Abstract

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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References

  1. 1.

    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).

  2. 2.

    , & Tamm-Horsfall glycoprotein: biology and clinical relevance. Am. J. Kidney Dis. 42, 658–676 (2003).

  3. 3.

    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).

  4. 4.

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

  5. 5.

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

  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.

    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).

  8. 8.

    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).

  9. 9.

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

  10. 10.

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

  11. 11.

    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).

  12. 12.

    & Genes and renal disease. Curr. Opin. Nephrol. Hypertens. 9, 273–277 (2000).

  13. 13.

    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).

  14. 14.

    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).

  15. 15.

    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).

  16. 16.

    , , & Assessing kidney function–measured and estimated glomerular filtration rate. N. Engl. J. Med. 354, 2473–2483 (2006).

  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.

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

  19. 19.

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

  20. 20.

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

  21. 21.

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

  22. 22.

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

  23. 23.

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

  24. 24.

    , , , & 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).

  25. 25.

    & Stanniocalcin 1 as a pleiotropic factor in mammals. Peptides 25, 1663–1669 (2004).

  26. 26.

    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).

  27. 27.

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

  28. 28.

    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).

  29. 29.

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

  30. 30.

    , , & Control of the mean number of false discoveries, Bonferroni and stability of multiple testing. The Annals of Applied Statistics 1, 179–190 (2007).

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Acknowledgements

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 http://www.chs-nhlbi.org/pi.htm. 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

Author notes

    • Anna Köttgen
    • , Nicole L Glazer
    • , Abbas Dehghan
    •  & Shih-Jen Hwang

    These authors contributed equally to this work.

    • Jacqueline C Witteman
    • , Josef Coresh
    • , Michael G Shlipak
    •  & Caroline S Fox

    These authors jointly directed the project.

Affiliations

  1. Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA.

    • Anna Köttgen
    • , Man Li
    • , Brad C Astor
    • , W H Linda Kao
    •  & Josef Coresh
  2. Cardiovascular Health Research Unit and Department of Medicine, University of Washington, Seattle, Washington, USA.

    • Nicole L Glazer
  3. Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.

    • Abbas Dehghan
    • , Yurii S Aulchenko
    • , Albert Hofman
    • , Cornelia M van Duijn
    •  & Jacqueline C Witteman
  4. National Heart, Lung, and Blood Institute Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts, USA.

    • Shih-Jen Hwang
    • , Daniel Levy
    •  & Caroline S Fox
  5. Department of Biostatistics, University of Washington, Seattle, Washington, USA.

    • Ronit Katz
    •  & Thomas Lumley
  6. Department of Biostatistics, Boston University, Boston, Massachusetts, USA.

    • Qiong Yang
  7. Icelandic Heart Association Research Institute, Kopavogur, Iceland.

    • Vilmundur Gudnason
    •  & Albert V Smith
  8. University of Iceland, Reykjavik, Iceland.

    • Vilmundur Gudnason
  9. Laboratory of Epidemiology, Demography, and Biometry, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, USA.

    • Lenore J Launer
    •  & Tamara B Harris
  10. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA.

    • Dan E Arking
    •  & Georg B Ehret
  11. Human Genetics Center and Division of Epidemiology, University of Texas Health Science Center at Houston, Houston, Texas, USA.

    • Eric Boerwinkle
  12. Division of Cardiology, Geneva University Hospital, Switzerland.

    • Georg B Ehret
  13. Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.

    • Ingo Ruczinski
    • , Robert B Scharpf
    •  & Josef Coresh
  14. Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.

    • Yii-Der Ida Chen
    •  & Talin Haritunians
  15. Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA.

    • Ian H de Boer
  16. Tufts-New England Medical Center, Boston, Massachusetts, USA.

    • Mark Sarnak
  17. Departments of Medicine and Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA.

    • David Siscovick
  18. Boston University Schools of Medicine and Public Health, Boston, Massachusetts, USA.

    • Emelia J Benjamin
  19. Renal Section, Boston Medical Center and Boston University School of Medicine, Boston, Massachusetts, USA.

    • Ashish Upadhyay
  20. Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.

    • Fernando Rivadeneira
    •  & André G Uitterlinden
  21. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

    • Daniel I Chasman
    • , Guillaume Paré
    •  & Paul M Ridker
  22. General Internal Medicine Division, San Francisco VA Medical Center, University of California, San Francisco, California, USA.

    • Michael G Shlipak
  23. Brigham and Women's Hospital Division of Endocrinology and Harvard Medical School, Boston, Massachusetts, USA.

    • Caroline S Fox
  24. Member of the Netherlands Consortium on Healthy Aging (NCHA).

    • Abbas Dehghan
    •  & Jacqueline C Witteman

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Contributions

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

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DOI

https://doi.org/10.1038/ng.377

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