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Genome-Wide Association Meta-Analysis Identifies Novel Loci for Kidney Failure

Title: Genome-Wide Association Meta-Analysis Identifies Novel Loci for Kidney Failure
Authors: van der Most, Peter Johannes; Wang, Siqi; Guan, Weihua; Schladt, David P.; Loza, Bao-Li; Caragh, Stapleton; Heinzel, Andreas; Israni, Ajay K.; Jacobson, Pamala A.; Keating, Brendan; Conlon, Peter J; Oberbauer, Rainer; Snieder, Harold; de Borst, Martin
Source: van der Most, P J, Wang, S, Guan, W, Schladt, D P, Loza, B-L, Caragh, S, Heinzel, A, Israni, A K, Jacobson, P A, Keating, B, Conlon, P J, Oberbauer, R, Snieder, H & de Borst, M 2022, 'Genome-Wide Association Meta-Analysis Identifies Novel Loci for Kidney Failure', Nephrology Dialysis Transplantation, vol. 37, no. Supplement 3, pp. I800-I801. https://doi.org/10.1093/ndt/gfac102.001
Publication Year: 2022
Collection: University of Groningen research database
Subject Terms: GWAS; Kidney; Kidney failure; Kidney function; ESKD; Diabetes Mellitus
Description: BACKGROUND AND AIMS: The genetics of kidney function has been extensively studied, but since these analyses have been done mostly in populations with normal or mildly impaired kidney function, it is still unknown whether variants linked to kidney function also translate into genetic susceptibility for kidney failure. The primary aim of this study was to investigate the genetic background of kidney failure. METHOD: We performed a meta-analysis of kidney failure genome-wide association studies, using kidney transplant recipients as cases (n = 6942) and donors as controls (n = 4788). Secondary disease-specific analyses were performed for kidney failure due to diabetes, IgA nephropathy, glomerulonephritis or polycystic kidney disease. Subsequently, we investigated genetic overlap with eGFR and urinary albumin-creatinine ratio (UACR) variability, based on publicly available CKDgen consortium meta-analysis data. RESULTS: In the primary analysis, we found two suggestive hits for kidney failure: rs17046239 in GRM7 (P = 8.9 × 10−8), and rs9273431 in HLA-DQB1 (P = 5.3 × 10−8). In disease-specific analyses, we found three genome-wide (P < 5 × 10−8) significant hits for kidney failure due to diabetes: rs9273431 in HLA-DQB1 (P = 5.0 × 10−50), rs2476601 in PTPN22 (P = 2.9 × 10−13) and rs7110099 in INS-IGF2 (P = 4.4 × 10−9). Furthermore, we found suggestive hits for kidney failure due to glomerulonephritis (rs6531751, nearest gene: PDS5a, P = 9.3 × 10−8) or polycystic kidney disease (rs111857047 in PTPRD, P = 9.6 × 10−8). As follow-up analysis, we performed lookups for the identified SNPs in prior kidney function GWAS results of the CKDGen consortium. Our top hits for kidney failure due to diabetes were nominally significant (P < 0.05) in the creatinine-based estimated glomerular filtration rate (eGFRcrea) and/or the UACR results. The other hits were not significantly associated with either phenotype. Linkage disequilibrium score regression (LDSC) analysis did not reveal a significant genetic correlation (rG) between ...
Document Type: conference object
Language: English
ISSN: 0931-0509; 1460-2385
Relation: info:eu-repo/semantics/altIdentifier/wos/000813350704092; info:eu-repo/semantics/altIdentifier/hdl/https://hdl.handle.net/11370/0c52381a-0f54-4c57-8dd2-3ffee53dbe5a; info:eu-repo/semantics/altIdentifier/pissn/0931-0509; info:eu-repo/semantics/altIdentifier/eissn/1460-2385
DOI: 10.1093/ndt/gfac102.001
Availability: https://hdl.handle.net/11370/0c52381a-0f54-4c57-8dd2-3ffee53dbe5a; https://research.rug.nl/en/publications/0c52381a-0f54-4c57-8dd2-3ffee53dbe5a; https://doi.org/10.1093/ndt/gfac102.001
Rights: info:eu-repo/semantics/closedAccess
Accession Number: edsbas.493921D8
Database: BASE