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Serum micro RNA s as predictors for liver fibrosis staging in hepatitis C virus‐associated chronic liver disease patients
Author(s) -
Shaker O. G.,
Senousy M. A.
Publication year - 2017
Publication title -
journal of viral hepatitis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.329
H-Index - 100
eISSN - 1365-2893
pISSN - 1352-0504
DOI - 10.1111/jvh.12696
Subject(s) - cirrhosis , fibrosis , medicine , liver disease , gastroenterology , receiver operating characteristic , genotype , hepatitis c virus , microrna , hepatic fibrosis , biomarker , chronic liver disease , downregulation and upregulation , stage (stratigraphy) , virus , immunology , biology , gene , biochemistry , paleontology
Summary Accurate staging of liver fibrosis is important for clinical decision making and personalized management. Liver fibrosis is influenced by patients’ genomics, including IFNL 3 genotype and micro RNA expression. However, incorporating micro RNA s into fibrosis prediction algorithms has not been investigated. We examined the potential of eight selected serum micro RNA s; miR‐122, miR‐126, miR‐129, miR‐199a, miR‐155, miR‐203a, miR‐221, and miR‐223 as non‐invasive biomarkers to stage liver fibrosis in HCV ‐associated chronic liver disease ( HCV ‐ CLD ). 145 Egyptian HCV ‐ CLD patients were divided according to Metavir fibrosis scores. Micro RNA s and IFNL 3 rs12979860 genotype were assayed by RT ‐ qPCR and allelic discrimination techniques, respectively. Serum miR‐122 was downregulated, whereas miR‐203a and miR‐223 were upregulated in significant fibrosis (≥F2) compared with no/mild fibrosis (F0‐F1). Serum miR‐126, miR‐129, miR‐203a, and miR‐223 were upregulated in severe fibrosis (≥F3) and cirrhosis (F4) compared with F0‐F2 and F0‐F3, respectively. miR‐221 was upregulated in ≥F3, but unchanged in F4. miR‐155, miR‐199a, and IFNL 3 rs12979860 genotype were not significantly different in all comparisons. Differentially expressed serum micro RNA s discriminated ≥F2, ≥F3, and F4 by receiver‐operating‐characteristic analysis. Multivariate logistic analysis revealed a model combining miR‐129, miR‐223, AST , and platelet count with high diagnostic accuracy for ≥F3 ( AUC =0.91). The model also discriminated F4 ( AUC =0.96) and ≥F2 ( AUC =0.783), and was superior to APRI and FIB ‐4 in discriminating ≥F3 and F4, but not ≥F2. In conclusion, combining serum micro RNA s with baseline predictors could serve as a new non‐invasive algorithm for staging HCV ‐associated liver fibrosis. Additional studies are required to confirm this model and test its significance in liver fibrosis of other etiologies.