TY - JOUR
T1 - Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies
AU - Lifelines Cohort Study
AU - Gorski, Mathias
AU - Rasheed, Humaira
AU - Teumer, Alexander
AU - Thomas, Laurent F.
AU - Graham, Sarah E.
AU - Sveinbjornsson, Gardar
AU - Winkler, Thomas W.
AU - Günther, Felix
AU - Stark, Klaus J.
AU - Chai, Jin Fang
AU - Tayo, Bamidele O.
AU - Wuttke, Matthias
AU - Li, Yong
AU - Tin, Adrienne
AU - Ahluwalia, Tarunveer S.
AU - Ärnlöv, Johan
AU - Åsvold, Bjørn Olav
AU - Bakker, Stephan J.L.
AU - Banas, Bernhard
AU - Bansal, Nisha
AU - Biggs, Mary L.
AU - Biino, Ginevra
AU - Böhnke, Michael
AU - Boerwinkle, Eric
AU - Bottinger, Erwin P.
AU - Brenner, Hermann
AU - Brumpton, Ben
AU - Carroll, Robert J.
AU - Chaker, Layal
AU - Chalmers, John
AU - Chee, Miao Li
AU - Chee, Miao Ling
AU - Cheng, Ching Yu
AU - Chu, Audrey Y.
AU - Ciullo, Marina
AU - Cocca, Massimiliano
AU - Cook, James P.
AU - Coresh, Josef
AU - Cusi, Daniele
AU - de Borst, Martin H.
AU - Degenhardt, Frauke
AU - Eckardt, Kai Uwe
AU - Endlich, Karlhans
AU - Evans, Michele K.
AU - Feitosa, Mary F.
AU - Franke, Andre
AU - Freitag-Wolf, Sandra
AU - Fuchsberger, Christian
AU - Gampawar, Piyush
AU - Meitinger, Thomas
N1 - Publisher Copyright:
© 2022 International Society of Nephrology
PY - 2022/9
Y1 - 2022/9
N2 - 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.
AB - 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.
KW - acute kidney injury
KW - chronic kidney disease
KW - diabetes
KW - gene expression
UR - https://www.scopus.com/pages/publications/85134811540
U2 - 10.1016/j.kint.2022.05.021
DO - 10.1016/j.kint.2022.05.021
M3 - Article
C2 - 35716955
AN - SCOPUS:85134811540
SN - 0085-2538
VL - 102
SP - 624
EP - 639
JO - Kidney International
JF - Kidney International
IS - 3
ER -
SDG 3 Good Health and Well-being