Proteomics and metabolomics in renal transplantation-quo vadis?

Transplant International

Volumn 26, Issue 3, 2013, Pages 225-241

  Bohra, Rahul ^a   Klepacki, Jacek ^a   Klawitter, Jelena ^a,b   Klawitter, Jost ^a   Thurman, Joshua M ^b   Christians, Uwe ^a  

^a UNIVERSITY OF COLORADO SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF COLORADO   (United States)

Author keywords

biomarkers; metabolomics; proteomics; qualification; renal transplantation; verification

Indexed keywords

AFAMIN; ALPHA 1 ANTITRYPSIN; ALPHA 1 BETA GLYCOPROTEIN; ALPHA3 INTEGRIN; ANGIOTENSINOGEN; BETA 2 MICROGLOBULIN; BETA3 INTEGRIN; BIOLOGICAL MARKER; BREVIN; COL1A2 PROTEIN; COL3A1 PROTEIN; COLLAGEN; COLLAGEN ALPHA1; CONNECTIN; HERMES ANTIGEN; KININOGEN I; LEUCINE RICH ALPHA 2 GLUYCOPROTEIN 1; LIPOPOLYSACCHARIDE BINDING PROTEIN; MATRILYSIN; NEUTROPHIL COLLAGENASE; POLYPEPTIDE; PROTEOHEPARAN SULFATE; SERINE PROTEINASE INHIBITOR; STAT1 PROTEIN; TAMM HORSFALL GLYCOPROTEIN; TISSUE INHIBITOR OF METALLOPROTEINASE 1; TRANSFERRIN; TUMOR NECROSIS FACTOR ALPHA; TUMOR NECROSIS FACTOR ALPHA ANTIBODY; UNCLASSIFIED DRUG; UNINDEXED DRUG;

ACUTE GRAFT REJECTION; CHRONIC GRAFT REJECTION; DISEASE MARKER; FALSE NEGATIVE RESULT; GENE CONTROL; HISTOPATHOLOGY; KIDNEY GRAFT REJECTION; KIDNEY TRANSPLANTATION; LIQUID CHROMATOGRAPHY MASS SPECTROMETRY; MASS SPECTROMETRY; METABOLOMICS; PRIORITY JOURNAL; PROSPECTIVE STUDY; PROTEOMICS; REVIEW; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; TRANSCRIPTOMICS;

BIOLOGICAL MARKERS; GRAFT REJECTION; GRAFT SURVIVAL; HUMANS; KIDNEY TRANSPLANTATION; METABOLOMICS; MONITORING, PHYSIOLOGIC; NEEDS ASSESSMENT; PROGNOSIS; PROTEOMICS; REPRODUCIBILITY OF RESULTS; SURVIVAL ANALYSIS;

EID: 84874110542     PISSN: 09340874     EISSN: 14322277     Source Type: Journal    
DOI: 10.1111/tri.12003     Document Type: Review

References (174)

1. Lamb KE, Lodhi S, Meier-Kriesche HU,. Long-term renal allograft survival in the United States: a critical reappraisal. Am J Transplant 2011; 11: 450.
2. Nankivell BJ, Kuypers DR,. Diagnosis and prevention of chronic kidney allograft loss. Lancet 2011; 378: 1428.
3. Nankivell BJ, Chapman JR,. Chronic allograft nephropathy: current concepts and future directions. Transplantation 2006; 81: 643.
4. Nankivell BJ, Borrows RJ, Fung CL, O'Connell PJ, Allen RD, Chapman JR,. The natural history of chronic allograft nephropathy. N Engl J Med 2003; 349: 2326.
5. Rosner MH,. Urinary biomarkers for the detection of renal injury. Adv Clin Chem 2009; 49: 73.
6. Nankivell BJ, Chapman JR,. The significance of subclinical rejection and the value of protocol biopsies. Am J Transplant 2006; 6: 2006.
7. Chapman JR, O'Connell PJ, Nankivell BJ,. Chronic renal allograft dysfunction. J Am Soc Nephrol 2005; 16: 3015.
8. Williams WW, Taheri D, Tolkoff-Rubin N, Colvin RB,. Clinical role of the renal transplant biopsy. Nat Rev Nephrol 2012; 8: 110.
9. Wishart DS,. Metabolomics: the principles and potential applications to transplantation. Am J Transplant 2005; 5: 2814.
