Genetics of Diabetic Nephropathy: a Long Road of Discovery

  • Amy Jayne McKnight
  • Seamus Duffy
  • Alexander P. MaxwellEmail author
Microvascular Complications—Nephropathy (T Isakova, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Microvascular Complications—Nephropathy


The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.


Albuminuria Association Diabetic nephropathy Genetics GWAS Meta-analysis SNP 


Compliance with Ethics Guidelines

Conflict of Interest

Amy Jayne McKnight, Seamus Duffy and Alexander P. Maxwell declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.


Papers of particular interest, published recently, have been highlighted as: •• Of major importance

  1. 1.
  2. 2.
    Quality and Outcomes Framework: 2012–13.
  3. 3.
    Hex N, Bartlett C, Wright D, et al. Estimating the current and future costs of type 1 and type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet Med. 2012;29(7):855–62.PubMedGoogle Scholar
  4. 4.
  5. 5.
    Ali MK, Bullard KM, Gregg EW, et al. A cascade of care for diabetes in the United States: visualizing the gaps. Ann Intern Med. 2014;161(10):681–9.PubMedGoogle Scholar
  6. 6.
    American Diabetes Association. Economic costs of diabetes in the U.S. in 2012. Diabetes Care. 2013;36(4):1033–46.PubMedCentralGoogle Scholar
  7. 7.
    Gilg J, Pruthi R, Fogarty D. UK renal registry 17th annual report: chapter 1 UK renal replacement therapy incidence in 2013: national and centre-specific analyses. Nephron Physiol. 2015;129 Suppl 1:1–29.Google Scholar
  8. 8.
    Chapter 1, United States Renal Data System, 2014 annual data report: an overview of the epidemiology of kidney disease in the United States.
  9. 9.
    Chapter 10, United States Renal Data System, 2014 annual data report: an overview of the epidemiology of kidney disease in the United States.
  10. 10.
    United States Renal Data System, 2014 annual data report: an overview of the epidemiology of kidney disease in the United States.
  11. 11.
    Coresh J, Turin TC, Matsushita K, et al. Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality. JAMA. 2014;311(24):2518–31.PubMedGoogle Scholar
  12. 12.
    Fox CS, Matsushita K, Woodward M, et al. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis. Lancet. 2012;380(9854):1662–73.PubMedCentralPubMedGoogle Scholar
  13. 13.
    Hill CJ, Cardwell CR, Patterson CC, et al. Chronic kidney disease and diabetes in the national health service: a cross-sectional survey of the U.K. National Diabetes Audit. Diabet Med. 2014;31(4):448–54.PubMedGoogle Scholar
  14. 14.
    Ho K, McKnight AJ. The changing landscape of diabetic kidney disease: new reflections on phenotype, classification, and disease progression to influence future investigative studies and therapeutic trials. Adv Chronic Kidney Dis. 2014;21(3):256–9.PubMedGoogle Scholar
  15. 15.••
    Marshall SM. Natural history and clinical characteristics of CKD in type 1 and type 2 diabetes mellitus. Adv Chronic Kidney Dis. 2014;21(3):267–72. Comprehensive review explaining the challenges of assigning clinical phenotypes for kidney disease in individuals with diabetes. PubMedGoogle Scholar
  16. 16.
    Mogensen CE, Christensen CK. Predicting diabetic nephropathy in insulin-dependent patients. N Engl J Med. 1984;311(2):89–93.PubMedGoogle Scholar
  17. 17.
    Andersen AR, Christiansen JS, Andersen JK, et al. Diabetic nephropathy in type 1 (insulin-dependent) diabetes: an epidemiological study. Diabetologia. 1983;25(6):496–501.PubMedGoogle Scholar
  18. 18.
    Borch-Johnsen K, Andersen PK, Deckert T. The effect of proteinuria on relative mortality in type 1 (insulin-dependent) diabetes mellitus. Diabetologia. 1985;28(8):590–6.PubMedGoogle Scholar
  19. 19.
    Marshall SM. Diabetic nephropathy in type 1 diabetes: has the outlook improved since the 1980s? Diabetologia. 2012;55(9):2301–6.PubMedGoogle Scholar
  20. 20.
    Mogensen CE, Keane WF, Bennett PH, et al. Prevention of diabetic renal disease with special reference to microalbuminuria. Lancet. 1995;346(8982):1080–4.PubMedGoogle Scholar
  21. 21.
    Viberti GC, Hill RD, Jarrett RJ, et al. Microalbuminuria as a predictor of clinical nephropathy in insulin-dependent diabetes mellitus. Lancet. 1982;1(8287):1430–2.PubMedGoogle Scholar
  22. 22.
    Parving HH, Persson F, Rossing P. Microalbuminuria: a parameter that has changed diabetes care. Diabetes Res Clin Pract. 2015;107(1):1–8.PubMedGoogle Scholar
  23. 23.
    Perkins BA, Ficociello LH, Silva KH, et al. Regression of microalbuminuria in type 1 diabetes. N Engl J Med. 2003;348(23):2285–93.PubMedGoogle Scholar
  24. 24.
    Perkins BA, Ficociello LH, Roshan B, et al. In patients with type 1 diabetes and new-onset microalbuminuria the development of advanced chronic kidney disease may not require progression to proteinuria. Kidney Int. 2010;77(1):57–64.PubMedCentralPubMedGoogle Scholar
  25. 25.
    Caramori ML, Fioretto P, Mauer M. Low glomerular filtration rate in normoalbuminuric type 1 diabetic patients: an indicator of more advanced glomerular lesions. Diabetes. 2003;52(4):1036–40.PubMedGoogle Scholar
  26. 26.
    Najafian B, Alpers CE, Fogo AB. Pathology of human diabetic nephropathy. Contrib Nephrol. 2011;170:36–47.PubMedGoogle Scholar
  27. 27.
    Tervaert TW, Mooyaart AL, Amann K, et al. Pathologic classification of diabetic nephropathy. J Am Soc Nephrol. 2010;21(4):556–63.PubMedGoogle Scholar
  28. 28.
    Mazzucco G, Bertani T, Fortunato M, et al. Different patterns of renal damage in type 2 diabetes mellitus: a multicentric study on 393 biopsies. Am J Kidney Dis. 2002;39(4):713–20.PubMedGoogle Scholar
  29. 29.
    Bell S, Fletcher EH, Brady I, et al. End-stage renal disease and survival in people with diabetes: a national database linkage study. QJM. 2015;108(2):127–34.PubMedCentralPubMedGoogle Scholar
  30. 30.
    Chan Y, Lim ET, Sandholm N, et al. An excess of risk-increasing low-frequency variants can be a signal of polygenic inheritance in complex diseases. Am J Hum Genet. 2014;94(3):437–52.PubMedCentralPubMedGoogle Scholar
  31. 31.
    Placha G, Canani LH, Warram JH, et al. Evidence for different susceptibility genes for proteinuria and ESRD in type 2 diabetes. Adv Chronic Kidney Dis. 2005;12(2):155–69.PubMedGoogle Scholar
  32. 32.
    Kottgen A, Pattaro C, Boger CA, et al. New loci associated with kidney function and chronic kidney disease. Nat Genet. 2010;42(5):376–84.PubMedCentralPubMedGoogle Scholar
  33. 33.
    Sandholm N, Forsblom C, Makinen VP, et al. Genome-wide association study of urinary albumin excretion rate in patients with type 1 diabetes. Diabetologia. 2014;57(6):1143–53.PubMedGoogle Scholar
  34. 34.••
    Sandholm N, McKnight AJ, Salem RM, et al. Chromosome 2q31.1 associates with ESRD in women with type 1 diabetes. J Am Soc Nephrol. 2013;24(10):1537–43. First identification of gender-specific SNP with genome-wide significance for diabetic nephropathy.PubMedCentralPubMedGoogle Scholar
  35. 35.
    Canani LH, Gerchman F, Gross JL. Familial clustering of diabetic nephropathy in Brazilian type 2 diabetic patients. Diabetes. 1999;48(4):909–13.PubMedGoogle Scholar
  36. 36.
    Skrunes R, Svarstad E, Reisaeter AV, et al. Familial clustering of ESRD in the Norwegian population. Clin J Am Soc Nephrol. 2014;9(10):1692–700.PubMedGoogle Scholar
  37. 37.
    Spray BJ, Atassi NG, Tuttle AB, et al. Familial risk, age at onset, and cause of end-stage renal disease in white Americans. J Am Soc Nephrol. 1995;5(10):1806–10.PubMedGoogle Scholar
  38. 38.
    Thameem F, Kawalit IA, Adler SG, et al. Susceptibility gene search for nephropathy and related traits in Mexican-Americans. Mol Biol Rep. 2013;40(10):5769–79.PubMedCentralPubMedGoogle Scholar
  39. 39.
    Adler AI, Stevens RJ, Manley SE, et al. Development and progression of nephropathy in type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS 64). Kidney Int. 2003;63(1):225–32.PubMedGoogle Scholar
  40. 40.
    DCCT Research. Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993;329(14):977–86.Google Scholar
  41. 41.
    Gaede P, Vedel P, Larsen N, et al. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med. 2003;348(5):383–93.PubMedGoogle Scholar
  42. 42.
    Forsblom CM, Kanninen T, Lehtovirta M, et al. Heritability of albumin excretion rate in families of patients with type II diabetes. Diabetologia. 1999;42(11):1359–66.PubMedGoogle Scholar
  43. 43.
    Fogarty DG, Rich SS, Hanna L, et al. Urinary albumin excretion in families with type 2 diabetes is heritable and genetically correlated to blood pressure. Kidney Int. 2000;57(1):250–7.PubMedGoogle Scholar
  44. 44.
    Langefeld CD, Beck SR, Bowden DW, et al. Heritability of GFR and albuminuria in Caucasians with type 2 diabetes mellitus. Am J Kidney Dis. 2004;43(5):796–800.PubMedGoogle Scholar
  45. 45.
    MacCluer JW, Scavini M, Shah VO, et al. Heritability of measures of kidney disease among Zuni Indians: the Zuni Kidney Project. Am J Kidney Dis. 2010;56(2):289–302.PubMedCentralPubMedGoogle Scholar
  46. 46.
    Harjutsalo V, Groop PH. Epidemiology and risk factors for diabetic kidney disease. Adv Chronic Kidney Dis. 2014;21(3):260–6.PubMedGoogle Scholar
  47. 47.
    Bell CG, Teschendorff AE, Rakyan VK, et al. Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus. BMC Med Genomics. 2010;3:33.PubMedCentralPubMedGoogle Scholar
  48. 48.
    Gu T, Gu HF, Hilding A, et al. Increased DNA methylation levels of the insulin-like growth factor binding protein 1 gene are associated with type 2 diabetes in Swedish men. Clin Epigenetics. 2013;5(1):21.PubMedCentralPubMedGoogle Scholar
  49. 49.
    Rakyan VK, Beyan H, Down TA, et al. Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis. PLoS Genet. 2011;7(9):e1002300.PubMedCentralPubMedGoogle Scholar
  50. 50.
    McKnight AJ, McKay GJ, Maxwell AP. Genetic and epigenetic risk factors for diabetic kidney disease. Adv Chron Kidney Dis. 2014;21(3):287–96.Google Scholar
  51. 51.
    McKnight AJ, O’Donoghue D, Peter MA. Annotated chromosome maps for renal disease. Hum Mutat. 2009;30(3):314–20.PubMedGoogle Scholar
  52. 52.
    Nazir N, Siddiqui K, Al-Qasim S, et al. Meta-analysis of diabetic nephropathy associated genetic variants in inflammation and angiogenesis involved in different biochemical pathways. BMC Med Genet. 2014;15(1):103.PubMedCentralPubMedGoogle Scholar
  53. 53.
    Tong Z, Yang Z, Patel S, et al. Promoter polymorphism of the erythropoietin gene in severe diabetic eye and kidney complications. Proc Natl Acad Sci U S A. 2008;105(19):6998–7003.PubMedCentralPubMedGoogle Scholar
  54. 54.
    Williams WW, Salem RM, McKnight AJ, et al. Association testing of previously reported variants in a large case-control meta-analysis of diabetic nephropathy. Diabetes. 2012;61(8):2187–94.PubMedCentralPubMedGoogle Scholar
  55. 55.
    McKnight AJ, Currie D, Maxwell AP. Unravelling the genetic basis of renal diseases; from single gene to multifactorial disorders. J Pathol. 2010;220(2):198–216.PubMedGoogle Scholar
  56. 56.
    Pezzolesi MG, Krolewski AS. The genetic risk of kidney disease in type 2 diabetes. Med Clin N Am. 2013;97(1):91–107.PubMedCentralPubMedGoogle Scholar
  57. 57.
    Igo Jr RP, Iyengar SK, Nicholas SB, et al. Genomewide linkage scan for diabetic renal failure and albuminuria: the FIND study. Am J Nephrol. 2011;33(5):381–9.PubMedCentralPubMedGoogle Scholar
  58. 58.
    Thameem F, Igo Jr RP, Freedman BI, et al. A genome-wide search for linkage of estimated glomerular filtration rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND). PLoS One. 2013;8(12):e81888.PubMedCentralPubMedGoogle Scholar
  59. 59.
    Mahajan A, Sim X, Ng HJ, et al. Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus. PLoS Genet. 2015;11(1):e1004876.PubMedCentralPubMedGoogle Scholar
  60. 60.
    Palmer ND, Goodarzi MO, Langefeld CD et al. Genetic variants associated with quantitative glucose homeostasis traits translate to type 2 diabetes in Mexican Americans: the GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium. Diabetes 2014.Google Scholar
  61. 61.
    Kuchenbaecker KB, Ramus SJ, Tyrer J, et al. Identification of six new susceptibility loci for invasive epithelial ovarian cancer. Nat Genet. 2015;47(2):164–71.PubMedGoogle Scholar
  62. 62.
    Al Olama AA, Kote-Jarai Z, Berndt SI, et al. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer. Nat Genet. 2014;46(10):1103–9.PubMedCentralPubMedGoogle Scholar
  63. 63.
    Lambert JC, Ibrahim-Verbaas CA, Harold D, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat Genet. 2013;45(12):1452–8.PubMedCentralPubMedGoogle Scholar
  64. 64.
    Ha NT, Freytag S, Bickeboeller H. Coverage and efficiency in current SNP chips. Eur J Hum Genet. 2014;22(9):1124–30.PubMedGoogle Scholar
  65. 65.
    Little J, Higgins JP, Ioannidis JP, et al. STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement. PLoS Med. 2009;6(2):e22.PubMedGoogle Scholar
  66. 66.
    Winkler TW, Day FR, Croteau-Chonka DC, et al. Quality control and conduct of genome-wide association meta-analyses. Nat Protoc. 2014;9(5):1192–212.PubMedCentralPubMedGoogle Scholar
  67. 67.
    Feehally J, Farrall M, Boland A, et al. HLA has strongest association with IgA nephropathy in genome-wide analysis. J Am Soc Nephrol. 2010;21(10):1791–7.PubMedCentralPubMedGoogle Scholar
  68. 68.
    Kiryluk K, Li Y, Scolari F, et al. Discovery of new risk loci for IgA nephropathy implicates genes involved in immunity against intestinal pathogens. Nat Genet. 2014;46(11):1187–96.PubMedCentralPubMedGoogle Scholar
  69. 69.
    Stanescu HC, Arcos-Burgos M, Medlar A, et al. Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy. N Engl J Med. 2011;364(7):616–26.PubMedGoogle Scholar
  70. 70.
    Genovese G, Tonna SJ, Knob AU, et al. A risk allele for focal segmental glomerulosclerosis in African Americans is located within a region containing APOL1 and MYH9. Kidney Int. 2010;78(7):698–704.PubMedCentralPubMedGoogle Scholar
  71. 71.
    Kopp JB, Smith MW, Nelson GW, et al. MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis. Nat Genet. 2008;40(10):1175–84.PubMedCentralPubMedGoogle Scholar
  72. 72.
    Kottgen A, Glazer NL, Dehghan A, et al. Multiple loci associated with indices of renal function and chronic kidney disease. Nat Genet. 2009;41(6):712–7.PubMedCentralPubMedGoogle Scholar
  73. 73.
    Liu CT, Garnaas MK, Tin A, et al. Genetic association for renal traits among participants of African ancestry reveals new loci for renal function. PLoS Genet. 2011;7(9):e1002264.PubMedCentralPubMedGoogle Scholar
  74. 74.
    Kao WH, Klag MJ, Meoni LA, et al. MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat Genet. 2008;40(10):1185–92.PubMedGoogle Scholar
  75. 75.••
    Sandholm N, Salem RM, McKnight AJ, et al. New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet. 2012;8(9):e1002921. Largest meta-analysis of GWAS conducted for diabetic nephropathy with replication confirming significant SNPs. PubMedCentralPubMedGoogle Scholar
  76. 76.
    Shimazaki A, Kawamura Y, Kanazawa A, et al. Genetic variations in the gene encoding ELMO1 are associated with susceptibility to diabetic nephropathy. Diabetes. 2005;54(4):1171–8.PubMedGoogle Scholar
  77. 77.
    Hanson RL, Millis MP, Young NJ, et al. ELMO1 variants and susceptibility to diabetic nephropathy in American Indians. Mol Genet Metab. 2010;101(4):383–90.PubMedGoogle Scholar
  78. 78.
    Leak TS, Perlegas PS, Smith SG, et al. Variants in intron 13 of the ELMO1 gene are associated with diabetic nephropathy in African Americans. Ann Hum Genet. 2009;73(2):152–9.PubMedCentralPubMedGoogle Scholar
  79. 79.
    Pezzolesi MG, Katavetin P, Kure M, et al. Confirmation of genetic associations at ELMO1 in the GoKinD collection supports its role as a susceptibility gene in diabetic nephropathy. Diabetes. 2009;58(11):2698–702.PubMedCentralPubMedGoogle Scholar
  80. 80.
    Wu HY, Wang Y, Chen M, et al. Association of ELMO1 gene polymorphisms with diabetic nephropathy in Chinese population. J Endocrinol Invest. 2013;36(5):298–302.PubMedGoogle Scholar
  81. 81.
    Yadav AK, Kumar V, Dutta P, et al. Variations in CCR5, but not HFE, ELMO1, or SLC12A3, are associated with susceptibility to kidney disease in north Indian individuals with type 2 diabetes CCR5HFEELMO1SLC12A32. J Diabetes. 2014;6(6):547–55.PubMedGoogle Scholar
  82. 82.
    Franceschini N, Shara NM, Wang H, et al. The association of genetic variants of type 2 diabetes with kidney function. Kidney Int. 2012;82(2):220–5.PubMedCentralPubMedGoogle Scholar
  83. 83.
    Hanson RL, Craig DW, Millis MP, 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. 2007;56(4):975–83.PubMedGoogle Scholar
  84. 84.
    McDonough CW, Palmer ND, Hicks PJ, et al. A genome-wide association study for diabetic nephropathy genes in African Americans. Kidney Int. 2011;79(5):563–72.PubMedCentralPubMedGoogle Scholar
  85. 85.
    Ebers GC, Sadovnik AD. Re: GAMES issue. J Neuroimmunol. 2004;153(1–2):4–5.PubMedGoogle Scholar
  86. 86.
    McKnight AJ, Maxwell AP, Sawcer S, et al. A genome-wide DNA microsatellite association screen to identify chromosomal regions harboring candidate genes in diabetic nephropathy. J Am Soc Nephrol. 2006;17(3):831–6.PubMedGoogle Scholar
  87. 87.
    Craig DW, Millis MP, DiStefano JK. Genome-wide SNP genotyping study using pooled DNA to identify candidate markers mediating susceptibility to end-stage renal disease attributed to type 1 diabetes. Diabet Med. 2009;26(11):1090–8.PubMedGoogle Scholar
  88. 88.
    Pezzolesi MG, Poznik GD, Mychaleckyj JC, et al. Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes. 2009;58(6):1403–10.PubMedCentralPubMedGoogle Scholar
  89. 89.
    Palmer ND, Ng MC, Hicks PJ, et al. Evaluation of candidate nephropathy susceptibility genes in a genome-wide association study of African American diabetic kidney disease. PLoS One. 2014;9(2):e88273.PubMedCentralPubMedGoogle Scholar
  90. 90.
    Martini S, Nair V, Patel SR, et al. From single nucleotide polymorphism to transcriptional mechanism: a model for FRMD3 in diabetic nephropathy. Diabetes. 2013;62(7):2605–12.PubMedCentralPubMedGoogle Scholar
  91. 91.
    Tryka KA, Hao L, Sturcke A, et al. NCBI’s database of Genotypes and Phenotypes: dbGaP. Nucleic Acids Res. 2014;42(Database issue):D975–9.PubMedCentralPubMedGoogle Scholar
  92. 92.
    Maeda S, Imamura M, Kurashige M, et al. Replication study for the association of 3 SNP loci identified in a genome-wide association study for diabetic nephropathy in European type 1 diabetes with diabetic nephropathy in Japanese patients with type 2 diabetes. Clin Exp Nephrol. 2013;17(6):866–71.PubMedGoogle Scholar
  93. 93.
    Sambo F, Malovini A, Sandholm N, et al. Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification. Diabetologia. 2014;57(8):1611–22.PubMedGoogle Scholar
  94. 94.
    Germain M, Pezzolesi MG, Sandholm N, et al. SORBS1 gene, a new candidate for diabetic nephropathy: results from a multi-stage genome-wide association study in patients with type 1 diabetes. Diabetologia. 2015;58(3):543–8.PubMedGoogle Scholar
  95. 95.
    Lettre G, Jackson AU, Gieger C, et al. Identification of ten loci associated with height highlights new biological pathways in human growth. Nat Genet. 2008;40(5):584–91.PubMedCentralPubMedGoogle Scholar
  96. 96.
    Lango AH, Estrada K, Lettre G, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010;467(7317):832–8.Google Scholar
  97. 97.
    Wood AR, Esko T, Yang J, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet. 2014;46(11):1173–86.PubMedCentralPubMedGoogle Scholar
  98. 98.
    Harjutsalo V, Maric C, Forsblom C, et al. Sex-related differences in the long-term risk of microvascular complications by age at onset of type 1 diabetes. Diabetologia. 2011;54(8):1992–9.PubMedGoogle Scholar
  99. 99.
    Charchar FJ, Bloomer LD, Barnes TA, et al. Inheritance of coronary artery disease in men: an analysis of the role of the Y chromosome. Lancet. 2012;379(9819):915–22.PubMedCentralPubMedGoogle Scholar
  100. 100.
    Sharma K, Karl B, Mathew AV, et al. Metabolomics reveals signature of mitochondrial dysfunction in diabetic kidney disease. J Am Soc Nephrol. 2013;24(11):1901–12.PubMedCentralPubMedGoogle Scholar
  101. 101.
    Higgins GC, Coughlan MT. Mitochondrial dysfunction and mitophagy: the beginning and end to diabetic nephropathy? Br J Pharmacol. 2014;171(8):1917–42.PubMedCentralPubMedGoogle Scholar
  102. 102.
    Swan EJ, Salem RM, Sandholm N et al. Genetic risk factors affecting mitochondrial function are associated with kidney disease in individuals with type 1 diabetes. Diabet Med 2015.Google Scholar
  103. 103.
    Swan EJ, Maxwell AP, McKnight AJ. Distinct methylation patterns in genes that affect mitochondrial function are associated with kidney disease in blood-derived DNA from individuals with type 1 diabetes. Diabet Med 2015.Google Scholar
  104. 104.
    Douglas AP, Vance DR, Kenny EM, et al. Next-generation sequencing of the mitochondrial genome and association with IgA nephropathy in a renal transplant population. Sci Rep. 2014;4:7379.PubMedCentralPubMedGoogle Scholar
  105. 105.
    McKnight AJ, Maxwell AP. Bioinformatic Resources for Diabetic Nephropathy. J Diabetes Bioinforma. 2013;1(1):11–8.Google Scholar
  106. 106.
    Martini S, Nair V, Keller BJ, et al. Integrative biology identifies shared transcriptional networks in CKD. J Am Soc Nephrol. 2014;25(11):2559–72.PubMedGoogle Scholar
  107. 107.
    Brennan EP, Morine MJ, Walsh DW, et al. Next-generation sequencing identifies TGF-beta1-associated gene expression profiles in renal epithelial cells reiterated in human diabetic nephropathy. Biochim Biophys Acta. 2012;1822(4):589–99.PubMedCentralPubMedGoogle Scholar
  108. 108.
    Liu R, Zhong Y, Li X, et al. Role of transcription factor acetylation in diabetic kidney disease. Diabetes. 2014;63(7):2440–53.PubMedGoogle Scholar
  109. 109.
    Miao F, Chen Z, Genuth S, et al. Evaluating the role of epigenetic histone modifications in the metabolic memory of type 1 diabetes. Diabetes. 2014;63(5):1748–62.PubMedCentralPubMedGoogle Scholar
  110. 110.
    Reddy MA, Sumanth P, Lanting L, et al. Losartan reverses permissive epigenetic changes in renal glomeruli of diabetic db/db mice. Kidney Int. 2014;85(2):362–73.PubMedCentralPubMedGoogle Scholar
  111. 111.
    Kato M, Zhang J, Wang M, et al. MicroRNA-192 in diabetic kidney glomeruli and its function in TGF-beta-induced collagen expression via inhibition of E-box repressors. Proc Natl Acad Sci U S A. 2007;104(9):3432–7.PubMedCentralPubMedGoogle Scholar
  112. 112.
    Zhou Q, Chung AC, Huang XR, et al. Identification of novel long noncoding RNAs associated with TGF-beta/Smad3-mediated renal inflammation and fibrosis by RNA sequencing. Am J Pathol. 2014;184(2):409–17.PubMedGoogle Scholar
  113. 113.
    Zhou J, Peng R, Li T, et al. A potentially functional polymorphism in the regulatory region of let-7a-2 is associated with an increased risk for diabetic nephropathy. Gene. 2013;527(2):456–61.PubMedGoogle Scholar
  114. 114.
    Smyth LJ, McKay GJ, Maxwell AP, et al. DNA hypermethylation and DNA hypomethylation is present at different loci in chronic kidney disease. Epigenetics. 2014;9(3):366–76.PubMedCentralPubMedGoogle Scholar
  115. 115.
    Zhang H, Cai X, Yi B, et al. Correlation of CTGF gene promoter methylation with CTGF expression in type 2 diabetes mellitus with or without nephropathy. Mol Med Rep. 2014;9(6):2138–44.PubMedCentralPubMedGoogle Scholar
  116. 116.
    Sapienza C, Lee J, Powell J, et al. DNA methylation profiling identifies epigenetic differences between diabetes patients with ESRD and diabetes patients without nephropathy. Epigenetics. 2011;6(1):20–8.PubMedGoogle Scholar
  117. 117.
    Hirayama A, Nakashima E, Sugimoto M, et al. Metabolic profiling reveals new serum biomarkers for differentiating diabetic nephropathy. Anal Bioanal Chem. 2012;404(10):3101–9.PubMedGoogle Scholar
  118. 118.
    Pena MJ, Lambers Heerspink HJ, Hellemons ME, et al. Urine and plasma metabolites predict the development of diabetic nephropathy in individuals with type 2 diabetes mellitus. Diabet Med. 2014;31(9):1138–47.PubMedGoogle Scholar
  119. 119.
    Stec DF, Wang S, Stothers C, et al. Alterations of urinary metabolite profile in model diabetic nephropathy. Biochem Biophys Res Commun. 2015;456(2):610–4.PubMedGoogle Scholar
  120. 120.
    Zubiri I, Posada-Ayala M, Sanz-Maroto A, et al. Diabetic nephropathy induces changes in the proteome of human urinary exosomes as revealed by label-free comparative analysis. J Proteomics. 2014;96:92–102.PubMedGoogle Scholar
  121. 121.
    Caseiro A, Barros A, Ferreira R, et al. Pursuing type 1 diabetes mellitus and related complications through urinary proteomics. Transl Res. 2014;163(3):188–99.PubMedGoogle Scholar
  122. 122.
    Zurbig P, Jerums G, Hovind P, et al. Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes. 2012;61(12):3304–13.PubMedCentralPubMedGoogle Scholar
  123. 123.
    Locke AE, Kahalo B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–206.PubMedCentralPubMedGoogle Scholar
  124. 124.
    Shungin D, Winkler TW, Croteau-Chonka DC, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015;518(7538):187–96.PubMedGoogle Scholar
  125. 125.
    Pers TH, Karjalainen JM, Chan Y, et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat Commun. 2015;6:5890.PubMedCentralPubMedGoogle Scholar
  126. 126.
    Abecasis GR, Auton A, Brooks LD, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422):56–65.PubMedGoogle Scholar
  127. 127.
    Genonics England. The 100,000 Genomes Project.
