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Multiple loci associated with indices of renal function and chronic kidney disease


Chronic kidney disease (CKD) has a heritable component and is an important global public health problem because of its high prevalence and morbidity1. We conducted genome-wide association studies (GWAS) to identify susceptibility loci for glomerular filtration rate, estimated by serum creatinine (eGFRcrea) and cystatin C (eGFRcys), and CKD (eGFRcrea < 60 ml/min/1.73 m2) in European-ancestry participants of four population-based cohorts (ARIC, CHS, FHS, RS; n = 19,877; 2,388 CKD cases), and tested for replication in 21,466 participants (1,932 CKD cases). We identified significant SNP associations (P < 5 × 10−8) with CKD at the UMOD locus, with eGFRcrea at UMOD, SHROOM3 and GATM-SPATA5L1, and with eGFRcys at CST and STC1. UMOD encodes the most common protein in human urine, Tamm-Horsfall protein2, and rare mutations in UMOD cause mendelian forms of kidney disease3. Our findings provide new insights into CKD pathogenesis and underscore the importance of common genetic variants influencing renal function and disease.

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Figure 1: Overview of GWAS results.
Figure 2: Genetic architecture of the genome-wide significant susceptibility loci for renal disease in the discovery samples.
Figure 3: Meta-analysis of the odds of CKD per each additional copy of the minor T allele at UMOD rs12917707 across strata of major kidney disease risk factors.


  1. 1

    Levey, A.S. et al. Chronic kidney disease as a global public health problem: approaches and initiatives — a position statement from Kidney Disease Improving Global Outcomes. Kidney Int. 72, 247–259 (2007).

    CAS  Article  Google Scholar 

  2. 2

    Serafini-Cessi, F., Malagolini, N. & Cavallone, D. Tamm-Horsfall glycoprotein: biology and clinical relevance. Am. J. Kidney Dis. 42, 658–676 (2003).

    CAS  Article  Google Scholar 

  3. 3

    Hart, T.C. et al. Mutations of the UMOD gene are responsible for medullary cystic kidney disease 2 and familial juvenile hyperuricaemic nephropathy. J. Med. Genet. 39, 882–892 (2002).

    CAS  Article  Google Scholar 

  4. 4

    Coresh, J. et al. Prevalence of chronic kidney disease in the United States. J. Am. Med. Assoc. 298, 2038–2047 (2007).

    CAS  Article  Google Scholar 

  5. 5

    Zhang, Q.L. & Rothenbacher, D. Prevalence of chronic kidney disease in population-based studies: systematic review. BMC Public Health 8, 117 (2008).

    Article  Google Scholar 

  6. 6

    National Institutes of Health. US Renal Data System, USRDS 2008 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States (National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, 2008).

  7. 7

    Sarnak, M.J. et al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association councils on kidney in cardiovascular disease, high blood pressure research, clinical cardiology, and epidemiology and prevention. Circulation 108, 2154–2169 (2003).

    Article  Google Scholar 

  8. 8

    Weiner, D.E. et al. Chronic kidney disease as a risk factor for cardiovascular disease and all-cause mortality: a pooled analysis of community-based studies. J. Am. Soc. Nephrol. 15, 1307–1315 (2004).

    Article  Google Scholar 

  9. 9

    Langefeld, C.D. et al. Heritability of GFR and albuminuria in Caucasians with type 2 diabetes mellitus. Am. J. Kidney Dis. 43, 796–800 (2004).

    Article  Google Scholar 

  10. 10

    Bochud, M. et al. Heritability of renal function in hypertensive families of African descent in the Seychelles (Indian Ocean). Kidney Int. 67, 61–69 (2005).

    Article  Google Scholar 

  11. 11

    Fox, C.S. et al. Genomewide linkage analysis to serum creatinine, GFR, and creatinine clearance in a community-based population: the Framingham Heart Study. J. Am. Soc. Nephrol. 15, 2457–2461 (2004).

    CAS  Article  Google Scholar 

  12. 12

    Freedman, B.I. & Satko, S.G. Genes and renal disease. Curr. Opin. Nephrol. Hypertens. 9, 273–277 (2000).

