Molecular Diagnosis & Therapy

, Volume 14, Issue 1, pp 1–11

Detecting Adaptive Immunity

Applications in Transplantation Monitoring
  • Georg A. Böhmig
  • Markus Wahrmann
  • Marcus D. Säemann
Current Opinion


In recent decades, continuous improvements in immunosuppressive therapy have led to a significant increase in kidney allograft survival. Despite innovative developments and improvements in immunosuppression, chronic allograft injury and late graft loss still remain major causes of morbidity and mortality. In clinical practice, long-term immunosuppression is adapted and fine-tuned according to drug levels, kidney function, and biopsy results. As an invasive procedure, indication biopsy still represents an indispensible diagnostic gold standard. However, in an effort to further improve outcomes on the basis of individualized treatment, there is an urgent need for noninvasive assays, as well as biomarkers, to more accurately monitor allogeneic responses and predict the risk of acute and chronic allograft rejection. This article discusses strategies for immune monitoring of T-cell responsiveness and humoral alloreactivity. Furthermore, new microarray and gene profiling data are highlighted, which may identify hyporesponsive transplant recipients who could benefit from a reduction or even withdrawal of immunosuppression. Finally, supplementary transplant risk assessment markers, such as soluble CD30 and urinary effector molecule analysis, are discussed as promising new tools. Recent developments and improvements in test principles to monitor and predict allograft immunity are encouraging and may herald the transition of present empiric immunosuppression to individualized immunosuppressive treatment. Nonetheless, before implementation of immune monitoring in routine clinical practice, there is still a need for prospective trials designed to clarify the actual diagnostic potential of individual test systems in a therapeutic context.


  1. 1.
    Racusen LC, Solez K, Colvin RB, et al. The Banff 97 working classification of renal allograft pathology. Kidney Int 1999; 55(2): 713–23PubMedCrossRefGoogle Scholar
  2. 2.
    Racusen LC, Halloran PF, Solez K. Banff 2003 meeting report: new diagnostic insights and standards. Am J Transplant 2004; 4(10): 1562–6PubMedCrossRefGoogle Scholar
  3. 3.
    Solez K, Colvin RB, Racusen LC, et al. Banff 07 classification of renal allograft pathology: updates and future directions. Am J Transplant 2008; 8(4): 753–60PubMedCrossRefGoogle Scholar
  4. 4.
    Kozakowski N, Regele H. Biopsy diagnostics in renal allograft rejection: from histomorphology to biological function. Transpl Int 2009; 22(10): 945–53PubMedCrossRefGoogle Scholar
  5. 5.
    Böhmig GA, Regele H, Hörl WH. Protocol biopsies after kidney transplantation. Transpl Int 2005; 18(2): 131–9PubMedCrossRefGoogle Scholar
  6. 6.
    Thaunat O, Legendre C, Morelon E, et al. To biopsy or not to biopsy? Should we screen the histology of stable renal grafts? Transplantation 2007; 84(6): 671–6PubMedCrossRefGoogle Scholar
  7. 7.
    Nankivell BJ, Chapman JR. The significance of subclinical rejection and the value of protocol biopsies. Am J Transplant 2006; 6(9): 2006–12PubMedCrossRefGoogle Scholar
  8. 8.
    Moreso F, Ibernon M, Goma M, et al. Subclinical rejection associated with chronic allograft nephropathy in protocol biopsies as a risk factor for late graft loss. Am J Transplant 2006; 6(4): 747–52PubMedCrossRefGoogle Scholar
  9. 9.
    Rush D. Protocol transplant biopsies: an underutilized tool in kidney transplantation. Clin J Am Soc Nephrol 2006; 1(1): 138–43PubMedCrossRefGoogle Scholar
  10. 10.
    Rush D, Arlen D, Boucher A, et al. Lack of benefit of early protocol biopsies in renal transplant patients receiving TAC and MMF: a randomized study. Am J Transplant 2007; 7(11): 2538–45PubMedCrossRefGoogle Scholar
  11. 11.
    Furness PN, Philpott CM, Chorbadjian MT, et al. Protocol biopsy of the stable renal transplant: a multicenter study of methods and complication rates. Transplantation 2003; 76(6): 969–73PubMedCrossRefGoogle Scholar
  12. 12.
    Patel R, Terasaki PI. Significance of the positive crossmatch test in kidney transplantation. N Engl J Med 1969; 280(14): 735–9PubMedCrossRefGoogle Scholar
  13. 13.
