Improved understanding of the proteome can facilitate the identification of causal mechanisms for complex traits. We conducted a comprehensive analysis of the common variant cis-regulatory genetic architecture of 4,665 plasma proteins from 7,213 European Americans (EA) and 1,871 African Americans (AA) from the Atherosclerosis Risk in Communities (ARIC) cohort study. We identified and fine-mapped 1,992 plasma proteins in EA and 1,605 in AA, which had significant cis-single-nucleotide polymorphism (SNP) associations. Estimates of cis-heritability (cis-h 2 ) for plasma proteins were similar across EA and AA (median cis-h 2 =0.09 for EA and 0.10 for AA).Elastic-net-based models for cis-SNP-based protein prediction produced high accuracy (median R 2 /cis-h 2 =0.79 for EA and 0.69 for AA). We illustrate the application of these models to conduct proteome-wide association studies (PWAS) for two related complex traits, serum urate and gout, and further conduct conditional analyses to interpret findings in the context of those from transcriptome-wide association studies (TWAS).

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.

Chronic kidney disease (CKD) is defined by reduced estimated glomerular filtration rate (eGFR). Previous genetic studies have implicated regulatory mechanisms contributing to CKD. Here we present epigenome-wide association studies of eGFR and CKD using whole-blood DNA methylation of 2264 ARIC Study and 2595 Framingham Heart Study participants to identify epigenetic signatures of kidney function. Of 19 CpG sites significantly associated (P < 1e-07) with eGFR/CKD and replicated, five also associate with renal fibrosis in biopsies from CKD patients and show concordant DNA methylation changes in kidney cortex. Lead CpGs at PTPN6/PHB2, ANKRD11, and TNRC18 map to active enhancers in kidney cortex. At PTPN6/PHB2 cg19942083, methylation in kidney cortex associates with lower renal PTPN6 expression, higher eGFR, and less renal fibrosis. The regions containing the 243 eGFR-associated (P < 1e-05) CpGs are significantly enriched for transcription factor binding sites of EBF1, EP300, and CEBPB (P < 5e-6). Our findings highlight kidney function associated epigenetic variation.