Urinary proteomics and molecular determinants of chronic kidney disease: Possible link to proteases

Expert Review of Proteomics

Volumn 11, Issue 5, 2014, Pages 535-548

  Filip, Szymon ^a,b   Pontillo, Claudia ^b,c   Peter Schanstra, Joost ^d   Vlahou, Antonia ^a   Mischak, Harald ^b,e   Klein, Julie ^f  

^a Academy of Athens Biomedical Research Foundation   (Greece)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^c MOSAIQUES DIAGNOSTICS GMBH   (Germany)

^d INSERM   (France)

^e UNIVERSITY OF GLASGOW   (United Kingdom)

^f UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

biomarker; CKD; CKD273; MMP; nephropathy; protease; proteomics; urine

Indexed keywords

ADAM PROTEIN; DIPEPTIDYL PEPTIDASE IV; MATRIX METALLOPROTEINASE; MICROSOMAL AMINOPEPTIDASE; PROTEINASE; BIOLOGICAL MARKER; PEPTIDE HYDROLASE; PROTEOME;

AGE; BLOOD ANALYSIS; CHRONIC KIDNEY DISEASE; COMPUTER MODEL; DISEASE ASSOCIATION; DISEASE COURSE; HUMAN; IMMUNOGLOBULIN A NEPHROPATHY; MOLECULAR PATHOLOGY; PREDICTION; PROTEOMICS; REVIEW; URETEROPELVIC JUNCTION OBSTRUCTION; URINALYSIS; BLOOD; CHRONIC KIDNEY FAILURE; COMPUTER SIMULATION; DIABETIC NEPHROPATHY; METABOLISM; SYSTEMS BIOLOGY; URINE;

BIOMARKERS; COMPUTER SIMULATION; DIABETIC NEPHROPATHIES; HUMANS; PEPTIDE HYDROLASES; PROTEOME; PROTEOMICS; RENAL INSUFFICIENCY, CHRONIC; SYSTEMS BIOLOGY;

EID: 84907271963     PISSN: 14789450     EISSN: 17448387     Source Type: Journal    
DOI: 10.1586/14789450.2014.926224     Document Type: Review

References (96)

