Of the case-control studies in the meta-analysis of European cohorts, 48 provided individual level data for analysis of which 43 were available for polygenic scoring. For these cohorts, we conducted a leave-one-cohort out GWAS meta-analysis to allow generation of polygenic scores (PGS) in the left-out target sample. Given a high variation in the effective sample size contributing to each SNP, we restricted to the set of SNPs with (Neff) ≥ max(Neff)*0.8, minor allele frequency > 0.05 and INFO > 0.75 in the full multi-ancestry analysis, resulting in 4.34 million SNPs. Preliminary analyses using the QC tool DENTIST42 justified this choice. We generated polygenic scores (PGS) on all individuals using two methods. A PGS is the sum of risk alleles weighted by the risk allele effect size; methods differ in the SNPs included and the effect sizes applied. To enable comparisons with previous publications, PGS were generated using the basic p-value clumping and thresholding (P+CT) method (LD clumping r2 threshold of 0.1, clump window of 500kb, 10 p-value thresholds). We also generated PGS using SBayesR,20 which is one of several methods
