In this study, we conducted a genetic analysis of kidney function, as measured by the estimated glomerular filtration rate based on serum creatinine (eGFRcrea), by integrating millions of individuals from 19 cohorts. We developed a catalog of eGFRcrea associations genome-wide for European-ancestry (n= 1,785,582), East Asian-ancestry (n = 282,852), African-ancestry populations (n = 67,943) as well as across all ancestries (n = 2,287,877). Within the multi-ancestry GWAS, we identified 99,595 genome-wide significant variants (P < 5E-8) in 1,026 independent loci (97 novel).

Further, we have generated Kidney Disease Genetic Scorecard, a multitude of multi-omics datasets for the annotation of regulatory variants, encompassing 32 kinds of genetic evidence including ASE, bASA, snASA, Open4Gene links, and coding variants. This strategy enabled us to prioritize 601 genes targeted by both regulatory variants and coding variants, including 161 genes with convergence of two kinds of variants.