Metabolomics in chronic hepatitis C: Decoding fibrosis grading and underlying pathways

Abstract

BACKGROUND Chronic Hepatitis C (CHC) affects 71 million people globally and leads to liver issues such as fibrosis, cirrhosis, cancer, and death. A better understanding and prognosis of liver involvement are vital to reduce morbidity and mortality. The accurate identification of the fibrosis stage is crucial for making treatment decisions and predicting outcomes. Tests used to grade fibrosis include histological analysis and imaging but have limitations. Blood markers such as molecular biomarkers can offer valuable insights into fibrosis. AIM To identify potential biomarkers that might stratify these lesions and add information about the molecular mechanisms involved in the disease. METHODS Plasma samples were collected from 46 patients with hepatitis C and classified into fibrosis grades F1 (n = 13), F2 (n = 12), F3 (n = 6), and F4 (n = 15). To ensure that the identified biomarkers were exclusive to liver lesions (CHC fibrosis), healthy volunteer participants (n = 50) were also included. An untargeted metabolomic technique was used to analyze the plasma metabolites using mass spectrometry and database verification. Statistical analyses were performed to identify differential biomarkers among groups. RESULTS Six differential metabolites were identified in each grade of fibrosis. This six-metabolite profile was able to establish a clustering tendency in patients with the same grade of fibrosis; thus, they showed greater efficiency in discriminating grades. CONCLUSION This study suggests that some of the observed biomarkers, once validated, have the potential to be applied as prognostic biomarkers. Furthermore, it suggests that liquid biopsy analyses of plasma metabolites are a good source of molecular biomarkers capable of stratifying patients with CHC according to fibrosis grade.