So far, multi-ethnic work has been slow in most disease areas54, limiting even the opportunity to assess PRS in non-European cohorts. Nonetheless, some previous work has assessed prediction accuracy across diverse populations in several traits and diseases for which GWAS summary statistics are available and identified large disparities across populations (Supplementary Note). These disparities are not simply methodological issues, as various approaches (e.g. pruning and thresholding versus LDPred) and accuracy metrics (R2 for quantitative traits and various pseudo-R2 metrics for binary traits) illustrate this consistently poorer performance in populations distinct from discovery samples across a range of polygenic traits (Supplementary Table 1). These assessments are becoming increasingly feasible with the growth and public availability of global bio banks as well as diversifying priorities from funding agencies55,56. We assessed how prediction accuracy decayed across globally diverse populations for 17 anthropometric and blood panel traits in the UK Bio bank (UKBB) when using European-derived summary statistics (Supplementary Note). Consistent with previous studies, we find that relative to European prediction accuracy, genetic prediction accuracy was far lower in other populations: 1.6-fold lower in