1. Levey AS, Coresh J. Chronic kidney disease. Lancet 2012;379(9811):165-80
2. National kidney and urologic diseases information clearinghouse (NKUDIC). Available from: www.kidney.niddk.nih.gov/kudiseases/pubs/kustats/
3. Tesauro M, Mascali A, Franzese O, et al. Chronic kidney disease, obesity, and hypertension: the role of leptin and adiponectin. Int J Hypertens 2012;2012:943605
4. O'seaghdha CM, Lyass A, Massaro JM, et al. A risk score for chronic kidney disease in the general population. Am J Med 2012; 125(3):270-7
5. Brosnahan G, Fraer M. Chronic kidney disease: whom to screen and how to treat, part 1: definition, epidemiology, and laboratory testing. South Med J 2010; 103(2):140-6
6. Cai G, Zheng Y, Sun X, Chen X. Prevalence, awareness, treatment, and control of hypertension in elderly adults with chronic kidney disease: results from the survey of Prevalence, Awareness, and Treatment Rates in Chronic Kidney Disease Patients with Hypertension in China. J Am Geriatr Soc 2013;61(12):2160-7
7. Parving HH, Hommel E, Mathiesen E, et al. Prevalence of microalbuminuria, arterial hypertension, retinopathy and neuropathy in patients with insulin dependent diabetes. Br Med J (Clin Res Ed) 1988;296(6616):156-60
8. 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
9. Mischak H, Coon JJ, Novak J, et al. Capillary electrophoresis-mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: An update of recent developments. Mass Spectrom Rev 2009; 28(5):703-24
10. Pejcic M, Stojnev S, Stefanovic V. Urinary proteomics-A tool for biomarker discovery. Ren Fail 2010;32(2):259-68
11. Heinzmann SS, Merrifield CA, Rezzi S, et al. Stability and robustness of human metabolic phenotypes in response to sequential food challenges. J Proteome Res 2012;11(2):643-55
12. Winnike JH, Busby MG, Watkins PB, O'connell TM. Effects of a prolonged standardized diet on normalizing the human metabolome. Am J Clin Nutr 2009;90(6): 1496-501
13. Mischak H, Kaiser T, Walden M, et al. Proteomic analysis for the assessment of diabetic renal damage in humans. Clin Sci 2004;107(5):485-95
14. Weissinger EM, Wittke S, Kaiser T, et al. Proteomic patterns established with capillary electrophoresis and mass spectrometry for diagnostic purposes. Kidney Int 2004;65(6): 2426-34
15. Chalmers MJ, Mackay CL, Hendrickson CL, et al. Combined top-down and bottom-up mass spectrometric approach to characterization of biomarkers for renal disease. Anal Chem 2005;77(22):7163-71
16. Haubitz M, Wittke S, Weissinger EM, et al. Urine protein patterns can serve as diagnostic tools in patients with IgA nephropathy. Kidney Int 2005;67(6):2313-20
17. Sharma K, Lee S, Han S, et al. Two-dimensional fluorescence difference gel electrophoresis analysis of the urine proteome in human diabetic nephropathy. Proteomics 2005;5(10):2648-55
18. Rao PV, Lu X, Standley M, et al. Proteomic identification of urinary biomarkers of diabetic nephropathy. Diabetes Care 2007;30(3):629-37
19. Mischak H, Apweiler R, Banks RE, et al. Clinical proteomics: A need to define the field and to begin to set adequate standards. Proteomics. Clin Appl 2007;1(2):148-56
20. Mischak H, Allmaier G, Apweiler R, et al. Recommendations for biomarker identification and qualification in clinical proteomics. Sci Transl Med 2010;2(46): 46ps42
21. Mischak H, Ioannidis JP, Argiles A, et al. Implementation of proteomic biomarkers: making it work. Eur J Clin Invest 2012; 42(9):1027-36
22. Mischak H, Vlahou A, Righetti PG, Calvete JJ. Putting value in biomarker research and reporting. J Proteomics 2014;96:A1-3
23. Schanstra JP, Mischak H. Proteomic urinary biomarker approach in renal disease: from discovery to implementation. Pediatr Nephrol 2014. [Epub ahead of print]
24. Siwy J, Schanstra JP, Argiles A, et al. Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy. Nephrol Dial Transplant 2014. [Epub ahead of print]
25. Decramer S, Gonzalez De PA, Breuil B, et al. Urine in clinical proteomics. Mol Cell Proteomics 2008;7(10):1850-62
