem cell core facilities at, yeah, exactly. So, part of trying to distribute the lines is that if we can, you know, individual investigators could get our lines from Coriell and get the licensing and everything to do that in their own lab, but it's, I think, going to be really great if we get some connections with the stem cell cores because then once we can provide the lines to them, they can distribute them to investigators that are part of the core.                                     And so, so far, we already have agreements in the works with University of Washington, UC Berkeley, and then the Salk Institute, but this is something that we're really hoping to expand this year. So I think, in particular, you know definitely contact us if there's questions about the lines or anything, but if you are part of a stem cell core at a university and you think that people at the university would be interested in using our lines we're working really hard to make, you know get, kind of, packages, protocol packages and everything available so that we can get these lines set up in the stem cell cores. Brock Roberts:             Right. Andrew Landstrom:     Well Brock and Kaytlyn, thank you so much for joining me. What an incredible resource that you all have created, and I especially appreciate how open and transparent you are with your lines and your quality control and how you just really, you know, try and strengthen collaborations and to start new ones. Brock Roberts:             Thank you very much for the conversation. Kaytlyn Gerbin:           Yeah, this has been fun, thank you. Jane Ferguson:             I hope you enjoyed listening to this episode of Getting Personal: Omics of the Heart. Let us know how we're doing by leaving a comment or tweeting at us at @circ_gen. We love to hear from you.   

Dr Wong:             Welcome to the monthly podcast, "On The Beat, for Circulation: Arrhythmia, and Electrophysiology." I'm doctor Paul Wong, editor in chief, with some of the key highlights from this month's issue. We'll also here from Dr. Suraj Kapa reporting on new research from the latest journal articles in the field.                                 In our first article, Mathew Daly and associates examine whether a high-resolution, 9 French, infrared thermography catheter can continuously image esophageal temperatures during atrial fibrillation catheter ablation. The infrared temperature catheter was inserted nasally or orally into the esophagus, adjacent to the left atrium. Endoscopy was performed within 24 hours to document esophageal injury. Thermal imaging showed that 10 out of 16 patients experienced one or more events where the peak esophageal temperature was greater than 40 degrees centigrade. Three patients experienced temperatures greater than 50 degrees centigrade and one experienced greater than 60 degrees centigrade. Analysis of temperature data from each subject's maximal thermal event revealed high radius, 2.3 degrees centigrade per millimeter and rates of change 1.5 degrees centigrade per second, with an average length of esophageal involvement of 11.0 millimeters.                                 Endoscopy identified three distinct thermal lesions, all in patients with temperatures greater than 50 degrees centigrade, all resolving within two weeks. The authors concluded that infrared thermography, high-resolution mapping of esophageal temperatures during catheter ablation may be performed. Esophageal thermal injury occurs with temperatures greater than 50 degrees centigrade, and was associated with large spacial-temporal gradients.                                 In our next article, Nitesh Sood and associates reported on the real-world incidence and predictors of perioperative complications in transvenous lead extractions involving ICD leads in the NCDR ICD registry. Lead extraction was defined as removal of leads implanted for greater than one year. Predictors of major perioperative complication for all extraction procedures, 11,304, and for high voltage leads, 8,362, or 74% across 762 centers were analyzed, using univariate and multivariate logistic regression. Major complications occurred in 258, or 2.3% of the extraction procedures. Of these, 258 procedures with a complication, 41 or 16% required urgent cardiac surgery. Of these, 14 or 34% died during surgery. Among the total 98, or 0.9% deaths reported, 18 or 0.16% of the total occurred during extraction.                                 In multivariate, logistic regression analysis of all extractions, female sex, admission other than electively for the procedure, three or more leads extracted, longer implant duration, dislodgement of other leads, patients' clinical status, requiring lead extraction, such as infection or perforation, were associated with increased risk of complications. For high voltage leads, smaller lead diameter, a flat versus round coil shape, in greater proximal surface coil area, were multivariate predictors of major perioperative complications.                                 The rate of major complications and mortality with transvenous lead extraction is similar in the real world compared to single center studies from high volume centers. There remains a significant risk of urgent cardiac surgery with a very high mortality, and planning for appropriate cardiothoracic surgical backup is imperative.                                 In our next paper, Bence Hegyi and associates, have reported on the repolarization reserve in failing rabbit ventricular myocytes, and the role of calcium and beta-adrenergic effects on delayed and inward rectifier potassium currents. The authors measured the major potassium currents, IKr, IKs, IK1, and their calcium and beta-adrenergic dependence in rabbit ventricular myocytes, in chronic pressure, in volume overload, induced heart failure, and compared them to age-matched controls.                                 The authors made a number of observations. One, action potential duration was significantly prolonged only at lower pacing rates, 0.2 to 1 Hertz, in heart failure under physiological ionic conditions and temperature. Two, beat to beat variability of action potential duration was also significantly increased in heart failure. Three, both IKr and IKs were significantly regulated in heart failure under action potential clamp but only when cytosolic calcium was not buffered. Four, CaMKII inhibition abolished IKs upregulation in heart failure, but did not affect IKr. Five, IKs response to beta-adrenergic stimulation was also significantly diminished in heart failure, and, six, IK1 was also decreased in heart failure regardless of calcium buffering, CaMKII inhibition or beta-adrenergic stimulation.                                 These observations changed when cytosolic calcium was buffered. The action potential prolongation in heart failure was also significant in higher pacing rates. The authors concluded that in heart failure, calcium dependent up regulation of IKr and IKs counter-balances the reduced IK1, maintaining the repolarization reserve, especially at higher heart rates. In physiologic conditions, unlike conditions of strong cytosolic calcium buffering. Under beta-adrenergic stimulation, reduced IKs responsiveness, severely limits the integrated repolarizing potassium current in repolarization reserve in heart failure, increasing the arrhythmia propensity.                                 In the next paper, Christopher Piorkowski and associates report on the feasibility of a combined endo-epicardial catheter approach for mapping the ablation of atrial fibrillation. The authors studied 59 patients with permanents pulmonary veins isolation and had further symptomatic recurrences of paroxysmal atrial fibrillation, persistent atrial fibrillation, or atrial tachycardia. These patients underwent repeat ablation using bi-atrial endo- and epicardial mapping and ablation. Identification of arrhythmia substrates and selection of ablation strategy were based on sinus rhythm voltage mapping. In all patients, endo-epicardial mapping ablation were feasible using standard technologies of catheter access, three dimensional mapping, and radiofrequency ablation.                                 Epicardial mapping and ablation did not add procedural risk. Exclusively, epicardial low voltage substrate were found in 14% of patients. For the first time, novel epicardial conduction abnormalities located in the epicardial fiber network were described in human patients, 19% of the cohort. Epicardial ablation was needed in 80% of the patients. Over 23 months of follow up, freedom from arrhythmia recurrence was 73%. The authors used continuous monitoring and three months blanking period. Freedom from ATR of greater than two minutes was defined as the primary end-point.                                 The authors concluded that endo-epicardial mapping ablation was feasible and safe. Epicardial ablation increases transient mortality of ablation lesions. Further studies will be needed to demonstrate reproducibility and long-term outcomes, and how the technique compares to other methods.                                 In the next article, Michael Wolf and associates examined the long-term results of substrate modification for ablation of ventricular tachycardia using substrate elimination, targeting local, abnormal ventricular activities, or LAVA, post-myocardial infarction. They reported on 159 consecutive patients undergoing first ablation, age 65, 92% with ICDs, 54% with storms, and 73% with appropriate shocks. LAVA were identified in 92% and VT was inducible in 73%. Complete LAVA elimination after ablation was achieved in 64% and non-inducibility was achieved in 85%. During a median follow-up of 47 months, single procedure, ventricular free survival was 55%, 10% storms, and 19% shocks. The ventricular arrhythmia free survival was 73% after one year and 49% after five years.                                 Complete LAVA elimination was associated with improved outcomes, ventricular arrhythmia free survival of 82% at one year and 61% at five years. The subgroup treated with multi-electrode mapping and real-time image integration had improved ventricular arrhythmia free survival, 86% at one year and 65% at four years. Repeat procedures were also performed in 18% of patients. The outcomes improved, 69% ventricular arrhythmia free survival during a median follow-up of 46 months.                                 In a single center study, substrate modification, targeting LAVA for post myocardial infarction ventricular tachycardia resulted in a substantial reduction in ventricular tachycardia storm and ICDs shocks with up to 49% of patients free of arrhythmias at five years after a single procedure. Complete LAVA elimination, multi-electrode mapping, and real-time integration were associated with improved ventricular arrhythmia free survival.                                 In the next paper, Jean-Baptiste Gourraud and associates examined the safety and feasibility of transvenous lead extraction in adults with congenital heart disease over a 20 year period at a single center. The authors reported on 71 transvenous lead extraction procedures in 49 patients with adult congenital heart disease, mean age 38 years in which a total of 121 leads were extracted. The primary indication for extraction were infection in 48%, lead failure in 31%. A laser sheath was required in 46% and a femoral approach in 8%. Complete transvenous lead extraction was achieved in 92% of the leads. 49% of the patients had transposition of the great arteries. In multivariate analysis, lead duration was predictive of transvenous lead extraction failure. No perioperative death or pericardial effusion was observed. Subpulmonary, atrioventricular valve regurgitation increased in eight patients, five of whom had TGA and were independently associated with ICD leak or valvular vegetation.                                 After a median of 54 months of follow up after the first lead extraction, three deaths occurred independently from lead management. The authors concluded that despite complex anatomical issues, transvenous lead extraction can be achieved successfully in most adult congenital heart disease patients using advanced extraction techniques. Subpulmonary AV valve regurgitation is a prevalent complication, particularly in patients with transposition of the great arteries.                                 