Observational Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Virol. Jun 25, 2025; 14(2): 101976
Published online Jun 25, 2025. doi: 10.5501/wjv.v14.i2.101976
Micro RNAs as a potential biomarker for predicting liver fibrosis severity in hepatitis C virus affected patients
Navneet Kaur, Ravinder Garg, Chaitanya Tapasvi, Gitanjali Goyal
Navneet Kaur, Department of Biochemistry, Guru Gobind Singh Medical College and Hospital, Baba Farid University of Health Sciences, Faridkot 151203, Punjab, India
Ravinder Garg, Department of Medicine, Guru Gobind Singh Medical College and Hospital, Baba Farid University of Health Sciences, Faridkot 151203, Punjab, India
Chaitanya Tapasvi, Department of Radiodiagnosis, Guru Gobind Singh Medical College and Hospital, Baba Farid University of Health Sciences, Faridkot 151203, Punjab, India
Gitanjali Goyal, Department of Biochemistry, All India Institute of Medical Sciences, Bathinda 151005, Punjab, India
Author contributions: Kaur N contributed towards concepts, design, literature search, clinical validation, experiments, data analysis, statistical analysis, manuscript preparation, editing and revision; Garg R, Tapasvi C and Goyal G contributed towards concepts, clinical study, data analysis, manuscript review and editing.
Institutional review board statement: The project initialized after due authorization from the Institutional Ethics Committee.
Informed consent statement: All participants who granted informed consent were enrolled in the study, regardless of gender or age.
Conflict-of-interest statement: There is no conflicts of interest to declare.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement- checklist of items.
Data sharing statement: The data supporting this study are not publicly available due to institutional restrictions and confidentiality agreements. Data sharing is subject to ethical approval and restrictions to protect participant confidentiality.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Navneet Kaur, MSc, Department of Biochemistry, Guru Gobind Singh Medical College and Hospital, Baba Farid University of Health Sciences, Sadiq Road, Faridkot 151203, Punjab, India. navmann23@yahoo.com
Received: October 8, 2024
Revised: January 26, 2025
Accepted: February 20, 2025
Published online: June 25, 2025
Processing time: 262 Days and 19.3 Hours
Abstract
BACKGROUND

Hepatitis C virus (HCV) infection process of progression encompasses multiple stages, commencing with inflammation and culminating in hepatocellular cancer. Numerous invasive and non-invasive procedures exist for diagnosing chronic HCV infection. Though beneficial, invasive procedures can cause morbidity and inadequate representation of the overall degree of fibrosis. Due to these reasons, non-invasive liver fibrosis biomarkers are becoming more prevalent to diagnose and track liver fibrosis without a liver biopsy. These biomarkers can detect liver fibrosis early, improving treatment and preventing cirrhosis and liver failure. Micro ribonucleic acid (MiRNA) dysregulation causes and worsens several diseases including liver disease. MiRNAs can facilitate the diagnosis of liver fibrosis and serve as a predictive tool to enhance patient care by minimizing invasive procedures and enabling more efficient and prompt therapy.

AIM

To investigate the diagnostic effectiveness of several miRNAs (miRNA-122, miRNA-21, miRNA-199a, miRNA-155) in assessing the liver fibrosis severity in untreated HCV patients from the Indian Punjab population. We seek to identify the intricate diagnostic relationship of miRNAs with the extent of fibrosis among individuals with HCV.

METHODS

We considered 100 persons determined as HCV infected by a quantitative Real-Time Polymerase Chain Reaction examination. We employed statistical as well as probabilistic tools to ascertain the diagnostic validity of miRNAs for determining the liver fibrosis stages. We employed Bayesian Networks, to introduce a unique diagnostic paradigm for miRNAs that can be adopted as benchmark to evaluate the liver fibrosis severity in HCV cases.

RESULTS

We found that miRNAs (miR-122, miR-155 and miR-21) showed significant upregulation when compared with control and according to severity of fibrosis (P ≤ 0.05). The area under the curve for miR-122, miR-155, miR-21 and miR-199a in HCV group in relation to Liver Stiffness Measurement was calculated as 0.889, 0.933, 0.912 and 0.035 respectively. MiR-199a was downregulated according to degree of fibrosis.

CONCLUSION

Depending on the diagnostic accuracy, we have concluded that miR-122, miR-155 and miR-21 are reliable markers to detect fibrosis in Hepatitis C patients.

Keywords: Hepatitis C virus; Non-invasive biomarkers; MicroRNAs; Complex bayesian networks; Liver fibrosis; Liver diseases

Core Tip: Early liver fibrosis detection by biomarkers improves treatment and prevents cirrhosis and liver failure. We investigated various microRNAs (miRNA-122, miRNA-21, miRNA-199a, miRNA-155) to determine liver fibrosis severity in untreated Hepatitis C virus (HCV) patients. Our study examined how miRNAs affect HCV fibrosis diagnosis. We tested miRNAs for liver fibrosis stage using statistical and probabilistic approaches for 100 HCV-positive individuals. Bayesian Networks were used to develop a miRNA diagnostic relationship for HCV liver fibrosis severity. miR-122, miR-155, and miR-21 were significantly elevated relative to controls and fibrosis severity (P ≤ 0.05) whereas MiR-199a decreased with fibrosis. Diagnostically, miR-122, miR-155, and miR-21 are accurate fibrosis biomarkers.