The Genetics Podcast

0:00 Introduction
1:30 The power of social media: How Eric published 10 papers based on ideas that he discussed on Twitter
5:50 Explanation of The Table of Everything, an internal database at Pfizer that catalogs nearly 20,000 human genes and their associated diseases and traits
13:20 How Eric’s team works to correlate genome-wide association study (GWAS) results to real biological phenotypes and outcomes
18:10 Introduction to protein quantitative trait locus (PQTL), including its importance in biological and genetic data
25:10 Examining the evolving bottlenecks in drug development and the challenges of validating genetic targets 
28:30 Navigating the gap between genetic hits and biological understanding, and how AI or functional studies could bridge this in target discovery
32:20 Linus Pauling's mentorship of Eric and how he might react to AlphaFold2’s breakthroughs in structural biology
35:15 Eric's take on using AI and how he's experimenting with it on trusted datasets
41:00 An introduction to Mendelian randomization, as well as its strengths and limitations
47:00 How Eric uses the TOP Model (Talent, Opportunity, and Passion) to guide this career choices and path
52:00 Diversity and collaboration in genetics research and implementation
55:00 Closing remarks
Resources mentioned throughout the episode:Mendelian Randomization with Proxy BiomarkersPaper: Mendelian randomisation with proxy exposures: challenges and opportunities, I Rahu, R Tambets, EB Fauman, Kaur Alasoo (2024)Explores proxy biomarkers as a method to assess in vivo activity of a protein target.
Trait Colocalization and Causal GenesPaper: Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation, CJ Smith, N Sinnott-Armstrong, A Cichońska, H Julkunen, EB Fauman, Jonathon Pritchard, Elife 11, e79348Demonstrates how traits with opposing effects on a genetic variant may suggest a causal gene sits between them
Metabolite Profiling in Human KnockoutsPaper: McGregor TL, Hunt KA, Yee E, et al. Characterising a healthy adult with a rare HAO1 knockout to support a therapeutic strategy for primary hyperoxaluria, Elife. 2020;9. Published 2020 Mar 24.
Community Workshop on Effector Gene StandardsPresentation: Watch on YouTube
TOP Model for Career GuidanceArticle: Grab the Helm: How to Take Charge of Your Purpose, Passion, Progress
The Table of EverythingOverview: Read more on Pfizer’s site
UK Biobank Protein QTL StudyPaper: Sun, B.B., Chiou, J., Traylor, M. et al. Plasma proteomic associations with genetics and health in the UK Biobank,Nature, 622, 329–338 (2023).
Eric’s First GWAS ContributionPaper: Shin SY, Fauman EB, Petersen AK, et al. An atlas of genetic influences on human blood metabolites, Nat Genet.2014;46(6):543-550.
Every Gene Ever Annotated (EGEA)Public Resource: View annotations on GitHub  Nine reasons not to use eQTLs to identify causal genes from GWAS:Random Sequences Can Create Regulatory Elements

• “~83% of random promoter sequences yielded measurable expression” - de Boer CG, Nat Biotechnol, 2020
• “Recently evolved enhancers are formed predominantly by exaptation of ancestral DNA” - Villar D, Cell, 2015
• “Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization” - Tambets R, et al., HGG Adv., 2024

Enhancer Variants and Buffering in Important Genes

• “eQTLs at GWAS loci are more likely to point to genes with low enhancer redundancy not associated with disease” - Wang X, Goldstein DB, Am J Hum Genet., 2020
• “GWAS and eQTL studies are systematically biased toward different types of variants” - Mostafavi H, et al., Nat Genet., 2023
• “CNVs are buffered by post-transcriptional regulation in 23%-33% of proteins significantly enriched in protein complex members” - Gonçalves E, et al., Cell Systems, 2017

eQTL Data Limitations vs. Proximity Information

• “cis-eQTL target genes are relatively poor indicators of ‘true positive’ causal genes” - Stacey D, et al., NAR., 2018
• “When molecular QTL colocalization evidence was removed, we saw similar classification results” - Mountjoy E, et al., Nat Genet., 2021
• “Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics” - Forgetta V, et al., Hum Genet., 2022

