A quantitative metabolomics profiling approach for the noninvasive assessment of liver histology in patients with chronic hepatitis C.
Clin Transl Med
; 5(1): 33, 2016 Dec.
Article
em En
| MEDLINE
| ID: mdl-27539580
ABSTRACT
BACKGROUND:
High-throughput technologies have the potential to identify non-invasive biomarkers of liver pathology and improve our understanding of basic mechanisms of liver injury and repair. A metabolite profiling approach was employed to determine associations between alterations in serum metabolites and liver histology in patients with chronic hepatitis C virus (HCV) infection.METHODS:
Sera from 45 non-diabetic patients with chronic HCV were quantitatively analyzed using (1)H-NMR spectroscopy. A metabolite profile of advanced fibrosis (METAVIR F3-4) was established using orthogonal partial least squares discriminant analysis modeling and validated using seven-fold cross-validation and permutation testing. Bioprofiles of moderate to severe steatosis (≥33 %) and necroinflammation (METAVIR A2-3) were also derived. The classification accuracy of these profiles was determined using areas under the receiver operator curves (AUROCSs) measuring against liver biopsy as the gold standard.RESULTS:
In total 63 spectral features were profiled, of which a highly significant subset of 21 metabolites were associated with advanced fibrosis (variable importance score >1 in multivariate modeling; R(2) = 0.673 and Q(2) = 0.285). For the identification of F3-4 fibrosis, the metabolite bioprofile had an AUROC of 0.86 (95 % CI 0.74-0.97). The AUROCs for the bioprofiles for moderate to severe steatosis were 0.87 (95 % CI 0.76-0.97) and for grade A2-3 inflammation were 0.73 (0.57-0.89).CONCLUSION:
This proof-of-principle study demonstrates the utility of a metabolomics profiling approach to non-invasively identify biomarkers of liver fibrosis, steatosis and inflammation in patients with chronic HCV. Future cohorts are necessary to validate these findings.
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Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article