GC-MS based metabolomics identification of possible novel biomarkers for schizophrenia in peripheral blood mononuclear cells
GC-MS based metabolomics identification of possible novel biomarkers for schizophrenia in peripheral blood mononuclear cells
复制标题
基于 GC-MS 的代谢组学鉴定外周血单核细胞中精神分裂症可能的新型生物标志物
DOI：
10.1039/c4mb00157e
复制
发表时间：
2014-01-01
影响因子：
--
通讯作者：
Xie, Peng
中科院分区：
文献类型：
--
作者：
Liu, Mei-Ling;Zheng, Peng;Xie, Peng
精神分裂症是一种使人衰弱的精神障碍。目前，缺乏支持客观实验室检查的疾病生物标志物构成了精神分裂症临床诊断的瓶颈。在这里，气相色谱-质谱（GC-MS）为基础的代谢组学方法被应用于表征精神分裂症受试者（n = 69）和健康对照（n = 85）在外周血单核细胞（PBMC）的代谢谱，以确定和验证精神分裂症的生物标志物。多变量统计分析被用来可视化组歧视，并确定差异表达的代谢物在精神分裂症受试者相对于健康对照。多因素分析显示，精神分裂症组与对照组有显著差异。总共鉴定了18种负责区分两组的代谢物。这些差异代谢产物主要参与能量代谢、氧化应激和神经递质代谢。由焦谷氨酸、山梨醇和生育酚-α组成的PBMC代谢物的简化组被鉴定为有效的诊断工具，在训练样品（45名精神分裂症受试者和50名健康对照）中产生0.82的受试者工作特征曲线（AUC）下的面积，在测试样品（24名精神分裂症患者和35名健康对照）中产生0.71的受试者工作特征曲线（AUC）下的面积。总之，这些发现有助于开发精神分裂症的诊断工具。
Schizophrenia is a debilitating mental disorder. Currently, the lack of disease biomarkers to support objective laboratory tests constitutes a bottleneck in the clinical diagnosis of schizophrenia. Here, a gas chromatography-mass spectrometry (GC-MS) based metabolomic approach was applied to characterize the metabolic profile of schizophrenia subjects (n = 69) and healthy controls (n = 85) in peripheral blood mononuclear cells (PBMCs) to identify and validate biomarkers for schizophrenia. Multivariate statistical analysis was used to visualize group discrimination and to identify differentially expressed metabolites in schizophrenia subjects relative to healthy controls. The multivariate statistical analysis demonstrated that the schizophrenia group was significantly distinguishable from the control group. In total, 18 metabolites responsible for the discrimination between the two groups were identified. These differential metabolites were mainly involved in energy metabolism, oxidative stress and neurotransmitter metabolism. A simplified panel of PBMC metabolites consisting of pyroglutamic acid, sorbitol and tocopherol-a was identified as an effective diagnostic tool, yielding an area under the receiver operating characteristic curve (AUC) of 0.82 in the training samples (45 schizophrenia subjects and 50 healthy controls) and 0.71 in the test samples (24 schizophrenic patients and 35 healthy controls). Taken together, these findings help to develop diagnostic tools for schizophrenia.