Podcasts about polygenic

Program notes:0:40 Polygenic risk score for prostate cancer1:40 90th percentile or higher2:40 Genetic risk for cancer3:41 Avoid false positives4:00 Cervical artery dissection and subsequent stroke risk5:00 High in older people, Black and Hispanic people6:00 Nonspecific symptoms may predict7:00 Preventing clotting in patients with cancer8:00 Standard dose followed by half dose8:44 USPSTF on supporting breastfeeding9:45 Support systems not that good10:55 What is the best strategy to support?12:14 End

Darshan H. Brahmbhatt, Podcast Editor of JACC: Advances, discusses a recently published original research paper on Polygenic Risk Scores in Myocardial Injury After Noncardiac Surgery: A VISION Substudy.

Today's guest is Dan Elton, a Staff Scientist at the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH). Dan returns to the program to explore how AI is advancing genetic research, from protein engineering to gene editing and risk prediction. One of the most significant breakthroughs in this space is AlphaFold, DeepMind's AI model that predicts protein structures with unprecedented accuracy. While it does not analyze genetic sequences directly, its ability to model protein folding is transforming drug development and protein engineering. Dan also discusses the potential for AI to improve polygenic risk prediction, where machine learning models are being applied to assess disease risk based on genetic markers. If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Send us a textDr. Matt Burgess interviews genetic counsellor and researcher Dr. Sibel Saya about integrating genetic testing into primary healthcare settings, focusing on polygenic risk scores as a tool for personalizing cancer screening.• Genetic counselling principles applied in primary care settings rather than just specialist clinics• Polygenic risk scores differ from traditional genetic tests by analyzing hundreds of common variants with small individual effects• Australia and New Zealand have the highest bowel cancer rates globally, making early detection tools particularly important• Tools like CRISP help assess individual bowel cancer risk using lifestyle factors combined with genetic information• Cultural differences must be considered when implementing genetic testing in diverse communities• GPs see genetic risk assessment as within their scope despite time constraints• Risk information alone doesn't change behaviour – it's the opportunity to discuss screening that matters• Implementation research happening alongside efficacy trials to speed translation into practice• Stratified screening approaches could be widely available within 5-10 yearsIf you'd like to learn more about polygenic risk scores or risk-stratified cancer screening, visit our website or subscribe to Demystifying Genetics for future episodes on these topics.Support the showDemystifying Genetics is sponsored by TrakGenehttps://www.trakgene.com/

This week on Health Matters, as we continue to observe Heart Month, we will explore the role that genetics play in heart health.Understanding your family history of cardiovascular health is essential. In fact, about 30% of heart disease can be linked to family history. We speak with Dr. Jessica Hennessy, a clinical cardiac electrophysiologist and cardiogenetics expert at NewYork-Presbyterian and Columbia to help break down which heart conditions and risk factors may be inherited. She provides valuable insight on effectively managing heart health, including the importance of lifestyle modifications in preventing heart disease, including for individuals with a genetic predisposition. She also explains who should get genetic testing and what that process looks like.___ Dr. Jessica Hennessey specializes in Cardiac Electrophysiology, with a special focus on Sports & Exercise Cardiology. She practices primarily in New York, NY, and is affiliated with NewYork-Presbyterian/Columbia University Irving Medical Center. Dr. Hennessey graduated from Duke University School of Medicine in 2014, and completed her training at Massachusetts General Hospital, NewYork-Presbyterian/Columbia University Irving Medical Center and NewYork-Presbyterian/Columbia University Irving Medical Center. She is board certified in Internal Medicine, Cardiovascular Disease and Cardiac Electrophysiology. ___ Health Matters is your weekly dose of health and wellness information, from the leading experts. Join host Courtney Allison to get news you can use in your own life. New episodes drop each Wednesday. If you are looking for practical health tips and trustworthy information from world-class doctors and medical experts you will enjoy listening to Health Matters. Health Matters was created to share stories of science, care, and wellness that are happening every day at NewYork-Presbyterian, one of the nation's most comprehensive, integrated academic healthcare systems. In keeping with NewYork-Presbyterian's long legacy of medical breakthroughs and innovation, Health Matters features the latest news, insights, and health tips from our trusted experts; inspiring first-hand accounts from patients and caregivers; and updates on the latest research and innovations in patient care, all in collaboration with our renowned medical schools, Columbia and Weill Cornell Medicine. To learn more visit: https://healthmatters.nyp.org

Imagine knowing your risk for disease long before symptoms appear. With early detection and targeted interventions, this knowledge could transform how complex healthcare challenges are addressed. Researchers are now leveraging genetic data to enhance disease risk prediction through an innovative tool known as a polygenic risk score. The episode features Victor Ortega, M.D., Ph.D., associate director of the Mayo Clinic Center for Individualized Medicine and Louise Wain, Ph.D., professor of respiratory research, University of Leicester. 

Editor's Summary by Kirsten Bibbins-Domingo, PhD, MD, MAS, Editor in Chief, and Christopher C. Muth, MD, Deputy Editor of JAMA, the Journal of the American Medical Association, for articles published from January 18-24, 2025.

At-home DNA tests are everywhere, but what can your DNA tell you about your risk for developing serious diseases like cancer? Returning guest Dr. Joel Evans from Genetype and The Center for Functional Medicine explains how a polygenic risk score may help optimize your future. During this episode you'll learn about: This week's guest: Dr. Joel Evans, OB-GYN and functional medicine doctor [0:55] How to use polygenic risk scores, a powerful disease prediction tool [2:45] What are SNPs (single nucleotide polymorphisms)? [5:57] Breakthrough genome-wide association studies (GWAS) [7:15] From GWAS to PRS: Polygenic risk scores show genetic predisposition to disease [10:55] How polygenic risk scores compare to popular DNA test kits [13:14] Who may benefit from getting their polygenic risk score measured? [17:22] Questions from the community If I score high on polygenic risk for something like cancer, does that mean I will get cancer? [22:22] How much do polygenic risk tests cost? Are they worth the cost? [26:49] Are polygenic risk scores the same as ancestry DNA tests? [28:55] How do polygenic risk scores work? Are they secure? Do I need to worry about privacy? [30:02] How can I use my polygenic risk score to optimize my health? [33:21] Resources to topics mentioned in this episode: Learn more about Dr. Joel Evan's work on polygenic risk scores at Genetype and The Center For Functional Medicine Discover more ways to test your health at home with Thorne Assess Your Biological Age With Thorne's Biological Age Health Panel How It Works: Health Panel Blood Draw What Can A Microbiome Test Tell You That A Genetic Test Can't? How Does Thorne's Biological Age Panel Work? Products mentioned in this episode: Biological Age Health Panel, Essential Health Panel, Advanced Health Panel Subscribe to More Content Subscribe to the show wherever you listen to podcasts so you never miss an episode. You can also learn more about the topics in the episode by checking out the latest news, videos, and stories on Thorne's Take 5 Daily blog.

