The prerequisite data for dramatically increasing diversity also hypothetically exist in several large-scale publicly funded datasets such as the Million Veterans Project and Trans-Omics for Precision Medicine (TOP Med), but with problematic data access issues in which even GWAS summary data within and across populations are not publicly shared. Existing GWAS consortia also need to carefully consider the granularity of summary statistics they release, as finer scale continental ancestries and phenotypes in large, multi-ethnic projects enable ancestry-matched analyses not possible with a single set of summary statistics. While there is an understandable patient privacy balance to strike when sharing individual-level data, GWAS summary statistics from all publicly funded and as many privately funded projects as possible should be made easily and publicly accessible to improve global health outcomes. Efforts to unify phenotype definitions, normalization approaches, and GWAS methods among studies will also improve comparability.
