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Genome-wide association studies of chronic kidney disease: what have we learned?

Nature Reviews Nephrology volume 8, pages 89–99 (2012)Cite this article

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Abstract

The past 3 years have witnessed a dramatic expansion in our knowledge of the genetic determinants of estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD). However, heritability estimates of eGFR indicate that we have only identified a small proportion of the total heritable contribution to the phenotypic variation. The majority of associations reported from genome-wide association studies identify genomic regions of interest and further work will be required to identify the causal variants responsible for a specific phenotype. Progress in this area is likely to stem from the identification of novel risk genotypes, which will offer insight into the pathogenesis of disease and potential novel therapeutic targets. Follow-up studies stimulated by findings from genome-wide association studies of kidney disease are already yielding promising results, such as the identification of an association between urinary uromodulin levels and incident CKD. Although this work is at an early stage, prospects for progress in our understanding of CKD and its treatment look more promising now than at any point in the past.

Key Points

  • Early attempts to identify the genetic basis of kidney disease in unselected populations, for example using the candidate gene approach or linkage analysis, were largely unsuccessful

  • Genome-wide association studies (GWASs) are unbiased screens of the genome for disease associations, and have revolutionized the study of complex, polygenic traits

  • Progress has been made in identifying novel loci associated with several renal traits, such as glomerular filtration rate, chronic kidney disease and albuminuria, using the GWAS approach

  • GWASs identify single nucleotide polymorphisms that tag a genomic region harboring the true causal variant, which requires further fine-mapping and functional studies for definitive identification of the causal variant

  • The major translational benefits of findings from GWASs are likely to be the identification of novel therapeutic targets and an improved understanding of the pathogenesis of chronic kidney disease

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Figure 1: An additive genetic model for GFR.
Figure 2: Graphical presentation of results from a GWAS of eGFR.
Figure 3: Magnitude of association between GFR estimated from creatinine and cystatin C and SNPs identified in a GWAS of GFR and CKD.

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References

  1. Hardy, J. & Singleton, A. Genomewide association studies and human disease. N. Engl. J. Med. 360, 1759–1768 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Ruggenenti, P., Bettinaglio, P., Pinares, F. & Remuzzi, G. Angiotensin converting enzyme insertion/deletion polymorphism and renoprotection in diabetic and nondiabetic nephropathies. Clin. J. Am. Soc. Nephrol. 3, 1511–1525 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Le, T. H. & Coffman, T. M. Targeting genes in the renin-angiotensin system. Curr. Opin. Nephrol. Hypertens. 17, 57–63 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. Heesom, A. E., Hibberd, M. L., Millward, A. & Demaine, A. G. Polymorphism in the 5′-end of the aldose reductase gene is strongly associated with the development of diabetic nephropathy in type I diabetes. Diabetes 46, 287–291 (1997).

    Article  CAS  PubMed  Google Scholar 

  5. Blüthner, M. et al. Increased frequency of G-protein β3-subunit 825 T allele in dialyzed patients with type 2 diabetes. Kidney Int. 55, 1247–1250 (1999).

    Article  PubMed  Google Scholar 

  6. Chowdhury, T. A. et al. Association of apolipoprotein epsilon2 allele with diabetic nephropathy in Caucasian subjects with IDDM. Diabetes 47, 278–280 (1998).

    Article  CAS  PubMed  Google Scholar 

  7. Yu, H., Freedman, B. I., Rich, S. S. & Bowden, D. W. Human Na+/H+ exchanger genes: identification of polymorphisms by radiation hybrid mapping and analysis of linkage in end-stage renal disease. Hypertension 35, 135–143 (2000).

    Article  CAS  PubMed  Google Scholar 

  8. Freedman, B. I. et al. Genetic analysis of nitric oxide and endothelin in end-stage renal disease. Nephrol. Dial. Transplant. 15, 1794–1800 (2000).

    Article  CAS  PubMed  Google Scholar 

  9. Morita, T. et al. Effect of a polymorphism of endothelial nitric oxide synthase gene in Japanese patients with IgA nephropathy. Clin. Nephrol. 52, 203–209 (1999).

    CAS  PubMed  Google Scholar 

  10. Tanaka, R. et al. Role of platelet-activating factor acetylhydrolase gene mutation in Japanese childhood IgA nephropathy. Am. J. Kidney Dis. 34, 289–295 (1999).

