基于^1HNMR代谢组学的抑郁症生物标志物发现及帕罗西汀干预作用

Discovering potential biomarkers of depression and drug intervention of paroxetine based on ^1H NMR metabolomics

寻找抑郁症患者血清中潜在生物标志物,为抑郁症临床诊断及药物作用机制研究提供依据。筛选符合纳入标准的16例中重度抑郁症患者和16例健康人分别作为疾病组和对照组,其中疾病组抑郁症患者服用抗抑郁药物帕罗西汀两周。采集对照组、抑郁症患者以及抑郁症患者服用帕罗西汀两周后的血清进行1H NMR测试,采用代谢组学技术结合多元统计方法分析血清中内源性代谢产物的变化及其规律,发现具有显著性差异的代谢产物,结合相关代谢途径及受试者工作曲线(ROC)分析发现潜在生物标志物,并进一步探讨其与抑郁症的相关性及应用于临床诊断的可靠性和可行性。抑郁症患者血清中谷氨酸、谷氨酰胺、丙氨酸、N-乙酰糖蛋白、亮氨酸及异亮氨酸的水平显著升高,而葡萄糖水平显著降低(P<0.05,P<0.01),而帕罗西汀对丙氨酸、N-乙酰糖蛋白、异亮氨酸及葡萄糖代谢水平具有显著的回调作用(P<0.05,P<0.01),并调节谷氨酸、谷氨酰胺及异亮氨酸代谢水平使其具有向正常水平恢复的趋势,因此可被确定为潜在生物标志物。上述生物标志物的应用将有助于提高抑郁症临床诊断的客观性和抗抑郁药物临床疗效评价的准确性。

The purpose of this study was to find potential biomarkers in the serum of patients with depression and provide the basis for clinical diagnosis of depression. Sixteen patients of severe depression were selected according to the inclusion criteria and 16 healthy people were used in the control group. The depression patients took paroxetine for two weeks. The serum was collected from the patients and healthy control group before and after paroxetine treatment. The samples were analyzed by 1H NMR based metabolomics to determine the changes in profiles of endogenous metabolites and metabolites with significant differences were selected in analysis. Related pathways and receiver operating characteristic（ROC） were examined in analysis of the correlation between the potential biomarkers and depression. Their feasibility and reliability was determined for the clinical practice. Significant differences were observed in the metabolic profile of serum of the patients and the healthy controls. Depression had an effect on metabolism for an increase in leucine, isoleucine and alanine, glutamate, glutamine and N-acetyl-glycoprotein and a decrease in glucose. Those may be considered as potential biomarkers of depression. Clinical application of the biomarkers may improve the objectivity of the diagnosis and treatment of depression by antidepressant drugs. The metabolomics approach is an effective tool in the investigation of biomarkers.