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Advances in understanding the genetic basis of diabetic kidney disease

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Abstract

Diabetic kidney disease (DKD) is a devastating complication of Type 1 and Type 2 diabetes and leads to increased morbidity and mortality. Earlier work in families has provided strong evidence that heredity is a major determinant of DKD. Previous linkage analyses and candidate gene studies have identified potential DKD genes; however, such approaches have largely been unsuccessful. Genome-wide association studies (GWAS) have made significant contribution in identifying SNPs associated with common complex diseases. Thanks to advanced technology, new analytical approaches, and international research collaborations, many DKD GWASs have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms. This review summarizes the current state of GWAS technology; findings from GWASs of DKD and its related traits conducted over the past 15 years and discuss the future of this field.

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References

  1. Krolewski ASWJ (1997) Clinical features and epidemiology of diabetic nephropathy. In: Pickup JCWG (ed) Textbook of diabetes, vol 2, 2nd edn. Blackwell Scientific Publications, Oxford, pp 53.51–53.13

    Google Scholar 

  2. Parving HHMM, Ritz E (2004) Diabetic nephropathy. In: BM B (ed) Brenner and Rector’s the kidney, 7th edn. Elsevier, Philadelphia, pp 1777–1818

    Google Scholar 

  3. Jones CA, Krolewski AS, Rogus J, Xue JL, Collins A, Warram JH (2005) Epidemic of end-stage renal disease in people with diabetes in the United States population: do we know the cause? Kidney Int 67(5):1684–1691

    Article  PubMed  Google Scholar 

  4. Fogarty DG, Rich SS, Hanna L, Warram JH, Krolewski AS (2000) Urinary albumin excretion in families with type 2 diabetes is heritable and genetically correlated to blood pressure. Kidney Int 57(1):250–257

    Article  CAS  PubMed  Google Scholar 

  5. Forsblom CM, Kanninen T, Lehtovirta M, Saloranta C, Groop LC (1999) Heritability of albumin excretion rate in families of patients with Type II diabetes. Diabetologia 42(11):1359–1366

    Article  CAS  PubMed  Google Scholar 

  6. Hunter DJ, Lange M, Snieder H, MacGregor AJ, Swaminathan R, Thakker RV, Spector TD (2002) Genetic contribution to renal function and electrolyte balance: a twin study. Clin Sci (Lond) 103(3):259–265

    Article  CAS  Google Scholar 

  7. Krolewski AS, Poznik GD, Placha G, Canani L, Dunn J, Walker W, Smiles A et al (2006) A genome-wide linkage scan for genes controlling variation in urinary albumin excretion in type II diabetes. Kidney Int 69(1):129–136

    Article  CAS  PubMed  Google Scholar 

  8. Langefeld CD, Beck SR, Bowden DW, Rich SS, Wagenknecht LE, Freedman BI (2004) Heritability of GFR and albuminuria in Caucasians with type 2 diabetes mellitus. Am J Kidney Dis 43(5):796–800

    Article  PubMed  Google Scholar 

  9. Hipkiss AR, Preston JE, Himsworth DT, Worthington VC, Keown M, Michaelis J, Lawrence J et al (1998) Pluripotent protective effects of carnosine, a naturally occurring dipeptide. Ann N Y Acad Sci 854:37–53

    Article  CAS  PubMed  Google Scholar 

  10. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K et al (2001) Initial sequencing and analysis of the human genome. Nature 409(6822):860–921. https://doi.org/10.1038/35057062

    Article  CAS  PubMed  Google Scholar 

  11. International HapMap C (2005) A haplotype map of the human genome. Nature 437(7063):1299–1320. https://doi.org/10.1038/nature04226

    Article  CAS  Google Scholar 

  12. Reich DE, Lander ES (2001) On the allelic spectrum of human disease. Trends Genet 17(9):502–510

    Article  CAS  PubMed  Google Scholar 

  13. Pezzolesi MG, Skupien J, Mychaleckyj JC, Warram JH, Krolewski AS (2010) Insights to the genetics of diabetic nephropathy through a genome-wide association study of the GoKinD collection. Semin Nephrol 30(2):126–140. https://doi.org/10.1016/j.semnephrol.2010.01.004

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wang WY, Barratt BJ, Clayton DG, Todd JA (2005) Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet 6(2):109–118. https://doi.org/10.1038/nrg1522

    Article  CAS  PubMed  Google Scholar 

  15. Grayson BL, Smith ME, Thomas JW, Wang L, Dexheimer P, Jeffrey J, Fain PR et al (2010) Genome-wide analysis of copy number variation in type 1 diabetes. PLoS One 5(11):e15393. https://doi.org/10.1371/journal.pone.0015393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wheeler E, Huang N, Bochukova EG, Keogh JM, Lindsay S, Garg S, Henning E et al (2013) Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat Genet 45(5):513–517. https://doi.org/10.1038/ng.2607

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Marchini J, Howie B (2010) Genotype imputation for genome-wide association studies. Nat Rev Genet 11(7):499–511. https://doi.org/10.1038/nrg2796

    Article  CAS  PubMed  Google Scholar 

  18. Browning SR, Browning BL (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Human Genet 81(5):1084–1097. https://doi.org/10.1086/521987

    Article  CAS  Google Scholar 

  19. Marchini J, Howie B, Myers S, McVean G, Donnelly P (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39(7):906–913. https://doi.org/10.1038/ng2088

    Article  CAS  PubMed  Google Scholar 

  20. Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 34(8):816–834. https://doi.org/10.1002/gepi.20533

    Article  PubMed  PubMed Central  Google Scholar 

  21. Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL et al (2015) A global reference for human genetic variation. Nature 526(7571):68–74. https://doi.org/10.1038/nature15393

    Article  CAS  PubMed  Google Scholar 

  22. Najafian B, Mauer M (2012) Morphologic features of declining renal function in type 1 diabetes. Semin Nephrol 32(5):415–422. https://doi.org/10.1016/j.semnephrol.2012.07.003

    Article  PubMed  PubMed Central  Google Scholar 

  23. Krolewski AS, Bonventre JV (2012) High risk of ESRD in type 1 diabetes: new strategies are needed to retard progressive renal function decline. Semin Nephrol 32(5):407–414. https://doi.org/10.1016/j.semnephrol.2012.07.002

    Article  PubMed  PubMed Central  Google Scholar 

  24. Finne P, Reunanen A, Stenman S, Groop PH, Gronhagen-Riska C (2005) Incidence of end-stage renal disease in patients with type 1 diabetes. JAMA 294(14):1782–1787. https://doi.org/10.1001/jama.294.14.1782

    Article  CAS  PubMed  Google Scholar 

  25. Harjutsalo V, Maric C, Forsblom C, Thorn L, Waden J, Groop PH (2011) Sex-related differences in the long-term risk of microvascular complications by age at onset of type 1 diabetes. Diabetologia 54(8):1992–1999. https://doi.org/10.1007/s00125-011-2144-2

    Article  CAS  PubMed  Google Scholar 

  26. Sandholm N, Salem RM, McKnight AJ, Brennan EP, Forsblom C, Isakova T, McKay GJ et al (2012) New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet 8(9):e1002921. https://doi.org/10.1371/journal.pgen.1002921

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Teumer A, Tin A, Sorice R, Gorski M, Yeo NC, Chu AY, Li M et al (2016) Genome-wide association studies identify genetic loci associated with albuminuria in diabetes. Diabetes 65(3):803–817. https://doi.org/10.2337/db15-1313

    Article  CAS  PubMed  Google Scholar 

  28. van Zuydam NR, Ahlqvist E, Sandholm N, Deshmukh H, Rayner NW, Abdalla M, Ladenvall C et al (2018) A genome-wide association study of diabetic kidney disease in subjects with Type 2 diabetes. Diabetes. https://doi.org/10.2337/db17-0914

    Article  PubMed  PubMed Central  Google Scholar 

  29. Sandholm N, Van Zuydam N, Ahlqvist E, Juliusdottir T, Deshmukh HA, Rayner NW, Di Camillo B et al (2017) The genetic landscape of renal complications in Type 1 diabetes. J Am Soc Nephrol 28(2):557–574. https://doi.org/10.1681/ASN.2016020231

    Article  PubMed  Google Scholar 

  30. Iyengar SK, Sedor JR, Freedman BI, Kao WH, Kretzler M, Keller BJ, Abboud HE et al (2015) Genome-wide association and trans-ethnic meta-analysis for advanced diabetic kidney disease: family investigation of nephropathy and diabetes (FIND). PLoS Genet 11(8):e1005352. https://doi.org/10.1371/journal.pgen.1005352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pezzolesi MG, Poznik GD, Mychaleckyj JC, Paterson AD, Barati MT, Klein JB, Ng DP et al (2009) Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes 58(6):1403–1410. https://doi.org/10.2337/db08-1514

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Shimazaki A, Kawamura Y, Kanazawa A, Sekine A, Saito S, Tsunoda T, Koya D et al (2005) Genetic variations in the gene encoding ELMO1 are associated with susceptibility to diabetic nephropathy. Diabetes 54(4):1171–1178

    Article  CAS  PubMed  Google Scholar 

  33. Germain M, Pezzolesi MG, Sandholm N, McKnight AJ, Susztak K, Lajer M, Forsblom C et al (2015) SORBS1 gene, a new candidate for diabetic nephropathy: results from a multi-stage genome-wide association study in patients with type 1 diabetes. Diabetologia 58(3):543–548. https://doi.org/10.1007/s00125-014-3459-6

    Article  CAS  PubMed  Google Scholar 

  34. Tanaka N, Babazono T, Saito S, Sekine A, Tsunoda T, Haneda M, Tanaka Y et al (2003) Association of solute carrier family 12 (sodium/chloride) member 3 with diabetic nephropathy, identified by genome-wide analyses of single nucleotide polymorphisms. Diabetes 52(11):2848–2853

    Article  CAS  PubMed  Google Scholar 

  35. Mueller PW, Rogus JJ, Cleary PA, Zhao Y, Smiles AM, Steffes MW, Bucksa J et al (2006) Genetics of Kidneys in Diabetes (GoKinD) study: a genetics collection available for identifying genetic susceptibility factors for diabetic nephropathy in type 1 diabetes. J Am Soc Nephrol 17(7):1782–1790. https://doi.org/10.1681/ASN.2005080822

    Article  CAS  PubMed  Google Scholar 

  36. Pezzolesi MG, Poznik GD, Skupien J, Smiles AM, Mychaleckyj JC, Rich SS, Warram JH et al (2011) An intergenic region on chromosome 13q33.3 is associated with the susceptibility to kidney disease in type 1 and 2 diabetes. Kidney Int 80(1):105–111. https://doi.org/10.1038/ki.2011.64

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Palmer ND, Ng MC, Hicks PJ, Mudgal P, Langefeld CD, Freedman BI, Bowden DW (2014) Evaluation of candidate nephropathy susceptibility genes in a genome-wide association study of African American diabetic kidney disease. PloS One 9(2):e88273. https://doi.org/10.1371/journal.pone.0088273

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Maeda S, Araki S, Babazono T, Toyoda M, Umezono T, Kawai K, Imanishi M et al (2010) Replication study for the association between four Loci identified by a genome-wide association study on European American subjects with type 1 diabetes and susceptibility to diabetic nephropathy in Japanese subjects with type 2 diabetes. Diabetes 59(8):2075–2079. https://doi.org/10.2337/db10-0067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Sandholm N, McKnight AJ, Salem RM, Brennan EP, Forsblom C, Harjutsalo V, Makinen VP et al (2013) Chromosome 2q31.1 associates with ESRD in women with type 1 diabetes. J Am Soc Nephrol 24(10):1537–1543. https://doi.org/10.1681/ASN.2012111122

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Sandholm N, Forsblom C, Makinen VP, McKnight AJ, Osterholm AM, He B, Harjutsalo V et al (2014) Genome-wide association study of urinary albumin excretion rate in patients with type 1 diabetes. Diabetologia 57(6):1143–1153. https://doi.org/10.1007/s00125-014-3202-3

    Article  CAS  PubMed  Google Scholar 

  41. Kao WH, Klag MJ, Meoni LA, Reich D, Berthier-Schaad Y, Li M, Coresh J et al (2008) MYH9 is associated with nondiabetic end-stage renal disease in African Americans. Nat Genet 40(10):1185–1192

    Article  CAS  PubMed  Google Scholar 

  42. Kopp JB, Smith MW, Nelson GW, Johnson RC, Freedman BI, Bowden DW, Oleksyk T et al (2008) MYH9 is a major-effect risk gene for focal segmental glomerulosclerosis. Nat Genet 40(10):1175–1184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Genovese G, Friedman DJ, Ross MD, Lecordier L, Uzureau P, Freedman BI, Bowden DW et al (2010) Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329(5993):841–845. https://doi.org/10.1126/science.1193032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Pattaro C, Teumer A, Gorski M, Chu AY, Li M, Mijatovic V, Garnaas M et al (2016) Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function. Nat Commun 7:10023. https://doi.org/10.1038/ncomms10023

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Gallagher MD, Chen-Plotkin AS (2018) The post-GWAS era: from association to function. Am J Human Genet 102(5):717–730. https://doi.org/10.1016/j.ajhg.2018.04.002

    Article  CAS  Google Scholar 

  46. Shimazaki A, Tanaka Y, Shinosaki T, Ikeda M, Watada H, Hirose T, Kawamori R et al (2006) ELMO1 increases expression of extracellular matrix proteins and inhibits cell adhesion to ECMs. Kidney Int 70(10):1769–1776

    Article  CAS  PubMed  Google Scholar 

  47. Martini S, Nair V, Patel SR, Eichinger F, Nelson RG, Weil EJ, Pezzolesi MG et al (2013) From single nucleotide polymorphism to transcriptional mechanism: a model for FRMD3 in diabetic nephropathy. Diabetes 62(7):2605–2612. https://doi.org/10.2337/db12-1416

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Gumienny TL, Brugnera E, Tosello-Trampont AC, Kinchen JM, Haney LB, Nishiwaki K, Walk SF et al (2001) CED-12/ELMO, a novel member of the CrkII/Dock180/Rac pathway, is required for phagocytosis and cell migration. Cell 107(1):27–41

    Article  CAS  PubMed  Google Scholar 

  49. Wu HY, Wang Y, Chen M, Zhang X, Wang D, Pan Y, Li L et al (2013) Association of ELMO1 gene polymorphisms with diabetic nephropathy in Chinese population. J Endocrinol Invest 36(5):298–302. https://doi.org/10.3275/8525

    Article  CAS  PubMed  Google Scholar 

  50. Leak TS, Perlegas PS, Smith SG, Keene KL, Hicks PJ, Langefeld CD, Mychaleckyj JC et al (2009) Variants in intron 13 of the ELMO1 gene are associated with diabetic nephropathy in African Americans. Ann Hum Genet 73(2):152–159

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hanson RL, Millis MP, Young NJ, Kobes S, Nelson RG, Knowler WC, DiStefano JK (2010) ELMO1 variants and susceptibility to diabetic nephropathy in American Indians. Mol Genet Metab 101(4):383–390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Pezzolesi MG, Katavetin P, Kure M, Poznik GD, Skupien J, Mychaleckyj JC, Rich SS et al (2009) Confirmation of genetic associations at ELMO1 in the GoKinD collection supports its role as a susceptibility gene in diabetic nephropathy. Diabetes 58(11):2698–2702

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Freedman BI, Langefeld CD, Lu L, Divers J, Comeau ME, Kopp JB, Winkler CA et al (2011) Differential effects of MYH9 and APOL1 risk variants on FRMD3 association with diabetic ESRD in African Americans. PLoS Genet 7(6):e1002150. https://doi.org/10.1371/journal.pgen.1002150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Pezzolesi MG, Jeong J, Smiles AM, Skupien J, Mychaleckyj JC, Rich SS, Warram JH et al (2013) Family-based association analysis confirms the role of the chromosome 9q21.32 locus in the susceptibility of diabetic nephropathy. PloS One 8(3):e60301. https://doi.org/10.1371/journal.pone.0060301

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, Motyer A et al (2017) Genome-wide genetic data on ~ 500,000 UK Biobank participants. BioRxiv. https://doi.org/10.1101/166298

    Article  Google Scholar 

  56. Gaziano JM, Concato J, Brophy M, Fiore L, Pyarajan S, Breeling J, Whitbourne S et al (2016) Million Veteran Program: A mega-biobank to study genetic influences on health and disease. J Clin Epidemiol 70:214–223. https://doi.org/10.1016/j.jclinepi.2015.09.016

    Article  PubMed  Google Scholar 

  57. Perkins BA, Ficociello LH, Silva KH, Finkelstein DM, Warram JH, Krolewski AS (2003) Regression of microalbuminuria in type 1 diabetes. N Engl J Med 348(23):2285–2293. https://doi.org/10.1056/NEJMoa021835

    Article  CAS  PubMed  Google Scholar 

  58. Perkins BA, Ficociello LH, Ostrander BE, Silva KH, Weinberg J, Warram JH, Krolewski AS (2007) Microalbuminuria and the risk for early progressive renal function decline in type 1 diabetes. J Am Soc Nephrol 18(4):1353–1361. https://doi.org/10.1681/asn.2006080872

    Article  CAS  PubMed  Google Scholar 

  59. Perkins BA, Ficociello LH, Roshan B, Warram JH, Krolewski AS (2010) 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 77(1):57–64. https://doi.org/10.1038/ki.2009.399

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Skupien J, Warram JH, Smiles AM, Niewczas MA, Gohda T, Pezzolesi MG, Cantarovich D et al (2012) The early decline in renal function in patients with type 1 diabetes and proteinuria predicts the risk of end-stage renal disease. Kidney Int 82(5):589–597. https://doi.org/10.1038/ki.2012.189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Krolewski AS (2015) Progressive renal decline: the new paradigm of diabetic nephropathy in type 1 diabetes. Diabetes Care 38(6):954–962. https://doi.org/10.2337/dc15-0184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Niewczas MA, Gohda T, Skupien J, Smiles AM, Walker WH, Rosetti F, Cullere X et al (2012) Circulating TNF receptors 1 and 2 predict ESRD in type 2 diabetes. J Am Soc Nephrol 23(3):507–515. https://doi.org/10.1681/asn.2011060627

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Gohda T, Niewczas MA, Ficociello LH, Walker WH, Skupien J, Rosetti F, Cullere X et al (2012) Circulating TNF receptors 1 and 2 predict stage 3 CKD in type 1 diabetes. J Am Soc Nephrol 23(3):516–524. https://doi.org/10.1681/asn.2011060628

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Pavkov ME, Weil EJ, Fufaa GD, Nelson RG, Lemley KV, Knowler WC, Niewczas MA et al (2016) Tumor necrosis factor receptors 1 and 2 are associated with early glomerular lesions in type 2 diabetes. Kidney Int 89(1):226–234. https://doi.org/10.1038/ki.2015.278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Bassi R, Fornoni A, Doria A, Fiorina P (2016) CTLA4-Ig in B7-1-positive diabetic and non-diabetic kidney disease. Diabetologia 59(1):21–29. https://doi.org/10.1007/s00125-015-3766-6

