Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies

Lifelines Cohort Study, Mathias Gorski*, Humaira Rasheed, Alexander Teumer, Laurent F Thomas, Sarah E Graham, Gardar Sveinbjornsson, Thomas W Winkler, Felix Günther, Klaus J Stark, Jin-Fang Chai, Bamidele O Tayo, Matthias Wuttke, Yong Li, Adrienne Tin, Tarunveer S Ahluwalia, Johan Ärnlöv, Bjørn Olav Åsvold, Stephan J L Bakker, Bernhard BanasNisha Bansal, Mary L Biggs, Ginevra Biino, Michael Böhnke, Eric Boerwinkle, Erwin P Bottinger, Hermann Brenner, Ben Brumpton, Robert J Carroll, Layal Chaker, John Chalmers, Miao-Li Chee, Miao-Ling Chee, Ching-Yu Cheng, Audrey Y Chu, Marina Ciullo, Massimiliano Cocca, James P Cook, Josef Coresh, Daniele Cusi, Martin H de Borst, Frauke Degenhardt, Kai-Uwe Eckardt, Ron T Gansevoort, Ilja M Nolte, Brenda W J H Penninx, Harold Snieder, Chris H L Thio, Pim van der Harst, Peter J van der Most, Niek Verweij

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)
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Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.

Original languageEnglish
Pages (from-to)624-639
Number of pages16
JournalKidney International
Issue number3
Early online date15-Jun-2022
Publication statusPublished - Sept-2022


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