10. Christians U, Albuisson J, Klawitter J, Klawitter J,. The role of metabolomics in the study of kidney diseases and in the development of diagnostic tools. In:, Edelstein CL, ed. Biomarkers of Kidney Disease. San Diego: Elsevier, 2010: 39-100.
11. Dieterle F, Riefke B, Schlotterbeck G, Ross A, Senn H, Amberg A,. NMR and MS methods for metabonomics. Methods Mol Biol 2011; 691: 385.
12. Christians U, McCrery S, Klawitter J, Klawitter J,. The role of proteomics in the study of kidney diseases and in the development of diagnostic tools. In:, Edelstein CL, ed. Biomarkers of Kidney Disease. San Diego: Elsevier, 2010: 101-176.
13. Aebersol R, Mann M,. Mass spectrometry-based proteomics. Nature 2003; 422: 198.
14. Domon B, Aebersold R,. Mass spectrometry in protein analysis. Science 2006; 312: 212.
15. Cravat BF, Simon GM, Yates JR,. The biological impact of mass-spectrometry-based proteomics. Nature 2007; 450: 991.
16. Xu EY, Schaefer WH, Xu Q,. Metabolomics in pharmaceutical research and development: metabolites, mechanisms and pathways. Curr Opin Drug Discov Devel 2009; 12: 40.
17. Griffiths WJ, Wang Y,. Mass spectrometry: from proteomics to metabolomics and lipidomics. Chem Soc Rev 2009; 38: 1882.
18. Schnackenberg LK,. Global metabolic profiling and its role in systems biology to advance personalized medicine in the 21st century. Expert Rev Mol Diagn 2007; 7: 247.
19. Weiss RH, Kim K,. Metabolomics in the study of kidney diseases. Nat Rev Nephrol 2012; 8: 22.
20. Roedder S, Vitalone M, Khatri P, Sarwal M,. Biomarkers in solid organ transplantation: establishing personalized transplantation medicine. Genome Med 2011; 3: 37.
21. Wishart DS,. Metabolomics in monitoring kidney transplants. Curr Opin Nephrol Hypertens 2006; 15: 637.
22. Wishart DS,. Metabolomics: a complementary tool in renal transplantation. Contrib Nephrol 2008; 160: 76.
23. Kienzl-Wagner K, Pratschke J, Brandacher G,. Proteomics- a blessing or a curse? Application of proteomics technology to transplant medicine. Transplantation 2011; 92: 499.
24. Naesens M, Sarwal M,. Molecular diagnostics in transplantation. Nat Rev Nephrol 2010; 6: 614.
25. Sarwal M,. De-convoluting the "omics' for organ transplantation. Curr Opin Organ Transplant 2009; 14: 544.
26. Mannon RB,. Immune monitoring and biomarkers to predict chronic allograft dysfunction. Kidney Int 2010; 119 (Suppl.): S59.
27. Bestard O, Cruzado JM, la Franquesa M, Grinyõ JM,. Biomarkers in renal transplantation. Curr Opin Organ Transplant 2010; 15: 467.
28. Liang SL, Clarke W,. Urine proteomic profiling of biomarkers of acute renal transplant rejection. Methods Mol Biol 2010; 641: 185.
29. Qunitana LF, Bañon-Maneus E, Solé-Gonzalez A, Campistol JM,. Urine proteomics biomarkers in renal transplantation: an overview. Transplantation 2009; 88 (Suppl. 3): S45.
30. Schaub S, Wilkins JA, Nickerson P,. Proteomics and renal transplantation: searching for novel biomarkers and therapeutic targets. Contrib Nephrol 2008; 160: 65.
31. Biomarkers Definition Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001; 69: 89.
32. Puntman VO,. How-to-guide on biomarkers: biomarker definitions, validation and applications with examples from cardiovascular disease. Postgrad Med J 2009; 85: 538.
33. Vasan RS,. Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation 2006; 113: 2335.
34. Goodsaid FM, Frueh FW, Mattes W,. Strategic paths for biomarker qualification. Toxicology 2008; 245: 219.
35. Holmes E, Wilson ID, Nicholson JK,. Metabolic phenotyping in health and disease. Cell 2008; 134: 714.
36. Nicholson JK,. Global systems biology, personalized medicine and molecular epidemiology. Mol Syst Biol 2006; 2: 52.
37. Peng J, Gygi SP,. Proteomics: the move to mixtures. J Mass Spectrom 2001; 36: 1083.
38. Christians U, Schmitz V, Klawitter J, Klawitter J,. Proteo-metabolomic strategies in the future of drug development. In:, Caroli S, Záray G, eds. The Applicability of Analytical Techniques to Clinical Studies. New York: John Wiley and Sons, 2012: 691-774.