In the next paper, Gabriela Orgeron and associates examined the incidence of ventricular arrhythmias and follow-up in ARVC patients grouped by the level of indication for ICD placement, based on the 2015 International Task Force Consensus Statement Risk Stratification Algorithms for ICD Placement in arrhythmogenic right ventricular dysplasia/cardiomyopathy. In 365 of arrhythmogenic right ventricular dysplasia/cardiomyopathy patients, the authors found that the algorithm accurately differentiates survival from any sustained VT/VF among the four risk groups, p < 0.001. Patients with a Class I indication had significantly worst survival from VT/VF than patients with a Class IIa indication or a Class IIb. However, the algorithm did not differentiate survival free from VF or V flutter between patients with Class I and Class II indications. Adding Colter results, less than 100 PVCs per 24 hours to the classification, helps differentiate the risk.                                 Patients with a high PVCs burden, greater than 1000 PCVs per 24 hours had a poor survival from both VT/VF and VF and V flutter.                                 In the next paper, Takeshi Kitamura and associates studied eight patients that had bi-atrial tachycardia, a rare form of atrial macroreentrant tachycardia, in which both atria form a critical part of the circuit and were mapped using an automatic, high resolution, mapping system. 708 patients had a history of persistent atrial fibrillation, including septal or anterior left atrial ablation before developing bi-atrial tachycardia. One of the patients had a history of atrial septal path closure with a massively enlarged right atrium. The authors found that 9 atrial tachycardias, with a median cycle length of 334 milliseconds had three different types. Three were peri-mitral and peri-tricuspid reentrant circuit, three utilized the right atrial septum in a peri-mitral circuit, and three utilized only the left atrium and the left right atrial septum.                                 Catheter ablation successfully terminated eight of the nine bi-atrial tachycardias. The authors found that all patients who developed bi-atrial tachycardia had an electrical obstacle on the intraseptal left atrium, primarily from prior ablation lesions.                                 In our next paper, Kwang-No Lee and associates randomized 500 patients with paroxysmal atrial fibrillation to one of two strategies after pulmonary vein isolation. One, elimination of non-PV triggers in 250 patients, group A, or, two, step-wise substrate modification using complex fractionated atrial electrogram or linear ablation until non-inducibility of atrial tachyarrhythmias was achieved, 250 patients in group B. Recurrence of atrial tachyarrhythmias was higher in group B compared to group A. 32% of patients in group A experienced at least one episode of recurrent atrial tachyarrhythmia after the single procedure, compared to 43.8% in group B. P-value of 0.012 after a median follow-up of 26 months. Competing risk analysis showed that the cumulative incidence of atrial tachycardia was significantly higher in group B compared to group A (p= 0.007).                                 The authors concluded that elimination triggers as the end-point of ablation in paroxysmal atrial fibrillation patients decreased long-term recurrence of atrial tachyarrhythmias compare to non-inducibility approach achieved by additional empiric ablation.                                 In our final paper of the month, Roland Tilz and associates reported on 10 year outcome after circumferential pulmonary vein isolation using a double lasso and three dimensional electro anatomic mapping technique. From 2003 to 2004, 161 patients with symptomatic drug refractory paroxysmal atrial fibrillation underwent electro-anatomical mapping guided circumferential pulmonary vein isolation. The procedure end-point was absence of pulmonary vein spikes thirty minutes after isolation, after a single procedure and a median follow up of 129 months, stable sinus rhythm was present in 32.9% of patients based on Holter-ECGs and telephonic interviews. After multiple procedures, mean 1.73 and median follow up of 123.4 months, stable sinus rhythm was seen in 62.7% of patients. Progression towards persistent atrial fibrillation was observed in 6.2%.                                 The authors concluded that although the 10-year single procedure outcome in patients with paroxysmal atrial fibrillation was low, 32.9%, it increased to 62.7% after multiple procedures and the progression rate to persistent atrial fibrillation was remarkably low.                                 That's it for this month but keep listening. Suraj Kapa will be surveying all journals for the latest topics of interest in our field. Remember to download the podcast, "On the beat." Take it away Suraj. Dr Kapa:               Thank you Paul, and welcome back everybody to Circulation’s “On the Beat”, where we'll be discussing hard hitting articles across the electrophysiology literature.                                 Today, we'll be reviewing 22 separate articles of particular interest, published in January 2018. The new year saw plenty of articles that are of particular interest either for the future of our field of for present management of our patients. First, within the realm of atrial fibrillation, we'll review several articles within the realm of anticoagulation and left atrial appendage occlusion.                                 The first article we'll review is by Yong et al in the American Heart Journal, volume 195, entitled "Association of insurance type with receipt of oral anticoagulation in insured patients with atrial fibrillation: A report from the American College of Cardiology NCDR PINNACLE registry." In this publication, the author sought to evaluate the effect of insurance type on the appropriate receipt of anticoagulant therapy, specifically looking at warfarin versus NOACs. They reviewed retrospectively over 360,000 patients and found significant differences in appropriate prescription of anticoagulants, irrespective of which anticoagulant was considered. Medicaid patients received less appropriate anticoagulant prescription than those who were privately insured on Medicare or military insured. Furthermore, those on military or private insurances had a higher rate of NOAC prescription than those with Medicare.                                 Furthermore, there was an even wider disparity in NOAC use than warfarin use amongst differently insured patients. These data are important in that they highlight potential variability in appropriate management of patients based on insurance type. Of course, there are many issues that might impact this, such as health care access or available pharmacy coverage of specific medications. Furthermore, the authors do not dive into the impact on outcomes based on the therapy availability.                                 The next article we'll review is by Jazayeri et al, entitled "Safety profiles of percutaneous left atrial appendage closure and lysis: An analysis of the Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database from 2009 to 2016" published in the Journal of Cardiovascular Electrophysiology in volume 29 issue 1. Here, the authors sought to evaluate the overall safety profiles of procedures performed with different percutaneous left atrial appendage occlusion devices, including LARIAT and WATCHMAN. They review 356 unique reports and compared outcomes pre- and post- approval of the WATCHMAN device. The look at the specific composite outcome of stroke, TIA, pericardiocentesis, cardiac surgery, and death. They noted that this composite outcome occurred more frequently with WATCHMAN than with LARIATs, and this is irrespective of pre- or post- approval status.                                 These findings highlight the importance of postoperative monitoring in evaluation of overall outcomes. The reason by which there was more frequent negative outcomes in the WATCHMAN than LARIATs need to be considered. Obviously there's several limitations in the MAUDE database, similar with all large databases. However, it does highlight the importance of considering the mechanisms or sure decision making necessary, not just amongst patients and their providers but amongst operators of the staff or amongst physicians and industry executives. To determine how to optimize devices going forward.                                 Speak of left atrial appendage occlusion devices and the potential future of these, we next review an article by Robinson et al, entitled "Patient-specific design of a soft occluder for the left atrial appendage" published in nature biomedical engineering, in volume two in the year 2018. Robinson et al used 3D printing to create a soft, immunocompatible, biocompatible, endocardial implant to occlude the left atrial appendage. They use the individual CT of an in vivo pig to three D print using a specialized material, a left atrial appendage occlusion device, and demonstrated feasibility of achieving adequate occlusion. This paper is important and is one of the initial [inaudible 00:22:03] to how three D printing may be used to optimize patient care. In fact, three D printing has the potential to overturn medical manufacturing and device development.                                 Anatomy tends to be more often patient-specific than not. That's one size fits all implant designs may not be optimal, and resulting exclusion or inadequate occlusion amongst many patients. Decide of three D printable patient specific rapidly prototype soft devices that are biocompatible and hemocompatible, holds the potential to revolutionize the occlusion.                                 Staying in the field of left atrial appendage occlusion, we next review an article by Lakkireddy et al entitled "left atrial appendage closure and systemic homeostasis: The LAA homeostasis study" published in JACC. The authors sought to evaluate the effect of epicardial-versus endocardial left atrial appendage occlusion on systemic homeostasis, including effects on neuro-hormonal profiles of patients. They performed a prospective, single center, observational study, including 77 patients, about half of whom received endocardial versus epicardial device. Interestingly, they noted that the epicardial left atrial appendage occlusion cohort exhibited significant decrease in blood adrenaline, noradrenaline and aldosterone levels. Those are not seen with endocardial devices. Internal epicardial devices are associated with increases in adiponectin and insulin levels as well as a decrease in free fatty acids and consistently lower systemic blood pressure.                                 These data suggest a significant difference in the effect of epicardial versus endocardial closure left atrial appendage on neurohormonal profile. The authors propose several mechanisms for these findings but not the exact mechanisms as yet unclear. Several factors potentially could lead to these findings. One is that epicardial ligation may result in more total ischemia of the left atrial appendage than endocardial closure. Another potential mechanism maybe that the presence for material in the pericardial space versus in the bloodstream may have different effects on neuro-hormonal profile. However, these significant differences in outcomes highlight the importance of considering whether all approaches of left atrial appendage occlusion are considered equal. Many flaws of this study is that it's observational and not randomized. Does it possible those receiving epicardial closure may have been perceived to be lower risk for epicardial puncture, in this, as result, had better long-term outcomes.                                 