Bayesian estimation of shared polygenicity identifies drug targets and repurposable medicines for human complex diseases

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

Published: March 17, 2025

Abstract Background Complex diseases may share portions of their polygenic architectures which can be leveraged to identify drug targets with low off-target potential or repurposable candidates. However, the literature lacks methods make these inferences at scale using publicly available data. Methods We introduce a Bayesian model estimate structure trait only gene-based association test statistics from GWAS summary data and returns gene-level posterior risk probabilities (PRPs). PRPs were used infer shared polygenicity between 496 pairs we measures that prioritize effects repurposing potential. Results Across 32 traits, estimated 69.5 97.5% disease-associated genes are multiple number druggable associated single disease ranged 1 (multiple sclerosis) 59 (schizophrenia). Estimating genetic architecture ALS all other traits identified KIT gene as potentially harmful target because its deleterious triglycerides, but also TBK1 SCN11B putatively safer non-association any 31 traits. additionally found 21 candidate repourposable for Alzheimer’s (AD) (e.g., PLEKHA1, PPIB ) 5 GAK, DGKQ ). Conclusions The sets have limited generally smaller compared pleiotropic targets, both represent promising directions future experimental studies.

Language: Английский

Transdiagnostic Polygenic Risk Models for Psychopathology and Comorbidity: Cross-Ancestry Analysis in the All of Us Research Program

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

Shared genetic architecture of type 2 diabetes with muscle mass and function and frailty reveals comorbidity etiology and pleiotropic druggable targets

Metabolism, Journal Year: 2024, Volume and Issue: unknown, P. 156112 - 156112

Published: Dec. 1, 2024

Language: Английский