Moderator: James P. Rathmell, M.D. Participants: Nicholas Joseph Douville, M.D., Ph.D. and Vesela P. Kovacheva, M.D., Ph.D. Articles Discussed: Polygenic Score for the Prediction of Postoperative Nausea and Vomiting: A Retrospective Derivation and Validation Cohort Study Polygenic Risk Scores: Coming to Your Operating Room? Transcript

Editor's Summary by Kirsten Bibbins-Domingo, PhD, MD, MAS, Editor in Chief, and Preeti Malani, MD, MSJ, Deputy Editor of JAMA, the Journal of the American Medical Association, for articles published from November 16-22, 2024.

Dr. Jim Keany, Co-Director of the Emergency Room at Mission Hospital in Mission Viejo, joins The Bill Handel Show for 'Medical News'! Dr. Keany talks with Bill about sitting being the new smoking, 1 in 3 surgery patients suffer complications, and polygenic rosk scores.

In this episode, Dr. Valentin Fuster discusses a groundbreaking study examining how both social determinants of health and polygenic risk scores independently contribute to the risk of coronary heart disease (CHD). The research highlights how factors like income, education, and food insecurity are linked to higher CHD risk, particularly among Black and Hispanic populations, while emphasizing the need to integrate both genetic and environmental factors for more accurate disease prevention models.

In this explainer episode, we've asked Arina Puzriakova, Scientific Curator at Genomics England, to explain what a polygenic disorder is. You can also find a series of short videos explaining some of the common terms you might encounter about genomics on our YouTube channel. If you've got any questions, or have any other topics you'd like us to explain, feel free to contact us on info@genomicsengland.co.uk. You can read the transcript below or download it here: https://www.genomicsengland.co.uk/assets/documents/Podcast-transcripts/What-is-a-polygenic-disorder.docx Florence: What is a polygenic disorder? I'm joined by Arina Puzriakova, Scientific Curator for Genomics England to find out more. So, Arina, first things first. How can our genes affect our health?   Arina: So, genes are short sections of DNA that contain information that the cells in your body need in order to make proteins. Each gene carries the instructions for making a specific protein, and each protein performs a different task that allows the body to develop and function properly, depending on the genes that we inherit from our parents. Also determines our unique physical features such as our eye colour, hair colour, and height.  When a gene contains a change that disrupts the gene's instructions, also known as a gene variant, in some cases, this can lead to the production of a defective protein or prevents a protein from being made altogether. A missing protein or one that is not working properly can have a knock-on effect on how the body functions and this can result in health issues or the development of a genetic disorder.  Florence: So then how can a gene variant lead to a disorder?   Arina: So the genetics of each disorder are unique. In some cases, a change in a single gene is enough to cause a genetic disorder, and these are known as monogenic disorders. These conditions often occur in childhood and tend to cause severe illness. individually, they are more rare affecting a smaller number of people in the population, and usually they run in families as parents pass the damaging variance onto their children.  But these changes can also happen spontaneously without a known cause. An example of a monogenic disorder, which some may be familiar with, is cystic fibrosis. Cystic fibrosis affects one in every 2,500 babies born in the UK, meaning that there's about 11,000 people living with cystic fibrosis.  Florence: So, we've just talked through monogenic disorders. What do we mean by polygenic disorder?   Arina: So polygenic disorders are on the other end of the spectrum for disorders.  They are caused by the combined effects of multiple different genes. Individually, each gene has a very small effect on causing the disease, but many variations in different genes can act together to have a great impact on individual's susceptibility to that condition. Environmental and behavioural factors such as your lifestyle and diet also often have an effect.  Polygenic disorders are much more common, typically affecting millions of people in the population, and they're usually diagnosed in adulthood.   Florence: Could you give me an example of a polygenic disorder?   Arina: A common example of a polygenic disorder is type two diabetes. It affects almost 4 million people in the UK.  So this means that we know there are many genetic variants that could have made these individuals more susceptible to diabetes, but there are also other factors such as age or being overweight that could have increased their risk.  Florence: Are there specific challenges when it comes to diagnosing or treating polygenic disorders?  Arina: So, if I start with monogenic disorders, these are much easier to test for because we simply need to look for the presence or the absence of a faulty gene in order to determine whether someone is a carrier of a genetic disorder. On the other hand, testing for a polygenic disorder is a lot more complex as they are influenced by the combined effects of many genes.  Meaning there is no single genetic test or treatment that will work for all patients with the same condition. We need large and diverse groups of patients to study in order to accurately determine which genes are important and which ones are not.  And this can be challenging to obtain. Also accurately measuring and comparing lifetime environmental factors and exposures further complicates the assessment.  Another challenge with polygenic disorders is that even though they can cluster in families, the inheritance is not as clear cut or predictable as it is with monogenic disorders. Carrying a specific combination of genetic variants that are already known to be associated with polygenic disorder does not necessarily mean that you will definitely develop that disorder.  However, this information can be used to calculate something known as a polygenic risk score, and this provides an estimate for the risk of developing polygenic disease at some point in life based on individual's unique genetic profile.  Florence: And why can knowing apologetic risk score be helpful?  Arina: So, by being informed about the probability of developing a particular polygenic disease, an individual can make behaviour or lifestyles changes that could help reduce their risk. To go back to the previous example, somebody who is more likely to develop type two diabetes based on their genetic makeup can do things like maintain a healthy weight. And eat a healthy diet to help reduce their risk of developing type two diabetes in the future.  Florence: That was Arina Puzriakova explaining what we mean by polygenic disorder. If you'd like to hear more explainer episodes like this, you can find them on our website at www.genomicsengland.co.uk. Thank you for listening. 

In this episode, Dr. Sonia Shah explores a study from Australian researchers that evaluates the effectiveness of a polygenic risk score in predicting heart failure among cancer survivors. While the score enhanced prediction compared to age and sex alone, it did not significantly outperform existing modifiable risk factors, highlighting the need for more comprehensive models that account for unique risks faced by cancer patients.

