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文拉法辛和氟西汀抗抑郁作用机制和药效特点的代谢组学研究

Antidepressant Mechanism and Pharmacodynamic Characteristics of Venlafaxine and Fluxetine Based on Metabolomics

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【作者】 薛水玉郑兴宇窦春艳李震宇秦雪梅

【Author】 XUE Shui-yua,b,ZHENG Xing-yua,b,DOU Chun-yana,b,LI Zhen-yua,QIN Xue-meia,b(Shanxi University,a.Modern Research Center for Traditional Chinese Medicine;b.College of Chemistry and Chemical Engineering,Taiyuan 030006,China)

【机构】 山西大学中医药现代研究中心山西大学化学化工学院

【摘要】 目的采用代谢组学技术比较并评价文拉法辛和氟西汀两种药物的抗抑郁药效及作用机制。方法采用两种药物对慢性不可预知应激(CUMS)动物模型进行干预,观察大鼠的行为学变化;同时采集尿液,进行GC-MS代谢组学分析,并寻找生物标志物。结果行为学数据显示,与模型组相比,文拉法辛和氟西汀组在行为学指标上均有显著性差异(P<0.05),显示出抗抑郁作用。代谢组学分析结果显示,散点图中文拉法辛距离正常对照组较近,其抗抑郁效果较优,通过正常对照与模型组的载荷图寻找出了CUMS抑郁模型的15个潜在生物标志物,文拉法辛所能回调的标志物较氟西汀多。结论两种药物都有明显的抗抑郁效果,且文拉法辛效果较优;运用代谢组学技术分析了两种药物对抑郁症有关标志物的回归调节作用并对其机制进行了初步比较研究,为药物药效的评价提供了新思路和新方法。

【Abstract】 OBJECTIVE To evaluate and compare the antidepressant effects and mechanisms of venlafaxine and fluoxetine by metabolomic approach.METHODS Two positive drugs were employed to intervene the chronic unpredictable mild stress(CUMS) induced rat depression model.The behavioral changes of rats were observed;meanwhile,urine samples were collected and subjected to GC-MS analysis to find potential biomarkers of depression.RESULTS The behavioral data of the drug treatment groups were significantly different(P<0.05) with the model group,showing obvious antidepressant effect.Metabolomic analysis showed that venlafaxine group located closer to the healthy controls,showing better antidepressant efficacy than fluoxetine.Fifteen potential biomarkers were identified from the loading plot between control and model group,and more perturbed metabolites were reversed by venlafaxine.CONCLUSION Both drugs have significant antidepressant efficacy,and venlafaxine shows better effect.Metabolomic approach was applied in this study to analyze the regulation of biomarkers and compare the mechanisms of the two drugs.These results provide new methods for the evaluation of drug efficacy.

【关键词】 文拉法辛; 氟西汀; 慢性不可预知应激; 气相色谱-质谱; 代谢组学;

【Key words】 venlafaxine; fluoxetine; chronic unpredictable mild stress; GC-MS; metabolomics;

【分类号】R971.3;R333.6;R971.4;

【基金】 国家自然科学基金项目(30772759);科技部国际合作项目(2008DFA30430);山西省科技厅/国际科技合作项目(2008081043;2010081070);山西省人事厅人才引进与开发专项资金;山西省教育厅中青年拔尖创新人才计划

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