Plasma lipidomics reveals potential lipid markers of major depressive disorder

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• 作者：Xinyu Liu ; Jia Li ; Peng Zheng ; Xinjie Zhao…
• 关键词：Major depressive disorder ; Non ; targeted lipidomics ; Diagnostic biomarker ; UPLC ; MS
• 刊名：Analytical and Bioanalytical Chemistry
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：408
• 期：23
• 页码：6497-6507
• 全文大小：1,697 KB
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Analytical Chemistry
  Food Science
  Inorganic Chemistry
  Physical Chemistry
  Monitoring, Environmental Analysis and Environmental Ecotoxicology
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1618-2650
• 卷排序：408

文摘

Major depressive disorder (MDD) is a grave debilitating mental disease with a high incidence and severely impairs quality of life. Therefore, its physiopathological basis study and diagnostic biomarker discovery are extremely valuable. In this study, a non-targeted lipidomics strategy using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was performed to reveal differential lipids between MDD (n = 60) and healthy controls (HCs, n = 60). Validation of changed lipid species was performed in an independent batch including 75 MDD and 52 HC using the same lipidomic method. Pronouncedly changed lipid species in MDD were discovered, which mainly were lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), 1-O-alkyl-2-acyl-PE (PE O), 1-O-alkyl-2-acyl-PC (PC O), sphingomyelin (SM), diacylglycerol (DG), and triacylglycerol (TG). Among these lipid species, LPC, LPE, PC, PE, PI, TG, etc. remarkably increased in MDD and showed pronounced positive relationships with depression severity, while 1-O-alkyl-2-acyl-PE and SM with odd summed carbon number significantly decreased in MDD and demonstrated negative relationships with depression severity. A combinational lipid panel including LPE 20:4, PC 34:1, PI 40:4, SM 39:1, 2, and TG 44:2 was defined as potential diagnostic biomarker with a good sensitivity and specificity for distinguishing MDD from HCs. Our study brings insights into lipid metabolism disorder in MDD and provides a specific potential biomarker for MDD diagnose.