Nature CommunicationsGeneticsPeer-reviewed journal article
Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals
Kira J. StanzickiD, Yong LiiD, Pascal SchlosseriD, Mathias GorskiiD, Matthias WuttkeiD, Laurent F. ThomasiD, Humaira RasheediD, Bryce X. RowaniD, Sarah E. GrahamiD, Brett R. Vanderweff, Snehal B. PatiliD, VA Million Veteran Program, Cassianne Robinson‐CoheniD, J. Michael GazianoiD, Christopher J. O’DonnelliD, Cristen J. WilleriD, Stein Ivar HallaniD, Bjørn Olav ÅsvoldiD, André Gessner, Adriana M. HungiD, Cristian PattaroiD, Anna KöttgeniD, Klaus J. StarkiD, Iris M. HeidiD, Thomas W. WinkleriD
Abstract
Chronic kidney disease (CKD) has a complex genetic underpinning. Genome-wide association studies (GWAS) of CKD-defining glomerular filtration rate (GFR) have identified hundreds of loci, but prioritization of variants and genes is challenging. To expand and refine GWAS discovery, we meta-analyzed GWAS data for creatinine-based estimated GFR (eGFRcrea) from the Chronic Kidney Disease Genetics Consortium (CKDGen, n=765,348, trans-ethnic) and UK Biobank (UKB, n=436,581, Europeans). The results (i) extend the number of eGFRcrea loci (424 loci; 201 novel; 8.9% eGFRcrea variance explained by 634 independent signals); (ii) improve fine-mapping resolution (138 99% credible sets with [≤]5 variants, 44 single-variant sets); (iii) ascertain likely kidney function relevance for 343 loci (consistent association with alternative biomarkers); and (iv) highlight 34 genes with strong evidence by a systematic Gene PrioritiSation (GPS). We provide a sortable, searchable and customizable GPS tool to navigate through the in silico functional evidence and select relevant targets for functional investigations.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- research focus: benchmarking
- approach: statistical model
- Citations
- 304
- FWCI
- 8.18
- Field percentile
- top 1%
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