Here we present PRS-CSx, an extension of PRS-CS19, that improves cross-population polygenic prediction by jointly modeling GWAS summary statistics from multiple populations. We compare the predictive performance of PRS-CSx with existing PRS construction methods across traits with a wide range of genetic architectures, cross-population genetic overlaps, and discovery GWAS sample sizes via simulations. We further apply PRS-CSx to predict quantitative traits using data from the UK Biobank (UKBB)28, Biobank Japan (BBJ)29,30, the Population Architecture using Genomics and Epidemiology Consortium (PAGE) study31 and the Taiwan Biobank (TWB)32,33, and predict schizophrenia risk using cohorts of European and East Asian ancestries15,34.