Tom Marwick, MBBS, PhD, MPH and Sivatharshini Ramalingam, MD discuss discuss the study design and findings, as well as the future use and potential development of cardio-oncology specific risk scores for prediction of heart failure in cancer survivors.

Professor Sir Peter Donnelly, Founder and CEO of Genomics plc, aims to use cutting-edge polygenic risk scores to identify inherited DNA mutations and genetic predispositions that could lead to common diseases. In partnership with the MassMutual life insurance company, Genomics offers a voluntary test that provides personalized risk measures and advice about conversations with clinicians. If the policyholder stays healthy longer, the insurance company will get paid more premiums before paying out to survivors. Win-win all the way around. Peter explains, "Until a few years ago, if I had the entire DNA sequence from a 40-year-old who's currently healthy, I'd have learned something interesting and medically actionable in maybe 1% or 2% of cases. That's because genetics has played into medicine through diseases where there's a single change in our DNA, called a mutation, which often stops a crucial gene from working. Think cystic fibrosis or Huntington's disease. Those are conditions that are individually serious. They're rare individually, thankfully, and actually, they're collectively rare. And so until a few years ago, and now still very much the case, genetic testing was about looking for those needles in haystacks, those one or two single places that caused a problem." "Now, if I have genetic information from a 40-year-old who's healthy, I learn something medically useful in about 70% of cases. So, that massive change from 2% to 70% is because we can now measure the genetic component of risk for all of the common diseases, as I said, for heart disease, diabetes, breast cancer, or prostate cancer." "What we've learned is that for any one of those diseases, if we take heart disease as an example, there's not one gene that matters for heart disease. There aren't two genes. There are a million or more places in our DNA individual positions in our DNA, which affect someone's risk of heart disease. And we've now got large enough data sets and clever enough algorithms to measure those places and combine the information to get an overall summary for someone of their genetic predisposition to heart disease."  #Genomics #Genetics #PRS #PolygenicRiskScores #DrugDiscovery #Biopharma genomicsplc.com Download the transcript here

Professor Sir Peter Donnelly, Founder and CEO of Genomics plc, aims to use cutting-edge polygenic risk scores to identify inherited DNA mutations and genetic predispositions that could lead to common diseases. In partnership with the MassMutual life insurance company, Genomics offers a voluntary test that provides personalized risk measures and advice about conversations with clinicians. If the policyholder stays healthy longer, the insurance company will get paid more premiums before paying out to survivors. Win-win all the way around. Peter explains, "Until a few years ago, if I had the entire DNA sequence from a 40-year-old who's currently healthy, I'd have learned something interesting and medically actionable in maybe 1% or 2% of cases. That's because genetics has played into medicine through diseases where there's a single change in our DNA, called a mutation, which often stops a crucial gene from working. Think cystic fibrosis or Huntington's disease. Those are conditions that are individually serious. They're rare individually, thankfully, and actually, they're collectively rare. And so until a few years ago, and now still very much the case, genetic testing was about looking for those needles in haystacks, those one or two single places that caused a problem." "Now, if I have genetic information from a 40-year-old who's healthy, I learn something medically useful in about 70% of cases. So, that massive change from 2% to 70% is because we can now measure the genetic component of risk for all of the common diseases, as I said, for heart disease, diabetes, breast cancer, or prostate cancer." "What we've learned is that for any one of those diseases, if we take heart disease as an example, there's not one gene that matters for heart disease. There aren't two genes. There are a million or more places in our DNA individual positions in our DNA, which affect someone's risk of heart disease. And we've now got large enough data sets and clever enough algorithms to measure those places and combine the information to get an overall summary for someone of their genetic predisposition to heart disease."  #Genomics #Genetics #PRS #PolygenicRiskScores #DrugDiscovery #Biopharma genomicsplc.com Listen to the podcast here

