基于超高效液相色谱/三重四极杆-飞行时间串联质谱技术分析抑郁症患者血清的代谢组学  

Serum metabolomics analysis of depression patients based on ultra performance liquid chromatography/quadrupole-time of flight-mass spectra

作　　者：刘史佳[1] 吕翔宇 熊玥 柯梦颖 孔德舜 卢嘉微 王珏 汪永胜[1] LIU Shi-jia;Lü Xiang-yu;XIONG Yue;KE Meng-ying;KONG De-shun;LU Jia-wei;WANG Jue;WANG Yong-sheng(Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing 210029,Jiangsu Province,China;School of Life Science and Technology,China Pharmaceutical University,Nanjing 211198,Jiangsu Province,China;School of Traditional Chinese Medicine,China Pharmaceutical University,Nanjing 211198,Jiangsu Province,China;Jiangsu Provincial Animal Product Quality Inspection and Testing Center,Nanjing 210036,Jiangsu Province,China;School of Life Science and Technology,Nanjing University of Chinese Medicine,Nanjing 210023,Jiangsu Province,China;School of Pharmacy,Nanjing University of Chinese Medicine,Nanjing 210023,Jiangsu Province,China)

机构地区：[1]南京中医药大学附属医院,江苏南京210029 [2]中国药科大学,生命科学学院,江苏南京211198 [3]中国药科大学中药学院,江苏南京211198 [4]江苏省畜产品质量检验测试中心,江苏南京210036 [5]南京中医药大生命科学学院,江苏南京210015 [6]南京中医药大学药学院,江苏南京210015

出　　处：《中国临床药理学杂志》2020年第12期1635-1638,共4页The Chinese Journal of Clinical Pharmacology

基　　金：国家自然科学基金资助项目(81774096);中华中医药学会2017-2019年度青年人才托举工程基金资助项目(QNRC2-B04);江苏省高层次卫生人才“六个一工程”拔尖人才基金资助项目(LGY2018061);江苏省“六大人才高峰”高层次人才基金资助项目(WSN-051);江苏省青年医学人才基金资助项目(QNRC2016642)。

摘　　要：目的用代谢组学的方法观察抑郁症患者的血清代谢产物变化规律。方法收集健康者42例和抑郁症患者22例的血清标本。将超高效液相色谱/三重四极杆-飞行时间串联质谱(UPLC/Q-TOF-MS)检测将所得数据输入SIMCA-14.0软件,对其进行多变量统计分析。用主成分分析法(PCA)模式识别分析各代谢物的变化。结果抑郁症患者和健康者的血清代谢表型有明显差异,样本点完全分离。抑郁症患者血清中色氨酸、二十二碳六烯酸、γ-亚麻酸等小分子代谢物变化倍数(FC)≥1,含量明显增加,苯丙氨酸含量明显降低(FC<1),与健康者相比差异均有统计学意义(均P<0.01)。结论与健康者相比,抑郁症患者体内血清中苯丙氨酸水平下降,而色氨酸、二十二碳六烯酸和γ-亚麻酸水平上升。可作为潜在的生物标志物进一步研究。Objective To observe the changes of serum metabolites in depression patients by metabolomics method.Methods Serum samples from normal human(42 cases)and depression patients(22 cases)were collected.They were detected by ultra performance liquid chromatography/quadrupole-time of flight-mass spectra.The data obtained were inputed into SIMCA-14.0 software for multivariate statistical analysis.Principal component analysis pattern recognition was used to analyze the changes in each metabolite.Results The serum metabolic phenotypes between depression patients and normal people were significantly different,and the sample points were completely separated.The fold change(FC)of tryptophan,docosahexaenoic acid andγ-linolenic acid≥1,which meant the levels of them in serum of depression patients increased.Besides,the levels of serum phenylalanine in depression patients decreased significantly(FC<1).These differences were statistically significant between depression patients and normal people(all P<0.01).Conclusion Compared with normal people,the levels of phenylalanine in patients with depression decreased,and the levels of tryptophan,docosahexaenoic acid andγ-linolenic acid increased.These metabolites can be further studied as potential biomarkers.

关 键 词：抑郁症 代谢组学 超高效液相色谱-质谱 差异代谢物 人血清 

分 类 号：R97[医药卫生—药品]