The Genetics Podcast

This week on The Genetics Podcast, Patrick is joined by Dr. Sek Kathiresan, CEO of Verve Therapeutics and SVP, Head of Obesity Research and Early Development at Eli Lilly. They discuss how protective genetic variants led to the development of a one-time gene editing therapy for heart disease in the face of early doubt, the phase one results for Verve-102, what recent trial failures mean for genetic target validation, and the unmet needs in obesity treatment.
Show Notes
0:00 Intro to The Genetics Podcast
00:59 Welcome to Sek 
01:40 Sek’s family history of heart disease and how it motivated him to pursue cardio therapeutics
03:29 Sek’s background and research on the genetics of coronary artery disease and protective mutations
08:03 Reactions to the Verve launch and the biological, technological, regulatory, and commercial risks
11:00 Verve-102 phase one results and the case for lifelong LDL lowering
16:14 Why cumulative exposure means lowering LDL earlier and for longer
17:53 Recent trial failures in genetically validated targets and what the Lp(a) trial leaves unanswered
20:33 Polygenic risk scores and who benefits most from LDL lowering
23:36 Sek’s new role at Lilly and the remaining unmet needs in obesity treatment
29:06 Whether one-time gene therapy could work for obesity and how GLP-1 drugs drive weight loss
30:38 Food intake, energy expenditure, and the search for new obesity mechanisms
32:15 Why Lilly is investing so heavily in genetic medicine
34:35 Closing remarks
Find out more
ANGPTL3 study in NEJM (https://pmc.ncbi.nlm.nih.gov/articles/PMC3008575/)

Verve-102 study (https://www.nejm.org/doi/10.1056/NEJMoa2601283)

This week on The Genetics Podcast, Patrick is joined by Dr. Luke Pilling, Senior Lecturer in Genetic Epidemiology at the University of Exeter. They discuss hemochromatosis and the case for earlier diagnosis, and the genetic drivers of multimorbidity, pharmacogenetics, and drug response.
Show Notes
0:00 Intro to The Genetics Podcast
00:59 Welcome to Luke 
01:37 An overview of HFE hemochromatosis and why diagnosis is delayed 
04:24 Iron levels and overload risk in heterozygous and compound heterozygous carriers
05:51 Aging-related effects seen in homozygotes 
06:43 How hemochromatosis is currently diagnosed and detected in the UK
09:26 Future screening and case finding, including the Our Future Health cohort
11:28 Genetic and environmental factors that shape outcomes in C282Y homozygotes 
13:28 The GEMINI project and the genetic drivers of multimorbidity
15:56 Drug targets from multimorbidity genetics, including repurposing and opposite effects
18:49 Using disease sequences in health records to look for earlier intervention points in multimorbidity
21:21 Data gaps limiting multimorbidity research, from primary care records to proteomics
23:17 Handling misdiagnosis and clinical code accuracy in health record research
24:55 International collaborations and the need for more diverse biobank data
26:08 Pharmacogenetics research and how genetic variants shape drug response
29:04 Limited clinical examples of pharmacogenetics and lessons from non-responders
33:08 Genetics of lifespan and healthy aging, and why geroscience pathways rarely appear in GWAS
36:06 Luke’s future research focuses 
40:39 Closing remarks
Find out more:
- Hereditary hemochromatosis study
- Multimorbidity study
- Pharmacogenetics framework study

This week on The Genetics Podcast, Patrick is joined by Dr. James Zou, Associate Professor of Biomedical Data Science at Stanford University. They discuss the concept of virtual biotechs and how AI agents link single cell data to clinical trial success, Paper to Agent and turning papers into living virtual authors, clinical AI from EchoNet to SleepFM, and the role of academia alongside big AI labs.
Show Notes
0:00 Intro to The Genetics Podcast
00:59 Welcome to James 
01:55 An overview of James’s virtual biotech and its AI scientist agents
04:11 How single cell evidence behind drug targets predicts clinical trial success
06:33 Behind the scenes of how autonomous the virtual biotech agents are
08:06 Missing proprietary trial data as the next gap for the virtual biotech
09:44 Scaling the number of collaborating AI agents as a new frontier for drug discovery
12:29 How teamwork and structure evolved among the agents 
15:53 Behind the idea of Paper to Agent and virtual authors
19:01 What converting over 100 papers into agents revealed about reproducibility
23:14 The story behind EchoNet, an FDA-cleared AI tool for cardiac ultrasound
26:28 Predicting risk for over 100 future diseases from one night of sleep
27:40 Transferring SleepFM from sleep labs to consumer wearables
28:43 Combining multimodal health data to predict disease
30:10 Longitudinal blood proteomics as the biggest data gap for health AI
31:18 The role of academia as an open, neutral counterweight to big AI labs
32:51 How James’s path from Cambridge math and Harvard machine learning led to biology
34:41 Closing remarks
Find out more
Virtual biotech paper (https://www.science.org/doi/10.1126/science.aeg6779)

Paper2Agent paper (https://www.nature.com/articles/s41586-026-11044-y)

This week on The Genetics Podcast, Patrick is joined by Dr. Jeffrey Barrett, Group Leader at the Ellis Institute Finland and the University of Helsinki. They discuss using AI and federated biobank data to stratify common chronic diseases, how LLMs reading clinical notes in Finland's health registries can reveal treatment response, how AI is changing the way scientists research and train, and what the UK's COVID genome sequencing effort means for biosecurity.
Show Notes
0:00 Intro to The Genetics Podcast
01:00 Welcome to Jeff 
02:08 Jeff's research focus for his new lab, including molecular subtyping of common chronic diseases with AI
06:18 Barriers to pooling biobank data across research environments for federated AI models
11:00 Why Jeff expects larger datasets to make complex models better at predicting disease
13:34 The three disease areas Jeff's lab will target first: cardiometabolic, inflammatory and neuropsychiatric
19:41 Using LLMs to read clinician notes in Finland's health registries for treatment response
24:50 How Jeff uses AI in his research and where humans still need to read and review
31:08 Using Claude to understand papers and the gaps in its literature searches
32:14 Jeff on AI solving open problems in mathematics and biology, and where researchers fit
35:48 Simultaneous discoveries and why lab data generation still needs experts
39:01 Jeff's COVID genome sequencing at Sanger and what it means for AI and biosecurity
43:16  Closing remarks

Summary
This week on The Genetics Podcast, Patrick is joined by Jenny Hsieh, Co-Founder and President of the Danon Foundation. They discuss how Danon disease affects males and females, why it is so often misdiagnosed, the current therapy landscape and research priorities, and how families can make informed decisions about gene therapy trials.
Show Notes
0:00 Intro to The Genetics Podcast
00:59 Welcome to Jenny 
01:28 An overview of Danon disease
02:34 Sex differences in Danon disease and severe disease in females
05:15 Why Danon disease is misdiagnosed and how it may be spotted earlier
08:50 Therapy pipeline for Danon and the Foundation's global patient coordination
13:46 Origin story of the Danon Foundation
18:10 Research priorities and the burden of Danon disease beyond the heart
22:39 Raising genetic testing awareness among ophthalmologists and cardiologists for Danon disease
25:20 Recognizing broader Danon symptoms and launching the first Danon Awareness Day
29:37 Informed consent and trial literacy for families weighing gene therapy
33:14 Patient-friendly trial experiences
36:19 Ways to support Danon research
37:37 Closing remarks
Find out more
Danon Foundation