Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.
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., Ärnlöv J., Åsvold BO., 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 MA., Josyula NS., Jung B., Kähönen M., Karabegović I., Khor C-C., Koenig W., Kramer H., Krämer BK., Kühnel B., Kuusisto J., Laakso M., Lange LA., Lehtimäki T., Li M., Lieb W., Lifelines cohort study None., Lind L., Lindgren CM., Loos RJF., Lukas MA., 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.
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.