0:00 Intro to The Genetics Podcast
01:00 Welcome to Noam and discussion of his motivation to drive rare disease forward
03:00 Noam’s daughter Noga’s experience of rare disease, including an 8 to 12 month journey to diagnosis
05:10 How the experience of his daughter receiving a genetic diagnosis motivated Noam to take change into his own hands
10:12 How meeting other families impacted by rare disease led Noam to work on gene therapy for children living with primary immune deficiencies
12:33 How Noga Therapeutics is aiming to reprogram blood stem cells and the potential impact on rare diseases
15:22 Why it’s not yet possible to use the technology to correct gain of function mutations
17:42 How Noga’s program is aiding treatment of multiple primary immune deficiencies
22:25 The techniques the company uses in XLA to modify stem cells and enable expression of a functional copy of the BTK gene
26:30 Why gene therapies don’t always provide a comprehensive solution or cure
28:10 Bridging the gap between transformative therapies and the cost of delivering drugs to very small ultra-rare disease populations
34:41 Noam’s history working in traditional Chinese medicine
39:53 The importance of thinking holistically about health, from understanding g genetic root causes to considering how genes impact whole organ systems
43:15 The collaborative nature of the rare disease community and how parents who want to use their personal experience to further research and advocacy can connect with Noam
44:37 Closing remarks

0:00 Invitation to The Genetics Podcast meetup
1:30 Intro to The Genetics Podcast
2:30 Welcome to Veera
3:20 The evolution on skin color in humans and their ancestors:Discussion on how a retrotransposon—often called a "jumping gene"—within the ASIP gene (agouti signaling protein) influenced the evolution of skin pigmentation in humans and their ancestors. ASIP, a paracrine hormone produced by skin cells, plays a key role in determining skin color.

• Veera’s Substack Post: How a Jumping Gene Shaped Human Skin Color Evolution - https://www.gwasstories.com/p/how-a-jumping-gene-shaped-the-human
• Original Research: Study by Dr. Po-Ru Loh and Dr. Steve McCarroll from the Broad Institute, published in Nature Genetics - https://www.nature.com/articles/s41588-024-01841-4

18:00 - An overlooked tau isoform could unlock an effective drug for Alzheimer’s diseaseExploration of big tau, an often overlooked isoform with unique properties that may make it a promising therapeutic target for tauopathies like Alzheimer's disease. The therapeutic mechanism is reminiscent of Casgevy, a gene therapy treatment used for sickle cell disease.Resources:

• Veera’s Substack Post: The Big Tau: A New Hope for Alzheimer’s - https://www.gwasstories.com/p/the-big-tau-a-new-hope-for-alzheimers
• Original Research: Study from Dr. Huda Zoghbi’s lab on how the big tau splice isoform resists Alzheimer’s-related pathological changes - https://www.biorxiv.org/content/10.1101/2024.07.30.605685v1

34:10 Protecting cortical neurons from herpes simplex virusAn international team of researchers, led by Jean-Laurent Casanova and Yi-Hao Chan at Rockefeller University, has discovered that tomoregulin-1 (TMEFF1), a neuronal membrane protein, protects human cortical neurons from herpes simplex viral infection. The gene responsible for producing TMEFF1 encodes a viral restriction membrane protein that prevents viruses from entering brain cells, offering potential therapeutic insights.

• Veera’s Substack Post: Discovery of TMEFF1, a viral restriction factor in the human brain - https://www.gwasstories.com/p/discovery-of-tmeff1-a-viral-restriction
• Original Research: Study by the Jean-Laurent Casanova Lab at Rockefeller University, Human TMEFF1 is a restriction factor for herpes simplex virus in the brain - https://www.nature.com/articles/s41586-024-07745-x

47:30 KCNB1 and a novel cardiac arrhythmia syndrome
A genetic investigation into cardiac arrhythmias has identified a new noncoding Mendelian disease mechanism stemming from a rare Mendelian disorder.