Changing gears now but staying within the realm of atrial fibrillation, we next review elements for cardiac mapping and ablation. The first article we review is one that has received significant press, published by Marrouche et al entitled "Catheter ablation for atrial fibrillation with heart failure" in the New England Journal of Medicine, volume 378. It is well recognized that morbidity and mortality are higher in heart failure patients who also have atrial fibrillation. Marrouche et al published the results of the CASTLE-AF trial, which attempted to determine if catheter ablation [inaudible 00:24:46] better outcomes among patients with heart failure and atrial fibrillation. They randomized 179 patients to ablation and 184 to medical therapy, which consisted of either rate or rhythm control. Inclusion criteria were those with NYHA class II to IV heart failure, LVEF of 35% or less, and an ICD.                                 The primary endpoint was a composite where the death from many causes or hospitalizations for worsening heart failure. They noted over a median of three as a follow up, the end-point was reached in 28.5% of the ablation group and 44.6% of the medical therapy group, accounting for a significant hazard ratio of 0.62. Furthermore, fewer patients that in the ablation group died from any cause, were hospitalized for worsening heart failure, or died from cardiac causes. These data made a big splash because they're highly supportive of the premise that catheter ablation may be beneficial in some patients with atrial fibrillation and heart failure, often beyond that of medical therapy alone.                                 One major strength of this paper is that the actual AF burden was tracked by the ICD, so we know for sure whether or not the procedure was successful and how controlled the atrial fibrillation was. One thing to note however, is that subgroup analysis suggest that those with more symptomatic heart failure, namely NYHA class III to IV, not benefit as much from ablation. Furthermore, it's also important to note that the five years expected mortality in patients was higher than predicted in the CASTLE-AF trial, however overall these trials highly suggest that the potential benefit that ablation may hold over conventional medical therapy. Extrapolation to comparison with the utility of interventions such as biventricular pace with AV node ablation, however, remains to be considered.                                 Next, we review an article by Chugh et al entitled "Spectrum of atrial arrhythmias using ligament of Marshall in patients with atrial fibrillation" published in Heart Rhythm volume 15, issue 1. They reviewed the spectrum of presentations associated with arrhythmogenesis attributed to the ligament of Marshall, amongst patients with atrial fibrillation. They demonstrate that nearly a third of those patients, ligament of Marshall associated arrhythmias had a pulmonary vein ligament connection, that variously required ablation, the left lateral ridge, the mitral annulus, or alcohol ablation. In addition, they noted about a quarter of patients had atrial tachycardia attributable to the ligament, and the remaining had periatrial reentry requiring either ablation or alcohol injection of the ligament to attain a conduction block.                                 The relevance of this publication, albeit it is of a small number of patients and a small center, lies in highlighting on the right mechanisms by which the ligament of Marshall may contribute to arrhythmogenesis. Namely, can include direct venous connections, inhibition to inaudibility to attain mitral block, and directly attributed atrial arrhythmias. Recognition of the various ways and situations under which the ligament of Marshall may play a role in arrhythmogenesis in atrial fibrillation patients, may optimize physician decisions to look for identify and target the ligaments. What is not as well understood however is the frequency with which ligament of Marshall plays a significant role in arrhythmogenesis in atrial fibrillation.                                 Moving gears, we next review an article by Pathik et al entitled "Transient rotor activity during prolonged three-dimensional phase mapping in human persistent atrial fibrillation" published in a special issue of JACC Clinical Electrophysiology, that focus on atrial fibrillation specifically, in volume 4 issue 1. Pathik et al sought to validate three-dimensional phase mapping system for persistent atrial fibrillation. Commercially available rotor mapping systems project the heart into two dimensions based on a three-dimensional catheter. Instead, Pathik et al used a combination of basket catheters along with the non-left atrial surface geometry to construct three D representations of phase progression. Amongst 9 out of 14 patients, they identified 34 rotors, with all these rotors being transients. Of particular interest, the rotors were only seen in areas of high electric density, where internal electric distances were shorter. They also noted the single wave front is also the most common propagation pattern. The importance of this publication lies in considering two things. First is the three dimensional representation of rotor position and the feasibility of this, and the second is really the high electro-density necessary to observe for others.                                 This has been one of the main problems in rotor analysis, namely what the spacial and temporal density is, that is required to identify rotors, especially given how transient they often are. The presence of rotors does not necessarily mean they're ablation targets in all patients. However, the question still remains regarding the optimal approach to mapping rotors, it needs to be remembered that rotors actually are meant to represent three dimensional scrollway phenomena, that cannot necessarily always be reflected in traditional two D mapping schema. Furthermore, to be remembered that when we claim three-dimensional mapping, this just reflects a two-dimensional surface being wrapped in three dimensions to reflect overall internal surface geometry but it does not take into account transmural activation.                                 Thus, taking into account all these elements it should be remembered as sometimes, it is possible that a rotor might exist but it's just not evident based on the two-dimensional representation or a two-dimensional representation that looks like a rotor may in fact not be a rotor when you consider it in a three-dimensional media.                                 Our last article within the realm of cardiac mapping and ablation we will consider is by Zghaib et al, entitled "Multimodal examination of atrial fibrillation substrate: Correlation of left atrial bipolar voltage using multielectrode fast automated mapping, point by point mapping, and magnetic resonance imaging intensity ratio", published in JACC Clinical Electrophysiology, in the same volume as the previous article. The authors sought to compare fast automated mapping with multiple electrodes versus point by point mapping and correlate with weighed gadolinium enhancement as seen by MRI, termed the image intensity ratio.                                 We all recognize that bipolar voltage is critical to recognizing and evaluating substrate. It's traditionally used in decay regions of substrate in both the atrium and ventricles. However, whether a newer automated approach used to characterize substrate perform equally well in comparison with traditional point to point mapping is still unknown. Thus, the authors in 26 patients perform cardiac MRI and mapping endocardial using both voltage mapping techniques. They noted that for each unit increase in image intensity ratio on MRI, in other words, increasing late enhancement, there was 57% reduction of bipolar voltage. They also noted that the bipolar voltage using other fast elevating mapping or point by point was significantly related with actual differences in calculated voltage, becoming more dissimilar in the extreme of high and low voltage areas.                                 The relevance of this publication is highlight in the potential utility of fast automated mapping in creating accurate voltage maps. The correlation of voltage values with image-intensity ratios suggest the utility of either approach. In turn, correlation with MRI suggest a pathologic correlate for all of these findings. However, whether substrate characterization guide ablation carries incremental benefit remains to be seen.                                 Changing gears but staying in the realm of atrial fibrillation, we next review elements of risk stratification and management. The first article we review is by Friedman et al, entitled "Association of left atrial appendage occlusion and readmission for thromboembolism amongst patients with atrial fibrillation undergoing concomitant cardiac surgery", published in JAMA, volume 319, issue four. Friedman et al sought to evaluate whether surgical left atrial appendage occlusion let to a reduction in long-term thromboembolic risk in a large database of Medicare recipients. They included the primary outcome as readmission for thromboembolism, including stroke, TIA, or systemic embolism, in up to three years of follow-up. With secondary end-points including hemorrhagic stroke, all-cause mortality, and a composite end-point of all outcomes.                                 Amongst more than 10,000 patients, there were almost 4,000 patients receiving surgical occlusion of left atrial appendage. Surgical occlusion was associated with a reduction in thromboembolic risk, OR of 6%, all cause mortality, 17 versus 24%, and the composite end-point, 21 versus 29%. However, interestingly, surgical occlusion was only associated with reduction in thromboembolic risk compared with no occlusion amongst those discharged without anticoagulation and those discharge with it. Namely, the thromboembolic risk reduction was primarily seen in those where the surgical occlusion, those who were sent home without any sort of anticoagulation. These data suggest that surgical occlusion leads to reduction of thromboembolic risk overall. As any large database based study, there are massive flaws in the database itself. Namely, we're relying on the coding of hospitals and operators. To know exactly what was done and what happens latter.                                 However, these data are hypothesis generating. One key element is the fact that surgical left atrial appendage occlusion was only superior in reducing thromboembolic risk amongst those discharged without anticoagulation. This raises the question as why. Was left atrial appendage completely closed in these patients? In which case, they may be at further increased risk or that the operators felt that there is a high risk for other reasons that cannot be cleaned from an administrative datasets? While the data support consideration of the benefit of left atrial appendage occlusion in a surgical manner, a kin to what has been seen in papers on WATCHMEN and other approaches, and how is the critical nature of randomized trials in this regard.                                 We next review an article published in JAMA Cardiology, volume three issue one by Inohara et al, entitled "Association of atrial fibrillation clinical phenotypes with treatment patterns and outcomes: A multicenter registry study." Traditionally classification of AF has depended largely on factors such as the nature of AF, paroxysmal versus persistent, LA size, and other factors such as extend of the late enhancement. Inohara et al sought to evaluate whether cluster analysis could better define heterogeneity of AF in the population. They included an observational cohort of almost 10,000 patients admitted to 124 sites in the United States in the ORBIT-AF registry.                                 Outcome was a composite major address cardiovascular and neurological events or major bleeding. Amongst these patients, they identified four clusters, including one those with lower rates of risk factors and comorbidities than other clusters, two, those with AF at younger ages and with comorbid behavior disorders. Three, those with AF with tachycardia-bradycardia type syndromes and had devices for sinus node dysfunction, and four, those with AF with other risk factors such as a coronary disease. Those in the first cluster had significantly lower risks of major events. All clusters were noted to have symptom dissociation to specific clinical outcomes.                                 