26. Thongboonkerd V. Recent progress in urinary proteomics. Proteomics Clin Appl 2007;1(8):780-91
27. Theodorescu D, Wittke S, Ross MM, et al. Discovery and validation of new protein biomarkers for urothelial cancer: A prospective analysis. Lancet Oncol 2006; 7(3):230-40
28. Mischak H, Delles C, Klein J, Schanstra JP. Urinary proteomics based on capillary electrophoresis-coupled mass spectrometry in kidney disease: discovery and validation of biomarkers, and clinical application. Adv Chronic Kidney Dis 2010;17(6):493-506
29. Fliser D, Wittke S, Mischak H. Capillary electrophoresis coupled to mass spectrometry for clinical diagnostic purposes. Electrophoresis 2005;26(14): 2708-16
30. Standard protocol for urine collection. Available from: www.eurokup.org/sites/default/files/StandardProtocolforUrine Collection.pdf
31. Shlipak MG, Mattes MD, Peralta CA. Update on cystatin C: incorporation into clinical practice. Am J kidney Dis 2013; 62(3):595-603
32. Liu KD, Yang W, Anderson AH, et al. Urine neutrophil gelatinase-Associated lipocalin levels do not improve risk prediction of progressive chronic kidney disease. Kidney Int 2013;83(5):909-14
33. Chou KM, Lee CC, Chen CH, Sun CY. Clinical value of NGAL, L-FABP and albuminuria in predicting GFR decline in type 2 diabetes mellitus patients. PLoS One 2013;8(1):e54863
34. Rau S, Habicht A, Kauke T, et al. Neutrophil gelatinase-Associated lipocalin and end-stage renal disease: it is not all about the kidneys!. Eur J Clin Invest 2013; 43(8):816-20
35. Kolch W, Mischak H, Pitt AR. The molecular make-up of a tumour: proteomics in cancer research. Clin Sci 2005;108(5): 369-83
36. Fliser D, Novak J, Thongboonkerd V, et al. Advances in urinary proteome analysis and biomarker discovery. J Am Soc Nephrol 2007;18(4):1057-71
37. Decramer S, Gonzalez De Peredo A, Breuil B, et al. Urine in clinical proteomics. Mol Cell Proteomics 2008;7(10):1850-62
38. Dakna M, Harris K, Kalousis A, et al. Addressing the challenge of defining valid proteomic biomarkers and classifiers. BMC Bioinformatics 2010;11:594
39. Dakna M, He Z, Yu WC, et al. Technical, bioinformatical and statistical aspects of liquid chromatography-mass spectrometry (LC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) based clinical proteomics: A critical assessment. J Chromatogr B Analyt Technol Biomed Life Sci 2009;877(13):1250-8
40. Mischak H, Massy ZA, Jankowski J. Proteomics in uremia and renal disease. Semin Dial 2009;22(4):409-16
41. Mullen W, Delles C, Mischak H, Euro KUPCA. Urinary proteomics in the assessment of chronic kidney disease. Curr Opin Nephrol Hypertens 2011;20(6): 654-61
42. Good DM, Zurbig P, Argiles A, et al. Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol Cell Proteomics 2010;9(11): 2424-37
43. Cheng S, Pollock AS, Mahimkar R, et al. Matrix metalloproteinase 2 and basement membrane integrity: A unifying mechanism for progressive renal injury. FASEB J 2006; 20(11):1898-900
44. Argiles A, Siwy J, Duranton F, et al. CKD273, a new proteomics classifier assessing CKD and its prognosis. PLoS One 2013;8(5):e62837
45. Siwy J, Mullen W, Golovko I, et al. Human urinary peptide database for multiple disease biomarker discovery. Proteomics Clin Appl 2011;5(5-6):367-74
46. Zurbig P, Decramer S, Dakna M, et al. The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease. Proteomics 2009;9(8): 2108-17
47. Merchant ML, Perkins BA, Boratyn GM, et al. Urinary Peptidome May Predict Renal Function Decline in Type 1 Diabetes and Microalbuminuria. J Am Soc Nephrol 2009;20(9):2065-74
48. Alkhalaf A, Zurbig P, Bakker SJ, et al. Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy. PLoS One 2010;5(10):e13421
49. Rossing K, Mischak H, Dakna M, et al. Urinary proteomics in diabetes and CKD. J Am Soc Nephrol 2008;19(7):1283-90
50. Molin L, Seraglia R, Lapolla A, et al. A comparison between MALDI-MS and CE-MS data for biomarker assessment in chronic kidney diseases. J Proteomics 2012; 75(18):5888-97
