Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies
Mathias Gorski, Humaira Rasheed, Alexander Teumer, Laurent Thomas, Sarah Graham, Gardar Sveinbjornsson, Thomas Winkler, Felix Günther, Klaus Stark, Jin-Fang Chai, Bamidele Tayo, Matthias Wuttke, Yong Li, Adrienne Tin, Tarunveer Ahluwalia, Johan Ärnlöv, Bjørn Åsvold, Stephan Bakker, Bernhard Banas, Nisha Bansal, Mary Biggs, Ginevra Biino, Michael Böhnke, Eric Boerwinkle, Erwin Bottinger, Hermann Brenner, Ben Brumpton, Robert Carroll, Layal Chaker, John Chalmers, Miao-Li Chee, Miao-Ling Chee, Ching-Yu Cheng, Audrey Chu, Marina Ciullo, Massimiliano Cocca, James Cook, Josef Coresh, Daniele Cusi, Martin Borst, Frauke Degenhardt, Kai-Uwe Eckardt, Karlhans Endlich, Michele Evans, Mary Feitosa, Andre Franke, Sandra Freitag-Wolf, Christian Fuchsberger, Piyush Gampawar, Ron Gansevoort, Mohsen Ghanbari, Sahar Ghasemi, Vilmantas Giedraitis, Christian Gieger, Daniel Gudbjartsson, Stein Hallan, Pavel Hamet, Asahi Hishida, Kevin Ho, Edith Hofer, Bernd Holleczek, Hilma Holm, Anselm Hoppmann, Katrin Horn, Nina Hutri-Kähönen, Kristian Hveem, Shih-Jen Hwang, M. Ikram, Navya Josyula, Bettina Jung, Mika Kähönen, Irma Karabegović, Chiea-Chuen Khor, Wolfgang Koenig, Holly Kramer, Bernhard Krämer, Brigitte Kühnel, Johanna Kuusisto, Markku Laakso, Leslie Lange, Terho Lehtimäki, Man Li, Wolfgang Lieb, Lars Lind, Cecilia Lindgren, Ruth Loos, Mary Lukas, Leo-Pekka Lyytikäinen, Anubha Mahajan, Pamela Matias-Garcia, Christa Meisinger, Thomas Meitinger, Olle Melander, Yuri Milaneschi, Pashupati Mishra, Nina Mononen, Andrew Morris, Josyf Mychaleckyj, Girish Nadkarni, Mariko Naito, Masahiro Nakatochi, Mike Nalls, Matthias Nauck, Kjell Nikus, Boting Ning, Ilja Nolte, Teresa Nutile, Michelle O'Donoghue, Jeffrey O'Connell, Isleifur Olafsson, Marju Orho-Melander, Afshin Parsa, Sarah Pendergrass, Penninx, Brenda W J H, Mario Pirastu, Michael Preuss, Bruce Psaty, Laura Raffield, Olli Raitakari, Myriam Rheinberger, Kenneth Rice, Federica Rizzi, Alexander Rosenkranz, Peter Rossing, Jerome Rotter, Daniela Ruggiero, Kathleen Ryan, Charumathi Sabanayagam, Erika Salvi, Helena Schmidt, Reinhold Schmidt, Markus Scholz, Ben Schöttker, Christina-Alexandra Schulz, Sanaz Sedaghat, Christian Shaffer, Karsten Sieber, Xueling Sim, Mario Sims, Harold Snieder, Kira Stanzick, Unnur Thorsteinsdottir, Hannah Stocker, Konstantin Strauch, Heather Stringham, Patrick Sulem, Silke Szymczak, Kent Taylor, Chris Thio, Johanne Tremblay, Simona Vaccargiu, van der Harst, Pim, van der Most, Peter J, Niek Verweij, Uwe Völker, Kenji Wakai, Melanie Waldenberger, Lars Wallentin, Stefan Wallner, Judy Wang, Dawn Waterworth, Harvey White, Cristen Willer, Tien-Yin Wong, Mark Woodward, Qiong Yang, Laura Yerges-Armstrong, Martina Zimmermann, Alan Zonderman, Tobias Bergler, Kari Stefansson, Carsten Böger, Cristian Pattaro, Anna Köttgen, Florian Kronenberg, Iris Heid
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.