Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies
Gorski, Mathias; Rasheed, Humaira; Teumer, Alexander; Thomas, Laurent F.; Graham, Sarah E.; Sveinbjornsson, Gardar; Winkler, Thomas W.; Günther, Felix; Stark, Klaus J.; Chai, Jin Fang; Tayo, Bamidele O.; Wuttke, Matthias; Li, Yong; Tin, Adrienne; Ahluwalia, Tarunveer S.; Ärnlöv, Johan; Åsvold, Bjørn Olav; Bakker, Stephan J.L.; Banas, Bernhard; Bansal, Nisha; Biggs, Mary L.; Biino, Ginevra; Böhnke, Michael; Boerwinkle, Eric; Bottinger, Erwin P.; Brenner, Hermann; Brumpton, Ben; Carroll, Robert J.; Chaker, Layal; Chalmers, John; Chee, Miao Li; Chee, Miao Ling; Cheng, Ching Yu; Chu, Audrey Y.; Ciullo, Marina; Cocca, Massimiliano; Cook, James P.; Coresh, Josef; Cusi, Daniele; de Borst, Martin H.; Degenhardt, Frauke; Eckardt, Kai Uwe; Hutri-Kähönen, Nina; Kähönen, Mika; Kuusisto, Johanna; Lehtimäki, Terho; Lyytikäinen, Leo Pekka; Mishra, Pashupati P.; Mononen, Nina; Nikus, Kjell (2022)
Gorski, Mathias
Rasheed, Humaira
Teumer, Alexander
Thomas, Laurent F.
Graham, Sarah E.
Sveinbjornsson, Gardar
Winkler, Thomas W.
Günther, Felix
Stark, Klaus J.
Chai, Jin Fang
Tayo, Bamidele O.
Wuttke, Matthias
Li, Yong
Tin, Adrienne
Ahluwalia, Tarunveer S.
Ärnlöv, Johan
Åsvold, Bjørn Olav
Bakker, Stephan J.L.
Banas, Bernhard
Bansal, Nisha
Biggs, Mary L.
Biino, Ginevra
Böhnke, Michael
Boerwinkle, Eric
Bottinger, Erwin P.
Brenner, Hermann
Brumpton, Ben
Carroll, Robert J.
Chaker, Layal
Chalmers, John
Chee, Miao Li
Chee, Miao Ling
Cheng, Ching Yu
Chu, Audrey Y.
Ciullo, Marina
Cocca, Massimiliano
Cook, James P.
Coresh, Josef
Cusi, Daniele
de Borst, Martin H.
Degenhardt, Frauke
Eckardt, Kai Uwe
Hutri-Kähönen, Nina
Kähönen, Mika
Kuusisto, Johanna
Lehtimäki, Terho
Lyytikäinen, Leo Pekka
Mishra, Pashupati P.
Mononen, Nina
Nikus, Kjell
2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202208206577
https://urn.fi/URN:NBN:fi:tuni-202208206577
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [19817]