selection using EA GWAS is generally appropriate. Moreover, for platelet count, diastolic blood pressure, and pulse pressure, EA selection worked better with HCHS/SOL weights. In simulations, this happened when either the LD of the selected SNP with the causal one was higher in ADM, or when the selected SNP was more frequent in ADM. Both phenomena can be related to natural selection (Slatkin (2008), and recent work from Guo et al. (2018), which investigated natural selection evidence for complex traits). It is an important avenue for future research to study the evidence of natural selection in admixed populations by phenotypes, and its implication for construction of PRSs. Finally, in simulation studies, SNP selection by META performed well, but not in data analysis. In Tables S6-S7 in the Supplementary Material, we demonstrate that the poor performance of META selection in the data analysis is due to the use of an EA reference panel for clumping. When we pruned SNPs based on base-pair distance instead of LD-clumped, META-based selection performed well, and better than EA-based PRSs (that clumped SNPs) for blood pressure and blood count traits, and worse for anthropometric traits.