Author Callie Burt discusses their article, "Polygenic Indices (aka Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation," published in the August 2024 issue of Sociological Methodology.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Superbabies: Putting The Pieces Together, published by sarahconstantin on July 12, 2024 on LessWrong. This post was inspired by some talks at the recent LessOnline conference including one by LessWrong user "Gene Smith". Let's say you want to have a "designer baby". Genetically extraordinary in some way - super athletic, super beautiful, whatever. 6'5", blue eyes, with a trust fund. Ethics aside[1], what would be necessary to actually do this? Fundamentally, any kind of "superbaby" or "designer baby" project depends on two steps: 1.) figure out what genes you ideally want; 2.) create an embryo with those genes. It's already standard to do a very simple version of this two-step process. In the typical course of in-vitro fertilization (IVF), embryos are usually screened for chromosomal abnormalities that would cause disabilities like Down Syndrome, and only the "healthy" embryos are implanted. But most (partially) heritable traits and disease risks are not as easy to predict. Polygenic Scores If what you care about is something like "low cancer risk" or "exceptional athletic ability", it won't be down to a single chromosomal abnormality or a variant in a single gene. Instead, there's typically a statistical relationship where many genes are separately associated with increased or decreased expected value for the trait. This statistical relationship can be written as a polygenic score - given an individual's genome, it'll crunch the numbers and spit out an expected score. That could be a disease risk probability, or it could be an expected value for a trait like "height" or "neuroticism." Polygenic scores are never perfect - some people will be taller than the score's prediction, some shorter - but for a lot of traits they're undeniably meaningful, i.e. there will be a much greater-than-chance correlation between the polygenic score and the true trait measurement. Where do polygenic scores come from? Typically, from genome-wide association studies, or GWAS. These collect a lot of people's genomes (the largest ones can have hundreds of thousands of subjects) and personal data potentially including disease diagnoses, height and weight, psychometric test results, etc. And then they basically run multivariate correlations. A polygenic score is a (usually regularized) multivariate regression best-fit model of the trait as a function of the genome. A polygenic score can give you a rank ordering of genomes, from "best" to "worst" predicted score; it can also give you a "wish list" of gene variants predicted to give a very high combined score. Ideally, "use a polygenic score to pick or generate very high-scoring embryos" would result in babies that have the desired traits to an extraordinary degree. In reality, this depends on how "good" the polygenic scores are - to what extent they're based on causal vs. confounded effects, how much of observed variance they explain, and so on. Reasonable experts seem to disagree on this.[2] I'm a little out of my depth when it comes to assessing the statistical methodology of GWAS studies, so I'm interested in another question - even assuming you have polygenic score you trust, what do you do next? How do you get a high-scoring baby out of it? Massively Multiplexed, Body-Wide Gene Editing? Not So Much, Yet. "Get an IVF embryo and gene-edit it to have the desired genes" (again, ethics and legality aside)[3] is a lot harder than it sounds. First of all, we don't currently know how to make gene edits simultaneously and abundantly in every tissue of the body. Recently approved gene-editing therapies like Casgevy, which treats sickle-cell disease, are operating on easy mode. Sickle-cell disease is a blood disorder; the patient doesn't have enough healthy blood cells, so the therapy consists of an injection of the patient's own blood cells which h...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Superbabies: Putting The Pieces Together, published by sarahconstantin on July 12, 2024 on LessWrong. This post was inspired by some talks at the recent LessOnline conference including one by LessWrong user "Gene Smith". Let's say you want to have a "designer baby". Genetically extraordinary in some way - super athletic, super beautiful, whatever. 6'5", blue eyes, with a trust fund. Ethics aside[1], what would be necessary to actually do this? Fundamentally, any kind of "superbaby" or "designer baby" project depends on two steps: 1.) figure out what genes you ideally want; 2.) create an embryo with those genes. It's already standard to do a very simple version of this two-step process. In the typical course of in-vitro fertilization (IVF), embryos are usually screened for chromosomal abnormalities that would cause disabilities like Down Syndrome, and only the "healthy" embryos are implanted. But most (partially) heritable traits and disease risks are not as easy to predict. Polygenic Scores If what you care about is something like "low cancer risk" or "exceptional athletic ability", it won't be down to a single chromosomal abnormality or a variant in a single gene. Instead, there's typically a statistical relationship where many genes are separately associated with increased or decreased expected value for the trait. This statistical relationship can be written as a polygenic score - given an individual's genome, it'll crunch the numbers and spit out an expected score. That could be a disease risk probability, or it could be an expected value for a trait like "height" or "neuroticism." Polygenic scores are never perfect - some people will be taller than the score's prediction, some shorter - but for a lot of traits they're undeniably meaningful, i.e. there will be a much greater-than-chance correlation between the polygenic score and the true trait measurement. Where do polygenic scores come from? Typically, from genome-wide association studies, or GWAS. These collect a lot of people's genomes (the largest ones can have hundreds of thousands of subjects) and personal data potentially including disease diagnoses, height and weight, psychometric test results, etc. And then they basically run multivariate correlations. A polygenic score is a (usually regularized) multivariate regression best-fit model of the trait as a function of the genome. A polygenic score can give you a rank ordering of genomes, from "best" to "worst" predicted score; it can also give you a "wish list" of gene variants predicted to give a very high combined score. Ideally, "use a polygenic score to pick or generate very high-scoring embryos" would result in babies that have the desired traits to an extraordinary degree. In reality, this depends on how "good" the polygenic scores are - to what extent they're based on causal vs. confounded effects, how much of observed variance they explain, and so on. Reasonable experts seem to disagree on this.[2] I'm a little out of my depth when it comes to assessing the statistical methodology of GWAS studies, so I'm interested in another question - even assuming you have polygenic score you trust, what do you do next? How do you get a high-scoring baby out of it? Massively Multiplexed, Body-Wide Gene Editing? Not So Much, Yet. "Get an IVF embryo and gene-edit it to have the desired genes" (again, ethics and legality aside)[3] is a lot harder than it sounds. First of all, we don't currently know how to make gene edits simultaneously and abundantly in every tissue of the body. Recently approved gene-editing therapies like Casgevy, which treats sickle-cell disease, are operating on easy mode. Sickle-cell disease is a blood disorder; the patient doesn't have enough healthy blood cells, so the therapy consists of an injection of the patient's own blood cells which h...

Dr. Lina Jonsson (Sahlgrenska Academy at University of Gothenburg, Sweden) joins AJP Audio to discuss the association of occupational dysfunction and hospital admissions with polygenic profiles in patients with bipolar disorder.  Afterwards, AJP Editor-in-Chief Dr. Ned Kalin discusses the rest of the July issue of AJP. 00:45     Jonsson interview 04:35     Occupational dysfunction and hospitalization in bipolar disorder 05:29     Crossover between groups in patients with schizophrenia spectrum disorder 06:37     Clinical implications for working with patients with bipolar disorder 07:46     Limitations 09:03     Future research 10:14     Kalin interview 10:31     Jonsson et al. 13:43     Baum et al. 15:00     Kang et al. 18:10     Rohde et al. 22:06     Ironside et al. 26:30     Chen et al. Transcript Be sure to let your colleagues know about the podcast, and please rate and review it on Apple Podcasts, Google Podcasts, Spotify, or wherever you listen to it. Subscribe to the podcast here. Listen to other podcasts produced by the American Psychiatric Association. Browse articles online. How authors may submit their work. Follow the journals of APA Publishing on Twitter. E-mail us at ajp@psych.org

This playlist features interviews recorded live by Oncology Data Advisor at the American Society of Clinical Oncology (ASCO) 2024 Annual Meeting in Chicago. Visit oncdata.com to learn more!

Contact the showIn this special episode, we hear from Professor Tim Frayling who was Andrew and Sian's first PhD student in 1995. He rapidly became the head of the analysis for the genetic susceptibility for Type 2 diabetes.  His leadership has made Exeter an international leader in polygenic trait genetics.

Polygenic risk scores (PRS), put simply, look at gene variants across the human genome in order to determine an individual's risk of getting a disease, from different types of cancer to type II diabetes. PRS could complement current risk prediction models and lead to a more accurate risk prediction. However, for PRS to become a useful clinical instrument, transparent ways to assess their performance and careful communication of disease risks to individuals are key. In episode 22 of We're doomed we're saved, Andreas Horchler and Louise von Stechow speak to two PRS researchers, who contributed to the international and interdisciplinary, EU-funded INTERVENE project. Brooke Wolford, a Postdoctoral Fellow in the HUNT Center for Molecular and Clinical Epidemiology at the Norwegian University of Science and Technology and Kristi Läll, a researcher in statistical genetics at Institute of Genomics, University of Tartu, share their expertise on PRSs and discuss the potential of PRSs in the clinic and pinpoint strategies for addressing biases in PRS. Learn more about IINTERVENE here: INTERVENE is coordinated by the Institute for Molecular Medicine Finland at the University of Helsinki. The project includes 17 research and other organizations from 10 countries. Learn more about INTERVENE here: https://www.interveneproject.eu/ You can read more about Brooke at https://bnwolford.github.io/ Also check out recent publications here: https://www.medrxiv.org/content/10.1101/2023.11.20.23298215v1 https://www.medrxiv.org/content/10.1101/2023.06.12.23291186v1 Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: Acton Crawford via Unsplash

In this episode of ReInvent Healthcare, we dive into the world of personalized genetics with Joe Cohen, the founder and CEO of SelfDecode. SelfDecode empowers clients to understand their unique DNA and unlock its potential for optimizing personalized health and wellness. Join us as we explore the exciting world of genetic testing, learn how SelfDecode can help you take control of your health, and discuss the future of personalized medicine.Key Points:The Importance of Genetic TestingGenetic testing holds immense promise for revolutionizing healthcare. A personalized approach to precision health that includes genetic insights,could transform medicine from a reactive system to a proactive one. With the right tools and knowledge, genetic testing has the potential to empower clients to take charge of their health, optimize their well-being, and pave the way for a future of preventive and personalized medicine.Methodology of Polygenic Risk Scoring in Understanding Health ConditionsMany diseases aren't caused by a single faulty gene, but rather a combination of smaller genetic variations. Polygenic risk scoring tackles this complexity by analyzing numerous genetic markers across your DNA. By considering these variations together, it creates a score that estimates your overall genetic susceptibility to a particular health condition. This approach provides a more nuanced picture than traditional genetic testing and can help identify clients at higher risk, allowing for earlier intervention, preventive measures, and personalized strategies.Analyzing Genes To Make Effective Health RecommendationsGenetic testing offers a wealth of information, and translating it into actionable health advice requires validation. Environmental factors, lifestyle choices, and even interactions between different genes can significantly influence how genetic codes play out. To make effective recommendations, we have SelfDecode to validate these genetic predictions. Important ReInvent Healthcare Links Sign up to access Dr. Ritamarie's FREE Guide to Using Genetic Testing to Optimize Patient Outcomes here.For our invaluable genetics charts and video trainings, check out our Nutrigenomics Bundle here.And to go even more in-depth on Functional Nutrigenomics in Clinical Practice we suggest the digital videos and materials form our 3-day 2023 event which you can access here. Access Additional Resources for Practitioners ready to improve clinical outcomes through our Nutritional Endocrinology Practitioner TrainingVisit the ReInvent Healthcare site to check out other podcast episodes and resources to support you in empowering your clients health recovery journeysJoe Cohen LinksVisit the SelfDecode website here. Subscribe to Joe Cohen's YouTube channel here.Follow Joe Cohen on

https://www.astralcodexten.com/p/who-does-polygenic-selection-help 

View the Show Notes For This EpisodeGet Free Weekly Health Tips from Dr. HymanSign Up for Dr. Hyman's Weekly Longevity JournalGet Ad-free Episodes & Dr. Hyman+ Audio ExclusivesDr. Sharon Hausman-Cohen is the Chief Medical Officer and co-founder of IntellxxDNA and has been in the field of integrative medicine for over 25 years. She is the co-author of many publications and a textbook chapter on using genomics to improve outcomes in cognitive decline and autism.This episode is brought to you by Rupa Health, Fatty15, BiOptimizers, and ARMRA.Streamline your lab orders with Rupa Health. Access more than 3,000 specialty lab tests and register for a FREE live demo at RupaHealth.com.Fatty15 contains pure, award-winning C15:0 in a bioavailable form. Get an exclusive 10% off a 90-day starter kit subscription. Just visit Fatty15.com and use code DRHYMAN10 to get started.Tackle an overlooked root cause of stress with Magnesium Breakthrough. Visit bioptimizers.com/hyman and use code HYMAN10 to save 10% and receive free gifts with your purchase.Save 15% on your first order of ARMRA Colostrum and unlock the power of 400+ functional nutrients. Just visit TryARMRA.com/Mark or use code MARK.In this episode we discuss (audio version / Apple Subscriber version):What are genes and what do they do? (6:37 / 4:33)Genetic predisposition does not mean predestined (9:22 / 7:18)The difference between genetics vs genomics (13:10 / 11:06)Polygenic risk scoring for chronic disease (18:18 / 16:14)Dementia risk and treatment (33:59 / 29:24)Mental and cognitive health issues in children (46:00 / 41:25)The similarities between Autism and Alzheimer's patients (49:49 / 45:14)My genomic test results, specifically related to detoxification and osteoporosis (52:21 / 47:45)Genetic vs genomic testing (1:06:29 / 1:01:54)Learn more at IntellxxDNA.com. Hosted on Acast. See acast.com/privacy for more information.

Our guest today is Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation. Steve is an entrepreneur and has started successful ventures in embryo selection, forensic genetics and artificial intelligence. Steve Hsu- Steve is a polymath- you can see just how wide his interests are on his blog infoproc. Despite his mathematical chops Steve is great at having conversations- I recommend Aporia listeners check out his podcast Manifold. During the 2020 racial reckoning, after some controversy, Steve stepped down as Senior Vice President for Research and Innovation at Michigan State University. You can see his response to the allegations against him here and his resignation here. Steve published the first paper showing that polygenic scores can predict phenotype with accuracy- see his paper on height here. Steve and his team also have shown that Genomic Prediction's aneuploidy testing improves pregnancy outcomes. We also talked about my article for Aporia on ethical objections to polygenic screening. In China, Yousheng, loosely translated as "eugenics" doesn't have a bad connotation- as Steve points out here. Steve is skeptical about the deleterious effects of polygenic screening or gene editing due to pleiotropy. Simone Collins, former Aporia guest, was also interviewed on Manifold. She used Genomic Prediction's health index. We talked about Bryan Caplan's books, The Case Against Education and "Selfish Reasons to Have More Kids"

We've been gradually working our way through the conversation around E. Fuller Torrey's concerns about schizophrenia genetics - last week we had It's Fair To Describe Schizophrenia As Probably Mostly Genetic, the week before Unintuitive Properties Of Polygenic Disorders. Here are two more arguments Torrey makes that we haven't gotten to: Studies have failed to find any schizophrenia genes of large effect. If schizophrenia is genetic, it must be caused of thousands of genes, hidden in the most obscure corners of the genome, each with effects too small to detect with current technology. This seems less like the sort of thing that happens naturally, and more like the sort of thing you would claim if you wanted to make your theory untestable. Schizophrenia is bad for fitness, so if it were genetic, evolution would have eliminated those genes. In the comments of the Unintuitive Properties post, Michael Roe points out that one of these mysteries solves the other: https://www.astralcodexten.com/p/evolution-explains-polygenic-structure 

E. Fuller Torrey recently published a journal article trying to cast doubt on the commonly-accepted claim that schizophrenia is mostly genetic. Most of his points were the usual “if we can't name all of the exact genes, it must not be genetic at all” - but two arguments stood out: Even though twin studies say schizophrenia is about 80% genetic, surveys of twin pairs show that if one identical twin has schizophrenia, the other one only has a 15% to 50% chance of having it. The Nazis ran a eugenics program that killed most of the schizophrenics in Germany, eliminating their genes from the gene pool. But the next generation of Germans had a totally normal schizophrenia rate, comparable to pre-Nazi Germany or any other country. I used to find arguments like these surprising and hard to answer. But after learning more about genetics, they no longer have such a hold on me. I'm going to try to communicate my reasoning with a very simple simulation, then give links to people who do the much more complicated math that it would take to model the real world. https://www.astralcodexten.com/p/some-unintuitive-properties-of-polygenic 

Commentary by Dr. Candice Silversides

Commentary by Dr. Candice Silversides

Join Patrick Short and Professor Clare Turnbull, Professor in Translational Cancer Genetics at the Institute of Cancer Research, as they discuss polygenic risk scores and their application in healthcare. Delve into the complexities of predicting disease, the challenges of screening programs, and the potential impact of integrating genomics into healthcare systems. Discover the limitations and potential of polygenic risk scores and gain valuable insights into the future of personalized medicine. 0:00 Intro 1:00 Clare's path to becoming a clinical geneticist and her research in uncovering genetic links to cancer 3:20 How do Polygenic Risk Scores help to predict disease, particularly breast cancer? 10:00 The influence of environmental and genetic effects on breast cancer presentation 11:30 Next clinical steps after determining genetic risk for breast cancer 17:30 How effective and accurate are polygenic risk scores in predicting various types of cancer, given the potential for false positives or negatives? 25:00 The potential for integrating genetic screenings and polygenic risk scores into early cancer diagnosis 27:20 How do monogenic risk scores like BRCA 1 and 2 fit into the paradigm of cancer research? 31:30 Using both monogenic and polygenic to explain population prevalence of disease 35:00 Integration of genomics and genetic screenings into the UK healthcare system 40:30 What comes after the genetic test? What is the use in identifying risk for a disease if nothing is subsequently done to prevent it? 44:50 Clare's upcoming work in remodeling NHS systems for evidence protocols and clinical use of genetic tests 46:50 Closing remarks

Join Patrick Short and Professor Clare Turnbull, Professor in Translational Cancer Genetics at the Institute of Cancer Research, as they discuss polygenic risk scores and their application in healthcare. Delve into the complexities of predicting disease, the challenges of screening programs, and the potential impact of integrating genomics into healthcare systems. Discover the limitations and potential of polygenic risk scores and gain valuable insights into the future of personalized medicine. 0:00 Intro 1:00 Clare's path to becoming a clinical geneticist and her research in uncovering genetic links to cancer 3:20 How do Polygenic Risk Scores help to predict disease, particularly breast cancer? 10:00 The influence of environmental and genetic effects on breast cancer presentation 11:30 Next clinical steps after determining genetic risk for breast cancer 17:30 How effective and accurate are polygenic risk scores in predicting various types of cancer, given the potential for false positives or negatives? 25:00 The potential for integrating genetic screenings and polygenic risk scores into early cancer diagnosis 27:20 How do monogenic risk scores like BRCA 1 and 2 fit into the paradigm of cancer research? 31:30 Using both monogenic and polygenic to explain population prevalence of disease 35:00 Integration of genomics and genetic screenings into the UK healthcare system 40:30 What comes after the genetic test? What is the use in identifying risk for a disease if nothing is subsequently done to prevent it? 44:50 Clare's upcoming work in remodeling NHS systems for evidence protocols and clinical use of genetic tests 46:50 Closing remarks

These scores — composite measures of a person's autism-linked common genetic variants — cannot predict an autism diagnosis but could help researchers better understand the condition's underlying biology.

These scores — composite measures of a person's autism-linked common genetic variants — cannot predict an autism diagnosis but could help researchers better understand the condition's underlying biology.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Reply to a fertility doctor concerning polygenic embryo screening, published by GeneSmith on May 29, 2023 on LessWrong. New LessWrong user grll_nrg, a fertility doctor, left a comment on my post about how to have polygenically screened children that brought up many of the common objections raised to polygenic embryo screening. I've heard these concerns brought up many times at conferences and in talks by professionals in the fertility industry. I thought other people might be interested in the discussion, so I decide to make a stand-alone post. Here's grll_nrg's original comment: Great post. Thank you. Fertility doctor here and a supporter of ART (assisted reproductive technologies) in general. A few thoughts (although you touched on a few of these below, worth emphasizing in my opinion): PGT-P has not been validated yet, which may take decades to do, if ever. The science in terms of GWAS isn't quite there yet IMHO - we don't know all the genes that are important for most traits and we may be inadvertently selecting against some desirable traits, for example. Comparing clinic success rates using CDC data is imperfect because of different patient characteristics, patient selection, and reporting bias. IVF pregnancies carry a significantly higher complication rate (hypertensive disorders, preterm birth, placental abnormalities, etc.) compared to spontaneous pregnancies - unclear if this is due to IVF or underlying infertility diagnosis. The risk-benefit calculus of PGT-P is going to be different for a couple who already needs to do IVF anyway to have a baby (low additional risk/cost) compared to a couple doing IVF just so that they can do PGT-P (higher additional risk/cost). IVF is notoriously inefficient at present. Depending on female partner age, each cycle may yield only very few embryos making the benefit and utility of PGT-P limited. It may not be practical, safe, or financially feasible to do multiple cycles of IVF to increase the cohort of transferable embryos. IVF is expensive and often not covered by insurance which creates access disparities. PGT-P would exacerbate these disparities in access. This is not unique to IVF I realize. Slippery-slope eugenics and discrimination are real ethical concerns that would need to be mitigated. In-vitro gametogenesis (IVG) would be a game-changer. The utility of PGT-P would be greatly enhanced if suddenly you had thousands of eggs and hundreds of embryos to select from. Thanks for the reply. I'm glad professionals from the ART field are reading this. PGT-P has not been validated yet, which may take decades to do, if ever. I think the ART field should probably reconsider what it considers acceptable evidence of "validation". In my mind, the question of "Has PGT-P been validated" should hinge on whether or not we can be confident that embryos selected via polygenic scores will display different trait values than those selected at random. For example, we want to know whether an embryo that has a low polygenic risk score for hypertension will indeed go on to develop hypertension at a lower rate. All the people I've heard criticize PGT-P seem to think that the ONLY way to do this is with some kind of randomized control where some embryos with certain polygenic risk scores are implanted and others are not, and we then wait 20-70 years to see whether or not the polygenically screened group develops diseases at a different rate than the control group. I think this view is incorrect and is only taken because people are blindly applying traditional validation methodology to PGT-P without asking whether it is necessary. Genes have a very special property that gives us a huge advantage over researchers trying to test whether or not a medication works; nature has already conducted a randomized control trial for us! From the section in ...

