Shing Wan Choi

Abstract Understanding the genetic architecture of human traits is of key biological, medical and evolutionary importance. Despite much progress, little is known about how genetic architecture varies across the trait continuum and, in particular, if it differs in the tails of complex traits, where disease often occurs.

Abstract Here we present BridgePRS, a novel Bayesian polygenic risk score (PRS) method that leverages shared genetic effects across ancestries to increase PRS portability. We evaluate BridgePRS via simulations and real UK Biobank data across 19 traits in individuals of African, South Asian and East Asian ancestry, using both UK Biobank and Biobank Japan genome-wide association study summary statistics; out-of-cohort validation is performed in the Mount Sinai (New York) BioMe biobank.

Pathway PRSs for disease stratification While genome-wide PRSs can predict genetic liability to disease because they aggregate individual predictors of disease status, it is unclear if they will be predictive of disease subtypes because they are not optimized to capture disease heterogeneity. In contrast, pathway PRSs may be well suited for disease stratification, since, in theory, the pathway PRS for any pathway that differentiates subtypes can be isolated and exploited for stratification.