Cao Bing, Liu Yuan-Li, Wang Na, Huang Yan, Lu Chen-Xuan, Li Qian-Ying, Zou Hong-Yu
Key Laboratory of Cognition and Personality, Faculty of Psychology, Ministry of Education, Southwest University, Chongqing 400715, China.
Department of Laboratory Medicine, Jiulongpo District Psychiatric Health Center of Chongqing, Chongqing 401329, China.
World J Psychiatry. 2025 May 19;15(5):102618. doi: 10.5498/wjp.v15.i5.102618.
BACKGROUND: Major depressive disorder (MDD) is characterized by persistent depressed mood and cognitive symptoms. This study aimed to discover biomarkers for MDD, explore its pathological mechanisms, and examine the associations of the identified biomarkers with clinical and psychological variables. AIM: To discover candidate biomarkers for MDD identification and provide insight into the pathological mechanism of MDD. METHODS: The current study adopted a single-center cross-sectional case-control design. Serum samples were obtained from 100 individuals diagnosed with MDD and 97 healthy controls (HCs) aged between 18 to 60 years. Metabolomics was performed on an Ultimate 3000 UHPLC system coupled with Q-Exactive MS (Thermo Scientific). The online software Metaboanalyst 6.0 was used to process and analyze the acquired raw data of peak intensities from the instrument. RESULTS: The study included 100 MDD patients and 97 HCs. Metabolomic profiling identified 35 significantly different metabolites (, cortisol, sebacic acid, and L-glutamic acid). Receiver operating characteristic curve analysis highlighted 8-HETE, 10-HDoHE, cortisol, 12-HHTrE, and 10-hydroxydecanoic acid as top diagnostic biomarkers for MDD. Significant correlations were found between metabolites (, some lipids, steroids, and amino acids) and clinical and psychological variables. CONCLUSION: Our study reported metabolites (some lipids, steroids, amino acids, carnitines, and alkaloids) responsible for discriminating MDD patients and HCs. This metabolite profile may enable the development of a laboratory-based diagnostic test for MDD. The mechanisms underlying the association between psychological or clinical variables and differential metabolites deserve further exploration.
背景:重度抑郁症(MDD)的特征是持续的情绪低落和认知症状。本研究旨在发现MDD的生物标志物,探索其病理机制,并研究已确定的生物标志物与临床和心理变量之间的关联。 目的:发现用于识别MDD的候选生物标志物,并深入了解MDD的病理机制。 方法:本研究采用单中心横断面病例对照设计。从100名年龄在18至60岁之间被诊断为MDD的个体和97名健康对照(HCs)中获取血清样本。代谢组学分析在与Q-Exactive MS(赛默飞世尔科技)联用的Ultimate 3000超高效液相色谱系统上进行。使用在线软件Metaboanalyst 6.0处理和分析从仪器获取的原始峰强度数据。 结果:该研究纳入了100名MDD患者和97名HCs。代谢组学分析确定了35种显著不同的代谢物(如皮质醇、癸二酸和L-谷氨酸)。受试者工作特征曲线分析突出显示8-羟基二十碳四烯酸(8-HETE)、10-羟基二十二碳六烯酸(10-HDoHE)、皮质醇、12-羟基六氢番茄红素(12-HHTrE)和10-羟基癸酸为MDD的顶级诊断生物标志物。发现代谢物(如一些脂质、类固醇和氨基酸)与临床和心理变量之间存在显著相关性。 结论:我们的研究报告了可区分MDD患者和HCs的代谢物(一些脂质、类固醇、氨基酸、肉碱和生物碱)。这种代谢物谱可能有助于开发基于实验室的MDD诊断测试。心理或临床变量与差异代谢物之间关联的潜在机制值得进一步探索。
World J Psychiatry. 2025-5-19
Front Psychiatry. 2022-2-21
Medicine (Baltimore). 2021-2-26
Front Psychiatry. 2022-12-14
Front Psychiatry. 2023-12-4
J Cachexia Sarcopenia Muscle. 2023-12
Adv Sci (Weinh). 2023-6
Arch Biochem Biophys. 2023-3-15