These data are interesting and highlight the highly heterogeneous nature of classifying risk attributable to atrial fibrillation. When broad datasets associated atrial fibrillation with specific outcomes. Maybe suggest an attribution to all patients with atrial fibrillation. However, this single relationship was specific to the outcomes suggest the limitation of applying outcome as approach to understand atrial fibrillation impacts and outcomes, namely depending on clusters that may take into account patient age or comorbidities, it may be irrelevant in discriminating patient outcomes than the traditional paradigm in the same paroxysmal versus persistent or depending on the left atrial size.                                 These data also highlight the importance of considering the inclusion criteria in randomized trials of atrial fibrillation before stripling real world outcomes to patients who don't fit within that trial.                                 Next, we will be reviewing an article by Chou et al entitled "Relationship of aging and incident comorbidities to stroke risk in patients with atrial fibrillation," published in JACC, volume 71 issue two. Chou et al sought to evaluate the effect of aging and evolving instant comorbidities to stroke risk in patients with atrial fibrillation. Many large database studies or trials where added baseline CHADSVASC score and the then ensuing follow up period to define risk over time of ischemic stroke.                                 The authors hypothesized that as patients age, develop new comorbidities that would change the score, may be more predictable of long-term outcomes than the score itself. They included over 31,000 patients who do not have comorbidities to CHADSVASC aside from age and sex but had atrial fibrillation. They didn't calculate a delta score defined as the difference between the baseline and follow up scores. The mean baseline score was 1.29 with an increase in 2.3 during follow up, with an average delta of one. The score may not change over follow up in 41% of patients. Interestingly, significantly more patients had a delta CHADSVASC of one or more and develop ischemic stroke than non-ischemic stroke. The delta CHADSVASC was shown to better predictor of ischemic stroke than either baseline or follow up CHADSVASC score. This data suggest that additive shifts in the CHADSVASC score over time may be more predictive of stroke risk than the actual score itself.                                 These findings are thoughtful and logical. They indicate the potential impact of continued aging or acquisition identification of new comorbidities. In some patients, potential discovery or new comorbidities or follow-up; for example, hypertension and coronary artery disease may lead to reclassification of stroke risk. That is important to maintain close follow up of atrial fibrillation patients, and not to show a continued need or lack of need of anticoagulation on the basis of a baseline evaluation. This also holds relevance single center long-term outcomes in patients specific scores. Whether is acquisition of new comorbidities or presence of baseline comorbidities or predict a long-term score, should we consider when assessing the need for anticoagulation, particularly in perceived initially low risk cohorts who go on to develop ischemic stroke.                                 Lastly, within the realm of atrial fibrillation, we review an article by Hussain et al, entitled "Impact of cardiorespiratory fitness on frequency of atrial fibrillation, stroke, and all-cause mortality" published in the American Journal of Cardiology, volume 121 issue one. Hussain et al review the effect of cardiorespiratory fitness on overall outcomes and incidence of atrial fibrillation and outcomes amongst patients with atrial fibrillation. Amongst over 12,000 individuals prospectively followed up after treadmill exercise test, they noted 1,222 had a incidence of AF, 1,128 developed stroke, and 1,580 died. For every 10% increase in functional layover capacity, there was a 7% decrease in risk of incident AF, stroke, or death.                                 Similarly, in those who developed AF, stroke was lower in those with higher functional aerobic capacity. These findings support the notion known to other areas of cardiovascular disease that better cardiorespiratory fitness is associated with better outcomes, in this case to stroke, incident AF, or mortality. Furthermore, even on the presence of AF, those with better functional capacity had a lower risk of stroke. These data highlight the continued importance of counseling patients on the benefits of physical fitness even in the setting of already present AF.                                 Moving on to a different area of electrophysiology, we review the realm of ICD pacemakers and the CRT.                                 The first article review is by Sze et al entitled "Impaired recovery of left ventricular function in patients with cardiomyopathy and left bundle branch block" published in JACC volume 71 issue 3. Patients with left bundle branch block and cardiomyopathy are known to respond to CRT therapy. Thus the investigators sought to evaluate whether guideline medical therapy in patients with reduced LVEF and left bundle branch block, afford a beneficial first line approach therapy. The reason for this currently guidelines suggest waiting at least three months before consideration of CRT has had as some patients may recover on guideline directed medical therapy without the need for device implantation.                                 They review patients with a LVEF of less or equal than 35% and baseline ECG showing left bundle branch block. In evaluating left ventricular ejection fraction at follow up of three to six months. They excluded patients with severe valvular disease, and already present cardiac device, an LVAD, or heart transplant. Among 659 patients meeting criteria, they notice 74% had a narrow QRS duration of less than 120 whereas 17% had QRS duration greater than 120, and the remainder had a QRS duration greater 120 but was not left bundle branch block. The mean increase in the left ventricular ejection fraction on guideline directed medical therapy was in those with a narrow QRS duration and least in those with left bundle branch block, 8.2%.                                 Furthermore, when comparing mean LVEF improvement, those with on versus non-on guideline directed medical therapy, there was virtually no difference in rates of recovery. Furthermore, composite end-point of heart failure hospitalization mortality was highest in those with left bundle branch block. These data suggest that those with bundle branch block and cardiomyopathy received less overall benefit from guideline directed medical therapy over the three to six months follow up period. Whether this is due to already more severe myopathic process to start with or due to the CRT is unclear. However, it may suggest that in some patients, left bundle branch block may benefit from inclusion of CRT early in their disease course as known the significant number of patients up to three to six months guideline directed medical therapy with insufficient DF recovery may then benefit from CRT. As well as intervening earlier may result in better outcomes, especially knowing the high and term raise mortality in heart failure hospitalization remains to be seen.                                 A trial studying early implantation of CRT on these patients may be relevant.                                 The next article review is by Gierula et al entitle "Rate-response programming tailored to the force-frequency relationship improves exercise tolerance in chronic heart failure" published in JACC Heart Failure, in volume six, issue two. The authors sought to evaluate whether tailored rate-response programming improved exercise tolerance in chronic heart failure. The double blinded, randomized, control, crossover study, they compared the effects of tailored programming on the basis of calculated force-frequency relationship, defined as including critical heart rate, peak contractility, and the slope, multidimensional programming and exercise time and maximal oxygen consumption. They demonstrate amongst 98 enrolled patients that rate-response settings limiting heart rate raise to below the critical heart rate led to create exercise timing and higher peak oxygen consumption.                                 These data suggest that personalizing rate-response therapies may improve exercise time and oxygen consumption values in patients with heart failure and pacing devices. The main limitation of the study is that the number of patients was small, 90, and then the number of patients crossing over was even smaller, 52. However, highlights the potential of working closely between device programmers and consideration of individual's characteristics and their exercise needs in determining optimal programming strategy.                                 Finally, within the realm of devices, we review an article by Hawkins et al, entitled "Long-term complications, reoperations, and survival following cardioverter defibrillator implant" published in Heart, volume 104 issue three. Hawkins et al sought to evaluate the long-term complications and risk of reoperation associated with defibrillator implantations in a large [inaudible 00:41:56] population of 300,410 patients, they noted over a 30-month follow up period there was a 12% reoperation rate within the year of implant. This is most prominent for CRT devices, with a risk of 18% in one year post-implant. Furthermore, CRT had the highest rate of early complications, with device complexity, age, or the presence of atrial fibrillation being significantly associated with complication risk.                                 Mortality also increased over time from 5% within the first year to nearly a third after five years. However, younger patients exhibited five years survival similar to the general population with a progressive decline of this as older patients were considered. These findings highlight several critical issues. First, they report a high one year reoperation rate for a variety of reasons. This finding highlights the importance of considering protocols to minimize the need for reoperation. Furthermore, they note the higher rate amongst CRT patients, with seems logical given the likely longer associated procedural risk and need for more leads. Finally, the impact of age on expectant survival are to be taken into consideration with the device and the life-saving potential of the defibrillator.                                 Moving on to cellular electrophysiology, review one article by Zhang et al, entitled "Reduced N-type calcium channels in atrioventricular ganglion neuron are involved in ventricular arrhythmogenesis" published at the journal of the American Heart Association, in volume seven issue two. Zhang et al reported a rat model of ventricular arrhythmogenesis and characterized the role of atrioventricular ganglion neurons in risk of arrhythmogenesis as well as the mechanism for this risk this model relates in humans to the attenuated cardiac vagal activity in heart failure patients, which is known to relate to their arrhythmic risk. The demonstrated reduced N-type calcium channel in these AV ganglion neurons, which project innervating systems to the myocardium, resulting in increased risk of PVCs, and increased susceptibility to induction of ventricular arrhythmias with programmed stimulation.                                 The relevance of the intrinsic cardiac nervous system arrhythmogenesis has become increasingly prominent as methods to study it have improved. Understanding the direct and most relevant inputs may facilitate better understanding of risk of arrhythmias in patients. In the case of this study by Zhang et al, the critical finding is that disorder of the atrioventricular ganglion neurons may lead to increased susceptibility for ventricular arrhythmogenesis. Clinical relevance includes consideration of effects on this specific ganglion when performing ablation on for other conditions, and potential long-term effect on arrhythmogenic risk, as well as potentially relevant functional explanations for arrhythmogenesis.                                 