39. Christians U, Klawitter J, Klawitter J, Brunner N, Schmitz V,. Biomarkers of immunosuppressant organ toxicity after transplantation- status, concepts and misconceptions. Expert Opin Drug Metabol Toxicol 2011; 7: 175.
40. Lee JW, Figeys D, Vasilescu J,. Biomarker assay translation from discovery to clinical studies in cancer drug development: quantification of emerging protein biomarkers. Adv Cancer Res 2007; 96: 269.
41. Burckart GJ, Amur S, Goodsaid FM, et al,. Qualification of biomarkers for drug development in organ transplantation. Am J Transplant 2008; 8: 267.
42. Wagner JA, Williams SA, Webster CJ,. Biomarkers and surrogate end points for fit-for-purpose development and regulatory evaluation of new drugs. Clin Pharmacol Ther 2007; 81: 104.
43. Lesko LJ, Atkinson AJ Jr,. Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies. Annu Rev Pharmacol Toxicol 2001; 41: 347.
44. Bai JPF, Bell R, Buckman SA, et al,. Translational biomarkers: from preclinical to clinical: a report of 2009 AAPS/AAPC biomarker workshop. AAPS J 2011; 13: 274.
45. United States Food and Drug Administration, Center for Drug Evaluation and Research. Manual of policies and procedures: processing and reviewing voluntary genomic data submissions (VGDSs). Version 3/16/2005. http://www.fda.gov/downloads/AboutFDA/CentersOffices/CDER/ ManualofPoliciesProcedures/ucm073575.pdf (accessed April 4, 2012).
46. European Medicines Agency. Scientific advice working party of CHMP. Qualification of novel methodologies for drug development: guidance to applicants. EMA/CHMP/SAWP/72894/2008 Rev.1, Version 1-9-2012. http://www.emea.europa.eu/docs/en-GB/document-library/Regulatory-and-procedural- guideline/2009/10/WC500004201.pdf (accessed April 4, 2012)
47. Nobeli I, Thornton JM,. A bioinformatician's view of the metabolome. Bioassays 2006; 28: 534.
48. Wishart DS,. Computational approaches to metabolomics. Methods Mol Biol 2010; 593: 283.
49. Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD,. Analytical and statistical approaches to metabolomics research. J Sep Sci 2009; 32: 2183.
50. Wishart DS,. Current progress in computational metabolomics. Brief Bioinform 2007; 8: 279.
51. Wishart DS,. Introduction to cheminformatics. Curr Protoc Bioinformatics 2007; Jun; Chapter 14: Unit 14.1. Review. PubMed PMID: 18428788
52. Kaddurah-Daouk R, Kristal BS, Weinshilboum RM,. Metabolomics: a global biochemical approach to drug response and disease. Annu Rev Pharmacol Toxicol, 2008; 48: 653.
53. Wishart DS, Knox C, Guo AC, et al,. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 2009; 37: D603.
54. Domon B, Aebersold R,. Challenges and opportunities in proteomics data analysis. Mol Cell Proteomics 2006; 5: 1921.
55. Ganter B, Zidek N, Hewitt PR, Müller D, Vladimirova A,. Pathway analysis tools and toxicogenomics reference databases for risk assessment. Pharmacogenomics 2008; 9: 35.
56. Wheelock CE, Wheelock AM, Kawashima S, et al,. Systems biology approaches and pathway tools for investigating cardiovascular disease. Mol BioSyst 2009; 5: 588.
57. Materi W, Wishart DS,. Computational systems biology in drug discovery and development: methods and applications. Drug Discov Today 2007; 12: 295.
58. Leach SM, Tipney H, Feng W, et al,. Biomedical discovery acceleration, with applications to craniofacial development. PLoS Comput Biol 2009; 5: e1000215.
59. Fawcett T,. Introduction to ROC analysis. Pattern Recogn Lett 2006; 27: 861.
60. Parikh CR, Philbrook HT,. Statistical considerations in analysis and interpretation of biomarker studies. In:, Edelstein CL, ed. Biomarkers of Kidney Disease. San Diego: Elsevier, 2010: 25-38.
61. Müller PY, Dieterle F,. Tissue-specific, non-invasive toxicity biomarkers: translation from preclinical safety assessment to clinical safety monitoring. Expert Opin Drug Metab Toxicol 2009; 5: 1023.
62. Christians U, Klepacki J, Shokati T, Klawitter J, Klawitter J,. Mass spectrometry-based multiplexing for the analysis of biomarkers in drug development and clinical diagnostics- how much is too much? Microchem J 2012; 105: 32.
63. Rifai N, Gillette MA, Carr SA,. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol 2006; 24: 971.
64. United States Department of Health and Human Services, Food and Drug Administration. Draft Guidance for Industry and Food and Drug Administration Staff. In vitro Companion Diagnostics Devices. Version July 14, 2011 http://www.fda.gov/medicaldevices/deviceregulationandguidance/guidancedocuments/ ucm262292.htm, (accessed April 4, 2012)
65. Ioannidis JP,. A roadmap for successful applications of clinical proteomics. Proteomics Clin Appl 2011; 5: 241.
66. Editorial. What happened to personalized medicine? Nat Biotechnol 2012; 30: 1.
67. Ioannidis JPA, Tzoulaki I,. Minimal and null predictive effects of the most popular blood biomarkers of cardiovascular disease. Circ Res 2012; 110: 658.
68. Christians U, Klawitter J, Hornberger A, Klawitter J,. How unbiased is non-targeted metabolomics and is targeted pathway screening the solution? Curr Pharm Biotechnol 2011; 12: 1053.
69. Storey JD, Taylor JE, Siegmund D,. Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: a unified approach. J R Statist Soc B 2004; 66: 187.
70. Tong T, Wang Y,. Optimal shrinkage estimation of variances with applications to microarray data analysis. J Am Stat Assoc 2007; 102: 113.
71. Wang Y, Ma Y, Carroll RJ,. Variance estimation in the analysis of microarray data. J R Statist Soc B 2009; 71: 425.
72. Efron B, Tibshirani R, Storey JD, Tusher V,. Empirical Bayes analysis of a microarray experiment. J Am Stat Assoc 2001; 96: 1151.
73. Tusher VG, Tibshirani R, Chu G,. Significance analysis of microarrays applied to the ionizing radiation response. Proc Nat Acad Sci U S A 2001; 98: 5116.
74. Cai T, Lv J,. Discussion: the Dantzig selector: statistical estimation when p is much larger than n. Annals Stat 2007; 35: 2365.
75. Fan J, Lv J,. Sure independence screening for ultrahigh dimensional feature space. J R Statist Soc B 2008; 70: 849.
76. Gieser G, Harigaya H, Colangelo PM, Burckart G,. Biomarkers in solid-organ transplantation. Clin Pharmacol Ther 2011; 90: 217.
77. Zürbig P, Decramer S, Dakna M, et al,. The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease. Proteomics 2009; 9: 2108.
78. Takeda A, Horike K, Ohtsuka Y, et al,. Current problems of chronic active antibody-mediated rejection. Clin Transplant 2011; 25 (Suppl. 23): 2.
79. Cook NR,. The use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007; 115: 928.
80. Siew ED, Ware LB, Ikizler TA,. Biological markers of acute kidney injury. J Am Soc Nephrol 2011; 22: 810.
81. Vaidya VS, Ferguson MA, Bonventre JV,. Biomarkers of acute kidney injury. Annu Rev Pharmacol Toxicol 2008; 48: 463.
82. Kellum JA, Levin N, Bouman C, Lameire N,. Developing a consensus classification system for acute renal failure. Curr Opin Crit Care 2002; 8: 509.
83. Psychogios N, Hau DD, Peng J, et al,. The human serum metabolome. PLoS ONE 2011; 6: e16957.
84. Schmitz V, Klawitter J, Bendrick-Peart J, et al,. Metabolic profiles in urine reflect nephrotoxicity of sirolimus and cyclosporine following rat kidney transplantation. Nephron 2009; 111: e80.
85. Klawitter J, Bendrick-Peart J, Rudolph B, et al,. Urine metabolites reflect time-dependent effects of cyclosporine and sirolimus on rat kidney function. Chem Res Toxicol 2009; 22: 118.
86. Klawitter J, Klawitter J, Kushner E, et al,. Association of immunosuppressant-induced protein changes in the rat kidney with changes in urine metabolite patterns: a proteo-metabonomic study. J Proteome Res 2010; 9: 865.
87. Serkova NJ, Christians U,. Biomarkers for toxicodynamic monitoring of immunosuppressants: NMR-based quantitative metabonomics of the blood. Ther Drug Monit 2005; 20: 652.
