Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals.
Kira J StanzickYong LiPascal SchlosserMathias GorskiMatthias WuttkeLaurent F ThomasHumaira RasheedBryce X RowanSarah E GrahamBrett R VanderweffSnehal B Patilnull nullCassiane Robinson-CohenJohn M GazianoChristopher J O'DonnellCristen J WillerStein HallanBjørn Olav ÅsvoldAndre GessnerAdriana M HungCristian PattaroAnna KottgenKlaus J StarkIris M HeidThomas W WinklerPublished in: Nature communications (2021)
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.
Keyphrases
- genome wide
- copy number
- genome wide association
- genome wide identification
- dna methylation
- systematic review
- small cell lung cancer
- chronic kidney disease
- bioinformatics analysis
- high resolution
- air pollution
- genome wide analysis
- genome wide association study
- epidermal growth factor receptor
- case control
- gene expression
- small molecule
- metabolic syndrome
- meta analyses
- high density
- uric acid
- transcription factor
- end stage renal disease
- mass spectrometry