Moving on to the genetic channelop, these are considered two separate articles. The first one by Bilmayer et al, entitled "ExomeChip-Wide analysis of 95,626 individuals identified ten novel loci associated QT and JT intervals" published in Circulation: Genomic and Precision Medicine, in volume 11 issue 1. This whole exome study reviewed several novel loci that modified the QT and JT intervals. They include over 100,000 individuals and identified ten novel loci not previously reported in the literature. This increases the number of known loci that impact from ventricular portal adjacent by nearly one third. These loci appear to be responsible for myocyte and channel structure and interconnections that internally impact the ventricular repolarization.                                 While long QT syndrome be characterized amongst the known genes in 75% of affected individuals, that also means one fourth long QT syndrome cannot be characterized based on known genes impacting ventricular repolarization. The identification of novel loci or novel that may be affect repolarization kinetics to unique means are critical to define novel therapies as well as in genetic counseling the patients in potential effects on family members when screening them for potential disease risk. These findings should assess an opportunity for further studying the mechanisms by which these loci modulate QT and JT intervals and the potential contribution to phenotypic risk.                                 The second paper within this realm we review is by Zumhagen et al, entitled "Impact of presynaptic sympathetic imbalance on long QT syndrome by positron emission tomography" published in Heart, volume 104. The authors sought to evaluate by a PET scan the impact of sympathetic heterogeneity on long-QT syndrome risk. Amongst 25 patients with long-QT syndrome, including long-QT type I and II, and 20 ostensibly healthy controls, they noted that regional retention in disease were similar between affected patients and controls. However, regional washout rates were higher in the lateral left ventricles in patients with long-QT syndrome. Internal global washout rates were associated with greater frequency of clinical symptoms. That's there seem to be some relationship between regional and global sympathetic heterogeneity, particularly during washout, with overall risk in long-QT syndrome patients.                                 These findings report the notion for sympathetic imbalance, partly mediating the risk attributable to long-QT syndrome. The findings on PET suggest regional imbalance of presynaptic cathecholamine and reuptake and release, being one mechanisms. This was most prominent in long-QT I patients who also often drive most benefit from left sided sympathectomy. The novelty of these findings is in the potential role of imaging to determine basic contributors to congenital long-QT syndrome in given patients. The larger prospect of size would really need to be evaluated this further.                                 Moving on to the realm of ventricular arrhythmias, we review three different articles. The first one, by Hamon et al, entitled "Circadian variability patterns predict and guide premature ventricular contraction ablation, procedural disability, and outcomes" published in Heart Rhythm, volume 15 issue one. Hamon et al sought to evaluate whether circadian variability of PVC frequency can predict optimal drug response intraprocedurally during PVC ablation. One of the main problems of PVC ablation is when PVC are infrequent and tend to disappear during the procedure, achieving procedural success or attaining sufficient frequencies of PVCs to map becomes very difficult. Next, they use Holter monitoring in the ambulatory stripe to define three groups. Those of higher PVC burden during faster heart rates, those with higher PVC burden during slower heart rates, and those with no correlation between their PVCs burden and their heart rate.                                 More than half the one hundred and one patients included a high burden of PVCs at fast rate while 40% had no correlation between the two and 10% had higher burden in slower heart rates. Almost one third of patients taken for ablation have infrequent PVCs during a procedure, while the best predictor of this being a low ambulatory PVC burden of less than 120 per hour. Isoproterenol infusion was only useful in lessening PVCs in those with PVCs associated with fast heart rates. The isoproterenol washout or phenylephrine where used with those associated with slower heart rates.                                 Interestingly, not a single drug was effective in inducing PVCs in those with infrequent PVCs that have not heart rate correlation in the ambulatory stages. They noted that outcomes ablates were similar amongst those with higher heart rate associated PVCs and non-heart rate correlated PVCs previously responded to a drug. But, [inaudible 00:48:08] noted only a 15% success rate from ablation in infrequent PVCs in patients who lacked correlation between PVC burden and heart rate and who were unresponsive to drug previously. These data are important highlighting the potential for further defining idiopathic PVC ablation needs and likelihood of success based on ambulatory data, by correlating PVC burden with heart rate and their circadian variability, it's possible to predict likelihood specific intraoperative drugs working when dealing with infrequent intraprocedural PVCs.                                 Furthermore, the finding of lack of correlation with slower or fast heart rate in terms of PVC burden is associated with the poor success rate unless those PVCs are drug responsive. Highlights the potential benefit of performing preoperative antiarrhythmic drug testing to get likelihood of ablation success in this patients.                                 The next article we review is by Lee et al, entitled "Incidence and significance of the lesions encountered during epicardial mapping and ablation of ventricular tachycardia in patients with no history of prior cardiac surgery or pericarditis" published in Heart Rhythm, volume 15 issue one. Lee et al sought to determine the frequency of pericardial lesions, impeding mapping in patients without prior surgery, operative procedure, or pericarditis, in other words virgin hearts. Amongst 155 first time attempts of access, 8% had pericardial lesions. The only clinical predictor was the presence of severe renal impairment.                                 In addition, no patients with supposedly normal hearts had a lesions. Notably, those with a lesion had more frequent impairment in mapping and lower overall success rates; there were similar complication rates as those without the lesions. These data are relevant in highlighting the ease of mapping of pericardial access may not always be present, even when dealing with inversion of pericardial space. A lesion may be present in patients, particularly with severe renal disease. Advising patients of this possibility prior to the procedure and considering that epicardial access may be impaired in a fair number of patients, even the absence of prior history of surgery, epicardial access or pericarditis isn't important.                                 The final article we'll review within the realm of ventricular arrhythmias is by Kumar et al, published in Journal of Cardiovascular Electrophysiology, volume 29 issue one, entitled "Right ventricular scar-related ventricular tachycardia in nonischemic cardiomyopathy: Electrophysiological characteristics, mapping, and ablation underlying heart disease." Kumar et al sought to evaluate the substrate and outcomes associated with right ventricle scar related ventricular tachycardia ablation in nonischemic patients at large, but particularly in those with neither stroke or coronary artery disease as potential explanations for this scar. They reviewed 100 patients consecutively over half of whom had ARVC and the remainder was sarcoid or RV scar of unclear origin. Those with RV scar of unknown origin tend to be older compared to the ARVC patients, and had more severe LV dysfunction compared with saroid patients.                                 However, the scar distribution extend was similar within all these groups. Furthermore VT/VF survival was higher in those with RV scar of unknown origin. The velocity of survival free or death or cardiac transplant and VT/VF survival seen in sarcoid patients. These data suggest that close to one third of patients, RV scar related VT may have VT of unknown cause. Total outcome was superior overall to those with defined myopathic processes. What's most interesting is, over follow up, none of those with RV scar of unknown origin develop any further findings to reclassify them as sarcoid or ARVC. It is possible this group reflects some mild form of either disease however. Again, the exact pathophysiologic process remains unclear. These findings may help in counseling patients who are in long-term expected outcomes from ablation intervention.                                 The final article we'll review this month is within the realm of other EP concepts that may be broadly applicable, published by van Es et al, entitled "Novel methods for electrotissue contact measurement with multielectrode catheters", published in Europace, volume 20 issue one. In this publication, the authors sought to evaluate the potential utility of a novel measure on evaluating electro tissue contact. With multielectrode catheters it is known that one of the problems with assessing contact is a contact force that cannot be used. Electro with coupling index is often used but even this has fragile problems, especially when you get into high impedance areas, that can be affected by surrounding ion impedance structures. Due to the fact that measuring contacts forces challenging in such multielectrode catheters, the authors measure electric interface resistance by applying a low level electrical field, pushing neighboring electrodes. They compared the effectiveness of assessing contact by this approach without using contact force in a poor side model.                                 They know that this measure was directly correlated with contact force in measuring tissue contacts. These findings support a role for aversion of an active electrode location and determining tissue proximity and contact-based on the coupling between the electrodes on multipolar catheters in the tissue. These findings may be highly useful when there is a variety of catheters where contact force cannot be implemented. Further studies on the methods and cutoff to establish tissue proximity on the end of contact will be also needed.                                 To summarize, however, as a term was brilliant here that was not well explained, active electrical location is actually a phenomenon that occurs in nature. This is seen in deep sea fish, which actually have multiple electrodes oriented around its body. They emit a small electrical field that results in a general impedance field surrounding the fish. This essentially is the way of visualizing the world around them. Perturbations based on proximity to different structures, whether they are live or death, and based on whether they are live or death, results in changes in the perturbations of this resistive fields, resulting in proximity determination by the fish. Several individuals are looking into potential applications of this to understanding tissue proximity when using catheters in the body. This consideration of impedance is fundamentally different than the traditional measure impedance were used by traditional generator.                                 I appreciate everyone's attention to this key and hardening articles that we've just focus on or this past month of cardiac electrophysiology across literature. Thanks for listening. Now back to Paul. Dr Wong:             Thanks Suraj, you did a terrific job surveying all journals for the latest articles on topics of interesting in our field. There's not an easier way of staying in touch with the latest advances. These summaries and the list of all major articles in our field for month can be downloaded from the Circulation: Arrhythmia and Electrophysiology website. We hope that you find the journal to be the go to place for everyone interested in the field.                                 See you next month.  

