| Title: |
Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies |
| Authors: |
Gorski, M; Rasheed, H; Teumer, A; Thomas, LF; Graham, SE; Sveinbjornsson, G; Winkler, TW; Günther, F; Stark, KJ; Chai, JF; 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, ML; Cheng, CY; Chu, AY; Ciullo, M; Cocca, M; Cook, JP; Coresh, J; Cusi, D; de Borst, MH; Degenhardt, F; Eckardt, KU; 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, SJ; Ikram, MA; Josyula, NS; Jung, B; Kähönen, M; Karabegović, I; Khor, CC; Koenig, W; Kramer, H; Krämer, BK; Kühnel, B; Kuusisto, J; Laakso, M; Lange, LA; Lehtimäki, T; Li, M; Lieb, W; Lind, L; Lindgren, CM; Loos, RJF; Lukas, MA; Lyytikäinen, LP; 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; Woodward, Mark |
| Source: |
urn:ISSN:0085-2538 ; urn:ISSN:1523-1755 ; Kidney International, 102, 3, 624-639 |
| Publisher Information: |
Elsevier |
| Publication Year: |
2022 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
32 Biomedical and Clinical Sciences; 3202 Clinical Sciences; Human Genome; Kidney Disease; Clinical Research; Prevention; Genetics; 2.1 Biological and endogenous factors; Renal and urogenital; Cross-Sectional Studies; Genetic Loci; Genome-Wide Association Study; Glomerular Filtration Rate; Humans; Kidney; Longitudinal Studies; N-Acetylgalactosaminyltransferases; Renal Insufficiency; Chronic; acute kidney injury; chronic kidney disease; diabetes; gene expression; Lifelines Cohort Study; anzsrc-for: 32 Biomedical and Clinical Sciences; anzsrc-for: 3202 Clinical Sciences; anzsrc-for: 1103 Clinical Sciences |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/unsworks_82805; https://doi.org/10.1016/j.kint.2022.05.021 |
| DOI: |
10.1016/j.kint.2022.05.021 |
| Availability: |
https://hdl.handle.net/1959.4/unsworks_82805; https://unsworks.unsw.edu.au/bitstreams/90b52fba-aae6-4be1-9833-ba52f9f45a0b/download; https://doi.org/10.1016/j.kint.2022.05.021 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY ; https://creativecommons.org/licenses/by/4.0/ ; free_to_read |
| Accession Number: |
edsbas.22884961 |
| Database: |
BASE |