    McKenna RM, Takemoto SK, Terasaki PI. Anti-HLA antibodies after solid organ transplantation. Transplantation 2000; 69(3): 319–26PubMedCrossRefGoogle Scholar
  14. 14.
    Gebel HM, Bray RA, Nickerson P. Pre-transplant assessment of donor-reactive, HLA-specific antibodies in renal transplantation: contraindication vs risk. Am J Transplant 2003; 3(12): 1488–500PubMedCrossRefGoogle Scholar
  15. 15.
    Terasaki PI. Humoral theory of transplantation. Am J Transplant 2003; 3(6): 665–73PubMedCrossRefGoogle Scholar
  16. 16.
    Racusen LC, Colvin RB, Solez K, et al. Antibody-mediated rejection criteria: an addition to the Banff 97 classification of renal allograft rejection. Am J Transplant 2003; 3(6): 708–14PubMedCrossRefGoogle Scholar
  17. 17.
    Flechner SM, Kerman RH, Van Buren CT, et al. The use of cyclosporine in living-related renal transplantation: donor-specific hyporesponsiveness and steroid withdrawal. Transplantation 1984; 38(6): 685–91PubMedCrossRefGoogle Scholar
  18. 18.
    Reinsmoen NL, Matas AJ. Evidence that improved late renal transplant outcome correlates with the development of in vitro donor antigen-specific hyporeactivity. Transplantation 1993; 55(5): 1017–23PubMedCrossRefGoogle Scholar
  19. 19.
    Ghobrial II, Morris AG, Booth LJ. Clinical significance of in vitro donor-specific hyporesponsiveness in renal allograft recipients as demonstrated by the MLR. Transpl Int 1994; 7(6): 420–7PubMedCrossRefGoogle Scholar
  20. 20.
    Böhmig GA, Säemann MD, Bergmann M, et al. Long-term evaluation of proliferative donor antigen-specific reactivity in cadaveric kidney transplant recipients. Transpl Int 2000; 13(3): 187–93PubMedCrossRefGoogle Scholar
  21. 21.
    Stiller CR, Sinclair NR, Abrahams S, et al. Transplant monitoring: patterns of the immune response. Proc Eur Dial Transplant Assoc 1976; 12: 415–22PubMedGoogle Scholar
  22. 22.
    Kristensen T, Grunnet N, Hansen HE, et al. Immunological diagnosis of rejection in human renal allotransplanted patients: a prospective study. Proc Eur Dial Transplant Assoc 1977; 14: 313–20PubMedGoogle Scholar
  23. 23.
    Goulmy E, Persijn G, Blokland E, et al. Cell-mediated lympholysis studies in renal allograft recipients. Transplantation 1981; 31(3): 210–7PubMedCrossRefGoogle Scholar
  24. 24.
    Carrodeguas L, Orosz CG, Waldman WJ, et al. Trans vivo analysis of human delayed-type hypersensitivity reactivity. Hum Immunol 1999; 60(8): 640–51PubMedCrossRefGoogle Scholar
  25. 25.
    VanBuskirk AM, Burlingham WJ, Jankowska-Gan E, et al. Human allograft acceptance is associated with immune regulation. J Clin Invest 2000; 106(1): 145–55PubMedCrossRefGoogle Scholar
  26. 26.
    Kawai T, Cosimi AB, Spitzer TR, et al. HLA-mismatched renal transplantation without maintenance immunosuppression. N Engl J Med 2008; 358(4): 353–61PubMedCrossRefGoogle Scholar
  27. 27.
    van Besouw NM, van der Mast BJ, de Kuiper P, et al. Donor-specific T-cell reactivity identifies kidney transplant patients in whom immunosuppressive therapy can be safely reduced. Transplantation 2000; 70(1): 136–43PubMedGoogle Scholar
  28. 28.
    Kowalski R, Post D, Schneider MC, et al. Immune cell function testing: an adjunct to therapeutic drug monitoring in transplant patient management. Clin Transplant 2003; 17(2): 77–88PubMedCrossRefGoogle Scholar
  29. 29.
    Kowalski RJ, Post DR, Mannon RB, et al. Assessing relative risks of infection and rejection: a meta-analysis using an immune function assay. Transplantation 2006; 82(5): 663–8PubMedCrossRefGoogle Scholar
  30. 30.
    Zeevi A, Britz JA, Bentlejewski CA, et al. Monitoring immune function during tacrolimus tapering in small bowel transplant recipients. Transpl Immunol 2005; 15(1): 17–24PubMedCrossRefGoogle Scholar
  31. 31.
    Serban G, Whittaker V, Fan J, et al. Significance of immune cell function monitoring in renal transplantation after Thymoglobulin induction therapy. Hum Immunol 2009 Nov; 70(11): 882–90PubMedCrossRefGoogle Scholar
  32. 32.
    Gebauer BS, Hricik DE, Atallah A, et al. Evolution of the enzyme-linked immunosorbent spot assay for post-transplant alloreactivity as a potentially useful immune monitoring tool. Am J Transplant 2002; 2(9): 857–66PubMedCrossRefGoogle Scholar
  33. 33.
    Hricik DE, Rodriguez V, Riley J, et al. Enzyme linked immunosorbent spot (ELISPOT) assay for interferon-gamma independently predicts renal function in kidney transplant recipients. Am J Transplant 2003; 3(7): 878–84PubMedCrossRefGoogle Scholar
  34. 34.
    Nickel P, Presber F, Bold G, et al. Enzyme-linked immunosorbent spot assay for donor-reactive interferon-gamma-producing cells identifies T-cell presensitization and correlates with graft function at 6 and 12 months in renal-transplant recipients. Transplantation 2004; 78(11): 1640–6PubMedCrossRefGoogle Scholar
  35. 35.
    Bestard O, Nickel P, Cruzado JM, et al. Circulating alloreactive T cells correlate with graft function in longstanding renal transplant recipients. J Am Soc Nephrol 2008; 19(7): 1419–29PubMedCrossRefGoogle Scholar
  36. 36.
    Tary-Lehmann M, Hricik DE, Justice AC, et al. Enzyme-linked immunosorbent assay spot detection of interferon-gamma and interleukin 5-producing cells as a predictive marker for renal allograft failure. Transplantation 1998; 66(2): 219–24PubMedCrossRefGoogle Scholar
  37. 37.
    van den Boogaardt DE, van Miert PP, de Vaal YJ, et al. The ratio of interferon-gamma and interleukin-10 producing donor-specific cells as an in vitro monitoring tool for renal transplant patients. Transplantation 2006; 82(6): 844–8PubMedCrossRefGoogle Scholar
  38. 38.
    Macedo C, Orkis EA, Popescu I, et al. Contribution of naive and memory T-cell populations to the human alloimmune response. Am J Transplant 2009; 9(9): 2057–66PubMedCrossRefGoogle Scholar
  39. 39.
    Süsal C, Opelz G. Options for immunologic support of renal transplantation through the HLA and immunology laboratories. Am J Transplant 2007; 7(6): 1450–6PubMedCrossRefGoogle Scholar
  40. 40.
    Zachary AA, Leffell MS. Detecting and monitoring human leukocyte antigen-specific antibodies. Hum Immunol 2008; 69(10): 591–604PubMedCrossRefGoogle Scholar
  41. 41.
    Tait BD, Hudson F, Cantwell L, et al. Review article: Luminex technology for HLA antibody detection in organ transplantation. Nephrology (Carlton) 2009; 14(2): 247–54CrossRefGoogle Scholar
  42. 42.
    Solez K, Colvin RB, Racusen LC, et al. Banff’05 meeting report: differential diagnosis of chronic allograft injury and elimination of chronic allograft nephropathy (‘CAN’). Am J Transplant 2007; 7(3): 518–26PubMedCrossRefGoogle Scholar
  43. 43.
    Böhmig GA, Exner M, Habicht A, et al. Capillary C4d deposition in kidney allografts: a specific marker of alloantibody-dependent graft injury. J Am Soc Nephrol 2002; 13(4): 1091–9PubMedGoogle Scholar
  44. 44.
    Mauiyyedi S, Crespo M, Collins AB, et al. Acute humoral rejection in kidney transplantation: II. Morphology, immunopathology, and pathologic classification. J Am Soc Nephrol 2002; 13(3): 779–87PubMedGoogle Scholar
  45. 45.
    Terasaki PI, Ozawa M. Predictive value of HLA antibodies and serum creatinine in chronic rejection: results of a 2-year prospective trial. Transplantation 2005; 80(9): 1194–7PubMedCrossRefGoogle Scholar
  46. 46.
