Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals

Nat Commun. 2021 Jul 16;12(1):4350. doi: 10.1038/s41467-021-24491-0.


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.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biomarkers
  • Creatinine / blood
  • Cystatins / pharmacology
  • Databases, Genetic
  • Europe
  • Gene Expression Regulation / genetics
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study
  • Glomerular Filtration Rate / genetics*
  • Humans
  • Kidney / metabolism*
  • Kidney / physiology
  • Organ Specificity
  • Quantitative Trait Loci
  • RNA-Seq
  • Renal Insufficiency, Chronic / genetics
  • Renal Insufficiency, Chronic / metabolism*
  • Risk Factors
  • Single-Cell Analysis


  • Biomarkers
  • Cystatins
  • Creatinine