    Article  CAS  PubMed  Google Scholar 

  11. Deenitchina, S. S. et al. Association of a T-cell receptor constant alpha chain gene polymorphism with progression of IgA nephropathy in Japanese patients. Am. J. Kidney Dis. 34, 279–288 (1999).

    Article  CAS  PubMed  Google Scholar 

  12. Hirschhorn, J. N. & Daly, M. J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Hirschhorn, J. N., Lohmueller, K., Byrne, E. & Hirschhorn, K. A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002).

    Article  CAS  PubMed  Google Scholar 

  14. Reeders, S. T. et al. A highly polymorphic DNA marker linked to adult polycystic kidney disease on chromosome 16. Nature 317, 542–544 (1985).

    Article  CAS  PubMed  Google Scholar 

  15. Köttgen, A. et al. New loci associated with kidney function and chronic kidney disease. Nat. Genet. 42, 376–384 (2010).

    PubMed  PubMed Central  Google Scholar 

  16. 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).

    Article  CAS  PubMed  Google Scholar 

  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. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Bash, L. D. et al. Defining incident chronic kidney disease in the research setting: The ARIC Study. Am. J. Epidemiol. 170, 414–424 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Mattix, H. J., Hsu, C. Y., Shaykevich, S. & Curhan, G. Use of the albumin/creatinine ratio to detect microalbuminuria: implications of sex and race. J. Am. Soc. Nephrol. 13, 1034–1039 (2002).

    CAS  PubMed  Google Scholar 

  21. Jorde, L. B. & Wooding, S. P. Genetic variation, classification and 'race'. Nat. Genet. 36, S28–S33 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Sachidanandam, R. et al. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 409, 928–933 (2001).

    Article  CAS  PubMed  Google Scholar 

  23. Li, W. H. & Sadler, L. A. Low nucleotide diversity in man. Genetics 129, 513–523 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Altshuler, D., Daly, M. J. & Lander, E. S. Genetic mapping in human disease. Science 322, 881–888 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Gabriel, S. B. et al. The structure of haplotype blocks in the human genome. Science 296, 2225–2229 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Neale, B. M. Introduction to linkage disequilibrium, the HapMap, and imputation. Cold Spring Harb. Protoc. http://dx.doi.org/10.1101/pdb.top74.

  27. Tishkoff, S. A. et al. The genetic structure and history of Africans and African Americans. Science 324, 1035–1044 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Spencer, C. C., Su, Z., Donnelly, P. & Marchini, J. Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genet. 5, e1000477 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Johnson, R. C. et al. Accounting for multiple comparisons in a genome-wide association study (GWAS). BMC Genomics 11, 724 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  30. van den Oord, E. J. Controlling false discoveries in genetic studies. Am. J. Med. Genet. B Neuropsychiatr. Genet. 147B, 637–644 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Hunter, D. J. & Kraft, P. Drinking from the fire hose—statistical issues in genomewide association studies. N. Engl. J. Med. 357, 436–439 (2007).

    Article  CAS  PubMed  Google Scholar 

  32. Pearson, T. A. & Manolio, T. A. How to interpret a genome-wide association study. JAMA 299, 1335–1344 (2008).

    Article  CAS  PubMed  Google Scholar 

  33. Manolio, T. A. Genomewide association studies and assessment of the risk of disease. N. Engl. J. Med. 363, 166–176 (2010).

    Article  CAS  PubMed  Google Scholar 

  34. Chanock, S. J. et al. Replicating genotype-phenotype associations. Nature 447, 655–660 (2007).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Köttgen, A. et al. Uromodulin levels associate with a common UMOD variant and risk for incident CKD. J. Am. Soc. Nephrol. 21, 337–344 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  38. 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).

    Article  CAS  PubMed  Google Scholar 

  39. Hirschhorn, J. N. Genomewide association studies—illuminating biologic pathways. N. Engl. J. Med. 360, 1699–1701 (2009).

    Article  CAS  PubMed  Google Scholar 

  40. Chambers, J. C. et al. Genetic loci influencing kidney function and chronic kidney disease. Nat. Genet. 42, 373–375 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Perkovic, V. et al. High prevalence of chronic kidney disease in Thailand. Kidney Int. 73, 473–479 (2008).

    Article  CAS  PubMed  Google Scholar 

  42. Tareen, N. et al. Chronic kidney disease in African American and Mexican American populations. Kidney Int. Suppl. 97, S137–S140 (2005).