    CAS  Article  Google Scholar 

  13. 13

    Psaty, B.M. et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from five cohorts. Circulation: Cardiovascular Genetics 2, 73–80 (2009).

    Google Scholar 

  14. 14

    Levey, A.S. et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann. Intern. Med. 130, 461–470 (1999).

    CAS  Article  Google Scholar 

  15. 15

    Stevens, L.A. et al. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am. J. Kidney Dis. 51, 395–406 (2008).

    CAS  Article  Google Scholar 

  16. 16

    Stevens, L.A., Coresh, J., Greene, T. & Levey, A.S. Assessing kidney function–measured and estimated glomerular filtration rate. N. Engl. J. Med. 354, 2473–2483 (2006).

    CAS  Article  Google Scholar 

  17. 17

    National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am. J. Kidney Dis. 39, S1–S266 (2002).

  18. 18

    Vylet'al, P. et al. Alterations of uromodulin biology: a common denominator of the genetically heterogeneous FJHN/MCKD syndrome. Kidney Int. 70, 1155–1169 (2006).

    CAS  Article  Google Scholar 

  19. 19

    Rampoldi, L. et al. Allelism of MCKD, FJHN and GCKD caused by impairment of uromodulin export dynamics. Hum. Mol. Genet. 12, 3369–3384 (2003).

    CAS  Article  Google Scholar 

  20. 20

    Bachmann, S. et al. Renal effects of Tamm-Horsfall protein (uromodulin) deficiency in mice. Am. J. Physiol. Renal Physiol. 288, F559–F567 (2005).

    CAS  Article  Google Scholar 

  21. 21

    Benetti, E. et al. Immature renal structures associated with a novel UMOD sequence variant. Am. J. Kidney Dis. 53, 327–331 (2009).

    Article  Google Scholar 

  22. 22

    Nishimura, T. & Takeichi, M. Shroom3-mediated recruitment of Rho kinases to the apical cell junctions regulates epithelial and neuroepithelial planar remodeling. Development 135, 1493–1502 (2008).

    CAS  Article  Google Scholar 

  23. 23

    Anad, F. et al. Alagille syndrome and deletion of 20p. J. Med. Genet. 27, 729–737 (1990).

    CAS  Article  Google Scholar 

  24. 24

    Hwang, S.J., Yang, Q., Meigs, J.B., Pearce, E.N. & Fox, C.S. A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study. BMC Med. Genet. 8 (Suppl. 1), S10 (2007).

    Article  Google Scholar 

  25. 25

    Yoshiko, Y. & Aubin, J.E. Stanniocalcin 1 as a pleiotropic factor in mammals. Peptides 25, 1663–1669 (2004).

    CAS  Article  Google Scholar 

  26. 26

    Huang, L. et al. Anti-inflammatory and renal protective actions of stanniocalcin-1 in a model of anti-glomerular basement membrane glomerulonephritis. Am. J. Pathol. 174, 1368–1378 (2009).

    CAS  Article  Google Scholar 

  27. 27

    Servin, B. & Stephens, M. Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet. 3, e114 (2007).

    Article  Google Scholar 

  28. 28

    Coresh, J. et al. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am. J. Kidney Dis. 39, 920–929 (2002).

    CAS  Article  Google Scholar 

  29. 29

    Hsu, C.C. et al. Apolipoprotein E and progression of chronic kidney disease. J. Am. Med. Assoc. 293, 2892–2899 (2005).

    CAS  Article  Google Scholar 

  30. 30

    Gordon, A., Glazko, G., Qui, X. & Yakovlev, A. Control of the mean number of false discoveries, Bonferroni and stability of multiple testing. The Annals of Applied Statistics 1, 179–190 (2007).

    Article  Google Scholar 

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We are indebted to the staff and participants of the AGES Reykjavik Study, the ARIC Study, the CHS Study, the FHS Study, the Rotterdam Study and the WGHS Study for their contributions.

AGES: The Age, Gene/Environment Susceptibility Reykjavik Study has been funded by US National Institutes of Health contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament). We thank T. Aspelund and G. Eiriksdottir for their contribution to collecting, analyzing and preparing the AGES Reykjavik Study data.