88. Klawitter J, Haschke M, Kahle C, et al,. Toxicodynamic effects of ciclosporin are reflected by metabolite profiles in the urine of healthy individuals after a single dose. Br J Clin Pharmacol 2010; 70: 241.
89. Fuller TF, Serkova N, Neimann CU, Freise CE,. Influence of donor pretreatment with N-acetylcysteine on ischemia/reperfusion injury in rat kidney grafts. J Urol 2004; 171: 1296.
90. Hauet T, Gibelin H, Godart C, Eugene M, Carretier M,. Kidney retrieval conditions influence damage to renal medulla: evaluation by proton nuclear magnetic resonance (NMR) spectroscopy. Clin Chem Lab Med 2000; 38: 1085.
91. Hauet T, Baumert H, Gibelin H, et al,. Noninvasive monitoring of citrate, acetate, lactate, and renal medullary osmolyte excretion in urine as biomarkers of exposure to ischemic reperfusion injury. Cryobiology 2000; 41: 280.
92. Hauet T, Baumert H, Gibelin H, Godart C, Carretier M, Eugene M,. Citrate, acetate and renal medullary osmolyte excretion in urine as predictor of renal changes after cold ischaemia and transplantation. Clin Chem Lab Med 2000; 38: 1093.
93. Hauet T, Gibelin H, Richer JP, Godart C, Eugene M, Carretier M,. Influence of retrieval conditions on renal medulla injury: evaluation by proton NMR spectroscopy in an isolated perfused pig kidney model. J Surg Res 2000; 93: 1.
94. Hauet T, Goujon JM, Tallineau C, Carretier M, Eugene M,. Early evaluation of renal reperfusion injury after prolonged cold storage using proton nuclear magnetic resonance spectroscopy. Br J Surg 1999; 86: 1401.
95. Schmitz V, Klawitter J, Bendrick-Peart J, et al,. Graft flushing with histidine-tryptophane-ketoglutarate (HTK) followed by extended cold preservation in University of Wisconsin (UW) solution in a rat kidney transplantation model- An improved preservation protocol? Eur J Surg Res 2006; 38: 388.
96. Foxall PJ, Mellotte GJ, Bending MR, Lindon JC, Nicholson JK,. NMR spectroscopy as a novel approach to the monitoring of renal transplant function. Kidney Int 1993; 43: 234.
97. Le Moyec L, Pruna A, Eugène M, et al,. Proton nuclear magnetic resonance spectroscopy of urine and plasma in renal transplantation follow-up. Nephron 1993; 65: 433.
98. Rush D, Somorjai R, Deslauriers R, Shaw A, Jeffery J, Nickerson P,. Subclinical rejection-a potential surrogate marker for chronic rejection-may be diagnosed by protocol biopsy or urine spectroscopy. Ann Transplant 2000; 5: 44.
99. Wang NJ, Zhou Y, Zhu TY, Wang X, Guo YL,. Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI-FTMS. J Proteome Res 2008; 7: 3597.
100. Wang J, Zhou Y, Xu M, Rong R, Guo Y, Zhu T,. Urinary metabolomics in monitoring acute tubular injury of renal allografts: a preliminary report. Transplant Proc 2011; 43: 3738.
101. Prunotto M, Ghiggeri GM, Brushi M, et al,. Renal fibrosis and proteomics: current knowledge and still key questions for proteomic investigation. J Proteomics 2011; 74: 1855.
102. Konvalinka A, Scholey JW, Diamandis EP,. Searching for new biomarkers of renal diseases through proteomics. Clin Chem 2012; 58: 353.
103. Mishak 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: 493.
104. Spasovski G, Ortiz A, Vanholder R, El Nahas M,. Proteomics in chronic kidney diseases: the issues clinical nephrologists need an answer for. Proteomics Clin Appl 2011; 5-6: 233.
105. Mullen W, Delles C, Mischak H, et al,. Urinary proteomics in the assessment of chronic kidney disease. Curr Opin Nephrol Hypertens 2011; 20: 654.
106. Dai Y, Lv T, Wang K, Huang Y, Li D, Liu J,. Detection of acute renal allograft rejection by analysis of renal tissue proteomics in rat models of renal transplantation. Saudi J Kidney Dis Transplant 2008; 19: 952.
107. Reuter S, Reiermann S, Wörner R, et al,. IF/TA-related metabolic changes- proteome analysis of rat renal allografts. Nephrol Dial Transplant 2010; 25: 2492.
