Use of cytokine polymorphisms and Epstein-Barr virus viral load to predict development of post-transplant lymphoproliferative disorder in paediatric liver transplant recipients
- PMID: 16824159
- DOI: 10.1111/j.1399-0012.2006.00498.x
Use of cytokine polymorphisms and Epstein-Barr virus viral load to predict development of post-transplant lymphoproliferative disorder in paediatric liver transplant recipients
Abstract
Objective: Currently there are no tests to accurately identify paediatric liver transplant patients at risk for post-transplant lymphoproliferative disorder (PTLD). Herein we describe the use of cytokine polymorphisms and real-time quantitative polymerase chain reaction (qPCR) Epstein-Barr virus (EBV) viral load to identify patients at risk for PTLD development.
Methods: Between 2001 and 2004, approximately 1047 patient samples were collected for qPCR for EBV in 59 patients. EBV viral load was reported in three groups: low EBV (<4,000 copies/microg DNA), high EBV/no PTLD (>4000 copies/microg DNA) and biopsy-proven PTLD. All 59 patients also had cytokine polymorphism genotyping performed for six cytokine polymorphisms (transforming growth factor (TGF)-beta, tumor necrosis factor (TNF)-alpha, interleukins (IL)-6, IL-10, IL-2, and interferon (IFN)-gamma) from DNA isolated from peripheral blood mononuclear cells. Positive predictive value (PPV) and negative predictive value (NPV) were calculated using qPCR and cytokine polymorphism results. Data are reported as a mean +/- standard error of the mean.
Results: There were 35 males and 24 females with a mean follow-up of 34.9 months. EBV viral load had a PPV and NPV of 29 and 95%, respectively. The low IFN-gamma (A/A) polymorphism was found to be present in 4/6 PTLD patients (67%) and only 17/53 (33%) non-PTLD patients. When the low A/A IFN-gamma polymorphism was combined with EBV viral load for prediction of PTLD, PPV and NPV were 57 and 93%, respectively.
Discussion: Use of cytokine genotyping in conjunction with qPCR for EBV viral load can significantly improve the predictive value of diagnostic tests for identification of patients at high risk for PTLD.
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