Serum MicroRNA Transcriptomics and Acute Rejection or Recurrent Hepatitis C Virus in Human Liver Allograft Recipients: A Pilot Study. Issue 4 (11th May 2021)

• Record Type: Journal Article
• Authors: Muthukumar, Thangamani; Akat, Kemal M.; Yang, Hua; Schwartz, Joseph E.; Li, Carol; Bang, Heejung; Ben-Dov, Iddo Z.; Lee, John R.; Ikle, David; Demetris, Anthony J.; Tuschl, Thomas; Suthanthiran, Manikkam
• Is Part Of: Transplantation. Volume 106:Issue 4(2022)
• Page Start: 806
• Page End: 820
• Publication Date: 2021-05-11
• Subjects: Transplantation of organs, tissues, etc -- Periodicals; Transplantation immunology -- Periodicals; 617.95
• DOI: 10.1097/TP.0000000000003815
• Languages: English
• ISSNs: 0041-1337

Abstract

Abstract : Background: 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. Methods: 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. Results: 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. Conclusions: 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. Abstract :