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Metabolic phenotyping for enhanced mechanistic stratification of chronic hepatitis C-induced liver fibrosis

Metabolic phenotyping for enhanced mechanistic stratification of chronic hepatitis C-induced liver fibrosis
Metabolic phenotyping for enhanced mechanistic stratification of chronic hepatitis C-induced liver fibrosis

OBJECTIVES: The invasive nature of biopsy alongside issues with categorical staging and sampling error has driven research into noninvasive biomarkers for the assessment of liver fibrosis in order to stratify and personalize treatment of patients with liver disease. Here, we sought to determine whether a metabonomic approach could be used to identify signatures reflective of the dynamic, pathological metabolic perturbations associated with fibrosis in chronic hepatitis C (CHC) patients.

METHODS: Plasma nuclear magnetic resonance (NMR) spectral profiles were generated for two independent cohorts of CHC patients and healthy controls (n=50 original and n=63 validation). Spectral data were analyzed and significant discriminant biomarkers associated with fibrosis (as graded by enhanced liver fibrosis (ELF) and METAVIR scores) identified using orthogonal projection to latent structures (O-PLS).

RESULTS: Increased severity of fibrosis was associated with higher tyrosine, phenylalanine, methionine, citrate and, very-low-density lipoprotein (vLDL) and lower creatine, low-density lipoprotein (LDL), phosphatidylcholine, and N-Acetyl-α1-acid-glycoprotein. Although area under the receiver operator characteristic curve analysis revealed a high predictive performance for classification based on METAVIR-derived models, <40% of identified biomarkers were validated in the second cohort. In the ELF-derived models, however, over 80% of the biomarkers were validated.

CONCLUSIONS: Our findings suggest that modeling against a continuous ELF-derived score of fibrosis provides a more robust assessment of the metabolic changes associated with fibrosis than modeling against the categorical METAVIR score. Plasma metabolic phenotypes reflective of CHC-induced fibrosis primarily define alterations in amino-acid and lipid metabolism, and hence identify mechanistically relevant pathways for further investigation as therapeutic targets.

Adult, Biomarkers/blood, Female, Hepatitis C, Chronic/blood, Humans, Lipid Metabolism, Liver Cirrhosis/blood, Magnetic Resonance Spectroscopy, Male, Middle Aged, Phenotype, Severity of Illness Index
0002-9270
159-169
Sands, Caroline J
d6b1fb57-9763-4a9c-8395-e6e93b0d88ae
Guha, Indra N
a3dddb81-7413-4309-b85d-afa33b8d3fce
Kyriakides, Michael
598aaf0d-78e1-40f9-b78c-2156ea295022
Wright, Mark
43325ef9-3459-4c75-b3bf-cf8d8dac2a21
Beckonert, Olaf
ce45a902-89a6-418e-b48f-9112c567caa0
Holmes, Elaine
d3b92a6b-1c3f-4758-b653-ba35afd3f57d
Rosenberg, William M
145ebec3-ffb6-45e7-8711-aa520ed42f55
Coen, Muireann
a4ad37ca-ea2d-4353-a09b-098159e1e273
Sands, Caroline J
d6b1fb57-9763-4a9c-8395-e6e93b0d88ae
Guha, Indra N
a3dddb81-7413-4309-b85d-afa33b8d3fce
Kyriakides, Michael
598aaf0d-78e1-40f9-b78c-2156ea295022
Wright, Mark
43325ef9-3459-4c75-b3bf-cf8d8dac2a21
Beckonert, Olaf
ce45a902-89a6-418e-b48f-9112c567caa0
Holmes, Elaine
d3b92a6b-1c3f-4758-b653-ba35afd3f57d
Rosenberg, William M
145ebec3-ffb6-45e7-8711-aa520ed42f55
Coen, Muireann
a4ad37ca-ea2d-4353-a09b-098159e1e273

Sands, Caroline J, Guha, Indra N, Kyriakides, Michael, Wright, Mark, Beckonert, Olaf, Holmes, Elaine, Rosenberg, William M and Coen, Muireann (2015) Metabolic phenotyping for enhanced mechanistic stratification of chronic hepatitis C-induced liver fibrosis. The American journal of gastroenterology, 110 (1), 159-169. (doi:10.1038/ajg.2014.370).

Record type: Article

Abstract

OBJECTIVES: The invasive nature of biopsy alongside issues with categorical staging and sampling error has driven research into noninvasive biomarkers for the assessment of liver fibrosis in order to stratify and personalize treatment of patients with liver disease. Here, we sought to determine whether a metabonomic approach could be used to identify signatures reflective of the dynamic, pathological metabolic perturbations associated with fibrosis in chronic hepatitis C (CHC) patients.

METHODS: Plasma nuclear magnetic resonance (NMR) spectral profiles were generated for two independent cohorts of CHC patients and healthy controls (n=50 original and n=63 validation). Spectral data were analyzed and significant discriminant biomarkers associated with fibrosis (as graded by enhanced liver fibrosis (ELF) and METAVIR scores) identified using orthogonal projection to latent structures (O-PLS).

RESULTS: Increased severity of fibrosis was associated with higher tyrosine, phenylalanine, methionine, citrate and, very-low-density lipoprotein (vLDL) and lower creatine, low-density lipoprotein (LDL), phosphatidylcholine, and N-Acetyl-α1-acid-glycoprotein. Although area under the receiver operator characteristic curve analysis revealed a high predictive performance for classification based on METAVIR-derived models, <40% of identified biomarkers were validated in the second cohort. In the ELF-derived models, however, over 80% of the biomarkers were validated.

CONCLUSIONS: Our findings suggest that modeling against a continuous ELF-derived score of fibrosis provides a more robust assessment of the metabolic changes associated with fibrosis than modeling against the categorical METAVIR score. Plasma metabolic phenotypes reflective of CHC-induced fibrosis primarily define alterations in amino-acid and lipid metabolism, and hence identify mechanistically relevant pathways for further investigation as therapeutic targets.

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More information

Published date: 1 January 2015
Keywords: Adult, Biomarkers/blood, Female, Hepatitis C, Chronic/blood, Humans, Lipid Metabolism, Liver Cirrhosis/blood, Magnetic Resonance Spectroscopy, Male, Middle Aged, Phenotype, Severity of Illness Index

Identifiers

Local EPrints ID: 481059
URI: http://eprints.soton.ac.uk/id/eprint/481059
ISSN: 0002-9270
PURE UUID: d0a4f8f2-217a-4185-89e7-5d0d7c031bab

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Date deposited: 15 Aug 2023 16:43
Last modified: 17 Mar 2024 02:13

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Contributors

Author: Caroline J Sands
Author: Indra N Guha
Author: Michael Kyriakides
Author: Mark Wright
Author: Olaf Beckonert
Author: Elaine Holmes
Author: William M Rosenberg
Author: Muireann Coen

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