Integrated metabolomics and lipidomics profiling of hippocampus reveal metabolite biomarkers in a rat model of chronic unpredictable mild stress-induced depression

对海马进行整合代谢组学和脂质组学分析,揭示了慢性不可预测轻度应激诱导抑郁症大鼠模型中的代谢物生物标志物。

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Abstract

BACKGROUND: Prolonged exposure to stress triggers depression, threatening human health. Thus, to thoroughly understand the underlying pathophysiologic mechanism of chronic unpredictable mild stress (CUMS)-induced depression is urgently needed. Ultra-high-performance liquid chromatography-mass spectroscopy (UPLC-MS)-based lipidomic and metabolomic approaches has been used for discovering metabolite biomarkers to develop new diagnostic and therapeutic means. Thus, our study aimed to conduct integrated metabolomics and lipidomics to identify metabolites and lipids biomarkers in the hippocampus in rat models of CUMS-induced depression. METHODS: Twelve eight-week-old male Sprague-Dawley rats (weight 210±30 g) were randomly distributed to one of the following two groups (n=6): control or CUMS. Established UPLC-MS-based lipidomic and metabolomic approaches were used to determine the metabolites and lipids in the hippocampus of rats. SICMA-P and GraphPad software were performed to discover potential metabolites and lipids biomarkers in the hippocampus of rats between the two groups. RESULTS: A total of 35 potential metabolites and 171 lipids were identified and found to be mainly related to amino acid and lipid metabolism. These metabolites were involved in different metabolic pathways and connected to each other, which might participate in the occurrence and development of depression. CONCLUSIONS: Our findings underlined the metabolites, lipids and metabolic pathways that were changed in the hippocampus in CUMS compared to the controls, providing novel insights in the metabolism in the hippocampus of rats and revealing the new lipid-related targets.

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