Table of Contents Author Guidelines Submit a Manuscript
Disease Markers
Volume 2017 (2017), Article ID 9264904, 12 pages
https://doi.org/10.1155/2017/9264904
Clinical Study

Peritransplant Soluble CD30 as a Risk Factor for Slow Kidney Allograft Function, Early Acute Rejection, Worse Long-Term Allograft Function, and Patients’ Survival

1Department of Laboratory Diagnostics and General Pathology, State Institution “Zaporizhzhia Medical Academy of Postgraduate Education Ministry of Health of Ukraine”, 20 Winter Boulevard, Zaporizhzhia 69096, Ukraine
2Department of Transplantology, Endocrine Surgery and Cardiovascular Surgery, State Institution “Zaporizhzhia Medical Academy of Postgraduate Education Ministry of Health of Ukraine”, Zaporizhzhia Regional Hospital, 10 Orikhiv Highway, Zaporizhzhia 69050, Ukraine
3Institute of Cardiovascular Surgery and Transplantology, State Institution “Zaporizhzhia Medical Academy of Postgraduate Education Ministry of Health of Ukraine”, 20 Winter Boulevard, Zaporizhzhia 69096, Ukraine
4Immunological Laboratory, Zaporizhzhia Regional Hospital, State Institution “Zaporizhzhia Medical Academy of Postgraduate Education Ministry of Health of Ukraine”, 10 Orikhiv Highway, Zaporizhzhia 69050, Ukraine

Correspondence should be addressed to Andriy V. Trailin

Received 1 December 2016; Revised 27 March 2017; Accepted 11 April 2017; Published 11 June 2017

Academic Editor: Michele Malaguarnera

Copyright © 2017 Andriy V. Trailin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. Saran, Y. Li, B. Robinson et al., “US renal data system 2014 annual data report: epidemiology of kidney disease in the United States,” American Journal of Kidney Diseases, vol. 66, supplement 1, no. 1, pp. S1–S306, 2014. View at Publisher · View at Google Scholar · View at Scopus
  2. B. Aguiar, T. Santos Amorim, C. Romãozinho et al., “Malignancy in kidney transplantation: a 25-year single-center experience in Portugal,” Transplantation Proceedings, vol. 47, no. 4, pp. 976–980, 2015. View at Publisher · View at Google Scholar · View at Scopus
  3. A. K. Israni, J. J. Snyder, M. A. Skeans et al., “PORT investigators. Predicting coronary heart disease after kidney transplantation: Patient Outcomes in Renal Transplantation (PORT) study,” American Journal of Transplantation, vol. 10, no. 2, pp. 338–353, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. D. Wang, W. Z. Wu, J. H. Chen et al., “Pre-transplant soluble CD30 level as a predictor of not only acute rejection and graft loss but pneumonia in renal transplant recipients,” Transplant Immunology, vol. 22, no. 3-4, pp. 115–120, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. M. S. Kim, H. J. Kim, S. I. Kim et al., “Pretransplant soluble CD30 level has limited effect on acute rejection, but affects graft function in living donor kidney transplantation,” Transplantation, vol. 82, no. 12, pp. 1602–1605, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. J. H. Shin, E. H. Koo, S. H. Ha et al., “The impact of slow graft function on graft outcome is comparable to delayed graft function in deceased donor kidney transplantation,” International Urology and Nephrology, vol. 48, no. 3, pp. 431–439, 2016. View at Publisher · View at Google Scholar · View at Scopus
  7. P. F. Halloran, D. G. de Freitas, G. Einecke et al., “An integrated view of molecular changes, histopathology and outcomes in kidney transplants,” American Journal of Transplantation, vol. 10, no. 10, pp. 2223–2230, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. G. M. Del Prete, F. De Carli, C. K. Almerigogna et al., “Preferential expression of CD30 by human CD4+ T cells producing Th2-type cytokines,” Federation of American Societies for Experimental Biology Journal, vol. 9, no. 1, pp. 81–86, 1995. View at Google Scholar
  9. C. Süsal, S. Pelzl, B. Döhler, and G. Opelz, “Identification of highly responsive kidney transplant recipients using pretransplant soluble CD30,” Journal of the American Society of Nephrology, vol. 13, no. 6, pp. 1650–1656, 2002. View at Publisher · View at Google Scholar · View at Scopus
  10. S. Pelzl, G. Opelz, M. Wiesel et al., “Soluble CD30 as a predictor of kidney graft outcome,” Transplantation, vol. 73, no. 1, pp. 3–6, 2002. View at Publisher · View at Google Scholar