ARIC: The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022, R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. A.K. was supported by a German Research Foundation Fellowship. W.H.L.K. was supported by K01DK067207.

CHS: The CHS research reported in this article was supported by contract numbers N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01-HC-55222, N01-HC-75150, N01-HC-45133, grant numbers U01 HL080295 and R01 HL087652, and R01 AG027002 from the National Heart, Lung, and Blood Institute, with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal CHS investigators and institutions can be found at DNA handling and genotyping was supported in part by National Center for Research Resources grant M01RR00069 to the Cedars-Sinai General Clinical Research Center Genotyping core and National Institute of Diabetes and Digestive and Kidney Diseases grant DK063491 to the Southern California Diabetes Endocrinology Research Center.

FHS: This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the National Heart, Lung, and Blood Institute's Framingham Heart Study (contract no. N01-HC-25195) and its contract with Affymetrix for genotyping services (contract no. N02-HL-6-4278). A portion of this research used the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center.

RS: The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research; the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly; The Netherlands Heart Foundation; the Ministry of Education, Culture and Science; the Ministry of Health Welfare and Sports; the European Commission; and the Municipality of Rotterdam. Support for genotyping was provided by the Netherlands Organization for Scientific Research (NWO) (175.010.2005.011, 911.03.012) and Research Institute for Diseases in the Elderly (RIDE). This study was further supported by the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810. We thank P. Arp, M. Jhamai, M. Moorhouse, M. Verkerk and S. Bervoets for their help in creating the Rotterdam database and M. Struchalin for his contributions to the imputations of the Rotterdam data.

WGHS: The WGHS was supported by the National Heart, Lung, and Blood Institute (HL 043851) and the National Cancer Institute (CA 047988). Collaborative scientific and genotyping support was provided by Amgen.

Author information




A.K., N.L.G., A.D., S.-J.H., Q.Y., I.H.d.B., T.L., D.S., D.L., V.G., J.C., M.G.S. and C.S.F. contributed to the design of this analysis. A.K., N.L.G., A.D., S.-J.H., Q.Y., E.B., I.R., I.H.d.B., T.L., D.S., D.L., A.V.S., V.G., W.H.L.K., J.C.W., J.C., M.G.S. and C.S.F. contributed to the interpretation of the results. A.K., N.L.G., A.D., S.-J.H., J.C., M.G.S. and C.S.F. drafted the manuscript; all others reviewed and commented on the manuscript. A.K., N.L.G., A.D., S.J.H., R.K., M.L., Q.Y., D.E.A., G.B.E., I.R., R.B.S., T.L., F.R., C.M.v.D., A.V.S., D.I.C., G.P. and J.C. contributed to statistical methods and analysis. D.S., E.J.B., D.L., V.G., J.C. and C.S.F. contributed to recruitment and follow up of subjects. E.B., Y.-D.I.C., T.H., F.R. and A.G.U. contributed to genotyping; M.L., Q.Y., G.B.E., Y.S.A., F.R., A.G.U., A.V.S. and G.P. contributed to bioinformatics. V.G., L.J.L., T.B.H. and A.V.S. participated in the AGES Study. A.K., M.L., W.H.L.K., J.C., D.E.A., B.C.A., E.B., G.B.E., I.R. and R.B.S. participated in the ARIC Study. N.L.G., M.G.S., Y.-D.I.C., I.H.d.B., T.H., T.L., M.S. and D.S. participated in the CHS Study. E.J.B., D.L., A.U., S.-J.H., Q.Y. and C.S.F. participated in the FHS Study. Y.S.A., A.H., F.R., A.G.U., C.M.v.D., A.D. and J.C.W. participated in the RS Study. D.I.C., G.P. and P.M.R. participated in the WGHS Study.

Corresponding authors

Correspondence to Jacqueline C Witteman or Josef Coresh or Michael G Shlipak or Caroline S Fox.

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Supplementary Methods, Supplementary Tables 1–6 and Supplementary Figures 1 and 2 (PDF 3790 kb)

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Köttgen, A., Glazer, N., Dehghan, A. et al. Multiple loci associated with indices of renal function and chronic kidney disease. Nat Genet 41, 712–717 (2009).

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