Serum lipidomic analysis for the discovery of biomarkers for major depressive disorder in drug-free patients

被引:28
|
作者
Kim, Eun Young [1 ,2 ]
Lee, Jae Won [3 ]
Lee, Min Young [3 ,4 ]
Kim, Se Hyun [5 ]
Mok, Hyuck Jun [3 ]
Ha, Kyooseob [1 ,6 ]
Ahn, Yong Min [1 ,6 ]
Kim, Kwang Pyo [3 ]
机构
[1] Seoul Natl Univ Hosp, Dept Neuropsychiat, 101 Daehak Ro, Seoul, South Korea
[2] Seoul Natl Univ, Hlth Care Ctr, Mental Hlth Ctr, Seoul, South Korea
[3] Kyung Hee Univ, Coll Appl Sci, Dept Appl Chem, Yongin, South Korea
[4] Inst Syst Biol, Seattle, WA USA
[5] Dongguk Univ, Sch Med, Dongguk Univ Int Hosp, Dept Neuropsychiat, Goyang, South Korea
[6] Seoul Natl Univ, Coll Med, Inst Human Behav Med, Seoul, South Korea
关键词
Major depressive disorder; Lipidomics; Biomarker; Peripheral lipid signature; PROTEIN-KINASE-C; CHROMATOGRAPHY-MASS SPECTROMETRY; CHOLESTEROL LEVELS; MOUSE MODEL; BRAIN; DISEASE; PLASMA; ACID; METABOLISM; RECEPTORS;
D O I
10.1016/j.psychres.2018.04.029
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Lipidomic analysis can be used to efficiently identify hundreds of lipid molecular species in biological materials and has been recently established as an important tool for biomarker discovery in various neuropsychiatric disorders including major depressive disorder (MDD). In this study, quantitative targeted serum lipidomic profiling was performed on female subjects using liquid chromatography-mass spectrometry. Global lipid profiling of pooled serum samples from 10 patients currently with MDD (cMDD), 10 patients with remitted MDD (rMDD), and 10 healthy controls revealed 37 differentially regulated lipids (DRLs). DRLs were further verified using multiple-reaction monitoring (MRM) in each of the 25 samples from the three groups of independent cohorts. Using multivariate analysis and MRM data we identified serum biomarker panels of discriminatory lipids that differentiated between pairs of groups: lysophosphatidic acid (LPA)(16:1), triglycerides (TG)(44:0), and TG(54:8) distinguished cMDD from controls with 76% accuracy; lysophosphatidylcholines(16:1), TG(44:0), TG(46:0), and TG(50:1) distinguished between cMDD and rMDD at 65% accuracy; and LPA(16:1), TG(52:6), TG(54:8), and TG(58:10) distinguished between rMDD and controls with 60% accuracy. Our lipidomic analysis identified peripheral lipid signatures of MDD, which thereby provides providing important biomarker candidates for MDD.
引用
收藏
页码:174 / 182
页数:9
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