Dual Metabolomic Platforms Identified a Novel Urinary Metabolite Signature for Hepatitis B Virus-Infected Patients with Depression

• Published in: Diabetes, metabolic syndrome and obesity Vol. 13; pp. 1677 - 1683
• Main Authors: Xie, Jing, Chen, Chang, Hou, Li-Juan, Zhou, Chan-Juan, Fang, Liang, Chen, Jian-Jun
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2020; Taylor & Francis Ltd; Dove; Dove Medical Press
• Subjects: Acids; biomarker; Biomarkers; Chromatography; Data analysis; depression; Depression (Mood disorder); Drug use; Hepatitis; Hepatitis B; Hepatitis B virus; HIV; Human immunodeficiency virus; Laboratories; Mass spectrometry; Mental depression; Mental disorders; Metabolism; Metabolites; metabolomics; NMR; Nuclear magnetic resonance; Original Research; Regression analysis; Spectrum analysis; Urine; China; depression; biomarker; metabolomics; hepatitis B virus
• ISSN: 1178-7007; 1178-7007
• DOI: 10.2147/DMSO.S251034

Depression could make the treatment outcome worse. However, up to now, no objective methods were developed to diagnose depression in hepatitis B virus (HBV)-infected patients. Therefore, the dual metabolomic platforms were used here to identify potential biomarkers for diagnosing HBV-infected patients with depression (dHB). Both gas chromatography-mass spectrometry-based and nuclear magnetic resonance-based metabolomic platforms were used to conduct urine metabolic profiling of dHB subjects and HBV-infected patients without depression (HB). Orthogonal partial least-squares discriminant analysis was used to identify the differential metabolites between dHB subjects and HB subjects, and the step-wise logistic regression analysis was used to identify potential biomarkers. In total, 21 important metabolites responsible for distinguishing dHB subjects from HB subjects were identified. Meanwhile, seven potential biomarkers (α-ydroxyisobutyric acid, hippuric acid, azelaic acid, isobutyric acid, malonic acid, levulinic acid, and phenylacetylglycine) were viewed as potential biomarkers. The simplified biomarker panel consisting of these seven metabolites had an excellent diagnostic performance in discriminating dHB subjects from HB subjects. Moreover, this panel could yield a higher accuracy in separating dHB subjects from HB subjects than our previous panels (identified by single metabolomic platform) did. These results suggested that the dual metabolomic platforms could yield a better urinary biomarker panel for dHB subjects than any single metabolomic platform did, and our results could be helpful for developing an objective method in future to diagnose depression in HBV-infected patients.