    Article  Google Scholar 

  43. Liu, C.-T. et al. Genetic association for renal traits among participants of African ancestry reveals new loci for renal function. PLoS Genet. 7, e1002264 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kao, W. H. et al. MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat. Genet. 40, 1185–1192 (2008).

    Article  CAS  PubMed  Google Scholar 

  45. Kopp, J. B. et al. MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis. Nat. Genet. 40, 1175–1184 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Smith, M. W. & O'Brien, S. J. Mapping by admixture linkage disequilibrium: advances, limitations and guidelines. Nat. Rev. Genet. 6, 623–632 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Freedman, B. I. et al. Non-muscle myosin heavy chain 9 gene MYH9 associations in African Americans with clinically diagnosed type 2 diabetes mellitus-associated ESRD. Nephrol. Dial. Transplant. 24, 3366–3371 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Barreiro, L. B., Laval, G., Quach, H., Patin, E. & Quintana-Murci, L. Natural selection has driven population differentiation in modern humans. Nat. Genet. 40, 340–345 (2008).

    Article  CAS  PubMed  Google Scholar 

  49. Sabeti, P. C. et al. Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913–918 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Oleksyk, T. K., Nelson, G. W., An, P., Kopp, J. B. & Winkler, C. A. Worldwide distribution of the MYH9 kidney disease susceptibility alleles and haplotypes: evidence of historical selection in Africa. PLoS ONE 5, e11474 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Genovese, G. et al. Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329, 841–845 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Sabeti, P. C. et al. Positive natural selection in the human lineage. Science 312, 1614–1620 (2006).

    Article  CAS  PubMed  Google Scholar 

  53. O'Seaghdha, C. M. et al. The MYH9/APOL1 region and chronic kidney disease in European-Americans. Hum. Mol. Genet. 20, 2450–2456 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Freedman, B. I. et al. The apolipoprotein L1 (APOL1) gene and nondiabetic nephropathy in African Americans. J. Am. Soc. Nephrol. 21, 1422–1426 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Pezzolesi, M. G. et al. Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes 58, 1403–1410 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ni, X. et al. Molecular cloning and characterization of the protein 4.1O gene, a novel member of the protein 4.1 family with focal expression in ovary. J. Hum. Genet. 48, 101–106 (2003).

    Article  CAS  PubMed  Google Scholar 

  57. Shimazaki, A. et al. Genetic variations in the gene encoding ELMO1 are associated with susceptibility to diabetic nephropathy. Diabetes 54, 1171–1178 (2005).

    Article  CAS  PubMed  Google Scholar 

  58. Leak, T. S. et al. Variants in intron 13 of the ELMO1 gene are associated with diabetic nephropathy in African Americans. Ann. Hum. Genet. 73, 152–159 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Pezzolesi, M. G. et al. Confirmation of genetic associations at ELMO1 in the GoKinD collection supports its role as a susceptibility gene in diabetic nephropathy. Diabetes 58, 2698–2702 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Shimazaki, A. et al. ELMO1 increases expression of extracellular matrix proteins and inhibits cell adhesion to ECMs. Kidney Int. 70, 1769–1776 (2006).

    Article  CAS  PubMed  Google Scholar 

  61. Caramori, M. L. et al. Cellular basis of diabetic nephropathy: 1. Study design and renal structural-functional relationships in patients with long-standing type 1 diabetes. Diabetes 51, 506–513 (2002).

    Article  CAS  PubMed  Google Scholar 

  62. Maeda, S. et al. A single nucleotide polymorphism within the acetyl-coenzyme A carboxylase beta gene is associated with proteinuria in patients with type 2 diabetes. PLoS Genet. 6, e1000842 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Abu-Elheiga, L., Matzuk, M. M., Abo-Hashema, K. A. & Wakil, S. J. Continuous fatty acid oxidation and reduced fat storage in mice lacking acetyl-CoA carboxylase 2. Science 291, 2613–2616 (2001).

    Article  CAS  PubMed  Google Scholar 

  64. James, M. T., Hemmelgarn, B. R. & Tonelli, M. Early recognition and prevention of chronic kidney disease. Lancet 375, 1296–1309 (2010).

    Article  CAS  PubMed  Google Scholar 

  65. Böger, C. A. et al. CUBN is a gene locus for albuminuria. J. Am. Soc. Nephrol. 22, 555–570 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Birn, H. et al. Characterization of an epithelial approximately 460-kDa protein that facilitates endocytosis of intrinsic factor-vitamin B12 and binds receptor-associated protein. J. Biol. Chem. 272, 26497–26504 (1997).