51. Lapolla A, Molin L, Sechi A, et al. A further investigation on a MALDI-based method for evaluation of markers of renal damage. J Mass Spectrom 2009;44(12): 1754-60
52. Andersen S, Mischak H, Zurbig P, et al. Urinary proteome analysis enables assessment of renoprotective treatment in type 2 diabetic patients with microalbuminuria. BMC Nephrol 2010; 11:29
53. Zurbig P, Jerums G, Hovind P, et al. Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes 2012;61(12): 3304-13
54. Roscioni SS, De Zeeuw D, Hellemons ME, et al. A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus. Diabetologia 2013; 56(2):259-67
55. 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
56. Haubitz M, Good DM, Woywodt A, et al. Identification and validation of urinary biomarkers for differential diagnosis and evaluation of therapeutic intervention in anti-neutrophil cytoplasmic antibody-Associated vasculitis. Mol Cell Proteomics 2009;8(10):2296-307
57. Carty DM, Siwy J, Brennand JE, et al. Urinary proteomics for prediction of preeclampsia. Hypertension 2011;57(3): 561-9
58. Kalantari S, Rutishauser D, Samavat S, et al. Urinary prognostic biomarkers and classification of iga nephropathy by high resolution mass spectrometry coupled with liquid chromatography. PloS One 2013; 8:12
59. Takahashi K, Wall SB, Suzuki H, et al. Clustered O-glycans of IgA1: defining macro- and microheterogeneity by use of electron capture/transfer dissociation. Mol Cell Proteomics 2010;9(11):2545-57
60. Drube J, Zurbig P, Schiffer E, et al. Urinary proteome analysis identifies infants but not older children requiring pyeloplasty. Pediatr Nephrol 2010;25(9):1673-8
61. Decramer S, Wittke S, Mischak H, et al. Predicting the clinical outcome of congenital unilateral ureteropelvic junction obstruction in newborn by urinary proteome analysis. Nat Med 2006;12(4): 398-400
62. Stalmach A, Albalat A, Mullen W, Mischak H. Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications. Electrophoresis 2013;34(11): 1452-64
63. Fuchs JE, Von Grafenstein S, Huber RG, et al. Cleavage entropy as quantitative measure of protease specificity. PLOS Comput Biol 2013;9(4):e1003007
64. Klingler D, Hardt M. Profiling protease activities by dynamic proteomics workflows. Proteomics 2012;12(4-5):587-96
65. Choi KY, Swierczewska M, Lee S, Chen X. Protease-Activated drug development. Theranostics 2012;2(2):156-78
66. Castro HC, Abreu PA, Geraldo RB, et al. Looking at the proteases from a simple perspective. J Mol Recognit 2011;24(2): 165-81
67. Quertle. Available from: www.quertle.info
68. Thrailkill KM, Clay Bunn R, Fowlkes JL. Matrix metalloproteinases: their potential role in the pathogenesis of diabetic nephropathy. Endocrine 2009;35(1):1-10
69. Rodriguez D, Morrison CJ, Overall CM. Matrix metalloproteinases: what do they not do? New substrates and biological roles identified by murine models and proteomics. Biochim Biophys Acta 2010; 1803(1):39-54
70. Tan RJ, Liu Y. Matrix metalloproteinases in kidney homeostasis and diseases. Am J Physiol Renal Physiol 2012;302(11): F1351-61
71. Van Der Zijl NJ, Hanemaaijer R, Tushuizen ME, et al Urinary matrix metalloproteinase-8 and -9 activities in type 2 diabetic subjects: A marker of incipient diabetic nephropathy? Clin Biochem 2010;43(7-8):635-9
72. Altemtam N, Nahas ME, Johnson T. Urinary matrix metalloproteinase activity in diabetic kidney disease: A potential marker of disease progression. Nephron Extra 2012;2:219-32
73. Caseiro A, Ferreira R, Quintaneiro C, et al. Protease profiling of different biofluids in type 1 diabetes mellitus. Clin Biochem 2012;45(18):1613-19
74. Jiang Z, Sui T, Wang B. Relationships between MMP-2, MMP-9, TIMP-1 and TIMP-2 levels and their pathogenesis in patients with lupus nephritis. Rheumatol Int 2010;30(9):1219-26
