Research Paper Volume 10, Issue 9 pp 2252—2265

GC-MS-based metabolomics approach to diagnose depression in hepatitis B virus-infected patients with middle or old age

Lijuan Hou1, , Xiaoxia Wei1, , Ya Zhuo1, , Lei Qin2, , Fang Yang2, , Lili Zhang2, , Xinwen Song1, ,

  • 1 Department of Infectious Disease, The First Affiliated Hospital of Xinxiang Medical University, Weihu 453100, Henan, China
  • 2 Department of Gastroenterology, The First Affiliated Hospital of Xinxiang Medical University, Weihu 453100, Henan, China

Received: June 28, 2018       Accepted: August 17, 2018       Published: September 2, 2018
How to Cite

Copyright: © 2018 Hou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Depression is concomitantly presented in hepatitis B virus (HBV)-infected patients (HB). However, there is still no objective method to diagnose HBV-infected patients with depression (dHB). Therefore, in this study, a gas chromatography-mass spectrometry (GC-MS)-based metabolomic approach was employed to profile urine samples from 59 dHB and 52 HB (the training set) in order to identify urinary metabolite biomarkers for dHB. Then, 41 dHB and 35 HB (the testing set) were used to independently validate the diagnostic generalizability of these biomarkers. In total, 13 differential metabolites responsible for the discrimination between dHB and HB were identified. These differential urinary metabolites belonged mainly to Lipid metabolism and Amino acid metabolism. A panel consisting of six urinary metabolite biomarkers (ethanolamine, azelaic acid, histidine, threitol, 2,4-dihydroxypyrimidine and levulinic acid) was identified. This panel was capable of distinguishing dHB from HB with an area under the receiver operating characteristic curve (AUC) of 0.986 in the training set. Moreover, this panel could classify blinded samples from the testing set with an AUC of 0.933. These findings indicated that the GC-MS-based metabolomics approach could be a useful tool in the clinical diagnosis of dHB, and the identified biomarkers were helpful for future developing an objective diagnostic method for dHB.


Hepatitis B virus: HBV; HBV-infected patients with depression: dHB; HBV-infected patients without depression: HB; nuclear magnetic resonance: NMR; gas chromatography-mass spectrometry: GC-MS; orthogonal partial least squares discriminant analysis: OPLS-DA; receiver-operating characteristic: ROC; area under the receiver operating characteristic curve: AUC; Hamilton Depression Rating Scale: HDRS; bipolar disorder: BD; Bayesian Information Criterion: BIC.