• Veera’s Substack Post: De novo enhancer creation by a noncoding mutation - https://www.gwasstories.com/p/de-novo-enhancer-creation-by-a-noncoding
• Original Research: A novel familial cardiac arrhythmia syndrome with widespread ST-segment depression. The authors note, “We believe this is the first description of an entirely de novo cryptic enhancer causing a Mendelian disorder.” - https://www.nejm.org/doi/full/10.1056/NEJMc1807668

57:40 - Genomes vs. exomesExploring the cost-effectiveness of whole genome sequencing compared to whole exome sequencing for gene discovery. This segment explores the long-standing debate over exomes versus genomes, highlighting challenges in studying noncoding variants and the value of each approach in the context of common versus rare diseases.

• Veera’s Substack Post: Genomes vs. Exomes - https://www.gwasstories.com/p/genomes-vs-exomes
• Original Research: Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank - https://www.nature.com/articles/s41588-024-01930-4

1:10:00 Closing remarks
1:14:30 Outro

0:00 Invitation to The Genetics Podcast meet up


1:30 Intro to The Genetics Podcast


2:25 Welcome to Mark


3:10 Introduction to the National Institute for Health Research (NIHR)


4:05 Mark’s roles with the NIHR in strategic partnerships


7:35 Challenges patients face in accessing NHS resources and the NIHR’s efforts to streamline availability


13:25 How to scale breakthroughs in precision therapies so they are widely accessible to patients across the NHS: Top-down vs. bottom-up strategies


17:00 Applying principles of cost consequence analysis to NHS strategy


17:45 Misconceptions regarding NHS financing and the allocation of funding for medical innovations


23:20 Best practices for working with under- and mis-represented populations to facilitate development of and access to medical innovations


29:45 East London Genes & Health and Born in Bradford: Two cases where deep engagement and trust building resulted in robust data collection and innovation


32:45 Insights into the D Cyphr Program (DNA, Children, Young People’s Health Resource) aimed at gaining population-level genomic data to address broader health issues such as mental health and diabetes

34:35 Closing remarks

We hope you will join us at our first (of hopefully many!) in-person podcast event! Please use this link to sign up. 

0:00 Invitation to our first in-person podcast event


1:30 Intro to The Genetics Podcast


2:20 Welcome to Paul


2:53 Adeno-associated virus (AAV) biology and its advantages over other viral vectors


5:20 The gene therapy landscape and options for therapy development and delivery


6:49 The limitations of working with AAV to deliver gene therapy, including genome capacity and challenges with dividing cells


9:37 Why enormous bioreactors and huge volumes are necessary in the AAV manufacturing process


11:22 Why the eye is an ideal target for AAV gene therapy, and the potential of single-dose gene therapies


13:36 Advantages of AAVs in delivering therapies into multiple different cell types


15:17 Moving pre-clinical AAV delivered therapies into a clinical setting


17:52 How Abeona’s therapies aim to address different types of inheritance patterns


18:53 The current landscape of monogenic eye disease and Abeona’s approach to inherited eye conditions


21:38 Exploring current relationships between government, industry, and academia when supporting research for rare diseases


22:27 Paul’s transition from academia to industry


26:12 How the barrier between academia and industry is becoming more porous and bidirectional – and what that means for research


28:06 Paul’s enthusiasm for a cutting-edge area of precision medicine that has yet to gain mainstream attention

30:38 Closing remarks

0:00 Introduction
1:00 Overview of Mike’s background and contributions to genomics and preventative medicine, as well as how he first became interested in deep data collection for health monitoring
4:20 The use of various tools, including smartwatches, blood tests, genetic testing, and more, to create a comprehensive view of an individual’s health
7:00 Using wearables to monitor chronic diseases, initiated by Mike’s personal experience with the Lyme disease
13:00 The prevalence of undiagnosed diabetes and the long-term health impacts of being in a borderline or prediabetic state
17:00 The benefits and shortcomings of polygenic risk scores in generating treatment models
19:00 The promise of integrating preventative medicine, wearable devices, and deep data into primary healthcare
25:00 Punctuated points of aging, where rapid changes in biological aging occur at specific and unique stages in a person’s lifespan
31:00 The potential of cell-free DNA in advancing cancer treatments
33:00 The lack of data and digital and biochemical markers for diagnosing and monitoring mental health and neurodegenerative conditions
36:40 The need to incite a cultural shift towards greater data awareness and proactive health monitoring
39:00 Final thoughts: The discrepancy between healthspan and lifespan
42:00 Outro
To learn more about Dr. Snyder’s work, explore his book Genomics and Personalized Medicine and his certificate programs offered through Stanford University:

