Duan Lihua, Fan Rong, Li Teng, Yang Zhaoyu, Hu En, Yu Zhe, Tian Jing, Luo Weikang, Zhang Chunhu
Department of Integrated Traditional Chinese and Western Medicine, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China.
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
Front Psychiatry. 2022 Mar 15;13:815211. doi: 10.3389/fpsyt.2022.815211. eCollection 2022.
Depressive disorder is the leading cause of disability and suicidality worldwide. Metabolites are considered indicators and regulators of depression. However, the pathophysiology of the prefrontal cortex (PFC) in depression remains unclear.
A chronic unpredictable mild stress (CUMS) model and a maturation rodent model of depression was used to investigate metabolic changes in the PFC. Eighteen male Sprague-Dawley rats were randomly divided into CUMS and control groups. The sucrose preference test (SPT) and forced swimming test (FST) were employed to evaluate and record depression-associated behaviors and changes in body weight (BW). High-performance liquid chromatography-tandem mass spectrometry was applied to test metabolites in rat PFC. Furthermore, principal component analysis and orthogonal partial least-squares discriminant analysis were employed to identify differentially abundant metabolites. Metabolic pathways were analyzed using MetaboAnalyst. Finally, a metabolite-protein interaction network was established to illustrate the function of differential metabolites.
SPT and FST results confirmed successful establishment of the CUMS-induced depression-like behavior model in rats. Five metabolites, including 1-methylnicotinamide, 3-methylhistidine, acetylcholine, glycerophospho-N-palmitoyl ethanolamine, α-D-mannose 1-phosphate, were identified as potential biomarkers of depression. Four pathways changed in the CUMS group. Metabolite-protein interaction analysis revealed that 10 pathways play roles in the metabolism of depression.
Five potential biomarkers were identified in the PFC and metabolite-protein interactions associated with metabolic pathophysiological processes were explored using the CUMS model. The results of this study will assist physicians and scientists in discovering potential diagnostic markers and novel therapeutic targets for depression.
抑郁症是全球致残和自杀的主要原因。代谢物被认为是抑郁症的指标和调节因子。然而,抑郁症中前额叶皮质(PFC)的病理生理学仍不清楚。
采用慢性不可预测轻度应激(CUMS)模型和抑郁症成熟啮齿动物模型来研究PFC中的代谢变化。18只雄性Sprague-Dawley大鼠随机分为CUMS组和对照组。采用蔗糖偏好试验(SPT)和强迫游泳试验(FST)来评估和记录与抑郁相关的行为及体重(BW)变化。应用高效液相色谱-串联质谱法检测大鼠PFC中的代谢物。此外,采用主成分分析和正交偏最小二乘判别分析来鉴定差异丰富的代谢物。使用MetaboAnalyst分析代谢途径。最后,建立代谢物-蛋白质相互作用网络以阐明差异代谢物的功能。
SPT和FST结果证实成功建立了CUMS诱导的大鼠抑郁样行为模型。包括1-甲基烟酰胺、3-甲基组氨酸、乙酰胆碱、甘油磷酸-N-棕榈酰乙醇胺、α-D-甘露糖1-磷酸在内的5种代谢物被确定为抑郁症的潜在生物标志物。CUMS组有4条代谢途径发生改变。代谢物-蛋白质相互作用分析表明有10条途径在抑郁症代谢中起作用。
在PFC中鉴定出5种潜在生物标志物,并使用CUMS模型探索了与代谢病理生理过程相关的代谢物-蛋白质相互作用。本研究结果将有助于医生和科学家发现抑郁症的潜在诊断标志物和新的治疗靶点。