108. Johnston O, Cassidy H, O'Connell S, et al,. Identification of β2-microglobulin as urinary biomarker for chronic allograft nephropathy using proteomics methods. Proteomics Clin Appl 2011; 7-8: 422.
109. Kurian SM, Heilman R, Mondala TS, et al,. Biomarkers for early and late stage chronic allograft nephropathy by proteogenomic profiling of peripheral blood. PLoS ONE 2009; 4: e6212.
110. Quintana LF, Campistol JM, Alcolea MP, Bañon-Maneus E, Sol-González A, Cutillas PR,. Application of label-free quantitative peptidomics for the identification of urinary biomarkers of kidney chronic allograft dysfunction. Mol Cell Proteomics 2009; 8: 1658.
111. Quintana LF, Solé-Gonzalez A, Kalko SG, et al,. Urine proteomics to detect biomarkers for chronic allograft dysfunction. J Am Soc Nephrol 2009; 20: 428.
112. Bañõn-Maneus E, Diekmann F, Carrascal M, et al,. Two-dimensional difference gel electrophoresis urinary proteomic profile in the search of nonimmune chronic allograft dysfunction biomarkers. Transplantation 2010; 89: 548.
113. Srivastava M, Eidelman O, Torosyan Y, Jozwik C, Mannon RB, Pollard HB,. Elevated expression levels of ANAX11, integrins β3 and α3, and TNF-α contribute to a candidate proteomic signature in urine for kidney allograft rejection. Proteomics Clin Appl 2011; 5-6: 311.
114. Sui W, Huang L, Dai Y, Chen J, Yan Q, Huang H,. Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS. Clin Exp Med 2010; 10: 259.
115. Metzger J, Chatzikyrkou C, Broecker V, et al,. Diagnosis of subclinical and clinical acute T-cell-mediated rejection in renal transplant patients by urinary proteome analysis. Proteomics Clin Appl 2011; 5-6: 322.
116. Wittke S, Haubitz M, Walden M, et al,. Detection of acute tubulointerstitial rejection by proteomic analysis of urinary samples in renal transplant recipients. Am J Transplant 2005; 5: 2479.
117. Sidgel TK, Kaushal A, Gritsenko M,. Shotgun proteomics identifies proteins specific for acute renal transplant rejection. Proteomics Clin Appl 2010; 4: 32.
118. Ling XB, Sidgel TK, Lau K, et al,. Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection. J Am Soc Nephrol 2010; 21: 646.
119. Freue GV, Sasaki M, Meredith A, et al,. Proteomic signatures in plasma during early acute allograft rejection. Mol Cell Proteomics 2010; 9: 1954.
120. Wu D, Zhu D, Xu M, et al,. Analysis of transcriptional factors and regulation networks in patients with acute renal allograft rejection. J Proteome Res 2011; 10: 175.
121. O'Riordan E, Orlova TN, Mei JJ, et al,. Bioinformatic analysis of the urine proteome of acute allograft rejection. J Am Soc Nephrol 2004; 15: 3240.
122. Clarke W, Silverman BC, Zhang Z, et al,. Characterization of renal allograft reception by urinary proteomic analysis. Ann Surg 2003; 237: 660.
123. Clarke W,. Proteomic research in renal transplantation. Ther Drug Monit 2006; 28: 19.
124. Schaub S, Rush D, Wilkins J, et al,. Proteomic-based detection of urine proteins associated with acute renal allograft rejection. J Am Soc Nephrol 2004; 15: 219.
125. Schaub S, Wilkins JA, Antonovici M, et al,. Proteomic-based identification of cleaved urinary beta2-microglobulin as a potential marker for acute tubular injury in renal allografts. Am J Transplant 2005; 5: 729.
126. Nakorchevsky A, Hewel JA, Kurian SM, et al,. Molecular mechanism of chronic kidney transplant rejection via large-scale proteogenomic analysis of tissue biopsies. J Am Soc Nephrol 2010; 21: 362.
127. Jahnukainen T, Malehorn D, Sun M, et al,. Proteomic analysis of urine in kidney transplant patients with BK virus nephropathy. J Am Soc Nephrol 2006; 17: 3248.
128. Sarwal MM, Sidgel TK, Salomon DR,. Functional proteogenomics- embracing complexity. Semin Immunol 2011; 23: 235.
129. Jantos-Siwy J, Schiffer E, Brand K, et al,. Quantitative urinary proteome analysis for biomarker evaluation in chronic kidney disease. J Proteome Res 2009; 8: 268.
