Na Cai

We are excited to share GPN-Star, a cost-effective, biologically grounded genomic language modeling framework that achieves state-of-the-art performance across a wide range of variant effect prediction tasks relevant to human genetics.
www.biorxiv.org/content/10.1...
(1/n)

🌎👩‍🔬 For 15+ years biology has accumulated petabytes (million gigabytes) of🧬DNA sequencing data🧬 from the far reaches of our planet.🦠🍄🌵

Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.

doi.org/10.1101/2024...

Postdoctoral Scholar – Genomics, Aging, Somatic Mutation, Structural Variation, Evolution , Cancer – Integrative Biology University of California, Berkeley is hiring. Apply now!

The Sudmant lab at UC Berkeley is seeking a postdoc to work on a fully funded NIH project to understand differences in DNA repair and somatic mutation across the primate tree of life. Please spread widely to those who may be interested aprecruit.berkeley.edu/JPF05052

The 2026 Probabilistic Modeling in Genomics (ProbGen) meeting will be held at UC Berkeley, March 25-28, 2026. We have an amazing list of keynote speakers and session chairs:
probgen2026.github.io

Please help spread the news.

Congratulations, very exciting! 🎉

‘Genetic Risk Effects on Psychiatric Disorders Act in Sets’, the title of our new preprint on
@medrxivpreprint.bsky.social! This huge collaborative effort advances our understanding of psychiatric genetic architecture and emphasizes the importance of looking beyond additive effects. 🧵1/n; 🧪👩🏽‍🔬🧬

GitHub - caina89/psychCE: Code used to implement coordinated epistasis on psychiatric disorders Code used to implement coordinated epistasis on psychiatric disorders - caina89/psychCE

Link to GitHub page: github.com/caina89/psyc...

Genetic risk effects on psychiatric disorders act in sets Genetic studies of psychiatric disorders have typically assumed that all genetic effects contribute additively to disease liability. However, it is likely that psychiatric disorders have unrecognized ...

Link to the preprint: www.medrxiv.org/lookup/conte...

This work would not have been possible if not for the persistent efforts of @jolienrietkerk.bsky.social Andy Dahl, Jonathan Flint, Andrew Schork and many others, as well as the data from participants in @ukbiobank.bsky.social and IPSYCH. We hope it will be informative to the field. 12/n

Though our investigations and findings are centered on psychiatric disorders, the implications are generalizable to all complex traits and diseases, especially those with heterogeneous architectures and unclear diagnostic boundaries. 11/n

Overall, our work provides a novel metric, the CE test, for informing diagnostic boundaries. Our results show that genetic effects on psych disorders act in sets, and calls for a re-evaluation of current approaches and assumptions. 10/n

Finally, we find that common genetic effects across all five psych disorders, expected to capture common etiological axes among them, forms a cross-order set most plausibly explained by common confounders external to each disorder’s etiology. 9/n

We further show that disorder-specific sets lead to comorbidity between two disorders, refuting the assumption that comorbidity is the result of additive effects of genetic effects on both, exemplified by the expectation that high rGs would lead to high comorbidity. 8/n

These findings imply that rGs are insufficient to inform nosology, and that the CE test provides a way to determine whether putative disorders or subtypes should be merged or remain separate diagnostically. 7/n

We also show that sets of genetic effects are disorder-specific, despite high genetic correlations (rG) between them. This opposes a well-established conjecture, based on high rG, that clinical boundaries do not reflect their pathogenic processes. 6/n

In our paper, we test for CE in five psychiatric disorders in the @ukbiobank.bsky.social and the iPSYCH dataset using both polygenic risk scores (PRS) and family-based genetic risk scores (FGRS). We find negative CE for 3 out of 5 disorders, demonstrating there are unrecognized subtypes. 5/n

A model and test for coordinated polygenic epistasis in complex traits | PNAS Interactions between genetic variants—epistasis—is pervasive in model systems and can profoundly impact evolutionary adaption, population disease d...

The existence of these sets induces a structured form of statistical interactions called coordinated epistasis (CE), detailed in previous publications by Andy Dahl, Noah Zaitlen www.pnas.org/doi/10.1073/...; negative CE is seen when there are different sets of genetic effects. 4/n

These sets, should they exist, would each drive an unrecognized etiological subtype. Our paper tests for the existence of these sets in five psychiatric disorders. 3/n

Our paper addresses a central question in quantgen: whether all genetic variants associated with a complex disease contribute additively to its liability as commonly assumed, or there exists sets of them that co-occur more in certain cases than expected under additivity. 2/n

Very happy to share our new paper now on @medrxivpreprint: “Genetic risk effects on psychiatric disorders act in sets”, a great effort led my PhD student @jolienrietkerk.bsky.social, and performed together with collaborators Andy Dahl, Jonathan Flint, Andrew Schork etc. Thread 1/n

GitHub - caina89/psychCE: Code used to implement coordinated epistasis on psychiatric disorders Code used to implement coordinated epistasis on psychiatric disorders - caina89/psychCE

Link to GitHub page: github.com/caina89/psyc...

Genetic risk effects on psychiatric disorders act in sets Genetic studies of psychiatric disorders have typically assumed that all genetic effects contribute additively to disease liability. However, it is likely that psychiatric disorders have unrecognized ...

Link to preprint: www.medrxiv.org/lookup/conte...

This work would not have been possible if not for the persistent efforts of @jolienrietkerk.bsky.social Andy Dahl, Jonathan Flint, Andrew Schork and many others, as well as the data from participants in @ukbiobank.bsky.social and IPSYCH. We hope it will be informative to the field. 12/n

Though our investigations and findings are centered on psychiatric disorders, the implications are generalizable to all complex traits and diseases, especially those with heterogeneous architectures and unclear diagnostic boundaries. 11/n

Overall, our work provides a novel metric, the CE test, for informing diagnostic boundaries. Our results show that genetic effects on psych disorders act in sets, and calls for a re-evaluation of current approaches and assumptions. 10/n

Finally, we find that common genetic effects across all five psych disorders, expected to capture common etiological axes among them, forms a cross-order set most plausibly explained by common confounders external to each disorder’s etiology. 9/n

We further show that disorder-specific sets lead to comorbidity between two disorders, refuting the assumption that comorbidity is the result of additive effects of genetic effects on both, exemplified by the expectation that high rGs would lead to high comorbidity. 8/n

These findings imply that rGs are insufficient to inform nosology, and that the CE test provides a way to determine whether putative disorders or subtypes should be merged or remain separate diagnostically. 7/n

We also show that sets of genetic effects are disorder-specific, despite high genetic correlations (rG) between them. This opposes a well-established conjecture, based on high rG, that clinical boundaries do not reflect their pathogenic processes. 6/n

In our paper, we test for CE in five psychiatric disorders in the @ukbiobank.bsky.social and the iPSYCH dataset using both polygenic risk scores (PRS) and family-based genetic risk scores (FGRS). We find negative CE for 3 out of 5 disorders, demonstrating there are unrecognized subtypes. 5/n