Biomarkers are urgently required for predicting rejection so that anti-rejection treatment can be taken early to protect the allograft from irreversible damage. We hypothesized that the combination of circulating fractalkine, IFN-γ and IP-10 might serve as effective biomarkers for predicting early acute renal allograft rejection. We conducted a retrospective study of 87 subjects, who were classified into acute rejection group (ARG; n = 38) and non-rejection group (NRG; n = 49). Serum fractalkine, IFN-γ and IP-10 levels were measured by Luminex. The levels of fractalkine on day 0 and 7th day, IP-10 on 4th and 7th day, and IFN-γ on 7th day in ARG was significantly higher than that in NRG. Kaplan-Meier survival analysis highlighted the higher-levels groups of fractalkine on day 0, 4th and 7th day, IFN-γ on day 0, 1st, 4th, and 7th day and IP-10 on the 4th and 7th day in rejection-free survival probability were significantly lower than low-levels groups. ROC analyses highlight the superiority of fractalkine on day 0, IP-10 on day 0, 4th and 7th day, and IFN-γ on day 0, 1st and 7th day in prediction of acute rejection. We found the combination of fractalkine on day 0, IP-10 on 7th day and IFN-γ on 7th day had the highest AUC (0.866) for predicting rejection with a sensitivity of 86.8% and a specificity of 89.8%. Our findings demonstrated a more powerful prediction of early acute renal allograft rejection during the first month after transplantation by combination of multiple-biomarkers of fractalkine, IFN-γ and IP-10, and the results might help stratify the immunologic risk of acute allograft rejection in recipients.
Keywords: Acute Rejection; Biomarker; Chemokine; Cytokine; Renal Transplantation.
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