    Article  CAS  PubMed  Google Scholar 

  67. Christensen, E. I., Verroust, P. J. & Nielsen, R. Receptor-mediated endocytosis in renal proximal tubule. Pflugers Arch. 458, 1039–1048 (2009).

    Article  CAS  PubMed  Google Scholar 

  68. Birn, H. & Christensen, E. I. Renal albumin absorption in physiology and pathology. Kidney Int. 69, 440–449 (2006).

    Article  CAS  PubMed  Google Scholar 

  69. Feng, M. et al. Expression level of cubilin in the rat model of diabetic nephropathy [Chinese]. Sichuan Da Xue Xue Bao Yi Xue Ban 37, 738–741 (2006).

    CAS  PubMed  Google Scholar 

  70. Russo, L. M. et al. Impaired tubular uptake explains albuminuria in early diabetic nephropathy. J. Am. Soc. Nephrol. 20, 489–494 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Tojo, A. et al. Reduced albumin reabsorption in the proximal tubule of early-stage diabetic rats. Histochem. Cell Biol. 116, 269–276 (2001).

    Article  CAS  PubMed  Google Scholar 

  72. Thrailkill, K. M. et al. Microalbuminuria in type 1 diabetes is associated with enhanced excretion of the endocytic multiligand receptors megalin and cubilin. Diabetes Care 32, 1266–1268 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S. & Hirschhorn, J. N. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat. Genet. 33, 177–182 (2003).

    Article  CAS  PubMed  Google Scholar 

  74. Göring, H. H., Terwilliger, J. D. & Blangero, J. Large upward bias in estimation of locus-specific effects from genomewide scans. Am. J. Hum. Genet. 69, 1357–1369 (2001).

    Article  PubMed  PubMed Central  Google Scholar 

  75. McCarthy, M. I. & Hirschhorn, J. N. Genome-wide association studies: potential next steps on a genetic journey. Hum. Mol. Genet. 17, R156–R165 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Haig, D. Does heritability hide in epistasis between linked SNPs? Eur. J. Hum. Genet. 19, 123 (2011).

    Article  PubMed  Google Scholar 

  77. Lander, E. S. et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).

    Article  CAS  PubMed  Google Scholar 

  78. McPherson, J. D. et al. A physical map of the human genome. Nature 409, 934–941 (2001).

    Article  CAS  PubMed  Google Scholar 

  79. Pareek, C. S., Smoczynski, R. & Tretyn, A. Sequencing technologies and genome sequencing. J. Appl. Genet. 52, 413–435 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Majewski, J., Schwartzentruber, J., Lalonde, E., Montpetit, A. & Jabado, N. What can exome sequencing do for you? J. Med. Genet. 48, 580–589 (2011).

    Article  CAS  PubMed  Google Scholar 

  81. Bamshad, M. J. et al. Exome sequencing as a tool for Mendelian disease gene discovery. Nat. Rev. Genet. 12, 745–755 (2011).

    Article  CAS  PubMed  Google Scholar 

  82. Luo, L., Boerwinkle, E. & Xiong, M. Association studies for next-generation sequencing. Genome Res. 21, 1099–1108 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. O'Donnell, C. J. & Nabel, E. G. Cardiovascular genomics, personalized medicine, and the National Heart, Lung, and Blood Institute: part I: the beginning of an era. Circ. Cardiovasc. Genet. 1, 51–57 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Wang, T. J. Assessing the role of circulating, genetic, and imaging biomarkers in cardiovascular risk prediction. Circulation 123, 551–565 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  85. O'Seaghdha, C. M., Yang, Q., Wu, H., Hwang, S. J. & Fox, C. S. Performance of a genetic risk score for CKD stage 3 in the general population. Am. J. Kidney Dis. http://dx.doi.org/10.1053/j.ajkd.2011.08.030.

  86. O'Seaghdha, C. M. et al. Development of a risk score for chronic kidney disease in population-based studies [abstract]. American Society of Nephrology Renal Week F-PO1920 (2010).

  87. Meigs, J. B. et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N. Engl. J. Med. 359, 2208–2219 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Talmud, P. J. et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ 340, b4838 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Qi, L. et al. Genetic risk score and risk of myocardial infarction in Hispanics. Circulation 123, 374–380 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Ripatti, S. et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses. Lancet 376, 1393–1400 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Paynter, N. P. et al. Association between a literature-based genetic risk score and cardiovascular events in women. JAMA 303, 631–637 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Pirmohamed, M. Pharmacogenetics: past, present and future. Drug Discov. Today 16, 852–861 (2011).

