Meta-analysis identifies multiple loci associated with kidney function–related traits in east Asian populations


Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function–related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function–related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10−8). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of 110,347 individuals. We identify pleiotropic associations among these loci with kidney function–related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

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Figure 1: Manhattan plots of the GWAS meta-analysis for kidney function–related traits.
Figure 2: Venn diagram of pleiotropic associations of the identified loci.


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The authors acknowledge the essential roles of AGEN in developing the study. BBJ was supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT). SP2 was funded by grants from the Biomedical Research Council of Singapore (BMRC 05/1/36/19/413 and 03/1/27/18/216) and the National Medical Research Council of Singapore (NMRC/1174/2008). SiMES was funded by the National Medical Research Council of Singapore (NMRC 0796/2003, IRG07nov013 and NMRC/STaR/0003/2008) and the Biomedical Research Council of Singapore (BMRC 09/1/35/19/616). SINDI and SCES were funded by grants from the Biomedical Research Council of Singapore (BMRC 09/1/35/19/616 and BMRC 08/1/35/19/550) and the National Medical Research Council of Singapore (NMRC/STaR/0003/2008). Y.-Y.T. acknowledges support from the Singapore National Research Foundation (NRF-RF-2010-05). E.-S.T. receives support from the National Medical Research Council of Singapore through a Clinician Scientist Award. We thank the Singapore BioBank and the Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, for providing services for tissue archiving and genotyping, respectively. KARE was supported by grants from the Korea Centers for Disease Control and Prevention (4845-301, 4851-302 and 4851-307) and an intramural grant from the Korea National Institute of Health (2010-N73002-00). Y.S.C. acknowledges support from a National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (2012R1A2A1A03006155). TWSC and TWT2D were supported by the Academia Sinica Genomic Medicine Multicenter Study (40-05-GMM). We acknowledge the National Center for Genome Medicine (NSC100-2319-B-001-001), the National Core Facility Program for Biotechnology of the National Science Council, Taiwan, for technical help in sample management and genotyping. GenSalt was supported by grants (U01HL072507, R01HL087263 and R01HL090682) from the National Heart, Lung, and Blood Institute, the US National Institutes of Health. CAGE was supported by grants for Core Research for Evolutional Science and Technology (CREST) from the Japan Science Technology Agency; the Program for Promotion of Fundamental Studies in Health Sciences, the National Institute of Biomedical Innovation Organization (NIBIO) and the grant of National Center for Global Health and Medicine (NCGM). We thank all the people who supported the Hospital-based Cohort Study at NCGM and the Amagasaki Study. We thank A. Taniguchi, H. Rakugi, K. Sugimoto, K. Kamide and C. Makibayashi for supporting the study.

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Y.O. and T. Tanaka designed the overall study. Y.O., X.S., M.J.G., C.-H.C., D.G., F.T. and P.C. analyzed GWAS data. Y.O. performed meta-analysis and other statistical analysis. Y.O., A.T., S.M., T. Tsunoda, K.Y., M.K., Y.N., N. Kamatani and T. Tanaka managed GWAS data of BBJ. X.S., P.C., S.-C.L., T.-Y.W., J.L., T.L.Y., T.A., M.S., Y.-Y.T. and E.-S.T. managed the GWAS data from SP2, SiMES, SINDI and SCES. M.J.G., Y.J.K., J.-Y.L., B.-G.H., D.K. and Y.S.C. managed the GWAS data from KARE and HEXA. C.-H.C., F.-J.T., L.-C.C., S.-J.C.F., Y.-T.C. and J.-Y.W. managed the GWAS data from TWSC and TWT2D. D.G., H.M., D.C.R., J.E.H., S.C. and J.H. managed the GWAS data from GenSalt. F.T., T.K., M.I., T.O. and N. Kato managed the GWAS data from CAGE. J.C.C., W.Z. and J.S.K. managed the data from the KidneyGen Consortium. E.A. managed the data from the GUGC consortium. Y.O., T. Tanaka, E.-S.T., Y.S.C., J.-Y.W., J.H. and N. Kato directed the study and wrote the manuscript.

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Correspondence to Yukinori Okada.

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Okada, Y., Sim, X., Go, M. et al. Meta-analysis identifies multiple loci associated with kidney function–related traits in east Asian populations. Nat Genet 44, 904–909 (2012).

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