75. Zakiyanov O, Kalousova M, KratochvilovaM, et al. Determinants of circulating matrix metalloproteinase-2 and pregnancy-Associated plasma protein-A in patients with chronic kidney disease. Clin Lab 2012;58(5-6):471-80
76. Zakiyanov O, Kalousova M, Kratochvilova M, et al. Changes in levels of matrix metalloproteinase-2 and -9, pregnancy-Associated plasma protein-A in patients with various nephropathies. J Nephrol 2013;26(3):502-9
77. Ban CR, Twigg SM, Franjic B, et al. Serum MMP-7 is increased in diabetic renal disease and diabetic diastolic dysfunction. Diabetes Res Clin Pract 2010;87(3):335-41
78. Peiskerova M, Kalousova M, Kratochvilova M, et al Fibroblast growth factor 23 and matrix-metalloproteinases in patients with chronic kidney disease: Are they associated with cardiovascular disease? Kidney Blood Press Res 2009;32(4):276-83
79. Hsu TW, Kuo KL, Hung SC, et al. Progression of kidney disease in non-diabetic patients with coronary artery disease: predictive role of circulating matrix metalloproteinase-2, -3, and -9. PLoS One 2013;8(7):e70132
80. Smith ER, Tomlinson LA, Ford ML, et al. Elastin degradation is associated with progressive aortic stiffening and all-cause mortality in predialysis chronic kidney disease. Hypertension 2012;59(5):973-8
81. Musial K, Zwolinska D. Matrix metalloproteinases (MMP-2, 9) and their tissue inhibitors (TIMP-1, 2) as novel markers of stress response and atherogenesis in children with chronic kidney disease (CKD) on conservative treatment. Cell Stress Chaperones 2011;16(1):97-103
82. Musial K, Zwolinska D. Novel indicators of fibrosis-related complications in children with chronic kidney disease. Clin Chim Acta 2013;430C:15-19
83. Pawlak K, Mysliwiec M, Pawlak D. Peripheral blood level alterations of MMP-2 and MMP-9 in patients with chronic kidney disease on conservative treatment and on hemodialysis. Clin Biochem 2011;44(10-11):838-43
84. Zhong J, Rao X, Rajagopalan S. An emerging role of dipeptidyl peptidase 4 (DPP4) beyond glucose control: potential implications in cardiovascular disease. Atherosclerosis 2013;226(2):305-14
85. Sun AL, Deng JT, Guan GJ, et al. Dipeptidyl peptidase-IV is a potential molecular biomarker in diabetic kidney disease. Diab Vasc Dis Res 2012;9(4):301-8
86. Tinoco AD, Tagore DM, Saghatelian A. Expanding the dipeptidyl peptidase 4-regulated peptidome via an optimized peptidomics platform. J Am Chem Soc 2010;132(11):3819-30
87. Pollheimer J, Fock V, Knofler M. Review: The ADAM metalloproteinases - Novel regulators of trophoblast invasion? Placenta 2014;35S:S57-63
88. Van Der Vorst EP, Keijbeck AA, De Winther MP, Donners MM. A disintegrin and metalloproteases: molecular scissors in angiogenesis, inflammation and atherosclerosis. Atherosclerosis 2012;224(2):302-8
89. Weber S, Saftig P. Ectodomain shedding and ADAMs in development. Development 2012;139(20):3693-709
90. Shen L, Lu G, Dong N, et al. Von Willebrand factor, ADAMTS13 activity, TNF-Alpha and their relationships in patients with chronic kidney disease. Exp Ther Med 2012;3(3):530-4
91. Gutwein P, Schramme A, Abdel-Bakky MS, et al. ADAM10 is expressed in human podocytes and found in urinary vesicles of patients with glomerular kidney diseases. J Biomed Sci 2010;17:3
92. Wickstrom M, Larsson R, Nygren P, Gullbo J. Aminopeptidase N (CD13) as a target for cancer chemotherapy. Cancer Sci 2011;102(3):501-8
93. Moon PG, Lee JE, You S, et al. Proteomic analysis of urinary exosomes from patients of early IgA nephropathy and thin basement membrane nephropathy. Proteomics 2011; 11(12):2459-75
94. Klein J, Eales J, Zurbig P, et al. Proteasix: A tool for automated and large-scale prediction of proteases involved in naturally occurring peptide generation. Proteomics 2013;13(7):1077-82
95. Siwy J, Zoja C, Klein J, et al. Evaluation of the Zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles. PLoS One 2012;7(12): e51334
96. Dominiczak AF, Herget-Rosenthal S, Delles C, et al. Systems biology to battle vascular disease. Nephrol Dial Transplant 2010;25(4):1019-22