Transcript for January 2018 Podcast Circulation: Genomic and Precision Medicine     Jane Ferguson:                 Hi, everyone. Happy New Year. You are listening to "Getting Personable: Omics of the Heart". I'm Jane Ferguson and this is episode twelve from January 2018.                                                  This month I have some exciting announcements to make. The journal formerly known as "Circulation: Cardiovascular Genetics" has a new name. As of this month, the podcast is brought to you by "Circulation: Genomic and Precision Medicine". We're still publishing papers focused on cardiovascular genetics but as genomics and other omics have expanded our scope has grown to so much more than just genetics.                                                 The new name, "Genomic and Precision Medicine" signifies the journals focus not only on genetics, but also genomics and all the other omic technologies and the feel of precision medicine. Along with the new name we have a new editing team. Dr. Kiran Musunuru, an associate professor of cardiovascular medicine and genetics at the Perelman School of Medicine at the University of Pennsylvania has officially taken over as editor-in-chief. He has already been implementing new initiatives to allow the journal to serve authors and readers even better.                                                 Along with create original research articles you can find accompanying editorials, videos and interviews with authors, including the interview we're featuring in this month's podcast.                                                 Finally, while "Circulation: Cardiovascular Genetics" was published every two months, "Circulation: Genomic and Precision Medicine" will now be published monthly. So, you can look forward to a new issue every month and even less time waiting for the newest research to be published. Check out the latest issue and all of the new material at circgenetics.ahajournals.org and follow us on Twitter at Circ_Gen.                                                 Now, along with the name change for the journal, we have another name change in the pipeline. Our AHA Council, Functional Genomics and Translational Biology, is also being renamed to "The Council on Genomic and Precision Medicine". As with the journal name change this better reflects the evolution in our scope and focus. This name change will be formalized in the coming months. So, if you are one of the many people who could never remember what the acronym FGTB stood for or what order all those letters came in, your struggles will soon be over.                                                 We have a number of interesting papers published this month, including an article by George Hindy and colleagues on how smoking modifies the relationship between a genetic risk score and coronary heart disease; a mendelian randomization study from Jie Zhao and  Mary Schooling on coagulation factors and ischemic heart disease; an exome wide association study of QT interfolds from Nathan Bihlmeyer and colleagues; a study on genetic testing of cardiac ion-channelopathies and still births from Patricia Munroe and colleagues; and a genetic study of cardiac disfunction in Duchenne Muscular Dystrophy from Tetsushi Yamamoto and colleagues.                                                 You can also catch up on the genetic cardi-oncology literature with a review by Marijke Linschoten and colleagues on chemotherapy related cardiac disfunction. And read a clinical case on left-ventricular non-compaction by Vi Tang and colleagues.                                                 Finally, we also have a scientific statement on the use of induced pluripotent stem cells for cardiovascular disease modeling in precision medicine by Kiran Musunuru and colleagues.                                                 Moving on to our feature article, Andrew Landstrom, an early career member of the Genomic and Precision Medicine Council, formerly FGTB, talk to Guillaume Paré and Sébastien Thériault about their article published this month entitled, "Polygenic Contribution in Individuals with Early Onset Coronary Artery Disease". In this paper, Dr. Thériault and colleagues report the use of the genetic risk score which improves on our ability to predict very early onset CAD. Listen on to the authors talk more about the background to this study and what they learned along the way. Andrew:              Welcome. My name is Andrew Landstrom, an assistant professor in the Department of Pediatrics, Section of Cardiology at Baylor College of Medicine. I am a member of the early career committee of the American Heart Association Council on Genomic and Precision Medicine, previously the Council Functional Genomics and Translational Biology. I'm joined today by Sebastien Theriault, assistant professor in the Department of Molecular Biology Medical Biochemistry and Pathology at Laval University, and Guillaume Pare, the Canada Research Chair in genetic and molecular epidemiology, assistant professor in integrative health bio-systems and associate professor of medicine at McMaster University. Guillaume:          Hi. Good morning. Andrew:              Well, I'm wondering if we could just start by introducing ourselves maybe a little bit more thoroughly than I just did and talking a bit about your research paper and what brought you to this as a research question. Guillaume:          Absolutely. So, this … [inaudible] and thank you for having us.                                 My name is Guillaume Pare, and as stated, I'm an associate professor at McMaster University, and I would say like my longstanding clinical interest is about individuals and families with very early coronary artery disease and heart disease. And this really was the basis for this project and to try to understand why do some people in family are afflicted by this disease when we cannot find any of the conventional risk factors. And as Sebastien came to join me and this endeavor, and spent two years with us here at McMaster and was instrumental in getting this project off the ground. Sebastien:           Yes, exactly. So, I was a physician trained in Quebec City and I went to McMaster University as a research and clinical fellowship. And that's where I did some cardiovascular clinics with Dr. Pare and that's when we noted that some patients with early coronary artery disease didn't have much explanation for their disease. So, that's how this project stem, that we wanted to understand what was going on and we thought that really genetic factors could be involved. Andrew:              And speaking of these genetic factors, in fact, you established a genetic risk score as sort of a way of aggregating a large number of genetic variants into a single prognostic risk indicator. How did you come up with the score, and where did these genetic variants that you aggregated come from? Sebastien:           So, the results of many of our studies looking at the association between common genetic variants and coronary artery disease have recently been released. For this study, we use the variants identified in the latest CARDIoGRAM for C4D consortium meter analysis, which includes more than 60000 individuals with coronary artery disease and 120000 individuals without coronary artery disease from a total of 48 studies. Most of the participants in these studies were European. And so we decided to use the independent variants that were associated with the disease in that very study and look if we could predict early coronary artery disease in some patients. Guillaume:          Andrew, maybe I'll backtrack a little bit. The initial idea about the gene score, first of all came from the observation that a lot of the patients who we're seeing do not have any traditional risk factor. The second observation is that we already knew that genetic risk scores are predictive of coronary artery disease. But the key question is, is it possible that there are people at the extreme of severity of a cardiovascular or genetic risk score that could be at much, much higher risk of having the disease. And this is what the hypotheses really that we wanted to test is whether these genes scores they could identify people that clearly have outlying risk, outlying genetic risk of having the disease.                                 And to explain, the patients that we were seeing a deflation in the clinic will clearly have an outlying risk of disease because they have a First Earth attack or multi vessel disease in their 30s or 40s, and we thought that this cannot be just like bad luck, there had to be some ... and this something is really most likely genetics. We cannot put a finger on it because all the known mutations that we know could cause this, well, we're just not finding them. Andrew:              Sure, sure. And there's certainly having a large number of genome association studies, which have implicated a number of common variants and not so common variants in coronary artery disease. So, is this where some of this idea behind the genetic risk or was initially thought of? Guillaume:          Absolutely. And I think you know ... and this is where Sebastian really came in and to really like look at this literature, to feel like the variants that went in into the score. Andrew:              And certainly to go to your earlier point, it seemed like you were saying early on that coronary artery disease would be a great phenotypic model to explore this question in, mainly because it would seem that at that age, with that severe disease, that it must be something innate to that person, and genetics would certainly play a role. Guillaume:          Absolutely. And to me, it's more than simply scientific because we see these patients at our clinic and we've got a lot of ref roles for these patients, and we really feel for them because they're really young people, and I think like when we think about genomic and like preventative medicine having an impact, I cannot see a greater impact than preventing a first heart attack in the 30s or early 40s. So, this is a ... it's a very vulnerable patient population. It's also a patient population that has a lot of questions about why this might be happening to them, and often what we see is that, I think everyone feels that clearly there's a genetic component, and one, a loved one has first attack in his or her 30s, this raises questions for the whole family really, and it clearly sends a shock wave in the family, and everyone, I think rightfully, is quite scared of having the disease and the fact that there is no answer for these people, to me is a huge unmet clinical need. And it's just for the sake of providing people with answers. Andrew:              Yeah. Absolutely, I think it's certainly a clinically relevant question that you attempted to answer. And to try to get to this a little bit, and you utilized a large UK-based biobank as your primary study population to establish this risk score. Can you tell me more about this biobank and what sort of data you were able to obtain from it? Sebastien:           Sure, I can speak a bit about it. So, the UK biobank is a large prospective cohort of about 500000 individuals between the age of 40 and 69, with an average of 58 years, and they were recruited from 2006 to 2010 in several centers in the United Kingdom, and the general objective is to study the effect on the environment and genetics on health. And what's interesting is that the data is made available to the research community worldwide following registration process. And the data in that includes a very vast amount of information, from questionnaires, specific evaluations, such as height, and weight, and aging data, and the diagnosis from the participants, medical charts, in addition to the genetic data of course.                                 