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@ARTICLE{Gorski:180380,
author = {M. Gorski and H. Rasheed and A. Teumer and L. F. Thomas and
S. E. Graham and G. Sveinbjornsson and T. W. Winkler and F.
Günther and K. J. Stark and J.-F. Chai and B. O. Tayo and
M. Wuttke and Y. Li and A. Tin and T. S. Ahluwalia and J.
Ärnlöv and B. O. Åsvold and S. J. L. Bakker and B. Banas
and N. Bansal and M. L. Biggs and G. Biino and M. Böhnke
and E. Boerwinkle and E. P. Bottinger and H. Brenner$^*$ and
B. Brumpton and R. J. Carroll and L. Chaker and J. Chalmers
and M.-L. Chee and M.-L. Chee and C.-Y. Cheng and A. Y. Chu
and M. Ciullo and M. Cocca and J. P. Cook and J. Coresh and
D. Cusi and M. H. de Borst and F. Degenhardt and K.-U.
Eckardt and K. Endlich and M. K. Evans and M. F. Feitosa and
A. Franke and S. Freitag-Wolf and C. Fuchsberger and P.
Gampawar and R. T. Gansevoort and M. Ghanbari and S. Ghasemi
and V. Giedraitis and C. Gieger and D. F. Gudbjartsson and
S. Hallan and P. Hamet and A. Hishida and K. Ho and E. Hofer
and B. Holleczek$^*$ and H. Holm and A. Hoppmann and K. Horn
and N. Hutri-Kähönen and K. Hveem and S.-J. Hwang and M.
A. Ikram and N. S. Josyula and B. Jung and M. Kähönen and
I. Karabegović and C.-C. Khor and W. Koenig and H. Kramer
and B. K. Krämer and B. Kühnel and J. Kuusisto and M.
Laakso and L. A. Lange and T. Lehtimäki and M. Li and W.
Lieb and L. Lind and C. M. Lindgren and R. J. F. Loos and M.
A. Lukas and L.-P. Lyytikäinen and A. Mahajan and P. R.
Matias-Garcia and C. Meisinger and T. Meitinger and O.
Melander and Y. Milaneschi and P. P. Mishra and N. Mononen
and A. P. Morris and J. C. Mychaleckyj and G. N. Nadkarni
and M. Naito and M. Nakatochi and M. A. Nalls and M. Nauck
and K. Nikus and B. Ning and I. M. Nolte and T. Nutile and
M. L. O'Donoghue and J. O'Connell and I. Olafsson and M.
Orho-Melander and A. Parsa and S. A. Pendergrass and B. W.
J. H. Penninx and M. Pirastu and M. H. Preuss and B. M.
Psaty and L. M. Raffield and O. T. Raitakari and M.
Rheinberger and K. M. Rice and F. Rizzi and A. R. Rosenkranz
and P. Rossing and J. I. Rotter and D. Ruggiero and K. A.
Ryan and C. Sabanayagam and E. Salvi and H. Schmidt and R.
Schmidt and M. Scholz and B. Schöttker$^*$ and C.-A. Schulz
and S. Sedaghat and C. M. Shaffer and K. B. Sieber and X.
Sim and M. Sims and H. Snieder and K. J. Stanzick and U.
Thorsteinsdottir and H. Stocker$^*$ and K. Strauch and H. M.
Stringham and P. Sulem and S. Szymczak and K. D. Taylor and
C. H. L. Thio and J. Tremblay and S. Vaccargiu and P. van
der Harst and P. J. van der Most and N. Verweij and U.
Völker and K. Wakai and M. Waldenberger and L. Wallentin
and S. Wallner and J. Wang and D. M. Waterworth and H. D.
White and C. J. Willer and T.-Y. Wong and M. Woodward and Q.
Yang and L. M. Yerges-Armstrong and M. Zimmermann and A. B.
Zonderman and T. Bergler and K. Stefansson and C. A. Böger
and C. Pattaro and A. Köttgen and F. Kronenberg and I. M.
Heid},
collaboration = {L. c. study},
title = {{G}enetic loci and prioritization of genes for kidney
function decline derived from a meta-analysis of 62
longitudinal genome-wide association studies.},
journal = {Kidney international},
volume = {102},
number = {3},
issn = {0085-2538},
address = {New York, NY},
publisher = {Elsevier},
reportid = {DKFZ-2022-01294},
pages = {624-639},
year = {2022},
note = {2022 Sep;102(3):624-639},
abstract = {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.},
keywords = {acute kidney injury (Other) / chronic kidney disease
(Other) / diabetes (Other) / gene expression (Other)},
cin = {C070},
ddc = {610},
cid = {I:(DE-He78)C070-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:35716955},
doi = {10.1016/j.kint.2022.05.021},
url = {https://inrepo02.dkfz.de/record/180380},
}