    Bartel G, Regele H, Wahrmann M, et al. Posttransplant HLA alloreactivity in stable kidney transplant recipients-incidences and impact on long-term allograft outcomes. Am J Transplant 2008; 8(12): 2652–60PubMedCrossRefGoogle Scholar
  47. 47.
    Lachmann N, Terasaki PI, Budde K, et al. Anti-human leukocyte antigen and donor-specific antibodies detected by Luminex posttransplant serve as bio-markers for chronic rejection of renal allografts. Transplantation 2009; 87(10): 1505–13PubMedCrossRefGoogle Scholar
  48. 48.
    Böhmig GA, Bartel G, Regele H, et al. Prospects and limitations of post-transplantation alloantibody detection in renal transplantation. Hum Immunol 2009 Aug; 70(8): 640–4PubMedCrossRefGoogle Scholar
  49. 49.
    Suberbielle C, Legendre C, Chkoff N, et al. Anti-HLA sensitization after renal transplant excision: a retrospective study in 84 patients. Transplant Proc 1996; 28(5): 2814PubMedGoogle Scholar
  50. 50.
    Adeyi OA, Girnita AL, Howe J, et al. Serum analysis after transplant nephrectomy reveals restricted antibody specificity patterns against structurally defined HLA class I mismatches. Transpl Immunol 2005; 14(1): 53–62PubMedCrossRefGoogle Scholar
  51. 51.
    Billen EV, Christiaans MH, Lee J, et al. Donor-directed HLA antibodies before and after transplantectomy detected by the Luminex single antigen assay. Transplantation 2009; 87(4): 563–9PubMedCrossRefGoogle Scholar
  52. 52.
    Perry DK, Pollinger HS, Burns JM, et al. Two novel assays of alloantibody-secreting cells demonstrating resistance to desensitization with IVIG and rATG. Am J Transplant 2008; 8(1): 133–43PubMedCrossRefGoogle Scholar
  53. 53.
    Perry DK, Burns JM, Pollinger HS, et al. Proteasome inhibition causes apoptosis of normal human plasma cells preventing alloantibody production. Am J Transplant 2009; 9(1): 201–9PubMedCrossRefGoogle Scholar
  54. 54.
    Han M, Rogers JA, Lavingia B, et al. Peripheral blood B cells producing donor-specific HLA antibodies in vitro. Hum Immunol 2009; 70(1): 29–34PubMedCrossRefGoogle Scholar
  55. 55.
    Fan X, Ang A, Pollock-Barziv SM, et al. Donor-specific B-cell tolerance after ABO-incompatible infant heart transplantation. Nat Med 2004; 10(11): 1227–33PubMedCrossRefGoogle Scholar
  56. 56.
    Pelzl S, Opelz G, Wiesel M, et al. Soluble CD30 as a predictor of kidney graft outcome. Transplantation 2002; 73(1): 3–6PubMedCrossRefGoogle Scholar
  57. 57.
    Süsal C, Pelzl S, Döhler B, et al. Identification of highly responsive kidney transplant recipients using pretransplant soluble CD30. J Am Soc Nephrol 2002; 13(6): 1650–6PubMedCrossRefGoogle Scholar
  58. 58.
    Süsal C, Pelzl S, Opelz G. Strong human leukocyte antigen matching effect in nonsensitized kidney recipients with high pretransplant soluble CD30. Transplantation 2003; 76(8): 1231–2PubMedCrossRefGoogle Scholar
  59. 59.
    Rajakariar R, Jivanji N, Varagunam M, et al. High pre-transplant soluble CD 30 levels are predictive of the grade of rejection. Am J Transplant 2005; 5(8): 1922–5PubMedCrossRefGoogle Scholar
  60. 60.
    Platt RE, Wu KS, Poole K, et al. Soluble CD30 as a prognostic factor for outcome following renal transplantation. J Clin Pathol 2009; 62(7): 662–3PubMedCrossRefGoogle Scholar
  61. 61.
    Slavcev A, Honsova E, Lodererova A, et al. Soluble CD30 in patients with antibody-mediated rejection of the kidney allograft. Transpl Immunol 2007; 18(1): 22–7PubMedCrossRefGoogle Scholar
  62. 62.
    Pelzl S, Opelz G, Daniel V, et al. Evaluation of posttransplantation soluble CD30 for diagnosis of acute renal allograft rejection. Transplantation 2003; 75(3): 421–3PubMedCrossRefGoogle Scholar
  63. 63.
    Langan LL, Park LP, Hughes TL, et al. Post-transplant HLA class II antibodies and high soluble CD30 levels are independently associated with poor kidney graft survival. Am J Transplant 2007; 7(4): 847–56PubMedCrossRefGoogle Scholar
  64. 64.
    Weimer R, Süsal C, Yildiz S, et al. Post-transplant sCD30 and neopterin as predictors of chronic allograft nephropathy: impact of different immunosuppressive regimens. Am J Transplant 2006; 6(8): 1865–74PubMedCrossRefGoogle Scholar
  65. 65.
    Nafar M, Farrokhi F, Vaezi M, et al. Pre-transplant and post-transplant soluble CD30 for prediction and diagnosis of acute kidney allograft rejection. Int Urol Nephrol 2009; 41(3): 687–93PubMedCrossRefGoogle Scholar
  66. 66.
    Cervelli C, Fontecchio G, Scimitarra M, et al. Evaluation of serum sCD30 in renal transplantation patients with and without acute rejection. Transplant Proc 2009; 41(4): 1159–61PubMedCrossRefGoogle Scholar
  67. 67.
    Sebille F, Gagne K, Guillet M, et al. Direct recognition of foreign MHC determinants by naive T cells mobilizes specific Vbeta families without skewing of the complementarity-determining region 3 length distribution. J Immunol 2001; 167(6): 3082–8PubMedGoogle Scholar
  68. 68.
    Gagne K, Brouard S, Giral M, et al. Highly altered V beta repertoire of T cells infiltrating long-term rejected kidney allografts. J Immunol 2000; 164(3): 1553–63PubMedGoogle Scholar
  69. 69.
    Brouard S, Dupont A, Giral M, et al. Operationally tolerant and minimally immunosuppressed kidney recipients display strongly altered blood T-cell clonal regulation. Am J Transplant 2005; 5(2): 330–40PubMedCrossRefGoogle Scholar
  70. 70.
    Boros P, Bromberg JS. Human FOXP3+ regulatory T cells in transplantation. Am J Transplant 2009; 9(8): 1719–24PubMedCrossRefGoogle Scholar
  71. 71.
    Suciu-Foca N, Manavalan JS, Scotto L, et al. Molecular characterization of allospecific T suppressor and tolerogenic dendritic cells: review. Int Immunopharmacol 2005; 5(1): 7–11PubMedCrossRefGoogle Scholar
  72. 72.
    Chang CC, Ciubotariu R, Manavalan JS, et al. Tolerization of dendritic cells by T(S) cells: the crucial role of inhibitory receptors ILT3 and ILT4. Nat Immunol 2002; 3(3): 237–43PubMedCrossRefGoogle Scholar
  73. 73.
    Pretagostini R, Cinti P, Lai Q, et al. Minimization of immunosuppressive therapy and immunological monitoring of kidney transplant recipients with long-term allograft survival. Transpl Immunol 2008; 20(1-2): 3–5PubMedCrossRefGoogle Scholar
  74. 74.
    Dijke IE, Korevaar SS, Caliskan K, et al. Inadequate immune regulatory function of CD4+CD25bright+FoxP3+ T cells in heart transplant patients who experience acute cellular rejection. Transplantation 2009; 87(8): 1191–200PubMedCrossRefGoogle Scholar
  75. 75.
    Yapici U, Bemelman FJ, Scheepstra CG, et al. Intragraft FOXP3 protein or mRNA during acute renal allograft rejection correlates with inflammation, fibrosis, and poor renal outcome. Transplantation 2009; 87(9): 1377–80PubMedCrossRefGoogle Scholar
  76. 76.
    Ruggenenti P, Perico N, Gotti E, et al. Sirolimus versus cyclosporine therapy increases circulating regulatory T cells, but does not protect renal transplant patients given alemtuzumab induction from chronic allograft injury. Transplantation 2007; 84(8): 956–64PubMedCrossRefGoogle Scholar
  77. 77.
    Dijke IE, Weimar W, Baan CC. Regulatory T cells after organ transplantation: where does their action take place? Hum Immunol 2008; 69(7): 389–98PubMedCrossRefGoogle Scholar
  78. 78.
    Kreijveld E, Koenen HJ, van Cranenbroek B, et al. Immunological monitoring of renal transplant recipients to predict acute allograft rejection following the discontinuation of tacrolimus. PLoS One 2008; 3(7): e2711PubMedCrossRefGoogle Scholar
  79. 79.
    Bunnag S, Einecke G, Reeve J, et al. Molecular correlates of renal function in kidney transplant biopsies. J Am Soc Nephrol 2009; 20(5): 1149–60PubMedCrossRefGoogle Scholar
  80. 80.
    Mengel M, Reeve J, Bunnag S, et al. Molecular correlates of scarring in kidney transplants: the emergence of mast cell transcripts. Am J Transplant 2009; 9(1): 169–78PubMedCrossRefGoogle Scholar
  81. 81.
    Perco P, Kainz A, Wilflingseder J, et al. Histogenomics: association of gene expression patterns with histological parameters in kidney biopsies. Transplantation 2009; 87(2): 290–5PubMedCrossRefGoogle Scholar
  82. 82.
    Saint-Mezard P, Berthier CC, Zhang H, et al. Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection. Transpl Int 2009; 22(3): 293–302PubMedCrossRefGoogle Scholar
  83. 83.
    Flechner SM, Kurian SM, Head SR, et al. Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes. Am J Transplant 2004; 4(9): 1475–89PubMedCrossRefGoogle Scholar
  84. 84.
    Deng MC, Eisen HJ, Mehra MR, et al. Noninvasive discrimination of rejection in cardiac allograft recipients using gene expression profiling. Am J Transplant 2006; 6(1): 150–60PubMedCrossRefGoogle Scholar
  85. 85.
    Brouard S, Mansfield E, Braud C, et al. Identification of a peripheral blood transcriptional biomarker panel associated with operational renal allograft tolerance. Proc Natl Acad Sci U S A 2007; 104(39): 15448–53PubMedCrossRefGoogle Scholar
  86. 86.
    Braud C, Baeten D, Giral M, et al. Immunosuppressive drug-free operational immune tolerance in human kidney transplant recipients: Part I. Blood gene expression statistical analysis. J Cell Biochem 2008; 103(6): 1681–92PubMedCrossRefGoogle Scholar
  87. 87.
    Murphy GP, Williams PD, Merrin CE. Diagnostic value of lymphocyturia in renal allograft rejection in man. Urology 1973; 2(3): 227–30PubMedCrossRefGoogle Scholar
  88. 88.
    Grunewald RW, Fiedler GM, Stock B, et al. Immunocytological determination of lymphocytes and monocytes/macrophages in urinary sediments of renal allograft recipients. Nephrol Dial Transplant 2000; 15(6): 888–92PubMedCrossRefGoogle Scholar
  89. 89.
    Margreiter R, Fuchs D, Hausen A, et al. Neopterin as a new biochemical marker for diagnosis of allograft rejection: experience based upon evaluation of 100 consecutive cases. Transplantation 1983; 36(6): 650–3PubMedCrossRefGoogle Scholar
  90. 90.
    Reibnegger G, Aichberger C, Fuchs D, et al. Posttransplant neopterin excretion in renal allograft recipients: a reliable diagnostic aid for acute rejection and a predictive marker of long-term graft survival. Transplantation 1991; 52(1): 58–63PubMedCrossRefGoogle Scholar
  91. 91.
    Li B, Hartono C, Ding R, et al. Noninvasive diagnosis of renal-allograft rejection by measurement of messenger RNA for perforin and granzyme B in urine. N Engl J Med 2001; 344(13): 947–54PubMedCrossRefGoogle Scholar
  92. 92.
    Kotsch K, Mashreghi MF, Bold G, et al. Enhanced granulysin mRNA expression in urinary sediment in early and delayed acute renal allograft rejection. Transplantation 2004; 77(12): 1866–75PubMedCrossRefGoogle Scholar
  93. 93.
    Dadhania D, Muthukumar T, Ding R, et al. Molecular signatures of urinary cells distinguish acute rejection of renal allografts from urinary tract infection. Transplantation 2003; 75(10): 1752–4PubMedCrossRefGoogle Scholar
  94. 94.
    Ozbay A, Torring C, Olsen R, et al. Transcriptional profiles in urine during acute rejection, bacteriuria, CMV infection and stable graft function after renal transplantation. Scand J Immunol 2009; 69(4): 357–65PubMedCrossRefGoogle Scholar
  95. 95.
    Yannaraki M, Rebibou JM, Ducloux D, et al. Urinary cytotoxic molecular markers for a noninvasive diagnosis in acute renal transplant rejection. Transpl Int 2006; 19(9): 759–68PubMedCrossRefGoogle Scholar
  96. 96.
    Ding R, Li B, Muthukumar T, et al. CD103 mRNA levels in urinary cells predict acute rejection of renal allografts. Transplantation 2003; 75(8): 1307–12PubMedCrossRefGoogle Scholar
  97. 97.
    Tatapudi RR, Muthukumar T, Dadhania D, et al. Noninvasive detection of renal allograft inflammation by measurements of mRNA for IP-10 and CXCR3 in urine. Kidney Int 2004; 65(6): 2390–7PubMedCrossRefGoogle Scholar
  98. 98.
    Muthukumar T, Dadhania D, Ding R, et al. Messenger RNA for FOXP3 in the urine of renal-allograft recipients. N Engl J Med 2005; 353(22): 2342–51PubMedCrossRefGoogle Scholar
  99. 99.
    Renesto PG, Ponciano VC, Cenedeze MA, et al. High expression of Tim-3 mRNA in urinary cells from kidney transplant recipients with acute rejection. Am J Transplant 2007; 7(6): 1661–5PubMedCrossRefGoogle Scholar
  100. 100.
    Manfro RC, Aquino-Dias EC, Joelsons G,et al. Noninvasive Tim-3 messenger RNA evaluation in renal transplant recipients with graft dysfunction. Transplantation 2008; 86(12): 1869–74PubMedCrossRefGoogle Scholar
  101. 101.
    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(1): 219–27PubMedCrossRefGoogle Scholar
  102. 102.
    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 (4 Pt 1): 729–38PubMedCrossRefGoogle Scholar
  103. 103.
    Schaub S, Mayr M, Hönger G, et al. Detection of subclinical tubular injury after renal transplantation: comparison of urine protein analysis with allograft histopathology. Transplantation 2007; 84(1): 104–12PubMedCrossRefGoogle Scholar
  104. 104.
    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(12): 3240–8PubMedCrossRefGoogle Scholar
  105. 105.
    O’Riordan E, Orlova TN, Podust VN, et al. Characterization of urinary peptide biomarkers of acute rejection in renal allografts. Am J Transplant 2007; 7(4): 930–40PubMedCrossRefGoogle Scholar
  106. 106.
    Mao Y, Yu J, Chen J, et al. Diagnosis of renal allograft subclinical rejection by urine protein fingerprint analysis. Transpl Immunol 2008; 18(3): 255–9PubMedCrossRefGoogle Scholar
  107. 107.
    Wang JN, Zhou Y, Zhu TY, et al. Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI-FTMS. J Proteome Res 2008; 7(8): 3597–601PubMedCrossRefGoogle Scholar
  108. 108.
    Zhang Y, Oetting WS, Harvey SB, et al. Urinary peptide patterns in native kidneys and kidney allografts. Transplantation 2009; 87(12): 1807–13PubMedCrossRefGoogle Scholar
  109. 109.
    Quintana LF, Sole-Gonzalez A, Kalko SG, et al. Urine proteomics to detect biomarkers for chronic allograft dysfunction. J Am Soc Nephrol 2009; 20(2): 428–35PubMedCrossRefGoogle Scholar
  110. 110.
    Hu H, Kwun J, Aizenstein BD, et al. Noninvasive detection of acute and chronic injuries in human renal transplant by elevation of multiple cytokines/ chemokines in urine. Transplantation 2009; 87(12): 1814–20PubMedCrossRefGoogle Scholar
  111. 111.
    Bechtel U, Scheuer R, Landgraf R, et al. Assessment of soluble adhesion molecules (sICAM-1, sVCAM-1, sELAM-1) and complement cleavage products (sC4d, sC5b-9) in urine: clinical monitoring of renal allograft recipients. Transplantation 1994; 58(8): 905–11PubMedCrossRefGoogle Scholar
  112. 112.
    Hönger G, Mayr M, Dickenmann M, et al. Urinary C4d does not correlate with C4d-staining in peritubular capillaries but reflects nonspecific glomerular injury. Transplantation 2008; 85(4): 542–6PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2010

Authors and Affiliations

  • Georg A. Böhmig
    • 1
  • Markus Wahrmann
    • 1
  • Marcus D. Säemann
    • 1
  1. 1.Division of Nephrology and Dialysis, Department of Medicine IIIMedical University of ViennaViennaAustria

Personalised recommendations