PuSH - Publikationsserver des Helmholtz Zentrums München

Gorski, M.* ; Rasheed, H.* ; Teumer, A.* ; Thomas, L.F.* ; Graham, S.E.* ; Sveinbjornsson, G.* ; Winkler, T.W.* ; Günther, F.* ; Stark, K.J.* ; Chai, J.F.* ; Tayo, B.O.* ; Wuttke, M.* ; Li, Y.* ; Tin, A.* ; Ahluwalia, T.S.* ; Ärnlöv, J.* ; Asvold, B.O.* ; Bakker, S.J.L.* ; Banas, B.* ; Bansal, N.* ; Biggs, M.L.* ; Biino, G.* ; Böhnke, M.* ; Boerwinkle, E.* ; Bottinger, E.P.* ; Brenner, H.* ; Brumpton, B.M.* ; Carroll, R.J.* ; Chaker, L.* ; Chalmers, J.* ; Chee, M.L.* ; Cheng, C.Y.* ; Chu, A.Y.* ; Ciullo, M.* ; Cocca, M.* ; Cook, J.P.* ; Coresh, J.* ; Cusi, D.* ; de Borst, M.H.* ; Degenhardt, F.* ; Eckardt, K.U.* ; Endlich, K.* ; Evans, M.K.* ; Feitosa, M.F.* ; Franke, A.* ; Freitag-Wolf, S.* ; Fuchsberger, C.* ; Gampawar, P.* ; Gansevoort, R.T.* ; Ghanbari, M.* ; Ghasemi, S.* ; Giedraitis, V.* ; Gieger, C. ; Gudbjartsson, D.F.* ; Hallan, S.* ; Hamet, P.* ; Hishida, A.* ; Ho, K.* ; Hofer, E.* ; Holleczek, B.* ; Holm, H.* ; Hoppmann, A.* ; Horn, K.* ; Hutri-Kähönen, N.* ; Hveem, K.* ; Hwang, S.J.* ; Ikram, M.A.* ; Josyula, N.S.* ; Jung, B.* ; Kähönen, M.* ; Karabegović, I.* ; Khor, C.C.* ; Koenig, W.* ; Kramer, H.* ; Krämer, B.K.* ; Kühnel, B. ; Kuusisto, J.* ; Laakso, M.* ; Lange, L.A.* ; Lehtimäki, T.* ; Li, M.* ; Lieb, W.* ; Lifelines Cohort Study* ; Lind, L.* ; Lindgren, C.M.* ; Loos, R.J.F.* ; Lukas, M.A.* ; Lyytikäinen, L.P.* ; Mahajan, A.* ; Matias-Garcia, P.R. ; Meisinger, C. ; Meitinger, T. ; Melander, O.* ; Milaneschi, Y.* ; Mishra, P.P.* ; Mononen, N.* ; Morris, A.P.* ; Mychaleckyj, J.C.* ; Nadkarni, G.N.* ; Naito, M.* ; Nakatochi, M.* ; Nalls, M.A.* ; Nauck, M.* ; Nikus, K.* ; Ning, B.* ; Nolte, I.M.* ; Nutile, T.* ; O'Donoghue, M.L.* ; O'Connell, J.* ; Olafsson, I.* ; Orho-Melander, M.* ; Parsa, A.* ; Pendergrass, S.A.* ; Penninx, B.W.J.H.* ; Pirastu, M.* ; Preuss, M.H.* ; Psaty, B.M.* ; Raffield, L.M.* ; Raitakari, O.T.* ; Rheinberger, M.* ; Rice, K.M.* ; Rizzi, F.* ; Rosenkranz, A.R.* ; Rossing, P.* ; Rotter, J.I.* ; Ruggiero, D.* ; Ryan, K.A.* ; Sabanayagam, C.* ; Salvi, E.* ; Schmidt, H.* ; Schmidt, R.* ; Scholz, M.* ; Schöttker, B.* ; Schulz, C.A.* ; Sedaghat, S.* ; Shaffer, C.M.* ; Sieber, K.B.* ; Sim, X.* ; Sims, M.* ; Snieder, H.* ; Stanzick, K.J.* ; Thorsteinsdottir, U.* ; Stocker, H.R.* ; Strauch, K. ; Stringham, H.M.* ; Sulem, P.* ; Szymczak, S.* ; Taylor, K.D.* ; Thio, C.H.L.* ; Tremblay, J.* ; Vaccargiu, S.* ; van der Harst, P.* ; van der Most, P.J.* ; Verweij, N.* ; Völker, U.* ; Wakai, K.* ; Waldenberger, M. ; Wallentin, L.* ; Wallner, S.* ; Wang, J.* ; Waterworth, D.M.* ; White, H.D.* ; Willer, C.J.* ; Wong, T.Y.* ; Woodward, M.* ; Yang, Q.* ; Yerges-Armstrong, L.M.* ; Zimmermann, M.* ; Zonderman, A.B.* ; Bergler, T.* ; Stefansson, K.* ; Böger, C.A.* ; Pattaro, C.* ; Köttgen, A.* ; Kronenberg, F.* ; Heid, I.M.*

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

Kidney Int. 102, 624-639 (2022)
Postprint Forschungsdaten DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
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.
Altmetric
Weitere Metriken?
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Acute Kidney Injury ; Chronic Kidney Disease ; Diabetes ; Gene Expression
ISSN (print) / ISBN 0085-2538
e-ISSN 1523-1755
Zeitschrift Kidney International
Quellenangaben Band: 102, Heft: 3, Seiten: 624-639 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Förderungen UK Biobank
Deutsche Forschungsgemeinschaft DFG