期刊
LIVER INTERNATIONAL
卷 40, 期 7, 页码 1693-1700出版社
WILEY
DOI: 10.1111/liv.14474
关键词
antiviral therapy; biomarker; hepatitis B virus; inflammation; tenofovir
资金
- Gilead Sciences
Background and Aims Most patients with cirrhosis induced by chronic HBV infection experience fibrosis regression after long-term antiviral treatment, while some remain cirrhotic. Fibrosis regression is associated with lower odds of developing hepatic decompensation and hepatocellular carcinoma, but mechanisms impacting differential fibrosis regression between individuals are unclear. We asked whether soluble molecules, including serum microRNAs, could serve as biomarkers of fibrosis regression. Methods We analysed cryopreserved sera from clinical trials in which cirrhotic HBV-infected patients (baseline Ishak fibrosis score of 5-6) received 240 weeks of nucleotide analogue treatment. Liver biopsies at week 240 in these trials showed 71/96 patients (74%) had fibrosis regression (Ishak <= 4) while 25/96 (26%) remained cirrhotic (Ishak 5-6). We quantified inflammatory markers (CXCL10, soluble CD163) and miRNAs (n = 179) from serum at baseline, week 48 and week 240 of treatment in a sub-cohort of patients with (n = 14) or without (n = 14) fibrosis regression. Results CXCL10, sCD163 and miRNAs previously associated with HBV replication and inflammation decreased during treatment but did not differ based on fibrosis regression. Two miRNAs (miR-421 and miR-454-3p) had lower baseline expression in patients with subsequent fibrosis regression. In all, 27 miRNAs differed at week 240 and had higher expression in patients with fibrosis regression (eg miR-199a-3p, miR-423-3p, miR-142-3p, miR-let-7d-5p). Several miRNAs (miR-141-3p, let-7d-5p) that correlated with regression have previously been implicated in the pathophysiology of non-alcoholic steatohepatitis. Conclusions In cirrhotic patients with chronic HBV infection treated with antiviral therapy, serum miRNAs have differential expression based on fibrosis regression, suggesting potential utility as biomarkers.
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