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• W3182222456 abstract "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." @default.
• W3182222456 created "2021-07-19" @default.
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• W3182222456 date "2021-07-16" @default.
• W3182222456 modified "2023-10-14" @default.
• W3182222456 title "Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals" @default.
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• W3182222456 doi "https://doi.org/10.1038/s41467-021-24491-0" @default.
• W3182222456 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8285412" @default.
• W3182222456 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34272381" @default.

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