  128. 128.
    McKnight AJ, Currie D, Patterson CC, et al. Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy. Hugo J. 2009;3(1–4):77–82.PubMedCentralPubMedGoogle Scholar
  129. 129.
    Savage DA, Patterson CC, Deloukas P, et al. Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy. Diabetologia. 2008;51(11):1998–2002.PubMedCentralPubMedGoogle Scholar
  130. 130.
    Cooke Bailey JN, Palmer ND, Ng MC, et al. Analysis of coding variants identified from exome sequencing resources for association with diabetic and non-diabetic nephropathy in African Americans. Hum Genet. 2014;133(6):769–79.PubMedGoogle Scholar
  131. 131.
    Collins R. What makes UK Biobank special? Lancet. 2012;379(9822):1173–4.PubMedGoogle Scholar
  132. 132.
    Kerr SM, Campbell A, Murphy L, et al. Pedigree and genotyping quality analyses of over 10,000 DNA samples from the Generation Scotland: Scottish Family Health Study. BMC Med Genet. 2013;14:38.PubMedCentralPubMedGoogle Scholar
  133. 133.
    Zhang C, Pierce BL. Genetic susceptibility to accelerated cognitive decline in the US Health and Retirement Study. Neurobiol Aging. 2014;35(6):1512–8.Google Scholar
  134. 134.
    Westra HJ, Peters MJ, Esko T, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet. 2013;45(10):1238–43.PubMedCentralPubMedGoogle Scholar
  135. 135.
    Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40(Database issue):D930–4.PubMedCentralPubMedGoogle Scholar
  136. 136.
    Mooyaart AL, Valk EJ, van Es LA, et al. Genetic associations in diabetic nephropathy: a meta-analysis. Diabetologia. 2014;57(3):650.Google Scholar
  137. 137.
    Garcia DL, Anderson S, Rennke HG, Brenner BM. Anemia lessens and its prevention with recombinant human erythropoietin worsens glomerular injury and hypertension in rats with reduced renal mass. Proc Natl Acad Sci U S A. 1988;85(16):6142–6.PubMedCentralPubMedGoogle Scholar
  138. 138.
    Veikkolainen V, Naillat F, Railo A, et al. ErbB4 modulates tubular cell polarity and lumen diameter during kidney development. J Am Soc Nephrol. 2012;23(1):112–22.PubMedCentralPubMedGoogle Scholar
  139. 139.
    Zeng F, Zhang MZ, Singh AB, et al. ErbB4 isoforms selectively regulate growth factor induced Madin-Darby canine kidney cell tubulogenesis. Mol Biol Cell. 2007;18(11):4446–56.PubMedCentralPubMedGoogle Scholar
  140. 140.
    Woroniecka KI, Park AS, Mohtat D, Thomas DB, Pullman JM, Susztak K. Transcriptome analysis of human diabetic kidney disease. Diabetes. 2011;60(9):2354–69.PubMedCentralPubMedGoogle Scholar
  141. 141.
    Schmid H, Boucherot A, Yasuda Y, et al. Modular activation of nuclear factor-kappaB transcriptional programs in human diabetic nephropathy. Diabetes. 2006;55(11):2993–3003.PubMedGoogle Scholar
  142. 142.
    Lin WH, Huang CJ, Liu MW, et al. Cloning, mapping, and characterization of the human sorbin and SH3 domain containing 1 (SORBS1) gene: a protein associated with c-Abl during insulin signaling in the hepatoma cell line Hep3B. Genomics. 2001;74(1):12–20.PubMedGoogle Scholar
  143. 143.
    Nakatani S, Kakehashi A, Ishimura E et al. Targeted proteomics of isolated glomeruli from the kidneys of diabetic rats: sorbin and SH3 domain containing 2 is a novel protein associated with diabetic nephropathy. Exp Diabetes Res. 2011.Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Amy Jayne McKnight
    • 1
  • Seamus Duffy
    • 1
  • Alexander P. Maxwell
    • 1
    • 2
    Email author
  1. 1.Nephrology Research Group, Centre for Public HealthQueen’s University Belfast, c/o Regional Genetics Centre, Level A, Tower Block, Belfast City HospitalBelfastUK
  2. 2.Regional Nephrology UnitBelfast City HospitalBelfastUK

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