Podcasts about prehypertension

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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.  

Dr. Carolyn Lam:               Welcome to Circulation on the Run, your weekly podcast summary and backstage pass to the journal and its editors. I'm Dr. Carolyn Lam, Associate Editor from the National Heart Center and Duke National University of Singapore. Our featured discussion today centers on new data from the Framingham Heart Study that addresses the question of the prognosis of pre-hypertension among individuals who never progressed to hypertension as well as the role of early versus late onset pre-hypertension in this context. Well, more soon, right after your summary of this week's journal.                                                 The first original paper provides mechanistic insights on the relationship between low and oscillatory wall shear stress, together known as disturbed flow, and atherosclerotic arterial remodeling and stiffness. Co-first authors doctors Kim and Pokutta-Paskaleva, co-corresponding authors Dr. Brewster and Jo from Georgia Institute of Technology in Emory University in Atlanta, Georgia used a novel mirroring model of disturbed blood flow to stimulate arterial stiffening through collagen deposition in young mice. They discovered a critical role for Thrombospondin 1, or TSP1 in activating TGF beta and stimulating arterial stiffening, all of which was significantly attenuated in the TSP1 knockout animal.                                                 Blockade of TSP1 activation of TGF beta decreased the up regulation of pro-fibrotic genes that contributed to arterial stiffening. Furthermore, they show that TSP1 localized to regions of disturbed flow in arteries from patients with peripheral artery disease and these arteries had similar increases in collagen gene expression. Thus, this work links TSP1 up regulation to arterial stiffening and identifies TSP1 as an important promoter of pathologic arterial remodeling in peripheral artery disease.                                                 The next study provides international insights on the degree to which secondary prevention treatment goals are achieved in clinical practice among patients with diabetes and cardiovascular disease. First and corresponding author, Dr. Pagidipati from Duke Clinical Research Institute at Duke University School of Medicine in Durham, North Carolina, looked at 13,616 patients from 38 countries with diabetes and cardiovascular disease in the TECOS trial. They found that only 30 percent of patients met all 5 secondary parameters of aspirin use, lipid control, blood pressure control, angiotensin-converting enzyme-inhibitor, or ARBUs, and non-smoking status.                                                 Only 58 percent of individuals with diabetes and cardiovascular disease attained blood pressure control. Furthermore, the degree to which secondary prevention goals were met in this trial varied by the world region and country. In summary, patients with diabetes and cardiovascular disease are still being undertreated globally with respect to secondary prevention, and especially with regard to blood pressure control. These gaps in care provide clear opportunities for improvement in this high risk population.                                                 The next study is the first to directly compare data from an electronic data research network to a large cardiovascular disease cohort. First author Dr. Ahmed, corresponding author Dr. Allen from Northwestern University in Chicago and colleagues sought to evaluate the degree of agreement of electronic data research networks compared with data collected by standardized research approaches in a cohort study. To achieve this goal, authors linked individual level data from the multi-ethnic study of atherosclerosis, or MESA community based cohort with Healthlink, a 2006 to 2012 database of electronic health records from 6 Chicago health systems.                                                 They identified areas of agreement and disagreement between blood pressure, cardiovascular risk factor diagnosis, and cardiovascular events between the two data sources. The correlation was low for systolic blood pressure, compared with MESA, Healthlink overestimated systolic blood pressure by 6.5mm mercury. Conversely, there was a high correlation between body mass index in MESA and Healthlink. Healthlink underestimated body mass index by 0.3 kilograms per meters square.                                                 Using ICD-9 codes and clinical data, the sensitivity and specificity for Healthlink queries for hypertension were 82.4 percent and 59.4 percent. For obesity these figures were 73 percent for sensitivity and 89.8 percent for specificity and for diabetes they were 79.8 percent for sensitivity and 93.3 percent for specificity.                                                 Finally compared with adjudicated events in MESA, the concordance rates for myocardial infarction, stroke, and heart failure were at 41.7 percent, 61.5 percent, and 62.5 percent, respectively. These findings therefore illustrate the limitations and strengths of electronic data repositories compared with information collected by traditional standardized epidemiologic approaches for the ascertainment of cardiovascular risk factors and events.                                                 The next paper helps physicians and patients to make an informed decision about whether or not to stop low dose aspirin use. First and corresponding author Dr. Sundstrom from Uppsala University in Sweden and colleagues investigated whether long term low dose aspirin discontinuation increased the risk of cardiovascular events in a cohort study of more than 600,000 users of low dose aspirin for primary or secondary prevention in the Swedish prescription register between 2005 and 2009.                                                 They found that patients who discontinued aspirin had a 37 percent higher rate of cardiovascular events than those who continued, corresponding to an additional cardiovascular event observed per year in one out of every 74 patients who discontinued aspirin. The risk increased shortly after discontinuation and did not appear to diminish over time. Thus, in long term users, discontinuation of low dose aspirin in the absence of major surgery or bleeding seemed to be associated with a more than 30 percent increased risk of cardiovascular events, thus adherence to low dose aspirin treatment in the absence of major surgery or bleeding may be an important treatment goal.                                                 