Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine and Department of Transplantation Medicine, New York Presbyterian-Weill Cornell Medicine, New York, NY.
Laboratory of RNA Molecular Biology, The Rockefeller University, New York, NY.
Transplantation. 2022 Apr 1;106(4):806-820. doi: 10.1097/TP.0000000000003815.
Acute rejection (AR) and recurrent hepatitis C virus (R-HCV) are significant complications in liver allograft recipients. Noninvasive diagnosis of intragraft pathologies may improve their management.
We performed small RNA sequencing and microRNA (miRNA) microarray profiling of RNA from sera matched to liver allograft biopsies from patients with nonimmune, nonviral (NINV) native liver disease. Absolute levels of informative miRNAs in 91 sera matched to 91 liver allograft biopsies were quantified using customized real-time quantitative PCR (RT-qPCR) assays: 30 biopsy-matched sera from 26 unique NINV patients and 61 biopsy-matched sera from 41 unique R-HCV patients. The association between biopsy diagnosis and miRNA abundance was analyzed by logistic regression and calculating the area under the receiver operating characteristic curve.
Nine miRNAs-miR-22, miR-34a, miR-122, miR-148a, miR-192, miR-193b, miR-194, miR-210, and miR-885-5p-were identified by both sRNA-seq and TLDA to be associated with NINV-AR. Logistic regression analysis of absolute levels of miRNAs and goodness-of-fit of predictors identified a linear combination of miR-34a + miR-210 (P < 0.0001) as the best statistical model and miR-122 + miR-210 (P < 0.0001) as the best model that included miR-122. A different linear combination of miR-34a + miR-210 (P < 0.0001) was the best model for discriminating NINV-AR from R-HCV with intragraft inflammation, and miR-34a + miR-122 (P < 0.0001) was the best model for discriminating NINV-AR from R-HCV with intragraft fibrosis.
Circulating levels of miRNAs, quantified using customized RT-qPCR assays, may offer a rapid and noninvasive means of diagnosing AR in human liver allografts and for discriminating AR from intragraft inflammation or fibrosis due to R-HCV.
急性排斥(AR)和复发性丙型肝炎病毒(R-HCV)是肝移植受者的重要并发症。肝移植物内病变的无创诊断可能改善其管理。
我们对来自非免疫、非病毒(NINV)原发性肝病患者的血清与肝移植活检相匹配的 RNA 进行了小 RNA 测序和 microRNA(miRNA)微阵列分析。使用定制的实时定量 PCR(RT-qPCR)检测 91 份与 91 份肝移植活检相匹配的血清中 30 份活检匹配的血清来自 26 位独特的 NINV 患者和 61 份活检匹配的血清来自 41 位独特的 R-HCV 患者中信息性 miRNA 的绝对水平:来自独特 NINV 患者的血清和 61 份活检匹配的血清来自 41 位独特的 R-HCV 患者。通过逻辑回归和计算接收者操作特征曲线下的面积来分析活检诊断与 miRNA 丰度之间的关联。
通过 sRNA-seq 和 TLDA 鉴定出与 NINV-AR 相关的 9 种 miRNA-miR-22、miR-34a、miR-122、miR-148a、miR-192、miR-193b、miR-194、miR-210 和 miR-885-5p。绝对水平的 miRNA 和预测因子的拟合优度的逻辑回归分析确定 miR-34a+miR-210 的线性组合(P<0.0001)作为最佳统计模型,miR-122+miR-210(P<0.0001)作为包含 miR-122 的最佳模型。miR-34a+miR-210 的另一个线性组合(P<0.0001)是区分伴有肝内炎症的 NINV-AR 与 R-HCV 的最佳模型,而 miR-34a+miR-122(P<0.0001)是区分伴有肝内纤维化的 NINV-AR 与 R-HCV 的最佳模型。
使用定制的 RT-qPCR 检测方法定量检测循环 miRNA 水平可能为诊断人类肝移植物中的 AR 提供一种快速、无创的方法,并有助于区分 AR 与 R-HCV 引起的肝内炎症或纤维化。