Editor's Summary by Mary McGrae McDermott, MD, Deputy Editor of JAMA, the Journal of the American Medical Association, for the May 23/30, 2023, issue. Related Content: Audio Highlights

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How to have Polygenically Screened Children, published by GeneSmith on May 7, 2023 on LessWrong. Polygenic screening is a method for modifying the traits of future children via embryo selection. If that sounds like gobbledygook, then think of it a bit like choosing stats for your baby. That may sound amazing. It may sound like science fiction. It may even sound horribly dystopian. But whatever your feelings, it is in fact possible. And these benefits are available for a price that, while expensive, is within reach for most middle-class families. On a more serious note, there is limited selection power available with today's technologies, so you will not be able to have a baby Einstein unless you are already a Nobel laureate. But polygenic screening will allow you to decrease your child's risk of common diseases by 10-60%, reduce their risk of mental disorders, and increase their IQ by somewhere between 3 and 8 points. If you are willing to wait a few years, you may be able to increase IQ by up to 13 points. These benefits are available for between $20k-100k depending on how strong of a benefit you want and what kinds of traits you want to select for. There has been quite a bit of discussion of this topic on LessWrong and adjacent communities but very little concrete advice for would-be parents who are curious whether the benefits are worth the price, particularly for those who have no other reason to do IVF. The purpose of this post is to fill that gap by addressing costs, potential medical complications, choice of clinic, which labs are best, and how age and infertility diagnosis affect the expected benefits. This is a long post and I expect most people will not want to read the whole thing. If this is you, please use the section selector in the sidebar to navigate to the section you are most interested in. You may want to simply skip to the section titled "Concrete Advice for Would-Be Parents". Background on IVF Wait, what even is polygenic embryo selection? Embryo selection is all about picking an embryo to (hopefully) turn into a baby. This occurs during the process of In-Vitro Fertilization, or IVF. In the typical IVF cycle, a couple goes into a fertility clinic because they want to have a baby. Usually this is because they've been having trouble conceiving naturally, but couples also seek out IVF when they want to do genetic testing, select the sex of their child, or to preserve fertility for later pregnancy. The doctor conducts a bunch of medical tests, and if they all check out, the woman begins a hormone regimen that will stimulate an abnormally large number of her eggs to mature all at once. At the end of the regiment, the doctor extracts a bunch of mature eggs from the woman's ovaries, which are then fertilized using the father's sperm and grown in a lab dish for 4-7 days. When the embryo has finished growing, there are often four or more that can be implanted in the mother. Most couples do not want four children, so a choice must be made about which embryo to pick. In ye olden days, doctors would often just transfer all the embryos at once in the hope that at least one of them would result in a baby. Sometimes this would work well; one of the embryos would happen to stick and the parents would be very happy. Other times it would work a little too well and more than one of the embryos would implant. This is why twin births are so much more common during IVF than during normal pregnancy. Transferring multiple embryos at a time is less common nowadays because the outcomes for twin births are on average worse than for single pregnancies. Twins are more likely to be born preterm, develop health problems, and put excess stress on the mother's body. This brings me back to my original point; the doctor or embryologist has to make a choice about which embryo to tr...

Joe Cohen, founder and CEO of SelfDecode joins me to discuss genomics, but more specifically our polygenic risk score. Joe, flips the script from focusing on one gene (or SNP), and instead shines a lens on how we consider a multitude of genes, along with presenting signs and symptoms, to determine what's true for the […] The post Mapping Polygenic Risk Scoring with Joe Cohen #359 appeared first on Functional Nutrition Alliance.

Have you heard of scientific wellness? In this episode, Nathan Price and Joe discuss whether the conventional approach of using pharmaceuticals to treat chronic diseases is effective, or if a preventative approach to complex conditions such as cardiovascular disease and Alzheimer's is the best choice. Nathan explains how genes can help predict the success of lifestyle-based interventions and talks about the accuracy of polygenic risk scores vs single variants for disease prediction, and how genetics can be used in healthcare. Nathan and Joe also talk about nicotinamide mononucleotide (NMN), nicotinamide riboside (NR), DHEA, and other supplements. Plus, Nathan explains the controversy of choline, carnitine, and TMAO, and if you should be worried. Dr. Nathan Price is the Chief Scientific Officer of Thorne HealthTech and author of The Age of Scientific Wellness. He was named one of the 10 Emerging Leaders in Health and Medicine by the National Academy of Medicine and was appointed to the Board on Life Sciences of the National Academies of Sciences, Engineering, and Medicine. - Preorder The Age of Scientific Wellness - Check out SelfDecode - Join Joe's online community - Follow Joe on Instagram & TikTok

