available. We chose to focus this study on EUR and EAS populations, as there is a very limited number of large GWAS in populations other than EUR and EAS1,40,41. As blood quantitative trait GWAS and disease GWAS were available from BBJ, we sought to collect matching EUR GWAS datasets to maximize phenotype overlap between populations. We included studies where cases were diagnosed by a physician and excluded studies which utilized self-reported cases, aiming to prepare comparable phenotypes between EAS and EUR GWAS. We downloaded such data from RIKEN, the Neale Lab and the GWAS Catalog. In summary, we collected summary statistics of 42 EAS and 69 EUR GWAS. All summary statistics used had an observed scale heritability z-score >1.96 as estimated by S-LDSC. All GWAS summary statistics were reformatted to be compatible with S-LDSC (see below) and thus contained the following information for each SNP (per row): rsID, A1 (reference allele), A2 (alternative allele), GWAS sample size (effective sample size per SNP, may vary with genotyping), chi-square statistic, z-score. For trans-ancestry genetic correlation and polygenic risk score prediction, all GWAS summary statistics were reformatted to contain the SNP ID (chr_position_A1_A2), chromosome, base pair, A1, A2, effect size estimate, effect size
