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

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

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

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

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

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

I just had the most wonderful time at the Quantgen GRC in Italy with these lovely and brilliant people :) hope to see everyone again in Ventura for the next Quantgen GRC in 2 years time, and sooner on other occasions!

New year new start! My group has moved to the Dept of Biosystems Science and Engineering in ETH Zurich - very excited to work with new colleagues here! We’re also hiring soon, if interested in a PhD/postdoc in quantitative genetics and genomics, esp with focus in psych disorders, pls get in touch!

My first PhD student Lianyun Huang has now successfully defended her PhD and is now Dr Huang! 🎉🎉🎉 Thank you for 4 years of hard work, it’s an honor to be part of your academic journey!

Good morning #wcpg2023! Today: My student Jolien Rietkerk is giving a talk at 1pm in the Stats Methods session (Rm 510) on use of PRS in pathway interaction test + method considerations; Lianyun Huang is giving a poster (no 74) on MDD symptom genetics. Come hear them out, feedback welcome! 🤩

On our way to #wcpg2023! This is a big year for Cai lab, all of us have talks! 🤩 Lianyun Huang is in the UKB session, Jolien Rietkerk is in the stats methods session, and I’m in a symposium on GWAS phenotyping. I’ll remind everyone on the morning of. 😉 See you all in Montreal!