4.7 Article

Divergent Urinary Metabolic Phenotypes between Major Depressive Disorder and Bipolar Disorder Identified by a Combined GC-MS and NMR Spectroscopic Metabonomic Approach

期刊

JOURNAL OF PROTEOME RESEARCH
卷 14, 期 8, 页码 3382-3389

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b00434

关键词

bipolar disorder; BD; major depressive disorder; MDD; metabonomic; biomarker; nuclear magnetic resonance; NMR; gas chromatography-mass spectrometry; GC-MS

资金

  1. Natural Science Foundation Project of China [31271189, 81200899, 31300917, 81401140]
  2. National Basic Research Program of China (973 Program) [2009CB918300]
  3. Chongqing Science & Technology Commission [cstc2014jcyjA10102]

向作者/读者索取更多资源

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 beta-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.

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