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Discovery of serum protein biomarkers in drug-free patients with major depressive disorder

重性抑郁障碍 生物标志物 生物标志物发现 病理生理学 蛋白质组 蛋白质组学 医学 生物信息学 内科学 生物 基因 遗传学 扁桃形结构
作者
Min Young Lee,Eun Young Kim,Se Hyun Kim,Kyung-Cho Cho,Kyooseob Ha,Kwang Pyo Kim,Yong Min Ahn
出处
期刊:Progress in Neuro-psychopharmacology & Biological Psychiatry [Elsevier BV]
卷期号:69: 60-68 被引量:74
标识
DOI:10.1016/j.pnpbp.2016.04.009
摘要

Major depressive disorder (MDD) is a systemic and multifactorial disorder involving complex interactions between genetic predisposition and disturbances of various molecular pathways. Its underlying molecular pathophysiology remains unclear, and no valid and objective diagnostic tools for the condition are available.We performed large-scale proteomic profiling to identify novel peripheral biomarkers implicated in the pathophysiology of MDD in 25 drug-free female MDD patients and 25 healthy controls. First, quantitative serum proteome profiles were obtained and analyzed by liquid chromatography-tandem mass spectrometry using serum samples from 10 MDD patients and 10 healthy controls. Next, candidate biomarker sets, including differentially expressed proteins from the profiling experiment and those identified in the literature, were verified using multiple-reaction monitoring in 25 patients and 25 healthy controls. The final panel of potential biomarkers was selected using multiparametric statistical analysis.We identified a serum biomarker panel consisting of six proteins: apolipoprotein D, apolipoprotein B, vitamin D-binding protein, ceruloplasmin, hornerin, and profilin 1, which could be used to distinguish MDD patients from controls with 68% diagnostic accuracy. Our results suggest that modulation of the immune and inflammatory systems and lipid metabolism are involved in the pathophysiology of MDD.Our findings of functional proteomic changes in the peripheral blood of patients with MDD further clarify the molecular biological pathway underlying depression. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for the diagnosis of MDD.
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