130. DiaPat, Chronic Nephropathies. http://www.diapat.de/DiaPat-Diagnostik/ chronic-nephropathies/ (accessed April 8, 2012).
131. Gwinner W,. Diagnosis of acute rejection in renal transplant patients by urine mass spectrometry. http://clinicaltrials.gov/ct2/show/NCT01315067 (accessed September 18, 2012)
132. Devarajan P, Williams LM,. Proteomics for biomarker discovery in acute kidney injury. Semin Nephrol 2007; 6: 637.
133. Ozer JS, Dieterle F, Troth S, et al,. A panel of urinary biomarkers to monitor reversibility of renal injury and a serum marker with improved potential to assess renal function. Nat Biotechnol 2010; 28: 486.
134. Vaidya VS, Ozer JS, Dieterle F, et al,. Kidney injury molecule-1 outperforms traditional biomarkers of kidney injury in preclinical biomarker qualification studies. Nat Biotechnol 2010; 28: 478.
135. Dieterle F, Perentes E, Cordier A, et al,. Urinary clusterin, cystatin C, beta2-microglobulin, and total protein as markers to detect drug-induced kidney injury. Nat Biotechnol 2010; 28: 463.
136. Bonventre JV, Vaidya VS, Schmouder R, Feig P, Dieterle F,. Next-generation biomarkers for detecting kidney toxicity. Nat Biotechnol 2010; 28: 436.
137. Devarajan P,. Emerging urinary biomarkers in the diagnosis of acute kidney injury. Expert Opin Med Diagn 2008; 2: 387.
138. Edelstein CL, Faubel S,. Biomarkers in acute kidney injury. In:, Edelstein CL, ed. Biomarkers of Kidney Disease. San Diego: Elsevier, 2010: 177.
139. Magnusson NE, Hornum M, Jørgensen KA, et al,. Plasma neutrophil gelatinase associated lipocalin (NGAL) is associated with kidney function in uraemic patients before and after kidney transplantation. BMC Nephrol 2012; 13: 8.
140. Bataille A, Abbas S, Semoun O, et al,. Plasma neutrophil gelatinase-associated lipocalin in kidney transplantation and early renal function prediction. Transplantation 2011; 92: 1024.
141. Ireland R,. Transplantation: urinary NGAL levels in potential deceased kidney donors may be useful in determining donor suitability. Nat Rev Nephrol 2011; 27: 364.
142. Hollmen ME, Kyllönen LE, Inkinen KA, Lalla ML, Merenmies J, Salmela KT,. Deceased donor neutrophil gelatinase-associated lipocalin and delayed graft function after kidney transplantation: a prospective study. Crit Care 2011; 15: R121.
143. Hollmen ME, Kyllönen LE, Inkinen KA, Lalla ML, Salmela KT,. Urine neutrophil gelatinase-associated lipocalin is a marker of graft recovery after kidney transplantation. Kidney Int 2011; 79: 89.
144. Hall IE, Yarlagadda SG, Coca SG, et al,. IL-18 and urinary NGAL predict dialysis and graft recovery after kidney transplantation. J Am Soc Nephrol 2010; 21: 189.
145. Malyszko J, Malyszko JS, Mysliwiec M,. Serum neutrophil gelatinase-associated lipocalin correlates with kidney function in renal allograft recipients. Clin Transplant 2009; 23: 681.
146. Parikh CR, Jani A, Mishra J, et al,. Urine NGAL and IL-18 are predictive biomarkers for delayed graft function following kidney transplantation. Am J Transplant 2006; 6: 1639.
147. Nauta FL, Bakker SJ, van Oeveren W, et al,. Albuminuria, proteinuria, and novel urine biomarkers as predictors of long-term allograft outcomes in kidney transplant recipients. Am J Kidney Dis 2011; 57: 733.
148. Malyszko J, Koc-Zorawska E, Malyszko JS, Mysliwiec M,. Kidney injury molecule-1 correlates with kidney function in renal allograft recipients. Transplant Proc 2010; 42: 3957.
149. Nijboer WN, Schuurs TA, Damman J, et al,. Kidney injury molecule-1 is an early noninvasive indicator for donor brain death-induced injury prior to kidney transplantation. Am J Transplant 2009; 9: 1752.
150. van Timmeren MM, Vaidya VS, van Ree RM, et al,. High urinary excretion of kidney injury molecule-1 is an independent predictor of graft loss in renal transplant recipients. Transplantation 2007; 84: 1625.