Commentary by Dr. Valentin Fuster

İnsan Genom Projesi'nin başlangıcından beri 32 sene geçmiş. Hala anlayamadık mı zekayla ilişkili genleri? Evet fularsızlar, bugün de genetik öğreneceğiz Mendelin izniyle. Genom araştırmalarını, kayıp kalıtsallık problemini öğreneceğiz ve sonra da 10 bölümü bulmuş serimizi özetleyip tamamlayacağız.(Bunca bölümdür devam etmemi sağlayan tek şey, Patreon'dan irili ufaklı destek veren sizin gibi dinleyiciler. Bu destek doğrudan bana geliyor, normal reklam gelirleri ise yapımcımla paylaşılıyor. Yok kalsın diyorsanız, buyrun buradan yakın: Safsatalar Ansiklopedisi Kısaltılmış Edisyon).----------------------------------------------------Bu podcast, Hiwell hakkında reklam içerir.Hiwell hakkında daha detaylı bilgi almak ve fular100 kodu ile %20 indirimden faydalanmak için tıklayın.----------------------------------------------------.Bölümler:(00:03) #SadeceDuymakİstedikleriniz(01:13) Lewontin Safsatasi(03:41) İnsan Genomu Projesi(06:31) Kayıp Kalıtsallık Problemi(07:45) Genetik 101(10:21) Genom Analizleri(14:07) Nedensellik(15:17) Polijenik Skor(17:17) Ya ikiz çalışmaları yanlışsa(18:53) Muhafazakarlığın kalıtsallığı(20:06) Nadir değişimler ve çoklu kıyas problemi(22:44) Büyük örneklemlerin büyük problemleri(24:49) Epigenetik(27:31) Daha her şey yeni başlıyor(28:36) Serinin özeti(32:18) Eğitim felsefesi ve "büyük adamlar" anlatısı(34:35) Genetikten korkmamak.Kaynaklar:Youtube: Genetik SerisiAkademik makale: The complete sequence of a human genomeAkademik makale: Solving the missing heritability problemNature makalesi: The broken promise that undermines human genome researchNature makalesi: Polygenic scores: prediction versus explanationGazete makalesi: How much do your genes shape your politicsAkademik makale: Epigenetic inheritance and the missing heritabilitySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

FH: What it is, Increased Cardiovascular Risk, Ruling Out Secondary Causes, and When to Refer Guest: Alicia Mickow, APRN, C.N.P., M.S.N. (@aliann2011)  Host: Stephen Kopecky, M.D. (@DrSteveKopecky) Joining us today to discuss Familial Hypercholesterolemia is Alicia Mickow, APRN, C.N.P., M.S.N., nurse practitioner at Mayo Clinic in Rochester, Minnesota. Specific topics discussed: What is FH? What is the clinical definition? What causes FH? Polygenic vs monogenic How do we categorize FH? Clinical criteria, LDL Criteria ≥190 mg, Genetic criteria What is the Overlap Among the Different Definitions of Familial Hypercholesterolemia? When should we suspect FH? Is treatment different than what we give patients that do not have Familial Hypercholesterolemia? What is the goal of therapy FH? Are all patients with high LDL at risk for developing CAD? Connect with Mayo Clinic's Cardiovascular Continuing Medical Education online at https://cveducation.mayo.edu or on Twitter @MayoClinicCV. NEW Cardiovascular Education App: The Mayo Clinic Cardiovascular CME App is an innovative educational platform that features cardiology-focused continuing medical education wherever and whenever you need it. Use this app to access other free content and browse upcoming courses. Download it for free in Apple or Google stores today! No CME credit offered for this episode. Podcast episode transcript found here.

https://www.metaculus.com/notebooks/9247/polygenic-selection-of-embryos/ In vitro fertilization (IVF) is a fertilization procedure in which ova are removed from a woman and combined with sperm in a laboratory culture, with the resulting embryo then implanted in the woman's or a surrogate mother's uterus. This assistive reproductive technology has been used successfully since 1978, and its use has increased over time, owing in part to women choosing to bear children later in their lives.  Often, combining sperm with extracted ova results in multiple viable embryos. For many years, doctors have been able to perform diagnostic screening tests to check the embryos for chromosomal abnormalities like Down syndrome and gene defects like Tay-Sachs, allowing them to select and implant the healthiest embryo.

This week Patrick is joined by Sir Peter Donnelly, CEO of Genomics PLC and Professor of Statistical Science at the University of Oxford. They discuss how to get from data to implementation in the clinic, the challenges of polygenic risk scores including prediction across different ethnic backgrounds, and the role of genomics in drug discovery.

This week Patrick is joined by Sir Peter Donnelly, CEO of Genomics PLC and Professor of Statistical Science at the University of Oxford. They discuss how to get from data to implementation in the clinic, the challenges of polygenic risk scores including prediction across different ethnic backgrounds, and the role of genomics in drug discovery.

Shai Carmi is Professor of Statistical and Medical Genetics at Hebrew University (Jerusalem). Carmi Lab: https://scarmilab.org/ Twitter: https://twitter.com/ShaiCarmi  Topics and links: Shai's educational background. From statistical physics and network theory to genomics. Shai's paper on embryo selection: Schizophrenia risk. Modeling synthetic sibling genomes. Variance among sibs vs general population. RRR vs ARR, family history and elevated polygenic risk. (Link to paper: https://www.biorxiv.org/content/10.1101/2020.11.05.370478v3) Response to the ESHG opinion piece on embryo selection. https://twitter.com/ShaiCarmi/status/1487694576458481664 Pleiotropy, Health Index scores. Genetic genealogy and DNA forensics. Solving cold cases, Othram, etc. (Link to paper: https://www.science.org/doi/10.1126/science.aau4832) Healthcare in Israel. Application of PRS in adult patients. Music used with permission from Blade Runner Blues Livestream improvisation by State Azure.--Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation at MSU and Director of the Institute of Theoretical Science at the University of Oregon. Hsu is a startup founder (SafeWeb, Genomic Prediction, Othram) and advisor to venture capital and other investment firms. He was educated at Caltech and Berkeley, was a Harvard Junior Fellow, and has held faculty positions at Yale, the University of Oregon, and MSU.Please send any questions or suggestions to manifold1podcast@gmail.com or Steve on Twitter @hsu_steve.

James Lee is a professor of psychology at the University of Minnesota. He is a leading researcher working in behavior genetics and statistical genetics. In this episode, he discusses recent progress in the genomic prediction of complex traits such as cognitive ability and educational attainment. Lee also discusses his recent Wall Street Journal editorial on embryo selection, Imagine a Future Without Sex.Resources Imagine a Future Without Sex: Reproductive technology may lead us to realize too late that being human is better than playing God James Lee academic web page Social Science Genetic Association Consortium (SSGAC) Nature Genetics: Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals Music used with permission from Blade Runner Blues Livestream improvisation by State Azure.Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation at MSU and Director of the Institute of Theoretical Science at the University of Oregon.Hsu is a startup founder (SafeWeb, Genomic Prediction, Othram) and advisor to venture capital and other investment firms. He was educated at Caltech and Berkeley, was a Harvard Junior Fellow, and has held faculty positions at Yale, the University of Oregon, and MSU.Please send any questions or suggestions to manifold1podcast@gmail.com or Steve on Twitter @hsu_steve.You can find Steve's writing on his blog Information Processing.ManifoldOne YouTube channel.