| Literature DB >> 26168936 |
Jian-Jun Chen1, Chan-Juan Zhou1, Zhao Liu2, Yu-Ying Fu2, Peng Zheng2, De-Yu Yang1, Qi Li2, Jun Mu2, You-Dong Wei2, Jing-Jing Zhou2, Hua Huang2, Peng Xie1,2.
Abstract
Bipolar disorder (BD) is a complex debilitating mental disorder that is often misdiagnosed as major depressive disorder (MDD). Therefore, a large percentage of BD subjects are incorrectly treated with antidepressants in clinical practice. To address this challenge, objective laboratory-based tests are needed to discriminate BD from MDD patients. Here, a combined gas chromatography-mass spectrometry (GC-MS)-based and nuclear magnetic resonance (NMR) spectroscopic-based metabonomic approach was performed to profile urine samples from 76 MDD and 43 BD subjects (training set) to identify the differential metabolites. Samples from 126 healthy controls were included as metabolic controls. A candidate biomarker panel was identified by further analyzing these differential metabolites. A testing set of, 50 MDD and 28 BD subjects was then used to independently validate the diagnostic efficacy of the identified panel using an area under the receiver operating characteristic curve (AUC). A total of 20 differential metabolites responsible for the discrimination between MDD and BD subjects were identified. A panel consisting of six candidate urinary metabolite biomarkers (propionate, formate, (R*,S*)2,3-dihydroxybutanoic acid, 2,4-dihydroxypyrimidine, phenylalanine, and β-alanine) was identified. This panel could distinguish BD from MDD subjects with an AUC of 0.913 and 0.896 in the training and testing sets, respectively. These results reveal divergent urinary metabolic phenotypes between MDD and BD. The identified urinary biomarkers can aid in the future development of an objective laboratory-based diagnostic test for distinguishing BD from MDD patients.Entities:
Keywords: BD; GC−MS; MDD; NMR; biomarker; bipolar disorder; gas chromatography−mass spectrometry; major depressive disorder; metabonomic; nuclear magnetic resonance
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Year: 2015 PMID: 26168936 DOI: 10.1021/acs.jproteome.5b00434
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466