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Title: Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies.
Authors: Morris, AP
Le, TH
Wu, H
Akbarov, A
van der Most, PJ
Hemani, G
Smith, GD
Mahajan, A
Gaulton, KJ
Nadkarni, GN
Valladares-Salgado, A
Wacher-Rodarte, N
Mychaleckyj, JC
Dueker, ND
Guo, X
Hai, Y
Haessler, J
Kamatani, Y
Stilp, AM
Zhu, G
Cook, JP
Ärnlöv, J
Blanton, SH
de Borst, MH
Bottinger, EP
Buchanan, TA
Cechova, S
Charchar, FJ
Chu, P-L
Damman, J
Eales, J
Gharavi, AG
Giedraitis, V
Heath, AC
Ipp, E
Kiryluk, K
Kramer, HJ
Kubo, M
Larsson, A
Lindgren, CM
Lu, Y
Madden, PAF
Montgomery, GW
Papanicolaou, GJ
Raffel, LJ
Sacco, RL
Sanchez, E
Stark, H
Sundstrom, J
Taylor, KD
Xiang, AH
Zivkovic, A
Lind, L
Ingelsson, E
Martin, NG
Whitfield, JB
Cai, J
Laurie, CC
Okada, Y
Matsuda, K
Kooperberg, C
Chen, Y-DI
Rundek, T
Rich, SS
Loos, RJF
Parra, EJ
Cruz, M
Rotter, JI
Snieder, H
Tomaszewski, M
Humphreys, BD
Franceschini, N
First Published: 3-Jan-2019
Publisher: Nature Research (part of Springer Nature)
Citation: Nature Communications, 2019, volume 10, Article number: 29
Abstract: Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.
DOI Link: 10.1038/s41467-018-07867-7
eISSN: 2041-1723
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: Association summary statistics will be made available from: (i) the COGENTKidney Consortium component of the trans-ethnic meta-analysis; and (ii) the trans-ethnic meta-analysis across the COGENT-Kidney Consortium, CKDGen Consortium and Biobank Japan Project. Fine-mapping data for each distinct eGFR signal will be made available, including the posterior probability of driving the association for each SNV. These data will be made available via: (i) the University of Liverpool Statistical Genetics and Pharmacogenomics Research Group website (; and (ii) the dbGaP CHARGE Summary Results site92 with accession number phs000930. The source data underlying Fig. 1 and Supplementary Figure 7 are provided as a Source Data file.
Appears in Collections:Published Articles, Dept. of Cardiovascular Sciences

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