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Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.
Wednesday,2022-07-20 21:03 America/Los_Angeles — ecterry
| Title | Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Authors | Gorski, M, Rasheed, H, Teumer, A, Thomas, LF, Graham, SE, Sveinbjornsson, G, Winkler, TW, Günther, F, Stark, KJ, Chai, J-F, Tayo, BO, Wuttke, M, Li, Y, Tin, A, Ahluwalia, TS, Arnlöv, J, Åsvold, BOlav, Bakker, SJL, Banas, B, Bansal, N, Biggs, ML, Biino, G, Böhnke, M, Boerwinkle, E, Bottinger, EP, Brenner, H, Brumpton, B, Carroll, RJ, Chaker, L, Chalmers, J, Chee, M-L, Chee, M-L, Cheng, C-Y, Chu, AY, Ciullo, M, Cocca, M, Cook, JP, Coresh, J, Cusi, D, de Borst, MH, Degenhardt, F, Eckardt, K-U, Endlich, K, Evans, MK, Feitosa, MF, Franke, A, Freitag-Wolf, S, Fuchsberger, C, Gampawar, P, Gansevoort, RT, Ghanbari, M, Ghasemi, S, Giedraitis, V, Gieger, C, Gudbjartsson, DF, 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, AM, Josyula, NShilpa, Jung, B, Kähönen, M, Karabegović, I, Khor, C-C, Koenig, W, Kramer, H, Krämer, BK, Kuhnel, B, Kuusisto, J, Laakso, M, Lange, LA, Lehtimäki, T, Li, M, Lieb, W, Lind, L, Lindgren, CM, Loos, RJF, Lukas, MAnn, Lyytikäinen, L-P, Mahajan, A, Matias-Garcia, PR, Meisinger, C, Meitinger, T, Melander, O, Milaneschi, Y, Mishra, PP, Mononen, N, Morris, AP, Mychaleckyj, JC, Nadkarni, GN, Naito, M, Nakatochi, M, Nalls, MA, Nauck, M, Nikus, K, Ning, B, Nolte, IM, Nutile, T, O'Donoghue, ML, O'Connell, J, Olafsson, I, Orho-Melander, M, Parsa, A, Pendergrass, SA, Penninx, BWJH, Pirastu, M, Preuss, MH, Psaty, BM, Raffield, LM, Raitakari, OT, Rheinberger, M, Rice, KM, Rizzi, F, Rosenkranz, AR, Rossing, P, Rotter, JI, Ruggiero, D, Ryan, KA, Sabanayagam, C, Salvi, E, Schmidt, H, Schmidt, R, Scholz, M, Schöttker, B, Schulz, C-A, Sedaghat, S, Shaffer, CM, Sieber, KB, Sim, X, Sims, M, Snieder, H, Stanzick, KJ, Thorsteinsdottir, U, Stocker, H, Strauch, K, Stringham, HM, Sulem, P, Szymczak, S, Taylor, KD, Thio, CHL, Tremblay, J, Vaccargiu, S, van der Harst, P, van der Most, PJ, Verweij, N, Völker, U, Wakai, K, Waldenberger, M, Wallentin, L, Wallner, S, Wang, J, Waterworth, DM, White, HD, Willer, CJ, Wong, T-Y, Woodward, M, Yang, Q, Yerges-Armstrong, LM, Zimmermann, M, Zonderman, AB, Bergler, T, Stefansson, K, Böger, CA, Pattaro, C, Köttgen, A, Kronenberg, F, Heid, IM |
| Corporate/Institutional Authors | LifeLines Cohort Study, |
| Journal | Kidney Int |
| Date Published | 2022 Jun 16 |
| ISSN | 1523-1755 |
| Abstract | <p>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.</p> |
| DOI | 10.1016/j.kint.2022.05.021 |
| Alternate Journal | Kidney Int |
| PubMed ID | 35716955 |
ePub date:
22/06