    Article  CAS  PubMed  Google Scholar 

  93. Teslovich, T. M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Al-Kateb, H. et al. Multiple superoxide dismutase 1/splicing factor serine alanine 15 variants are associated with the development and progression of diabetic nephropathy: the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Genetics study. Diabetes 57, 218–228 (2008).

    Article  CAS  PubMed  Google Scholar 

  95. Lim, S. C. et al. Microarray analysis of multiple candidate genes and associated plasma proteins for nephropathy secondary to type 2 diabetes among Chinese individuals. Diabetologia 52, 1343–1351 (2009).

    Article  CAS  PubMed  Google Scholar 

  96. Nomiyama, T. et al. The polymorphism of manganese superoxide dismutase is associated with diabetic nephropathy in Japanese type 2 diabetic patients. J. Hum. Genet. 48, 138–141 (2003).

    CAS  PubMed  Google Scholar 

  97. Lee, S. J., Choi, M. G., Kim, D. S. & Kim, T. W. Manganese superoxide dismutase gene polymorphism (V16A) is associated with stages of albuminuria in Korean type 2 diabetic patients. Metabolism 55, 1–7 (2006).

    Article  CAS  PubMed  Google Scholar 

  98. Möllsten, A. et al. A functional polymorphism in the manganese superoxide dismutase gene and diabetic nephropathy. Diabetes 56, 265–269 (2007).

    Article  CAS  PubMed  Google Scholar 

  99. Janssen, B. et al. Carnosine as a protective factor in diabetic nephropathy: association with a leucine repeat of the carnosinase gene CNDP1. Diabetes 54, 2320–2327 (2005).

    Article  CAS  PubMed  Google Scholar 

  100. Freedman, B. I. et al. A leucine repeat in the carnosinase gene CNDP1 is associated with diabetic end-stage renal disease in European Americans. Nephrol. Dial. Transplant. 22, 1131–1135 (2007).

    Article  CAS  PubMed  Google Scholar 

  101. McDonough, C. W. et al. The influence of carnosinase gene polymorphisms on diabetic nephropathy risk in African-Americans. Hum. Genet. 126, 265–275 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. McKnight, A. J. et al. A GREM1 gene variant associates with diabetic nephropathy. J. Am. Soc. Nephrol. 21, 773–781 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Millis, M. P., Bowen, D., Kingsley, C., Watanabe, R. M. & Wolford, J. K. Variants in the plasmacytoma variant translocation gene (PVT1) are associated with end-stage renal disease attributed to type 1 diabetes. Diabetes 56, 3027–3032 (2007).

    Article  CAS  PubMed  Google Scholar 

  104. Hanson, R. L. et al. Identification of PVT1 as a candidate gene for end-stage renal disease in type 2 diabetes using a pooling-based genome-wide single nucleotide polymorphism association study. Diabetes 56, 975–983 (2007).

    Article  CAS  PubMed  Google Scholar 

  105. Tiwari, A. K. et al. Oxidative stress pathway genes and chronic renal insufficiency in Asian Indians with type 2 diabetes. J. Diabetes Complications 23, 102–111 (2009).

    Article  PubMed  Google Scholar 

  106. Liu, L. et al. The manganese superoxide dismutase Val16Ala polymorphism is associated with decreased risk of diabetic nephropathy in Chinese patients with type 2 diabetes. Mol. Cell. Biochem. 322, 87–91 (2009).

    Article  CAS  PubMed  Google Scholar 

  107. Wanic, K. et al. Exclusion of polymorphisms in carnosinase genes (CNDP1 and CNDP2) as a cause of diabetic nephropathy in type 1 diabetes: results of large case-control and follow-up studies. Diabetes 57, 2547–2551 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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  1. National Heart, Lung and Blood Institute's Framingham Heart Study and the Center for Population Studies, 73 Mount Wayte Avenue, Suite 2, Framingham, 01702, MA, USA

    Conall M. O'Seaghdha & Caroline S. Fox

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C. M. O'Seaghdha and C. S. Fox contributed equally to discussion of content for the article, researching data to include in the manuscript and the reviewing and editing of the manuscript before submission.

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O'Seaghdha, C., Fox, C. Genome-wide association studies of chronic kidney disease: what have we learned?. Nat Rev Nephrol 8, 89–99 (2012). https://doi.org/10.1038/nrneph.2011.189

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