All of Us diversity and scale improve polygenic prediction contextually with greatest improvements for under-represented populations.

ABSTRACT: Recent studies have demonstrated that polygenic risk scores (PRS) trained on multi-ancestry data can improve prediction accuracy in groups historically underrepresented in genomic studies, but the availability of linked health and genetic data from large-scale diverse cohorts representative of a wide spectrum of human diversity remains limited. To address this need, the All of Us research program (AoU) generated whole-genome sequences of 245,388 individuals (release v7) who collectively reflect the diversity of the USA. Leveraging this resource and another widely-used population-scale biobank, the UK Biobank (UKB) with a half million participants, we developed PRS trained on multi-ancestry and multi-biobank data with up to ~750,000 participants for 32 common, complex traits and diseases ac

SUBMITTER: Tsuo K 

PROVIDER: S-EPMC11326295 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature