Circulating MicroRNAs: Dynamic Markers of Liver Transplant Injury
| Autor: | Valeria R Mas, Elissa Bardhi, Marina Berenguer |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Graft Rejection
Transplantation business.industry 030232 urology & nephrology MEDLINE Pilot Projects Hepatitis C Chronic Bioinformatics Allografts Article Liver Transplantation 03 medical and health sciences Circulating MicroRNA MicroRNAs 0302 clinical medicine Text mining Recurrence Medicine Humans business Transcriptome Biomarkers 030215 immunology |
| Zdroj: | Transplantation r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe instname |
| ISSN: | 0041-1337 |
| Popis: | 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 (P0.0001) as the best statistical model and miR-122 + miR-210 (P0.0001) as the best model that included miR-122. A different linear combination of miR-34a + miR-210 (P0.0001) was the best model for discriminating NINV-AR from R-HCV with intragraft inflammation, and miR-34a + miR-122 (P0.0001) 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. |
| Databáze: | OpenAIRE |
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