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

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 Banas, Nisha BansalMary 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, Nina Hutri-Kähönen, Mika Kähönen, Johanna Kuusisto, Terho Lehtimäki, Leo Pekka Lyytikäinen, Pashupati P. Mishra, Nina Mononen, Kjell Nikus

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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
Issue number3
Publication statusPublished - 2022
Publication typeA1 Journal article-refereed


  • acute kidney injury
  • chronic kidney disease
  • diabetes
  • gene expression

Publication forum classification

  • Publication forum level 2

ASJC Scopus subject areas

  • Nephrology


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