And for this study we used the first release of the genetic data, which included information on about 40 million variants in about 150000 individuals, and selected the individuals who had a diagnosis of early coronary artery disease, so aged 40 or less for men, 45 or less for women, and then it underwent a reversed relation procedure in order to identify patients with obstruction in coronary artery disease, and we used all the other participants as controls. And that's basically leveraging this huge amount of data that we were able to confirm the fact that patients with early coronary artery disease, some of them very high and pathogenic components of their disease. Andrew:              That certainly sounds like a really amazing, both biobank and cohort of information that could be utilized. Such a huge sample population with so many clinical variables as well as genetic variables and collected prospectively. What a great resource. Sebastien:           Yes indeed. Guillaume:          It's a fantastic resource and to me, this type of initiative it's a game changer to accelerate research, because with these data being made available, then it's really up to testing new bold ideas to try to improve our understanding of this disease. So, I think you know we have to say kudos to United Kingdom for financing this this great cohort and making it available to researcher worldwide. Andrew:              And you didn't just stop there. You also utilized a local cohort as a foundation cohort for your study. Could you speak a little more about that? Guillaume:          So, that's interesting because this cohort really stems from the patients that we've seen at the clinic. And essentially, we felt this was this huge unmet clinical need. To better address causes of disease, and these roles that's barely a disease. And then we said, well, if we were to do this, let's do this formal, and let's do this properly and collect the information and samples and everything, and we had a very enthusiastic response from our cardiologist, and international cardiologist colleagues that really helped us identify these early cases and send them to us and in our study. And so these are local patients. These are people that we care deeply about, and that's really want to make a difference. And again, you know, when Sebastian was with us at McMaster, we were seeing these patients together, and maybe he can add some of the details there if you want. Sebastien:           Yeah. Just to specify again, these were patients at the very early coronary artery disease, for age 40 or less for men, and age 45 or less for women. And these were patients without the clear secondary cause of their disease. Most of them were clueless about what were the factors that caused the disease outside a few risk factors such as smoking or hypertension, there wasn't clear explanation as to why they had such early disease, and we could see that it was a struggle to try to understand and then see if there is a risk for their family also. So yeah, it was really interesting to find an explanation for some of them, and we did report the findings to a few of them who seemed to have polygenic contribution to their disease, and it did make a difference. They were quite happy to at least have some kind of an explanation to what was happening to them. Guillaume:          And I think that one thing that I think was striking to me when doing this is that when we started to formally collect family history in these individuals, we just realized that and in many, if not most of them, the family history is really striking. And these are folks that clearly has a very severe individual disease, but when we start asking about their brothers, and sisters, and parents, and uncles, you just realized that coronary artery disease was just all over the place and was very aggressive and early. And I think to us, this gave us purpose in this project to say that, 'Yes, we have to do something about this,' but also, I think it also reassures us that our primary hypothesis was right in thinking that there has to be a genetic component that goes beyond just having bad luck, and this genetic component was expressing itself by the family history that we saw.                                 And a further clue that I think we might be on the right track is that the pattern of inheritance didn't shift one of the single mutations that aggregates in a family and that can explain the disease. So, the disease was more diffuse and oftentimes it was both from the paternal and maternal branch of the family without a clear genetic pattern that would be more in line with the so-called mendelian disease, where a single gene mutation causes the disease. And I think really that puts to us in the mind that we might be looking at the different modes of inheritance, and this is partly how we came with this idea of looking at gene scores in these individuals and families. Andrew:              So certainly a close clinical connection to the patients and their families that you're trying to risk stratify and certainly, it sounds like clinical suggestion that you were dealing with something genetic and inheritable, but not necessarily mendelian, where one gene defect leads to say an autosomal balanoid express disease, more of a polygenic family history exactly. Guillaume:          Exactly. Andrew:              And so with these two scores and this genetic risk score, what exactly did you all find? Sebastien:           So first we found that participants from the UK biobank who had this early coronary artery disease had a very significantly higher number of common genetic risk variants. So the score was very significantly higher in these patients. And what was interesting too is that the increase in risk that was associated with the score was independent from traditional risk factors such as smoking and high blood pressure. And when we looked in the local cohort with early coronary artery disease, out of 30 participants that were involved, we found seven with a significant polygenic contribution, which we define as, a two-fold increase in risk, and one of the participants actually more than six-fold estimated increase in risk. So we really did identify an explanation for some of these participants with the early coronary artery disease. Guillaume:          And I think this was maybe a bit of a eureka moment to see that some of these individuals actually had a much, much increased risk of disease based on the polygenic risk score, and this really was the primary hypothesis that when looking at extreme of disease, which is what we're looking at, we might find extreme of genetic predisposition. But the one thing I thought that's quite striking is then we went back to think all that. And to try to put this in perspective with what we would usually do in these patients that we've done already, and to look for mutations that cause familial hypercholesterolemia.                                 Familial hypercholesterolemia is a disease of cholesterol metabolism that leads to a much increased concentration of cholesterol and early coronary artery disease, and a discovery that led to a Nobel Prize for Goldstein and Brown, back in the day, and really like, up to this point, when we see people with early disease clinically, this is what we will be looking for. And certainly, there's a lot of these individuals that have very high cholesterol and a lot of them is due to familial hypercholesterolemia. But it's a minority of patients really. It looks like we're having an association and this gene score concept is really panning out. But I wouldn't compare to familial hypercholesterolemia, and I guess that the results were kind of surprising to us and I think we had to take a step back and think about the implications. And I don't know, Sebastien do you want to describe these results or ... Sebastien:           Yeah, sure of course. So we've looked at how frequent this polygenic contribution to coronary artery disease could be. So we look at the prevalence of high genetic risk or that would cause a risk similar to familial hypercholesterolemia see the ratio about 3.7, and we realized that one in 53 individuals had an increasing risk that was similar. So that's almost 2% of the population, and that is way more frequent than the actual prevalence of familial hypercholesterolemia, which is one in 250. So in other words, the polygenic contribution could be almost five times more frequent than familial hypercholesterolemia. Andrew:              But yet not all of those individuals manifest as disease, which sort of hits as something that's a common thread in genetic association studies where we're trying to describe sort of multifactorial disease en points with finite genetic and a whole spectrum of acquired disease, required lifestyle modifications and things. So no model is 100% perfect, and so where do you think that additional variation lies, either in the reduced penetrance of some of these disease phenotypes, or are there other genetic loci, or are these all secondary to acquired changes that happen, or where does some of that variation lie? Guillaume:          Well, to me I think there's two parts to this question. The first one is that I see the cells study as in some sense, proof of concept, to look for the concept of very high burden of polygenic risk as a mendelian equivalent really. But the fact is that, especially with the new discoveries and the genetics of coronary artery disease, the gene scores that we've been using for this study could be much improved. And I think the concept is there, but the gene score could be improved, and I think they will be improved and I think in three, four, five, ten, years from now, they're going to be even better because we will have many more variants that we know are preceded with coronary artery disease and that might be upwards to 1000 variance, for example will have much better gene score I think we'll have much more predictive gene scores.                                 So I think the concept is there, but I think it's going to improve, with the years is only going to get better. And I think part of this missing risk, if I may, is due to the fact that we're missing a lot of genetic variants associated with coronary artery disease, and I'm very confident that the community will find them in the years to come.                                 I think the second part of the study is that, that being said, I think genetic risk is obviously important but we shouldn't neglect also classical risk factors. And a lot of [inaudible] … they did have the classic risk factors and that was a fairly high proportion of smokers, and a few cases of diabetes, and I think that individually, this risk factor wouldn't be enough to explain the aggressiveness of this disease. But I think the fact that we do find an enrichment for these factors also give us ... I think it feeds the idea that it's not only genetics and that even in these individuals classic risk factors do matter and trying our best to decrease the burden of these risk factors on a community and its role family level is probably also very important. Sebastien:           I'd also want to know that there's an environmental part that's involved even in these individuals with high genetic risk. And as he just mentioned, we did notice a high proportion of traditional risk factors in patients with early coronary artery disease even in some of them with high polygenic score, some of the environmental factors seem to be also involved in their disease. Guillaume:          And to some extent I think that's going to be an interesting research question, in these individuals with very high polygenic burden, do traditional risk factor, do they at the time, are they stronger or weaker, is there a synergistic effect between, for example, smoking and being at this extreme of the polygenic risk? And these are kind of open questions that we couldn't address in the current study but I think will be interesting to see in the years to come. Andrew:              Absolutely. I think there's definitely a road ahead of us but this is definitely a step in the right direction. What are some of the practical applications of this genetic risk scores, either from your study or from others in the identification of individuals? Is it something that could be used for primary production? I mean, in theory, this could be done at birth. You could be screened for these genetic variants and the risks will be calculated within the first days of life. What do you think are the practical applications of this and where is this fit into a rapidly expanding world of clinical genetics? Guillaume:          Well, I think you know what you've just described is exactly how I see the future, and I think that if we want to be consistent, and we consider folks with a familial [inaudible] mutation to be at higher risk, I think that someone with a predicted polygenic risk of twofold, threefold, or fourfold increase risk of coronary artery disease should definitely be put in a higher risk category when it comes to primary prevention irrespective of other risk factors, or maybe like in combination with these other risk factors, and I think should be treated accordingly. And as we see, these are people are very aggressively affected by the disease, and I think the sooner we could identify these individuals at high risk and try to intervene to lessen as much as possible this risk, I think we will do these individuals and families a great service.                                 