Transdiagnostic Polygenic Risk Models for Psychopathology and Comorbidity: Cross-Ancestry Analysis in the All of Us Research Program DOI Creative Commons
Phil H. Lee, Jae-Yoon Jung,

Brandon T. Sanzo

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 27, 2025

Psychiatric disorders exhibit substantial genetic overlap, raising questions about the utility of transdiagnostic risk models. Using data from All Us Research Program (N=102,091), we evaluated common psychiatric (CPG) factor-based polygenic scores (PRSs) compared to standard disorder-specific PRSs. The CPG PRS consistently outperformed in predicting individual disorder risk, explaining 1.07 24.6 times more phenotypic variance across 11 conditions. Meanwhile, many PRSs retained independent but smaller contributions, highlighting complementary nature shared and risk. While alternative multi-factor models improved model fit, provided comparable or superior predictive performance most disorders, including overall comorbidity burden. Cross-ancestry analyses however revealed notable limitations European-centric GWAS datasets for other populations due ancestral differences architecture. These findings underscore potential value genetics while need equitable

Language: Английский

Transdiagnostic Polygenic Risk Models for Psychopathology and Comorbidity: Cross-Ancestry Analysis in the All of Us Research Program DOI Creative Commons
Phil H. Lee, Jae-Yoon Jung,

Brandon T. Sanzo

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 27, 2025

Psychiatric disorders exhibit substantial genetic overlap, raising questions about the utility of transdiagnostic risk models. Using data from All Us Research Program (N=102,091), we evaluated common psychiatric (CPG) factor-based polygenic scores (PRSs) compared to standard disorder-specific PRSs. The CPG PRS consistently outperformed in predicting individual disorder risk, explaining 1.07 24.6 times more phenotypic variance across 11 conditions. Meanwhile, many PRSs retained independent but smaller contributions, highlighting complementary nature shared and risk. While alternative multi-factor models improved model fit, provided comparable or superior predictive performance most disorders, including overall comorbidity burden. Cross-ancestry analyses however revealed notable limitations European-centric GWAS datasets for other populations due ancestral differences architecture. These findings underscore potential value genetics while need equitable

Language: Английский

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