And www.nature.com/articles/s41... in a more cross disorder setting - this one discusses the impact of phenotyping on cross disorder analyses

We have two more commentary/review like papers on this www.nature.com/articles/s41...

Importantly in this paper we derive a new metric PRS pleiotropy which we use to show shallow phenotypes indeed give non specific gwas signal that leads to non specific PRS predictions

We then worked out we can improve shallow phenotypes in biobank settings where there’s a small subset of individuals with high quality phenotypes through imputation www.nature.com/articles/s41...

Hi @michelnivard.bsky.social we have written quite a lot on sample size vs phenotyping quality. The earliest was www.nature.com/articles/s41... on depression where we show shallow phenotyping, despite giving higher gwas power, gives non specific gwas signal

Congratulations, very exciting! 🎉

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

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

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