  11. F. W. Vondran, K. Timrott, S. Kollrich et al., “Pre-transplant immune state defined by serum markers and alloreactivity predicts acute rejection after living donor kidney transplantation,” Clinical Transplantation, vol. 28, no. 9, pp. 968–979, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. M. A. Halim, T. Al-Otaibi, I. Al-Muzairai et al., “Serial soluble CD30 measurements as a predictor of kidney graft outcome,” Transplantation Proceedings, vol. 42, no. 3, pp. 801–803, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. A. Slavcev, J. Lácha, E. Honsová et al., “Soluble CD30 and HLA antibodies as potential risk factors for kidney transplant rejection,” Transplant Immunology, vol. 14, no. 2, pp. 117–121, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. I. H. Matinlauri, L. E. Kyllönen, K. T. Salmela, H. Helin, S. Pelzl, and C. Süsal, “Serum sCD30 in monitoring of alloresponse in well HLA-matched cadaveric kidney transplantations,” Transplantation, vol. 80, no. 12, pp. 1809–1812, 2005. View at Google Scholar
  15. R. Weimer, C. Süsal, S. Yildiz et al., “sCD30 and neopterin as risk factors of chronic renal transplant rejection: impact of cyclosporine , tacrolimus, and mycophenolate mofetil,” Transplantation Proceedings, vol. 37, no. 4, pp. 1776–1778, 2005. View at Publisher · View at Google Scholar · View at Scopus
  16. F. M. Heinemann, V. Rebmann, O. Witzke, T. Philipp, C. E. Broelsch, and H. Grosse-Wilde, “Association of elevated pretransplant sCD30 levels with graft loss in 206 patients treated with modern immunosuppressive therapies after renal transplantation,” Transplantation, vol. 83, no. 6, pp. 706–711, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. W. Dong, Y. Shunliang, W. Weizhen et al., “Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30,” Transplant Immunology, vol. 16, no. 1, pp. 41–45, 2006. View at Publisher · View at Google Scholar · View at Scopus
  18. L. L. Valke, B. van Cranenbroek, L. B. Hilbrands, and I. Joosten, “Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation,” Transplant Immunology, vol. 32, no. 1, pp. 18–22, 2015. View at Publisher · View at Google Scholar · View at Scopus
  19. N. Azarpira, M. H. Aghdaie, and Z. Malekpour, “Soluble CD30 in renal transplant recipients: is it a good biomarker to predict rejection?” Saudi Journal of Kidney Diseases and Transplantation, vol. 21, no. 1, pp. 31–36, 2010. View at Google Scholar
  20. K. Kamali, M. A. Abbasi, B. Farokhi et al., “Posttransplant soluble CD30 as a predictor of acute renal allograft rejection,” Experimental and Clinical Transplantation, vol. 7, no. 4, pp. 237–240, 2009. View at Google Scholar
  21. Y. Chen, Q. Tai, S. Hong et al., “Pretransplantation soluble CD30 level as a predictor of acute rejection in kidney transplantation: a meta-analysis,” Transplantation, vol. 94, no. 9, pp. 911–918, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. K. Abbas, R. Muzaffar, M. N. Zafar, M. Mubarak, S. A. Naqvi, and S. A. Rizvi, “Evaluation of pretransplant T-cell activation status by soluble CD 30 determination,” Journal of the Pakistan Medical Association, vol. 59, no. 4, pp. 212–215, 2009. View at Google Scholar
  23. S. Pelzl, G. Opelz, V. Daniel, M. Wiesel, and C. Süsal, “Evaluation of posttransplantation soluble CD30 for diagnosis of acute renal allograft rejection,” Transplantation, vol. 75, no. 3, pp. 421–423, 2003. View at Publisher · View at Google Scholar · View at Scopus
  24. C. Spiridon, A. Nikaein, M. Lerman, J. Hunt, R. Dickerman, and M. Mack, “CD30, a marker to detect the high-risk kidney transplant recipients,” Clinical Transplantation, vol. 22, no. 6, pp. 765–769, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. J. H. Chen, R. Lü, Y. Chen et al., “Influence of pre-transplant serum level of soluble CD30 on the long-term survival rates of kidney transplant recipients and grafts,” Zhonghua Yi Xue Za Zhi, vol. 85, no. 22, pp. 1560–1563, 2005. View at Google Scholar
  26. M. Fernández-Ruiz, P. Parra, F. López-Medrano et al., “Serum sCD30: a promising biomarker for predicting the risk of bacterial infection after kidney transplantation,” Transplant Infectious Disease, vol. 19, no. 2, 2017. View at Publisher · View at Google Scholar
  27. D. Wang, W. Wu, S. Yang, Q. Wang, and J. Tan, “Post-transplant monitoring of soluble CD30 level as predictor of graft outcome: a single center experience from China,” Transplant Immunology, vol. 27, no. 4, pp. 146–150, 2012. View at Publisher · View at Google Scholar · View at Scopus
  28. M. A. Amirzargar, A. Amirzargar, A. Basiri et al., “Early post-transplant immune monitoring can predict long-term kidney graft survival: soluble CD30 levels, anti-HLA antibodies and IgA-anti-Fab autoantibodies,” Human Immunology, vol. 75, no. 1, pp. 47–58, 2014. View at Publisher · View at Google Scholar · View at Scopus
  29. C. Süsal, B. Döhler, A. Ruhenstroth et al., “Donor-specific antibodies require preactivated immune system to harm renal transplant,” eBioMedicine, vol. 9, pp. 366–371, 2016. View at Publisher · View at Google Scholar · View at Scopus
  30. S. G. Melendreras, P. Martínez-Camblor, A. Menéndez et al., “Soluble co-signaling molecules predict long-term graft outcome in kidney-transplanted patients,” PloS One, vol. 9, no. 12, article e113396, 2014. View at Publisher · View at Google Scholar · View at Scopus
  31. J. C. Delgado, I. Y. Pavlov, and F. S. Shihab, “Post-transplant increased levels of serum sCD30 is a marker for prediction of kidney allograft loss in a 5-year prospective study,” Transplant Immunology, vol. 22, no. 1-2, pp. 1–4, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. C. Süsal, B. Döhler, M. Sadeghi et al., “Posttransplant sCD30 as a predictor of kidney graft outcome,” Transplantation, vol. 91, no. 12, pp. 1364–1369, 2011. View at Publisher · View at Google Scholar · View at Scopus
  33. J. Kovac, M. Arnol, B. Vidan-Jeras, A. F. Bren, and A. Kandus, “Does pretransplant soluble CD30 serum concentration affect deceased-donor kidney graft function 3 years after transplantation?” Transplantation Proceedings, vol. 40, no. 5, pp. 1357–1361, 2008. View at Publisher · View at Google Scholar · View at Scopus
  34. R. Iv, Q. He, H. P. Wang, J. Jin, Y. Chen, and J. H. Chen, “High serum level of the soluble CD30 identifies Chinese kidney transplant recipients at high risk of unfavorable outcome,” Transplantation Proceedings, vol. 40, no. 10, pp. 3375–3380, 2008. View at Publisher · View at Google Scholar · View at Scopus
  35. R. Weimer, C. Süsal, S. Yildiz et al., “Post-transplant sCD30 and neopterin as predictors of chronic allograft nephropathy: impact of different immunosuppressive regimens,” American Journal of Transplantation, vol. 6, no. 8, pp. 1865–1874, 2006. View at Publisher · View at Google Scholar · View at Scopus
  36. KDIGO, “KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease,” Kidney International Supplements, vol. 3, no. 1, pp. 1–150, 2013. View at Google Scholar
  37. A. Sánchez-Fructuoso, P. Naranjo Garcia, N. Calvo Romero et al., “Effect of the brain-death process on acute rejection in renal transplantation,” Transplantation Proceedings, vol. 39, no. 7, pp. 2214–2216, 2007. View at Publisher · View at Google Scholar · View at Scopus
  38. Q. Sun, Z. H. Liu, S. Ji et al., “Late and early C4d-positive acute rejection: different clinico-histopathological subentities in renal transplantation,” Kidney International, vol. 70, no. 2, pp. 377–383, 2006. View at Publisher · View at Google Scholar · View at Scopus
  39. D. Lopes, T. Barra, J. Malheiro et al., “Effect of different sensitization events on HLA alloimmunization in kidney transplantation candidates,” Transplantation Proceedings, vol. 47, no. 4, pp. 894–897, 2015. View at Google Scholar
  40. S. Vaidya, D. Partlow, T. Barnes, and K. Gugliuzza, “Pretransplant soluble CD30 is a better predictor of posttransplant development of donor-specific antibodies and acute vascular rejection than panel reactive antibodies,” Transplantation, vol. 82, no. 12, pp. 1606–1609, 2006. View at Publisher · View at Google Scholar · View at Scopus
  41. R. Rajakariar, N. Jivanji, M. Varagunam et al., “High pre-transplant soluble CD30 levels are predictive of the grade of rejection,” American Journal of Transplantation, vol. 5, no. 8, pp. 1922–1925, 2005. View at Publisher · View at Google Scholar · View at Scopus
  42. S. M. Schaefer, C. Süsal, G. Opelz et al., “Pre-transplant soluble CD30 in combination with total DSA but not pre-transplant C1q-DSA predicts antibody-mediated graft loss in presensitized high-risk kidney transplant recipients,” HLA, vol. 87, no. 2, pp. 89–99, 2016. View at Publisher · View at Google Scholar
  43. L. M. Rodríguez, S. C. París, M. Arbeláez et al., “Kidney graft recipients with pretransplantation HLA class I antibodies and high soluble CD30 are at high risk for graft loss,” Human Immunology, vol. 68, no. 8, pp. 652–660, 2007. View at Publisher · View at Google Scholar · View at Scopus
  44. W. Altermann, G. Schlaf, A. Rothhoff, and B. Seliger, “High variation of individual soluble serum CD30 levels of pre-transplantation patients: sCD30 a feasible marker for prediction of kidney allograft rejection?” Nephrology, Dialysis, Transplantation, vol. 22, no. 10, pp. 2795–2799, 2007. View at Publisher · View at Google Scholar · View at Scopus
  45. J. Kanter Berga, L. M. Pallardo Mateu, S. Beltran Catalan et al., “Donor-specific HLA antibodies: risk factors and outcomes after kidney transplantation,” Transplantation Proceedings, vol. 43, no. 6, pp. 2154–2156, 2011. View at Publisher · View at Google Scholar · View at Scopus
  46. Y. Lebranchu, C. Baan, L. Biancone et al., “Pretransplant identification of acute rejection risk following kidney transplantation,” Transplant International, vol. 27, no. 2, pp. 129–138, 2014. View at Publisher · View at Google Scholar · View at Scopus
  47. S. B. Campbell, E. Hothersall, J. Preston et al., “Frequency and severity of acute rejection in live- versus cadaveric-donor renal transplants,” Transplantation, vol. 76, no. 10, pp. 1452–1457, 2003. View at Publisher · View at Google Scholar · View at Scopus
  48. A. Loverre, C. Divella, G. Castellano et al., “T helper 1, 2 and 17 cell subsets in renal transplant patients with delayed graft function,” Transplant International, vol. 24, no. 3, pp. 233–242, 2011. View at Publisher · View at Google Scholar · View at Scopus
  49. L. R. Requião-Moura, M. S. de Durão Junior, A. C. Matos, and A. Pacheco-Silva, “Ischemia and reperfusion injury in renal transplantation: hemodynamic and immunological paradigms,” Einstein (Sao Paulo), vol. 13, no. 1, pp. 129–135, 2015. View at Publisher · View at Google Scholar · View at Scopus
  50. M. J. Espinar, I. M. Miranda, S. Costa-de-Oliveira, R. Rocha, A. G. Rodrigues, and C. Pina-Vaz, “Urinary tract infections in kidney transplant patients due to Escherichia coli and Klebsiella pneumoniae-producing extended-spectrum β-lactamases: risk factors and molecular epidemiology,” PloS One, vol. 10, no. 8, article e0134737, 2015. View at Publisher · View at Google Scholar · View at Scopus
  51. G. G. Donders, “Lower genital tract infections in diabetic women,” Current Infectious Disease Reports, vol. 4, no. 6, pp. 536–539, 2002. View at Publisher · View at Google Scholar
  52. J. P. Kusanovic, R. Romero, J. Esoinoza et al., “Maternal serum soluble CD30 is increased in pregnancies complicated with acute pyelonephritis,” The Journal of Maternal-Fetal & Neonatal Medicine, vol. 20, no. 11, pp. 803–811, 2007. View at Publisher · View at Google Scholar · View at Scopus
  53. H. M. Kim, H. Y. Shin, H. J. Jeong et al., “Reduced IL-2 but elevated IL-4, IL-6, and IgE serum levels in patients with cerebral infarction during the acute stage,” Journal of Molecular Neuroscience, vol. 14, no. 3, pp. 191–196, 2000. View at Publisher · View at Google Scholar
  54. S. Guo and J. Zhao, “Immunotherapy for tuberculosis: what’s the better choice?” Frontiers in Bioscience (Landmark Edition), vol. 17, no. 1, pp. 2684–2690, 2012. View at Publisher · View at Google Scholar · View at Scopus
  55. T. T. Tan and L. M. Coussens, “Humoral immunity, inflammation and cancer,” Current Opinion in Immunology, vol. 19, no. 2, pp. 209–216, 2007. View at Publisher · View at Google Scholar · View at Scopus
  56. Y. Feng, H. Yin, G. Mai et al., “Elevated serum levels of CCL17 correlate with increased peripheral blood platelet count in patients with active tuberculosis in China,” Clinical and Vaccine Immunology, vol. 18, no. 4, pp. 629–632, 2011. View at Publisher · View at Google Scholar · View at Scopus