The final study raises the possibility of using Histone Methyltransferase Inhibitors for the treatment of heart failure. Dr. Papait from Humanitas Clinical and Research Center in Italy and colleagues focused on G9A, a histone methyltransferase that defines a repressive epigenetic signature. Using normal and stressed cardiomyocytes from a conditional cardiac specific G9A knockout mouse, and a specific G9A inhibitor, they showed that the histone methyltransferase G9A was important in defining the epigenetic landscape that maintained the transcription program of the cardiomyocyte. It was also important for the regulation of gene expression reprogramming during cardiac hypertrophy.                                                 Furthermore, impaired G9A function promoted cardiac dysfunction. Thus, these findings suggest that G9A may represent a therapeutic target for early stages of cardiac hypertrophy.                                                 That wraps it up for your summaries, now for our feature discussion.                                                 For today's feature discussion, we're talking about the very important topic of the prognosis of prehypertension without progression to hypertension. Now, we've always known that mild blood pressure elevations that we call prehypertension are associated with cardiovascular risk. However, this risk could be attributable to the fact that these patients with prehypertension eventually progress to overt hypertension. But, what happens to the patients with prehypertension who do not progress to hypertension, and what is the role of early versus late onset prehypertension?                                                 Well, we have some answers today and I am so pleased to have the first and corresponding author with us, Dr.  Teemu Niiranen, from Boston University's Framingham Heart Study. Welcome, Teemu. Dr. Teemu Niiranen:       Thank you very much, great to be here. Dr. Carolyn Lam:               And to help us along in this discussion, we have a familiar voice. Dr. Wanpen Vongpatanasin, associate editor from UT Southwestern. Welcome back, Wanpen. Dr. Wanpen Vongpatanasin:       Thank you Carolyn. Happy to be here. Dr. Carolyn Lam:               Teemu, you know, I sort of set the background that you so nicely articulated in this research letter, but could you tell us a little bit more of what you were looking at, how you did it, and what you found? Dr. Teemu Niiranaen:     My boss, Dr. Vasan, was also a coauthor in this paper, he already showed some 15 years ago that prehypertension carries greater cardiovascular risk than perfectly normal blood pressure. However, it's pretty much unclear what happens to people who are prehypertension but never go on to develop hypertension because even the name suggests that if you have prehypertension you will get hypertension. We also looked at what effect does the age of developing prehypertension and hypertension have in this context.                                                 We used a case cohort setting in the Framingham Heart Study in the way that we only looked at 5 1/2 thousand decedents. These were people who had already passed away. Then we categorized those decedents into 5 categories, people who never got prehypertension or hypertension, people who developed prehypertension late in life, who never developed hypertension, and people who developed early onset prehypertension but never developed hypertension, and then people who went on to develop late or early onset hypertension. We used a cutoff of 55 years as the definition of early onset versus late onset.                                                 Then, in a case cohort setting, we estimated case versus controls, adjusted case versus control odds ratios, for the 4 prehypertension/hypertension categories versus those who died without ever developing prehypertension. Dr. Carolyn Lam:               Teemu, could I just stop you here before you share the intriguing results. I just wanted to remark that it's so amazing how the Framingham Heart Study really enables analysis like this, simply because of the long follow up and just the great detail and the standardization of blood pressure measurements and so on. I mean, as I said, I worked at the Framingham Heart Center, and we were trained to do this in a standardized fashion.                                                 Define prehypertension and hypertension, just in case, and then please tell us your results. Dr. Teemu Niiranaen:     Prehypertension was 120 to 135 systolic blood pressure, and a diastolic blood pressure of 80 to 89 millimeters mercury, and then hypertension was 140 over 90 millimeters mercury, or antihypertensive medication, and yes, your correct that the Framingham Heart Study provides a very unique setting. Especially for defining early versus late onset hypertension because we can define the age of hypertension or prehypertension or prehypertension onset objectively because these people have been followed up, they have attended so many exams, especially the original cohorts.                                                 But, to the results, so we observed that basically people who develop prehypertension, either early and especially late in life, but did not ever develop hypertension, their risk, or odds of dying of cardiovascular disease versus non-cardiovascular disease was pretty much similar to those who never develop prehypertension or hypertension, while conversely the people who went on to develop either late or especially early onset hypertension, or developed early onset hypertension they had considerably greater risk of cardiovascular death versus those who developed either prehypertension or hypertension. That's our main result. I won't go into conclusions yet. Dr. Carolyn Lam:               Okay, but maybe at this point, I could ask Wanpen to share some thoughts. I mean, this is very striking findings. Curious what you think the clinical implications were, and especially as we discussed among the editors. Dr. Wanpen Vongpatanasin:       It is very important study that, as Teemu outlined it, to look at the fate of people with prehypertension and I think that's the first time we had this kind of data to show whether the earlier versus late prehypertension and even hypertension itself. I don't think people have looked at in the large number in terms of outcome people who have early versus late onset hypertension. I found the result to be fascinating. Dr. Carolyn Lam:               Yeah, what does this mean