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Research Paper|Volume 11, Issue 3|pp 1008—1018

Urinary metabolite signature in bipolar disorder patients during depressive episode

Jian-jun Chen1,3, Jing Xie5, Li Zeng3,4, Chan-juan Zhou3, Peng Zheng2,3, Peng Xie2,3
  • 1Institute of Life Sciences, Chongqing Medical University, Chongqing, China
  • 2Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 3Institute of Neuroscience, Chongqing Medical University, Chongqing, China
  • 4Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 5Department of Endocrinology and Nephrology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing, China

* * Equal contribution

Received: November 21, 2018Accepted: January 24, 2019Published: February 5, 2019
https://doi.org/10.18632/aging.101805

Copyright: © 2019 Chen 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.

Abstract

The first few episodes of bipolar disorder (BD) are highly likely to be depressive. This phenomenon causes many BD patients to be misdiagnosed as having major depression. Therefore, it is very important to correctly diagnose BD patients during depressive episode. Here, we conducted this study to identify potential biomarkers for young and middle-aged BD patients during depressive episode. Both gas chromatography-mass spectroscopy (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy were used to profile the urine samples from the recruited subjects. In total, 13 differential metabolites responsible for the discrimination between healthy controls (HCs) and patients were identified. Most differential metabolites had a close relationship with energy homeostasis. Meanwhile, a panel consisting of five differential metabolites was identified. This panel could effectively distinguish the patients from HCs with an AUC of 0.998 in the training set and 0.974 in the testing set. Our findings on one hand could be helpful in developing an objective diagnostic method for young and middle-aged BD patients during depressive episode; on the other hand could provide critical insight into the pathological mechanism of BD and the biological mechanisms responsible for the transformation of different episodes.