The metabolic fingerprint of chronic hepatitis C progression: Metabolome shifts and cutting‐edge diagnostic options

Author:

Deep Amar12ORCID,Swaroop Suchit2,Dubey Durgesh3ORCID,Rawat Atul3ORCID,Verma Ajay3,Baisya Bikash3ORCID,Parihar Rashmi3,Goel Amit4,Rungta Sumit1ORCID

Affiliation:

1. Department of Medical Gastroenterology KGMU Lucknow India

2. Experimental and Public Health Laboratory, Department of Zoology Lucknow University Lucknow India

3. Centre of Biomedical Research Lucknow India

4. Department of Medical Gastroenterology SGPGIMS Lucknow India

Abstract

AbstractHepatitis C virus infection causes chronic diseases such as cirrhosis and hepatocellular carcinoma. Metabolomics research has been shown to be linked to pathophysiologic pathways in liver illnesses. The aim of this study was to investigate the serum metabolic profile of patients with chronic hepatitis C (CHC) infection and to identify underlying mechanisms as well as potential biomarkers associated with the disease. Nuclear magnetic resonance (NMR) was used to evaluate the sera of 83 patients with CHC virus and 52 healthy control volunteers (NMR). Then, multivariate statistical analysis was used to find distinguishing metabolites between the two groups. Sixteen out of 40 metabolites including include 3‐HB, betaine, carnitine, creatinine, fucose, glutamine, glycerol, isopropanol, lysine, mannose, methanol, methionine, ornithine, proline, serine, and valine—were shown to be significantly different between the CHC and normal control (NC) groups (variable importance in projection >1 and p < 0.05). All the metabolic perturbations in this disease are associated with pathways of Glycine, serine, and threonine metabolism, glycerolipid metabolism, arginine and proline metabolism, aminoacyl‐tRNA biosynthesis, cysteine and methionine metabolism, alanine, aspartate, and glutamate metabolism. Multivariate statistical analysis constructed using these expressed metabolites showed CHC patients can be discriminated from NCs with high sensitivity (90%) and specificity (99%). The metabolomics approach may expand the diagnostic armamentarium for patients with CHC while contributing to a comprehensive understanding of disease mechanisms.

Funder

University Grants Commission

Publisher

Wiley

Subject

Molecular Biology,Structural Biology

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