中文摘要：

目的：应用蛋白质组学方法,分析冠心病急性心肌梗死患者血清蛋白,探索冠心病痰瘀证候的分子生物学基础。方法：采集冠心病急性心肌梗死痰瘀证、血瘀证患者的血清,应用表面增强激光解析离子化飞行时间质谱技术作蛋白质组学检测,和正常对照者比较,分析冠心病痰、瘀证候的血清蛋白,寻找其特异性生物标记物。结果：1冠心病与正常对照组血清蛋白质组学比较有29个差异蛋白峰,M/Z 1 562.79等9个差异蛋白峰在冠心病组中呈高表达,M/Z 1 501.44等20个差异蛋白峰在冠心病组中呈低表达。M/Z 4 649.81和M/Z 9 536.92两个差异蛋白峰组成的生物标记物可以将冠心病组和正常对照组样品较好地分类。最终决策树模型对所有样品分组判别的正确率为96%,灵敏度为100%,特异性为94.7%。2冠心病痰瘀证和血瘀证血清蛋白质组学比较有35个差异蛋白峰,M/Z 1 986.37等12个差异蛋白峰在痰瘀组和血瘀组中呈高表达;M/Z 4 980.48等8个差异蛋白峰在痰瘀组和血瘀组中呈低表达;M/Z2 242.14等15个差异蛋白峰在痰瘀组中呈高表达,在血瘀组中呈低表达。M/Z 8 654.96、M/Z 2 081.65、M/Z 18 667.3和M/Z 2 242.14四个差异蛋白峰组成的生物标记物可以将痰瘀组和血瘀组样本较好地分类。最终决策树模型对所有样品分组判别的正确率为84.7%,灵敏度为92.2%,特异性为73.3%。结论：运用表面增强激光解析离子化飞行时间质谱技术进行血清的检测结果,冠心病及冠心病痰瘀证的血清都有差异蛋白,进一步用决策树方法建立的冠心病血清蛋白预测模型和冠心病痰瘀证血清蛋白预测模型都有较高正确率、灵敏度和特异性。

英文摘要：

Objective： To analyze the serum protein and to explore the molecular biological basis of phlegm and blood stasis syndrome of acute myocardial infarction（AMI）, with the method of proteomics. Methods： The serum samples of AMI patients with syndromes of phlegm and blood stasis were collected, and the proteomics was measured by surface enhanced laser desorption ionization time of flight（SELDI-TOF-MS）. Then, compared with the control subjects, the serum protein characteristics of AMI patients with syndrome of phlegm and blood stasis were analyzed to explore specific biomarkers. Results： 1The serum proteomics results showed that there were 29 differential protein peaks in the AMI group, comparing with the control group. Among them, 9 differential protein peaks（containing M/Z 1 562.79） in the AMI group were high expressed, and 20 differential protein peaks（containing M/Z 1 501.44） were low expressed. M/Z 4 649.81 and M/Z 9 536.92 protein were thought as specific biomarkers that could classify the AMI patients and the control ones. The decision tree model result showed that the accuracy, sensitivity and specificity of the classification were 96%, 100% and 94.7%, respectively. 2The serum proteomics results also showed that there were 35 differential protein peaks in the phlegm-blood stasis group, comparing with the blood stasis group. Among them, 12 differential protein peaks（containing M/Z 1 986.37） in the phlegm-blood stasis group and blood stasis group were high expressed, and 8 differential protein peaks（containing M/Z 4 980.48） were low expressed. Fifteen differential protein peaks（containing M/Z 2 242.14） in the phlegm-blood stasis group were high expressed, but low expressed in the blood stasis group. The protein including M/Z 8 654.96, M/Z 2 081.65, M/Z 18 667.3 and M/Z 2 242.14 were thought as specific biomarkers that could classify the phlegm-blood stasis patients and the blood stasis ones. The decision tree model result showed that the accuracy, sensitivity and specificity of t