Literature DB >> 24329857

Cross-sectional and dynamic change of serum metabolite profiling for Hepatitis B-related acute-on-chronic liver failure by UPLC/MS.

C Y Nie1, T Han, L Zhang, Y Li, H Liu, S X Xiao, Y Li, H Kang, S Y Liu.   

Abstract

Summary Acute-on-chronic liver failure(ACLF) is an increasingly recognized entity encompassing an acute deterioration of liver function and results in the failure of one or more organs with high short-term mortality. The focus of this study was to discover noninvasive and reliable biomarkers for the diagnosis and prognosis of hepatitis B-related ACLF. Ultra-performance liquid chromatography-mass spectrometry (UPLC/MS) was used to analyse serum metabolites of 28 patients with hepatitis B-related ACLF, 35 patients with Child-Pugh A cirrhosis, 30 patients with chronic hepatitis B and 35 healthy volunteers (HS). Characteristic metabolites were screened, identified and dynamically tracked to investigate their value for diagnosis and prognosis. After comparing serum metabolic profile of hepatitis B-related ACLF and Child-Pugh A cirrhosis, 99 characteristic metabolites were selected, and 38 of them were identified. Dynamic tracking model demonstrated that 17 metabolites were related to prognosis of hepatitis B-related ACLF, and there were also 11 metabolites which improved with treatment in the survival group. The correlations between these characteristic metabolites and the model for end-stage liver disease score were strong. These observations contributed to the investigation of the mechanisms of hepatitis B-related ACLF manifestation and progression on the metabolic level, and they provided information for the identification of biomarkers for the diagnosis and prognosis of hepatitis B-related ACLF.
© 2013 John Wiley & Sons Ltd.

Entities:  

Keywords:  biomarkers; hepatitis B; liver failure; metabolomics; prognosis; serum

Mesh:

Year:  2013        PMID: 24329857     DOI: 10.1111/jvh.12122

Source DB:  PubMed          Journal:  J Viral Hepat        ISSN: 1352-0504            Impact factor:   3.728


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