Metabonomic Analysis of Urine from Chronic Unpredictable Mild Stress Rats Using Gas Chromatography-Mass Spectrometry

被引:7
作者
Zhou, Yu-Zhi [1 ]
Zheng, Xing-Yu [1 ,2 ]
Liu, Xiao-Jie [1 ,2 ]
Li, Zhen-Yu [1 ]
Gao, Xiao-Xia [1 ]
Sun, Hai-Feng [1 ,2 ]
Zhang, Li-Zeng [1 ]
Guo, Xiao-Qing [1 ]
Du, Guan-Hua [3 ]
Qin, Xue-Mei [1 ]
机构
[1] Shanxi Univ, Modern Res Ctr Tradit Chinese Med, Taiyuan 030006, Peoples R China
[2] Shanxi Univ, Coll Chem & Chem Engn, Taiyuan 030006, Peoples R China
[3] Chinese Acad Med Sci, Inst Mat Med, Beijing 100050, Peoples R China
基金
中国国家自然科学基金;
关键词
Gas chromatography/mass spectrometry; Depression; Metabonomic; Urine; Time-dependent trajectory; SOCIAL STRESS; CONSUMPTION; EXPOSURE; SUCROSE; BRAIN; MODEL;
D O I
10.1007/s10337-011-2167-3
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Depression is a prevalent complex psychiatric disorder and its pathophysiological mechanism is not yet well understood. In this study, we investigated the metabolic profiling of urine samples from chronic unpredictable mild stress (CUMS) rats to find potential disease biomarkers and research pathology of depression. Metabolome in urine was analyzed using gas chromatography/mass spectrometry (GC/MS) in conjunction with multivariate statistical techniques. The urine samples of male Sprague-Dawley rats were collected at different time points and then were derivatized by methoximation/silylation. Clear separation between the model and control group was achieved, and 15 metabolites were identified, which suggested that the depressed state may be related to neurotransmitter, energy metabolism and immunity. The time-dependent trajectory of metabolites pattern revealed that the maximum biochemical change happened on the 21st day, which was consistent with the results of behavior tests. The study suggested that the metabonomic approach could be used as a potentially powerful tool to investigate the biochemical change in certain physiopathological conditions, such as depression, as an early diagnostic means.
引用
收藏
页码:157 / 164
页数:8
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