So I think it's definitely a case for primary prevention and especially in a world where genomics is more clinically prevalent and used, also we see a role for this and the role that's already affected. And to me personally, I see great value in providing people with answer on why they've had an event and probably providing an answer not only to them, but also to their families. Andrew:              And so if something like this were to be able to be applied broadly in the clinical arena, what sort of steps do you think need to happen from this point forward to make this sort of testing ready for prime time? Guillaume:          This is a great question and I have to say that my passion I would say is to bring genomics to the clinic. I think there's a long road ahead to make this happen. But I think there's two main obstacles. The first one is that I think there's a knowledge gap between people that do this 24/7 like me, and I think you know the rest of the community and that there's been so much rapid progress in the field of genomics in the last few years that I think there's a lot of education to be done for people to catch up and just the concept of polygenic risk.                                 I think only a minority of clinicians will know about this and very rightfully, because right now it's in the realm of research papers. So I think to make this happen, there's a huge role in education and awareness. I also think that our hospitals ... or maybe it's a Canadian thing, are not prepared just for the flow of information and how to derive the routines commercially, and probably how to handle these highly multi-dimensional data and to be able to take the right information out of them and I think in this world, I would think that probably the best way to do it is to do it in a way that these gene scores can be updated, the science progress. But we're so far away.                                 Sometimes I feel that our hospital system is struggling to provide [inaudible] time to clinicians. And I'm just thinking without the prevention or how to handle something as complex as polygenic score, in this case we barely had like all the plugs in 200 variants, but you could clearly imagine like genetic risk scores being done with hundreds of thousands, if not millions of variants and will bring a whole new set of challenges. Andrew:              And Sebastian, do you have a perspective on this? Sebastien:           Yeah. I would just add that this knowledge is in the research community but to really put that into the clinic there's old setting, you have first to interpret the results and also to disclose the results to patients in a way that they can understand and that wouldn't create unnecessary anxiety, but more give them informed and an informed view of their health. So there's this also translation to the patient that needs to be evaluated and developed for it to be used to mainstream I would say. Guillaume:          And I think the classic tools like publications also presentations and meeting and even reaching out to the cardiology community to start discussing these concepts will be important. And clearly it's a big shift from just classic genetics and even familial hypercholesterolemia, I think there isn't a lot of awareness, I don't think there's enough awareness as far as I'm concerned. And then we're bringing new concepts that might be even further remote from what people have been taught about genetics and score, it's going to be a huge challenge, but we have to. And I think the great thing about the medical community as far as I'm concerned, is that every time that there's been something that was worthwhile to do clinically, the community has always come around and making sure that these things are implemented and made available and everything. So I'm also very confident, but I think there's a great challenge ahead as well. Andrew:              It sounds like the challenge has a potential for great benefit and if proper partnerships between the clinicians, and the geneticists, the scientists, and the patients and their families can all sort of come together to establish a path forward for this type of information to be applied clinically. Guillaume:          Yeah, absolutely. And I really like that to add there that you've put the clinicians, geneticists, and patients as well. I think it's very important, patient advocates are a very important part of the equation here. Andrew:              Going forward, are other disease processes besides early onset coronary artery disease that you all feel might benefit from a similar polygenic risk? Sebastien:           The recent studies show that a lot of complex traits seem to have polygenic origin. So traits like hypertension, diabetes, obesity, atrial fibrillation, for example, they show a similar genetic architecture where there seem to be combinations of a very large number of common variants that explain the genetic risk. So it's a big number of variants with smaller effects that seem to be responsible for the appearance of these complex traits. So this concept could potentially be applied to a lot of different diseases. Guillaume:          I think I would maybe just go even one step further, but I really have the feeling that most late onset disease actually has a polygenic architecture, which means that similar polygenic risk score could be done targeting the extreme of distribution to look into this. I mean obviously, I think metabolic traits, diabetes, hypertension as Sebastien mentioned, but probably why not some cancers, or [inaudible] or any of the large number of disease where a polygenic inheritance either has been proven or is highly suspected.                                 So I think that we will hear a lot of polygenic risk score in the future, and I might be biased here, but I think it might become a staple of clinical practice that people will be looking at polygenic risk for a number of disease. And I think the great thing is that now that we've got genome-wide genotyping that is really affordable and we can type with statistical imputation and tens of millions of variants, then I think one concept is that we only have to genotype once and then we can derive these polygenic risk scores for ... why not a dozen diseases that are important and are actionable and really like turbo charge primary prevention by using this information. I might be getting ahead of myself, but I really think that this is something that we might see and that for us, we should see. Andrew:              And certainly that seems to be the way that at least the literature is trending, definitely towards more, and more data and more, and more exploration into a number of diseases that may have mendelian inheritance pattern but may also have a significant component that's polygenic, particularly like you were saying in those individuals that present at the extremes of severity. So I think it's certainly where we're heading.                                 Is there anything else that either of you would like to share about the study that you feel be important? Guillaume:          I think we've covered a lot of ground here, but perhaps the one thing is just to reiterate that this is a proof of concept, but I really think that the act of polygenic risk score will continue to improve for quite a while, and as it improves, it will only get better. So we can only move forward with this in terms of the accuracy of the prediction, and I think that that's a great thing and hopefully with this we'll be able to better predict risk. And the other thing as well is that, I would say that at this point we can identify people at risk. And I think it's great because it provides answers, we can target known risk factors.                                 But I think a big part that's still open is, can we use this risk to derive like more individualized treatment, or to actually choose what should be the best way to prevent events in these individuals. And again, I don't think we're there yet but this is something that I think it's worthwhile investigating in the future and maybe trying to dissect this polygenic risk and to see maybe it falls in one or two categories or maybe it's a global risk, and these are all open questions that I think are important, but that are still very much of a mystery right now. Andrew:              Sebastian? Sebastien:           I think we've covered a lot of ground like you said and I don't have too much to add. Otherwise, I think we'll see a lot of these polygenic risk scores in the future and for risk improvement even to understand better the physiology of disease. These are very important concepts. Guillaume:          And I think you know the common approach of physiology is good because these gene scores they don't seem to be associated with classical risk factor. In our study, rather weak association with blood pressure and families history. Now, family history is kind of logical. Blood pressure suggests that perhaps there's an overlap between the two pathways, but clearly adjusting for blood pressure like that only slightly attenuated the predictiveness.                                 So basically what this is telling us is that this polygenic risk score seems to be acting through pathways that we don't know of, that we're not measuring clinically, and I think that’s a big part of the future would be to say, 'well, what are these pathways, and can we actually assess them? Are there other cholesterols out there?' Cholesterol is great because it's causal, we've got synthetic pharmachemicals, you've got tools to decrease it, and we've got fantastic evidence that decreasing cholesterol decrease risk. Is it possible that there's other pathways that are there and that we could do to sign, and I think all of this gives us great clues that this might be so.                                 I think as happens quite often in science, we start with an hypothesis and we try to address it the best we can, and at the end of the day, here I guess we've been lucky because it kind of panned out, but it also opens so many more questions about; So what are these other pathways that these genetic risk scores are capturing that we're not capturing clinically right now. And how could this lead to better treatment, and how to implement this and everything, and I think this is really what's so exciting about doing research, and as far as I'm concerned, doing research that has an impact on people's lives and trying to improve people and provide answers to people. Andrew:              Sounds like a great summary of the rationale for doing this. Thank you very much for joining me and for sharing your work. Guillaume:          My pleasure. Sebastien:           Thanks.   Jane Ferguson:                 Thanks for listening to "Getting Personal: Omics of the Heart." You can subscribe on iTunes to get each new episode delivered straight to you. And we'll be back with more next month.