though when we see a patient with this sort of borderline hypertension, you know, falling in the prehypertension range. We don't know whether they're going to develop hypertension. What do you think the clinical implications are? Teemu? Dr. Teemu Niiranaen:     Unfortunately a lot of the people who develop prehypertension as the name suggests they go on to develop hypertension, but there is still a considerably great part that never develop hypertension, and our study shows basically that if you are able as a doctor or a patient to prevent progression to hypertension you are much better off and this really hasn't been previously shown, so it just should motivate patients and also doctors to strive to, if they see a prehypertensive individual, try to through lifestyle and other interventions try to prevent the progression to hypertension. Dr. Carolyn Lam:               Yeah, I think that was one of the take home messages for sure. Were there any other plans for future work you think that needs to be done? Dr. Teemu Niiranaen:     There's the everlasting problem with observational studies, so definitely it would be great if our results could be taken into clinical trials or anything to test whether interventions, A, that preventing the progression from prehypertension to hypertension could then impact cardiovascular outcomes. Dr. Carolyn Lam:               Indeed, and if I may comment, I've always wondered about ethnic differences when it comes to this. The one thing that Framingham, you know, it's difficult to see from there, is what happens in other ethnicities other than white ethnicities, isn't it? Still, very striking findings. Wanpen did you have any other comments or questions from Teemu? Dr. Wanpen Vongpatanasin:       Well, I think that one thing also that's interesting to me is even the people who had early onset prehypertension, although the number of CHD deaths were not significant, but the odds still 28 percent higher than the control that will never have prehypertension so, I think that that the signal is there but perhaps because the number of people who had prehypertension but never really progress to prehypertension is relatively small. It could be underpowered to see the significance and I think that from this study, it tells me that the exposure to blood pressure to our life, I think is the blood pressure lowered on the cardiovascular system, I think that's the one that really determine the cardiovascular outcome the most. I think that we should not discount that this is not a truly benign phenomenon, I think hopefully they'll be some more data from the Framingham group or other group.                                                 Also, I think that this study also very important to show that early onset hypertension actually have the worst prognosis, and often time when people come to see a doctor when they're 30 and 40 years old, they don't really want to take medicine, and the physician often time are reluctant to prescribe the drug, and I think that this study say that we probably need to be a little bit more serious about it, because they actually have the most cardiovascular events. Dr. Carolyn Lam:               What excellent points, and you know what? At this point I just want to highlight that beautiful figure that you have in your research letter, Teemu. I think it says it all. It highlights that point estimate for the prehypertension groups is not exactly 1. If anything, it is above 1, right? For the odds of poor outcomes, so I do take Wanpen's point as well. Beautiful figures, and I also actually want to use that to ask you a different question Teemu. You have 1 figure, because this is a research letter that only allows 1 figure and 800 words, and you've put so much important information into that space. I'd love for you to share that experience with our listeners too, of a research letter versus a full paper. Why did you choose to submit yours as a research letter, and how was that? Dr. Teemu Niiranaen:     One of the important take home messages from this was the differences between early onset versus late onset hypertension that we'd been also recently publishing on, so we wanted to delve more in depth on this prognosis of prehypertension versus hypertension so we don't have to be repetitive too much. We decided to focus on this very small topic most intensively, therefore we decided that maybe a research letter would be the most effective way so we could communicate all the really novel stuff that we have in just one figure. Well, it has 3 panels, but it still counts as 1 figure.                                                 I just wanted to point out that maybe the early onset prehypertension, yeah the confidence intervals are somewhat wide, but the panels sees for coronary heart disease versus non-cardiovascular disease deaths, so that's maybe a bit more underpowered than the back panel B, so the CHD deaths are part of the CBD deaths, so with CBD deaths, the early onset prehypertension, the odds ration was 1.09, but still of course the confidence intervals reach up to 1.49. Just to clarify the difference between panel B and panel C, so B's better powered. Dr. Carolyn Lam:               It's a very nice figure, and indeed, I think it works very, very well as a research letter, and I think the fact that we're discussing it right now shows that length doesn't dictate importance. Wanpen you had a few comments about that. What do you think of a research letter format? Dr. Wanpen Vongpatanasin:       Yes, I think this research letter is a really important part of articles in Circulation. I think that all the others should be aware that we're trying to enter at submission if it's suitable, just like this one. It actually show up in the pub med exactly like the full article and gets cited as much and sometimes much more than a regular article because it capture the essence of one more focused problem and the figures and table allow to show only one or two at a time, so they really capture the essence or the guts of the article and the reader can go through that quickly and grasp the concept and learn within flipping through a few pages.                                                 I think we should have many more interesting research letter like this. Dr. Carolyn Lam:               Congratulations again Teemu for a beautiful paper, a very important one. Thank you Wanpen for shepherding this one.                                                 And thank you listeners for joining us today. Don't forget to tune in again next week.  

This week, how to stop deadly diseases before they start