The purpose of this study was to evaluate T-cell immunity markers using serial post-transplantation monitoring of cytokine-producing cells during the first post-transplant months for the prediction of acute rejection and potentially chronic rejection of kidney allograft. We followed 57 kidney allograft recipients for meanly 3 years post-transplantation. Blood samples were collected pre-transplant, 2, 4 and 12 weeks post-transplant. The frequencies of IL-10-, IL-17- and IFN-γ-producing cells were determined in all time-points using ELISPOT assay. The results of ELISpot monitoring and levels of IL-23 and TGF-β were compared between recipients with acute (n = 12) or chronic rejection episodes and patients with stable graft function (n = 45). In all post-transplant time-points, significantly high frequencies of IFN-γ- and IL-17-producing cells and low frequency of IL-10-producing cells were observed in rejection group versus patients with stable graft function (P<0.0001). TheROCcurve analysis for determining the reliability of cytokine-producing cells for the prediction of acute rejection revealed that AUC was 0.046 for IL-10 (P<0.001), 0.927 for IL-17 (P<0.001) and 0.929 for INF-γ-producing cells (P<0.001). Our results indicate that analyzing the frequencies of INF-γ/IL-10/IL-17-producing cells may define a reliable panel for the prediction of acute rejection within the first post-transplant year which could also be applicable for the prediction of chronic rejection episodes.

中文翻译：

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酶联免疫吸附斑点（ELISpot）监测细胞因子产生细胞，以预测肾移植患者的急性排斥反应。

这项研究的目的是在移植后的头几个月中，使用连续的移植后细胞因子生成细胞监测来评估T细胞免疫标记，以预测肾移植的急性排斥反应和潜在的慢性排斥反应。我们追踪了57位同种异体肾移植患者，平均移植后3年。在移植前，移植后2、4和12周收集血样。使用ELISPOT测定法在所有时间点测定产生IL-10-，IL-17和IFN-γ的细胞的频率。的酶联免疫斑点法监测和IL-23和TGF-β的水平的结果与急性（收件人之间进行比较Ñ = 12）或慢性排斥反应和患者稳定的移植物功能（Ñ= 45）。与移植物稳定的患者相比，排斥组在所有移植后时间点均观察到产生IFN-γ和IL-17的细胞明显较高的频率和产生IL-10的细胞较低的频率（P <0.0001） 。ROC曲线分析用于确定产生细胞因子的细胞对急性排斥反应的预测可靠性，结果表明，IL-10的AUC为0.046（P <0.001），IL-17的AUC为0.927（P <0.001），产生INF-γ的AUC为0.929细胞（P<0.001）。我们的结果表明，分析产生INF-γ/ IL-10 / IL-17的细胞的频率可能为预测移植后第一年内的急性排斥反应定义一个可靠的面板，这也可能适用于预测慢性拒绝情节。