151. Ramesh G, Kwon O, Ahn K,. Netrin-1: a novel universal biomarker of human kidney injury. Transplant Proc 2010; 42: 1519.
152. Hall IE, Doshi MD, Poggio ED, Parikh CR,. A comparison of alternative serum biomarkers with creatinine for predicting allograft function after kidney transplantation. Transplantation 2011; 91: 48.
153. Bäckman L, Appelkvist EL, Ringdén O, Dallner G,. Glutathione transferase in the urine: a marker for post-transplant tubular lesions. Kidney Int 1988; 33: 571.
154. Przybylowski P, Koc-Zorawska E, Malyszko JS, Kozlowska S, Mysliwiec M, Malyszko J,. Liver fatty-acid-binding protein in heart and kidney allograft recipients in relation to kidney function. Transplant Proc 2011; 43: 3064.
155. Bone JM, Amara AB, Shenkin A, et al,. Calcineurin inhibitors and proximal renal tubular injury in renal transplant patients with proteinuria and chronic allograft nephropathy. Transplantation 2005; 79: 119.
156. Marchewka Z, Kuźniar J, Zynek-Litwin M, et al,. Kidney graft function in long-term cyclosporine and tacrolimus treatment: comparative study with nephrotoxicity markers. Transplant Proc 2009; 41: 1660.
157. Grenier FC, Ali S, Syed H, et al,. Evaluation of the ARCHITECT urine NGAL assay: assay performance, specimen handling requirements and biological variability. Clin Biochem 2010; 43: 615.
158. Halawa A,. The early diagnosis of acute renal graft dysfunction: a challenge we face. The role of novel biomarkers. Ann Transplant 2011; 16: 90.
159. Alkesh J,. Biomarkers in kidney transplantation. In:, Edelstein CL, ed. Biomarkers of Kidney Disease. San Diego: Elsevier, 2010: 233.
160. Friedewald J,. Proteogenomic monitoring and assessment of kidney transplant recipients ("Mini-Kidney"). http://clinicaltrials.gov/ct2/ show/NCT01531257 (accessed September 18, 2012)
161. Salamzadeh J,. Study of the effect of N-acetyl cysteine on the renal graft function biomarkers (IL18, NGAL). http://clinicaltrials.gov/ct2/show/ NCT01403506 (accessed September 18, 2012)
162. Goilav B,. Urinary kidney injury molecule-1 (KIM-1) excretion as biomarker for injury in kidney transplant recipients. http://clinicaltrials.gov/ ct2/show/NCT00805571 (accessed September 18, 2012)
163. Koop R,. Combinatorial biomarkers: from early toxicology assays to patient population profiling. Drug Discov Today 2005; 10: 781.
164. Chau CH, Rixe O, McLeod H, Figg WD,. Validation of analytic methods for biomarkers used in drug development. Clin Cancer Res 2008; 14: 5967.
165. Lee JW, Hall M,. Method validation of protein biomarkers in support of drug development or clinical diagnostics/prognosis. J Chromatogr B Analyt Technol Biomed Life Sci 2009; 877: 1259.
166. Mischak H, Ioannidis JP, Argiles A, et al,. Implementation of proteomic biomarkers: making it work. Eur J Clin Invest 2012; 42: 1027.
167. Mischak H,. How to get proteomics to the clinic? Issues in clinical proteomics, exemplified by CE-MS. Proteomics Clin Appl 2012; Jul 23. doi: 10.1002/prca.201200027. [Epub ahead of print] PubMed PMID: 22821927.
168. 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: 148.
169. Ioannidis JPA, Khoury MJ,. Improving validation practices in "omics" research. Science 2011; 334: 1230.
170. Baggerly K,. Disclose all data in publications. Nature 2010; 467: 401.
171. Baggerly KA, Coombes KR,. What information should be required to support clinical "omics" publications. Clin Chem 2011; 57: 688.
172. Waikar SS, Sabbisetti VS, Bonventre JV,. Normalization of urinary biomarkers to creatinine during changes in glomerular filtration rate. Kidney Int 2010; 78: 486.
173. Xu Y, Yang X, Wang E,. Review: aptamers in microfluidic chips. Anal Chim Acta 2010; 683: 12.
174. Rehberg PB,. Über die Bestimmung der Menge des Glomerulusfiltrats mittels Kreatinin als Nierenfunktionsprüfung, nebst einigen Bemerkungen über die Theorien der Harnbereitung. Zentralbl Inn Med 1929; 50: 367.