蛋白质组学
代谢组学
医学
重性抑郁障碍
脂质代谢
生物信息学
计算生物学
炎症
生物
内科学
生物化学
精神科
认知
基因
作者
Siwen Gui,Yiyun Liu,Xiaogang Zhong,Xinyu Liu,Peng Zheng,Juncai Pu,Jian Zhou,Jianjun Chen,Libo Zhao,Lanxiang Liu,Guowang Xu,Peng Xie
摘要
INTRODUCTION: Major depressive disorder (MDD) is a highly prevalent mental disorder affecting millions of people worldwide. However, a clear causative etiology of MDD remains unknown. In this study, we aimed to identify critical protein alterations in plasma from patients with MDD and integrate our proteomics and previous metabolomics data to reveal significantly perturbed pathways in MDD. An isobaric tag for relative and absolute quantification (iTRAQ)-based quantitative proteomics approach was conducted to compare plasma protein expression between patients with depression and healthy controls (CON). METHODS: For integrative analysis, Ingenuity Pathway Analysis software was used to analyze proteomics and metabolomics data and identify potential relationships among the differential proteins and metabolites. RESULTS: A total of 74 proteins were significantly changed in patients with depression compared with those in healthy CON. Bioinformatics analysis of differential proteins revealed significant alterations in lipid transport and metabolic function, including apolipoproteins (APOE, APOC4 and APOA5), and the serine protease inhibitor. According to canonical pathway analysis, the top five statistically significant pathways were related to lipid transport, inflammation and immunity. CONCLUSION: Causal network analysis by integrating differential proteins and metabolites suggested that the disturbance of phospholipid metabolism might promote the inflammation in the central nervous system.
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