Bridging the diversity gap: Analytical and study design considerations for improving the accuracy of trans-ancestry genetic prediction.

ABSTRACT: Genetic prediction of common complex disease risk is an essential component of precision medicine. Currently, genome-wide association studies (GWASs) are mostly composed of European-ancestry samples and resulting polygenic scores (PGSs) have been shown to poorly transfer to other ancestries partly due to heterogeneity of allelic effects between populations. Fixed-effects (FETA) and random-effects (RETA) trans-ancestry meta-analyses do not model such ancestry-related heterogeneity, while ancestry-specific (AS) scores may suffer from low power due to low sample sizes. In contrast, trans-ancestry meta-regression (TAMR) builds ancestry-aware PGS that account for more complex trans-ancestry architectures. Here, we examine the predictive performance of these four PGSs under multiple genetic arch

SUBMITTER: Bocher O 

PROVIDER: S-EPMC10336686 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature