Skip to main content

Advertisement

SpringerLink
Log in

Proteomics and diabetic nephropathy: what have we learned from a decade of clinical proteomics studies?

  • Invited Review
  • Published:
Journal of Nephrology Aims and scope Submit manuscript

An Erratum to this article was published on 16 July 2014

Abstract

Diabetic nephropathy (DN) has become the most frequent cause of chronic kidney disease worldwide due to the constant increase of the incidence of type 2 diabetes mellitus in developed and developing countries. The understanding of the pathophysiological mechanisms of human diseases through a large-scale characterization of the protein content of a biological sample is the key feature of the proteomics approach to the study of human disease. We discuss the main results of over 10 years of tissue and urine proteomics studies applied to DN in order to understand how far we have come and how far we still have to go before obtaining a full comprehension of the molecular mechanisms involved in the pathogenesis of DN and identifying reliable biomarkers for accurate management of patients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. U.S. Renal Data System (2012) USRDS 2012 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

  2. (2007) KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 49:S1–S179

  3. Craig KJ, Donovan K, Munnery M, Owens DR, Williams JD, Phillips AO (2003) Identification and management of diabetic nephropathy in diabetes clinic. Diabetes Care 26:1806–1811

    Article  PubMed  Google Scholar 

  4. Gross JL, de Azevedo MJ, Silverio SP, Canani LH, Caramori ML, Zelmanovitz T (2005) Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care 28:164–174

    Article  PubMed  Google Scholar 

  5. Ziyadeh FN, Sharma K (2003) Overview: combating diabetic nephropathy. J Am Soc Nephrol 14:1355–1357

    Article  PubMed  Google Scholar 

  6. Stewart JH, McCredie MR, Williams SM et al (2007) Trends in incidence of treated end-stage renal disease, overall and by primary renal disease, in persons aged 20–64 years in Europe, Canada and the Asia-Pacific region, 1998–2002. Nephrology (Carlton) 12:520–527

    Article  Google Scholar 

  7. Rosca MG, Mustata TG, Kinter MT et al (2005) Glycation of mitochondrial proteins from diabetic rat kidney is associated with excess superoxide formation. Am J Physiol Renal Physiol 289:F420–F430

    Article  CAS  PubMed  Google Scholar 

  8. Krolewski AS, Warram JH (1995) Genetic susceptibility to diabetic kidney disease: an update. J Diabetes Complications 9(4):277–2781

    Article  CAS  PubMed  Google Scholar 

  9. Giacco F, Brownlee M (2010) Oxidative stress and diabetic complications. Circ Res 107:1058–1070

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  10. Takenaka T, Inoue T, Ohno Y et al (2012) Elucidating mechanisms underlying altered renal autoregulation in diabetes. Am J Physiol Regul Integr Comp Physiol 303(5):R495–R504

    Article  CAS  PubMed  Google Scholar 

  11. Patinha D, Fasching A, Pinho D, Albino-Teixeira A, Morato M, Palm F (2013) Angiotensin II contributes to glomerular hyperfiltration in diabetic rats independently of adenosine type I receptors. Am J Physiol Renal Physiol 304(5):F614–F622

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Sochett EB, Cherney DZ, Curtis JR, Dekker MG, Scholey JW, Miller JA (2006) Impact of renin angiotensin system modulation on the hyperfiltration state in type 1 diabetes. J Am Soc Nephrol 17(6):1703–1709

    Article  CAS  PubMed  Google Scholar 

  13. Mathis KM, Banks RO (1996) Role of nitric oxide and angiotensin II in diabetes mellitus-induced glomerular hyperfiltration. J Am Soc Nephrol 7(1):105–112

    CAS  PubMed  Google Scholar 

  14. Kim HJ, Cho EH, Yoo JH et al (2007) Proteome analysis of serum from type 2 diabetics with nephropathy. J Proteome Res 6:735–743

    Article  CAS  PubMed  Google Scholar 

  15. Ziyadeh FN, Snipes ER, Watanabe M, Alvarez RJ, Goldfarb S, Haverty TP (1990) High glucose induces cell hypertrophy and stimulates collagen gene transcription in proximal tubule. Am J Physiol 259:F704–F714

    CAS  PubMed  Google Scholar 

  16. Schordan S, Schordan E, Endlich N et al (2009) Alterations of the podocyte proteome in response to high glucose concentrations. Proteomics 9:4519–4528

    Article  CAS  PubMed  Google Scholar 

  17. Colantonio DA, Chan DW (2005) The clinical application of proteomics. Clin Chim Acta 357:151–158

    Article  CAS  PubMed  Google Scholar 

  18. Mazzucco G, Bertani T, Fortunato M et al (2002) Different patterns of renal damage in type 2 diabetes mellitus: a multicentric study on 393 biopsies. Am J Kidney Dis 39(4):713–720

    Article  PubMed  Google Scholar 

  19. Thongboonked V, Malasit P (2005) Renal and urinary proteomics: current applications and challenges. Proteomics 5:1033–1042

    Article  Google Scholar 

  20. Bonomini M, Sirolli V, Magni F, Urbani A (2012) Proteomics and nephrology. J Nephrol 25(06):865–871

    Article  CAS  PubMed  Google Scholar 

  21. Magni F, Lalowski M, Mainini V et al (2013) Proteomics imaging and the kidney. J Nephrol 26(3):430–436

    Article  CAS  PubMed  Google Scholar 

  22. Santucci L, Candiano G, Bruschi M et al (2013) Urinary proteome in a snapshot: normal urine and glomerulonephritis. J Nephrol 26(4):610–616

    Article  CAS  PubMed  Google Scholar 

  23. Hummel KP, Dickie MM, Coleman DL (1966) Diabetes, a new mutation in the mouse. Science 153(3740):1127–1128

    Article  CAS  PubMed  Google Scholar 

  24. Chua SC, Chung WK, Wu-Peng XS et al (1996) Phenotypes of mouse diabetes and rat fatty due to mutations in the OB (leptin) receptor. Science 271(5251):994–996

    Article  CAS  PubMed  Google Scholar 

  25. Zhao HJ, Wang S, Cheng H et al (2006) Endothelial nitric oxide synthase deficiency produces accelerated nephropathy in diabetic mice. J Am Soc of Nephrol 17(10):2664–2669

    Article  CAS  Google Scholar 

  26. Kurtz TW, Morris RC, Pershadsingh HA (1989) The Zucker fatty rat as a genetic model of obesity and hypertension. Hypertension 13:896–901

    Article  CAS  PubMed  Google Scholar 

  27. Tilton RG, Haidacher SJ, Lejeune WS et al (2007) Diabetes induced changes in the renal cortical proteome assessed with two-dimensional gel electrophoresis and mass spectrometry. Proteomics 7:1729–1742

    Article  CAS  PubMed  Google Scholar 

  28. Zhang D, Yang H, Kong X et al (2011) Proteomics analysis reveals diabetic kidney as a ketogenic organ in type 2 diabetes. Am J Physiol Endocrinol Metab 300:E287–E295

    Article  CAS  PubMed  Google Scholar 

  29. Barati MT, Merchant ML, Kain AB et al (2007) Proteomic analysis defines altered cellular redox pathways and advanced glycation endproduct metabolism in glomeruli of db/db diabetic mice. Am J Physiol Renal Physiol 293:F1157–F1165

    Article  CAS  PubMed  Google Scholar 

  30. Nakatani S, Kakehashi A, Ishimura E et al (2011) 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 2011:979354

    Article  PubMed Central  PubMed  Google Scholar 

  31. Reimel BA, Pan S, May DH et al (2009) Proteomics on fixed tissue specimens—a review. Curr Proteomics 6:63–69

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  32. Ralton LD, Murray GI (2011) The use of formalin fixed wax embedded tissue for proteomic analysis. J Clin Pathol 64:297–302

    Article  CAS  PubMed  Google Scholar 

  33. Matsuda KM, Chung JY, Hewitt SM (2010) Histo-proteomic profiling of formalin-fixed, paraffin-embedded tissue. Expert Rev Proteomics 7:227–337

    Article  CAS  PubMed  Google Scholar 

  34. Murray GI (2012) Has the proteome of formalin-fixed wax-embedded tissue been unlocked? Nephrol Dial Transplant 27(9):3395–3398

    Article  PubMed  Google Scholar 

  35. Emmert-Buck MR, Bonner RF, Smith PD et al (1996) Laser capture microdissection. Science 274(5289):998–1001

    Article  CAS  PubMed  Google Scholar 

  36. Nakatani S, Wei M, Ishimura E et al (2012) Proteome analysis of laser microdissected glomeruli from formalin-fixed paraffin-embedded kidneys of autopsies of diabetic patients: nephronectin is associated with the development of diabetic glomerulosclerosis. Nephrol Dial Transplant 27(5):1889–1897

    Article  CAS  PubMed  Google Scholar 

  37. Satoskar AA, Shapiro JP, Bott CN et al (2012) Characterization of glomerular diseases using proteomic analysis of laser capture microdissected glomeruli. Mod Pathol 25(5):709–721

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Casadonte R, Caprioli RM (2011) Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc 6:1695–1709

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. Seeley EH, Schwamborn K, Caprioli RM (2011) Imaging of intact tissue sections: moving beyond the microscope. J Biol Chem 286:25459–25466

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Thongboonkerd V (2008) Urinary proteomics: towards biomarker discovery, diagnostics and prognostics. Mol BioSyst 4:810–815

    Article  CAS  PubMed  Google Scholar 

  41. Thongboonkerd V (2010) Current stauts of renal and urinary proteomics: ready for routine clinical application? Nephrol Dial Transplant 25:11–16

    Article  PubMed  Google Scholar 

  42. Bramham K, Mistry HD, Poston L et al (2009) The non-invasive biopsy-will urinary proteomics make the renal tissue biopsy redundant? QJM 102:523–538

    Article  CAS  PubMed  Google Scholar 

  43. Thongboonkerd V (2007) Practical points in urinary proteomics. J Proteome Res 6:3881–3890

    Article  CAS  PubMed  Google Scholar 

  44. Barratt J, Topham P (2007) Urine proteomics: the present and future of measuring urinary protein components in disease. CMAJ 177:361–368

    Article  PubMed Central  PubMed  Google Scholar 

  45. Gonzales-Buitrago JM, Ferreira L, Lorenzo I (2007) Urinary proteomics. Clin Chim Acta 375:49–56

    Article  Google Scholar 

  46. Decramer S, Gonzales de Peredo A, Breuil B et al (2008) Urine in clinical proteomics. Mol Cell Proteomics 7:1850–1862

    Article  CAS  PubMed  Google Scholar 

  47. Schaub S, Wilkins J, Weiler T et al (2004) Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry. Kidney Int 65:323–332

    Article  CAS  PubMed  Google Scholar 

  48. Theodorescu D, Wittke S, Ross MM et al (2006) Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis. Lancet Oncol 7:230–240

    Article  CAS  PubMed  Google Scholar 

  49. Papale M, Pedicillo MC, Thatcher BJ et al (2007) Urine profiling by SELDI–TOF/MS: monitoring of the critical steps in sample collection, handling and analysis. J Chromatogr B Analyt Technol Biomed Life Sci 856(1–2):205–213

    Article  CAS  PubMed  Google Scholar 

  50. Yamamoto T, Langham RG, Ronco P, Knepper MA, Thongboonkerd V (2008) Towards standard protocols and guidelines for urine proteomics: a report on the Human Kidney and Urine Proteome Project (HKUPP) symposium and workshop, 6 October 2007, Seoul, Korea and 1 November 2007, San Francisco, CA, USA. Proteomics 8(11):2156–2159

    Article  CAS  PubMed  Google Scholar 

  51. Jackson DH, Banks RE (2010) Banking of clinical samples for proteomic biomarker studies: a consideration of logistical issues with a focus on pre-analytical variation. Proteomics Clin Appl 4(3):250–270

    Article  CAS  PubMed  Google Scholar 

  52. Calvano CD, Aresta A, Iacovone M et al (2010) Optimization of analytical and pre-analytical conditions for MALDI-TOF-MS human urine protein profiles. J Pharm Biomed Anal 51(4):907–914

    Article  CAS  PubMed  Google Scholar 

  53. Court M, Selevsek N, Matondo M et al (2011) Toward a standardized urine proteome analysis methodology. Proteomics 11(6):1160–1171

    Article  CAS  PubMed  Google Scholar 

  54. Yates JR, Ruse CI, Nakorchevsky A (2009) Proteomics by mass spectrometry: approaches, advances, and applications. Annu Rev Biomed Eng 11:49–79

    Article  CAS  PubMed  Google Scholar 

  55. Kolch W, Neussus C, Pelzing M et al (2005) Capillary electrophoresis-mass spectrometry as a power tool in clinical diagnosis and biomarker discovery. Mass Spectrom Rev 34:959–977

    Article  Google Scholar 

  56. Wright GL Jr (2002) SELDI proteinchips MS: a platform for biomarker discovery and cancer diagnosis. Expert Rev Mol Diagn 2:549–563

    Article  CAS  PubMed  Google Scholar 

  57. Rossing K, Mischak H, Dakna M, PREDICTIONS Network et al (2008) Urinary proteomics in diabetes and CKD. J Am Soc Nephrol 19(7):1283–1290

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  58. Alkhalaf A, Zürbig P, Bakker SJ, PREDICTIONS Group et al (2010) Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy. PLoS ONE 5(10):e13421

    Article  PubMed Central  PubMed  Google Scholar 

  59. Good DM, Zürbig P, Argilés A et al (2010) Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol Cell Proteomics 9:2424–2437

    Article  PubMed Central  PubMed  Google Scholar 

  60. Zürbig P, Jerums G, Hovind P et al (2012) Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes 61(12):3304–3313

    Article  PubMed Central  PubMed  Google Scholar 

  61. Otu HH, Can H, Spentzos D, Nelson RG et al (2007) Prediction of diabetic nephropathy using urine proteomic profiling 10 years prior to development of nephropathy. Diabetes Care 30(3):638–643

    Article  CAS  PubMed  Google Scholar 

  62. Wu J, Chen YD, Yu JK, Shi XL, Gu W (2011) Analysis of urinary proteomic patterns for type 2 diabetic nephropathy by Protein Chip. Diabetes Res Clin Pract 91(2):213–219

    Article  CAS  PubMed  Google Scholar 

  63. Dihazi H, Müller GA, Lindner S et al (2007) Characterization of diabetic nephropathy by urinary proteomic analysis: identification of a processed ubiquitin form as a differentially excreted protein in diabetic nephropathy patients. Clin Chem 53(9):1636–1645

    Article  CAS  PubMed  Google Scholar 

  64. MacIsaac RJ, Tsalamandris C, Panagiotopoulos S, Smith TJ, McNeil KJ, Jerums G (2004) Nonalbuminuric renal insufficiency in type 2 diabetes. Diabetes Care 27:195–200

    Article  PubMed  Google Scholar 

  65. Ekinci EI, Jerums G, Skene A et al (2013) Renal structure in normoalbuminuric and albuminuric patients with type 2 diabetes and impaired renal function. Diabetes Care 36:3620–3626

    Article  CAS  PubMed  Google Scholar 

  66. Papale M, Di Paolo S, Magistroni R et al (2010) Urine proteome analysis may allow noninvasive differential diagnosis of diabetic nephropathy. Diabetes Care 33(11):2409–2415

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  67. Jin J, Ku YH, Kim Y et al (2012) Differential proteome profiling using iTRAQ in microalbuminuric and normoalbuminuric type 2 diabetic patients. Exp Diabetes Res 2012:168602

    Article  PubMed Central  PubMed  Google Scholar 

  68. Shadforth IP, Dunkley TP, Lilley KS, Bessant C (2005) i-Tracker: for quantitative proteomics using iTRAQ. BMC Genom 20(6):145

    Article  Google Scholar 

  69. Cocucci E, Racchetti G, Meldolesi J (2009) Shedding microvesicles: artefacts no more. Trends Cell Biol 19:43–51

    Article  CAS  PubMed  Google Scholar 

  70. Simpson RJ, Lim JW, Moritz RL, Mathivanan S (2009) Exosomes: proteomic insights and diagnostic potential. Expert Rev Proteomics. 6:267–283

    Article  CAS  PubMed  Google Scholar 

  71. Raimondo F, Corbetta S, Morosi L et al (2013) Urinary exosomes and diabetic nephropathy: a proteomic approach. Mol BioSyst 9(6):1139–1146

    Article  CAS  PubMed  Google Scholar 

  72. Papale M, Rocchetti MT, Gesualdo L (2013) Clinical proteomics: the potentiality of urine analysis for understanding diabetic nephropathy. Euro Med J Nephrol (1):32–39

  73. Kohda Y et al (2000) Analysis of segmental renal gene expression by laser capture microdissection. Kidney Int 57:321–331

    Article  CAS  PubMed  Google Scholar 

  74. Chaurand P et al (2006) Molecular imaging of thin mammalian tissue sections by mass spectrometry. Curr Opin Biotechnol 17(4):431–436

    Article  CAS  PubMed  Google Scholar 

Download references

Conflict of interest

The authors declare that there are no conflicts of interest.

Author information

Authors and Affiliations

  1. Nephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation (D.E.T.O), University of Bari “Aldo Moro”, Bari, Italy

    Grazia Vocino, Maria Teresa Rocchetti & Loreto Gesualdo

  2. Core Facility of Proteomics and Mass Spectrometry, Department of Surgery and Medical Sciences, University of Foggia, Foggia, Italy

    Massimo Papale

  3. Nephrology Unit, “Dimiccoli” Hospital, Barletta, Italy

    Salvatore Di Paolo

Authors
  1. Massimo Papale
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Salvatore Di Paolo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Grazia Vocino
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Maria Teresa Rocchetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Loreto Gesualdo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Loreto Gesualdo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Papale, M., Di Paolo, S., Vocino, G. et al. Proteomics and diabetic nephropathy: what have we learned from a decade of clinical proteomics studies?. J Nephrol 27, 221–228 (2014). https://doi.org/10.1007/s40620-014-0044-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40620-014-0044-5

Keywords

Search

Navigation