    Article  CAS  PubMed  Google Scholar 

  66. Baragetti I, El Essawy B, Fiorina P (2017) Targeting immunity in end-stage renal disease. Am J Nephrol 45(4):310–319. https://doi.org/10.1159/000458768

    Article  PubMed  Google Scholar 

  67. Dellepiane S, Ben Nasr M, Assi E, Usuelli V, Letizia T, D’Addio F, Zuccotti GV et al (2018) Sodium glucose cotransporters inhibitors in type 1 diabetes. Pharmacol Res 133:1–8. https://doi.org/10.1016/j.phrs.2018.04.018

    Article  CAS  PubMed  Google Scholar 

  68. The Genotype-Tissue Expression (GTEx) project (2013) Nat Genetics 45(6):580–585. https://doi.org/10.1038/ng.2653

    Article  CAS  Google Scholar 

  69. McKnight AJ, McKay GJ, Maxwell AP (2014) Genetic and epigenetic risk factors for diabetic kidney disease. Adv Chron Kidney Dis 21(3):287–296. https://doi.org/10.1053/j.ackd.2014.03.010

    Article  Google Scholar 

  70. Hirayama A, Nakashima E, Sugimoto M, Akiyama S, Sato W, Maruyama S, Matsuo S et al (2012) Metabolic profiling reveals new serum biomarkers for differentiating diabetic nephropathy. Anal Bioanal Chem 404(10):3101–3109. https://doi.org/10.1007/s00216-012-6412-x

    Article  CAS  PubMed  Google Scholar 

  71. Pena MJ, Lambers Heerspink HJ, Hellemons ME, Friedrich T, Dallmann G, Lajer M, Bakker SJ et al (2014) Urine and plasma metabolites predict the development of diabetic nephropathy in individuals with Type 2 diabetes mellitus. Diabet Med 31(9):1138–1147. https://doi.org/10.1111/dme.12447

    Article  CAS  PubMed  Google Scholar 

  72. Stec DF, Wang S, Stothers C, Avance J, Denson D, Harris R, Voziyan P (2015) Alterations of urinary metabolite profile in model diabetic nephropathy. Biochem Biophys Res Commun 456(2):610–614. https://doi.org/10.1016/j.bbrc.2014.12.003

    Article  CAS  PubMed  Google Scholar 

  73. Zurbig P, Jerums G, Hovind P, Macisaac RJ, Mischak H, Nielsen SE, Panagiotopoulos S et al (2012) Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes 61(12):3304–3313. https://doi.org/10.2337/db12-0348

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Zubiri I, Posada-Ayala M, Sanz-Maroto A, Calvo E, Martin-Lorenzo M, Gonzalez-Calero L, de la Cuesta F et al (2014) Diabetic nephropathy induces changes in the proteome of human urinary exosomes as revealed by label-free comparative analysis. J Proteom 96:92–102. https://doi.org/10.1016/j.jprot.2013.10.037

    Article  CAS  Google Scholar 

  75. Caseiro A, Barros A, Ferreira R, Padrao A, Aroso M, Quintaneiro C, Pereira A et al (2014) Pursuing type 1 diabetes mellitus and related complications through urinary proteomics. Transl Res 163(3):188–199. https://doi.org/10.1016/j.trsl.2013.09.005

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Division of Nephrology and Hypertension, Department of Internal Medicine,, University of Utah School of Medicine, Salt Lake City, UT, 84105, USA

    Man Li & Marcus G. Pezzolesi

  2. VA Boston Healthcare System, VA Cooperative Studies Program, Boston, MA, USA

    Man Li

  3. Diabetes and Metabolism Center, University of Utah School of Medicine, Salt Lake City, UT, USA

    Marcus G. Pezzolesi

  4. Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA

    Marcus G. Pezzolesi

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Li, M., Pezzolesi, M.G. Advances in understanding the genetic basis of diabetic kidney disease. Acta Diabetol 55, 1093–1104 (2018). https://doi.org/10.1007/s00592-018-1193-0

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