Significance Statement Genome-wide association studies (GWAS) are a powerful tool to identify genetic variants associated with CKD. However, knowledge of CKD-relevant target tissues and cell types important in the pathogenesis is incomplete. Integrating large-scale kidney function GWAS with gene expression datasets identified kidney and liver as the primary organs for kidney function traits. In the kidney, proximal tubule was the critical cell type for eGFR and urate, as well as for monogenic electrolyte or metabolic disease genes. Podocytes showed enrichment of genes implicated in glomerular disease. Compendia connecting traits, genes, and cell types allow further prioritization of genes in GWAS loci, enabling mechanistic studies. Background Genetic variants identified in genome-wide association studies (GWAS) are often not specific enough to reveal complex underlying physiology. By integrating RNA-seq data and GWAS summary statistics, novel computational methods allow unbiased identification of trait-relevant tissues and cell types. Methods The CKDGen consortium provided GWAS summary data for eGFR, urinary albumin-creatinine ratio (UACR), BUN, and serum urate. Genotype-Tissue Expression Project (GTEx) RNA-seq data were used to construct the top 10% specifically expressed genes for each of 53 tissues followed by linkage disequilibrium (LD) score–based enrichment testing for each trait. Similar procedures were performed for five kidney single-cell RNA-seq datasets from humans and mice and for a microdissected tubule RNA-seq dataset from rat. Gene set enrichment analyses were also conducted for genes implicated in Mendelian kidney diseases. Results Across 53 tissues, genes in kidney function–associated GWAS loci were enriched in kidney ( P =9.1E-8 for eGFR; P =1.2E-5 for urate) and liver ( P =6.8·10 -5 for eGFR). In the kidney, proximal tubule was enriched in humans ( P =8.5E-5 for eGFR; P =7.8E-6 for urate) and mice ( P =0.0003 for eGFR; P =0.0002 for urate) and confirmed as the primary cell type in microdissected tubules and organoids. Gene set enrichment analysis supported this and showed enrichment of genes implicated in monogenic glomerular diseases in podocytes. A systematic approach generated a comprehensive list of GWAS genes prioritized by cell type–specific expression. Conclusions Integration of GWAS statistics of kidney function traits and gene expression data identified relevant tissues and cell types, as a basis for further mechanistic studies to understand GWAS loci.