• Foundations of Genetics and Genomics
• Fundamentals of Data Science in Precision Medicine and Cloud Computing
• Fundamentals of AI/ML in Precision Medicine

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0:00 Intro to The Genetics Podcast
01:00 Welcome to Lon
01:51 Lon’s involvement in the very first GWAS and what drew him to large-scale genomics research
03:32 Was moving away from candidate genes towards GWAS and data sharing initially a controversial idea?
05:25 What Lon believes has driven collaboration and data sharing within research communities
07:38 How and why Lon transitioned from academia to working for GlaxoSmithKline (GSK) 
10:43 Why GSK was one of the largest initial investors in genetics and how the company came to have the largest genetics department in the world in the early 2000s
11:46 How the emergence of tens of thousands of biomarkers for genetic diseases has changed the way Lon thinks about the role of genetics in drug discovery
13:29 The future of genetics research and how much that path has diverged from expectations 20 years ago
18:14 The current challenge: From exquisitely precise genetics tools to clumsy phenotype predictions 

19:45 Paradigm shifts in the taxonomy of disease
22:29 What it takes to reorganize the taxonomic definition and approach to diseases such as metabolic dysfunction-associated steatohepatitis (MASH)
24:22 The changes needed within biotech and pharma to fully harness the possibilities of genetics in drug development
26:18 What drew Lon to the Jackson Lab, how it has evolved, and what he’s been focused on for the past three years
31:02 The Jackson Lab’s new precision medicine and cancer program, plus future plans for the institute’s legacy
35:56 What Lon has learned about running an international organization and global scientific collaboration 37:30 Lon’s advice to early career scientists on up-and-coming fields and technologies
41:40 Closing remarks

01:15 - Introductions 
02:02 - How our understanding of the non-coding genome has evolved throughout Nadav’s career
04:56 - Our current understanding of  non-coding genome grammar
07:40 - Is there a missing piece to the common variant, common disease paradigm?
10:25 - Introducing ultraconserved elements (UCEs) and human accelerated regions (HARs) 
12:50 - Can a simple code explain changes in certain regions of the genome? Does this require “messier” solutions, such as large language models?
14:25 - The potential of machine learning
16:56 - Using CRISPR and non-coding elements to treat haploinsufficiency-caused pediatric diseases
20:19 - Nadav’s experience of starting a company 
24:44 - How CRISPR A minimizes the risks associated with traditional CRISPR editing
26:04 - How engineering fat cells can starve cancer

32:08 - What’s on the horizon for Nadav’s lab?
34:52 - Bats as unlikely “superheroes,”, and what we can learn from their glucose levels 
38:43 - The genetic differences between archaic humans, like Neanderthals and Denisovans, and modern humans
40:33 - Closing remarks

0:00 Intro to The Genetics Podcast
01:00 Welcome to Marco
02:00 The areas Marco focused on during his academic career and what motivated him to found his first company
03:18 How our understanding of ageing has changed over the past two decades and some of the current big questions in ageing biology
06:01 How to get a clearer picture of the ageing process within a tissue or cell and if new technologies like single cell genomics can aid this process
11:08 Catalyst or cause? Understanding the role of cellular senescence in disease and how it impacts treatment pathways
12:54 The challenges of building a company that addresses an area of biology which sits at the core of so many diseases and disease types
16:17 Deciding on which therapeutic modality to target when using a platform biology approach
17:57 Identifying the most effective stage at which to intervene in the senescence process and if this changes dependent upon organ system or disease area
24:33 How another company founded by Marco, Turnbio, uses a different approach by focusing on turning back the biological clock rather than understanding the ageing process and intervening
31:08 Addressing if both preventative and intervention approaches are required to comprehensively treat or cure a disease
35:39 Whether there is potential to develop core therapeutics which can have a system-wide effect and address all-cause ageing
40:12 Why ‘biohacking’ therapies can present a risk to the field of ageing biology as a whole, as well as to individuals 
41:18 The developing area of science or technology Marco is most excited about and which he believes is going to have a significant impact in the coming years 43:23 Closing remarks 

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