多年来，心血管疾病已成为全球死亡的最主要原因，心血管疾病的研究也因此受到了 广泛的研究。随着高血压等慢性心血管疾病的患病人数不断增加，心血管疾病甚至展现出 了年轻化的趋势。心肌肥厚作为心血管疾病最常见的伴随性疾病，同时也是引起死亡的独 立因素。而血栓栓塞的患病人数也随着高血压、高血脂、高血糖患病人数的增加而呈现急 剧上升的趋势。目前对这两种心血管疾病的诊断和治疗主要是在疾病发生后开始进行，本 论文基于尿液蛋白质组学，对两种疾病的发病过程进行研究，通过对尿蛋白质组的检测研 究疾病发生发展规律，寻找相应的尿液生物标志物，探讨对疾病的早期预警和干预措施。 本论文包括以下两个部分:

第一部分，利用皮下注射低剂量异丙肾上腺素构建大鼠心肌肥厚疾病模型，同时在构 建疾病模型过程中收集早期、中期、晚期三个时间点的尿液，利用醇沉的方法提取尿液蛋 白组，然后通过 SDS-PAGE 以及 LC/MS-MS 分析三个时间点的尿液蛋白质组并找出差异 蛋白，并对差异蛋白进行分析，探讨不同阶段尿液蛋白变化特点与规律，为寻找心肌肥厚 疾病模型下的尿液生物标志物提供线索和思路。

通过称量大鼠左右心室重量(VW)和大鼠体重(BW)，计算比值得到检测指标心室重 量指数(VW/BW)具有显著差异(p<0.05)。通过 HE 染色观察出三个时间段心肌细胞纤 维化的程度逐渐加深。由此表明由异丙肾上腺素引起的大鼠心肌肥厚疾病模型构建成功。 利用 LC-MS/MS 技术分析结果显示:本实验共鉴定得到 170 种差异蛋白，去除重复蛋白后 共 126 种，其中 31 种具有人类同源蛋白，15 种属于人类核心尿液蛋白组成员。利用功能 注释分析表明异丙肾上腺素可能通过炎症反应激活机体肾素-血管紧张素系统，激活 AngII， 增加心脏的负荷引起心肌肥厚的发生。最后通过综合比较各个时间点的差异蛋白，发现 126 种差异蛋白中有 3 种蛋白在 3 个时间点都出现，其中 2 个与心肌肥厚发病过程相关;8 个 在早中期出现，23 个在中晚期出现，1 个在早晚期出现。可以推测，这 35 种在两个时间点 及以上出现的差异蛋白可以作为心肌肥厚疾病发病过程不同阶段的生物标志物的来源和 参考。

第二部分是腹腔注射低剂量鞣花酸构建大鼠慢性高凝态模型，同时在构建模型过程中 收集早期、中期、中晚期、晚期四个不同时间点的尿液，利用醇沉提取蛋白组、LC/MS-MS 分析四个时间点的尿液蛋白质组并找出差异蛋白，并对差异蛋白进行分析，探讨相关病理 机制，为寻找高凝态模型下的尿液生物标志物提供线索和思路。

通过静脉取血和对照组比较凝血相关指标(APTT、PT)，实验组凝血时间和对照组相 比具有显著差异(p<0.05)。由此表明由鞣花酸引起的大鼠高凝态模型构建成功。利用 LC- MS/MS 技术分析结果显示:本实验共鉴定得到 74 种差异蛋白，其中 25 种具有人类同源蛋白，14 种属于人类核心尿液蛋白组成员。利用功能注释分析表明鞣花酸可能通过炎症反应 激活机体肾素-血管紧张素系统，通过血管紧张素收缩血管引起高凝态;同时，激活血小板 引起高凝态的发生。最后通过综合比较各个时间点的差异蛋白，发现 74 种差异蛋白中有 10 种蛋白在 3 个时间点都出现，其中 1 个与高凝态发病过程相关;11 种蛋白在连续的 2 个 时间点都出现，其中 4 种与高凝态发病相关。可以推测，这 21 种在两个时间点及以上出现 的差异蛋白可以作为慢性高凝态发病过程不同阶段的生物标志物的来源和参考。

Over the years, cardiovascular disease has become the major cause of death all over the world, and the research on cardiovascular disease has been extensively studied. With the increasing number of patients who suffer from chronic cardiovascular diseases such as hypertension, people that come down with cardiovascular diseases get younger. As the most common concomitant disease of cardiovascular disease, Hypertrophic Cardiomyopathy is also an independent factor of death. The number of patients with thromboembolism also showed a sharp upward trend with the increase of hypertension, hyperlipidemia, and hyperglycemia. At present, the diagnosis and treatment of these two cardiovascular diseases are mainly started after the occurrence of the diseases. Therefore, we try to analyze urine proteomics to study the pathogenesis of the two diseases to find out the biomarkers of the two diseases, and study the changes of urinary proteins in each stage of the disease.

In the first part, low-dose subcutaneous injection of isoproterenol was used to establish a cardiac hypertrophy model, and urine samples were collected at three time points (early, middle and late) during the establishment of the disease model. The urine proteome was extracted by alcohol precipitation, and then analyzed by SDS-PAGE and LC/MS-MS to find out the differentially expressed proteins. The differentially expressed proteins were analyzed to find urine biomarkers in the cardiac hypertrophy disease model.

By weighing the left and right ventricular weight (VW) and the body weight (BW) of the rats, the ratio was calculated, and the detection index ventricular weight index (VW/BW) was significantly different (p<0.05). HE staining showed that the degree of myocardial fibrosis gradually deepened at three time periods. These results indicated that the cardiac hypertrophy model induced by isoproterenol was successfully constructed in rats. LC-MS/MS analysis showed that 170 differentially expressed proteins were identified in this study (44 identified at more than two times), of which 31 proteins found human homologous proteins and 15 proteins were members of the human core urinary protein group. Functional annotation analysis showed that isoproterenol may activate the renin-angiotensin system through inflammatory response to cause cardiac hypertrophy. Finally, comparing the differentially expressed proteins at each time point, we found that 3 of the 126 differential proteins appeared at 3 time points, and 2 of them were related to the pathogenesis of cardiac hypertrophy. Eight appeared in the early and middle stages, 23 in the middle and late stages, and 1 in the early and late stages. It can be speculated that these 35 differential proteins, which appeared at two time points and more, could serve as biomarkers at different stages of the pathogenesis of cardiac hypertrophic diseases.

In the second part, a rat model of plasma hypercoagulable disease was established by intraperitoneal injection of low dose of ellagic acid, and urine samples were collected at four different time points during the modeling process. The urine proteome at four time points was extracted by ethanol precipitation and analyzed by LC/MS-MS to find out the differentially expressed proteins. The differentially expressed proteins were analyzed to find urine biomarkers in the hypercoagulable disease model.

The coagulation time (APTT, PT) of the experimental group was significantly different from that of the control group (p<0.05). Thus, the rat hypercoagulable disease model induced by ellagic acid was successfully constructed. The results of LC-MS/MS analysis showed that 74 differentially expressed proteins were identified in this study, of which 25 had human homologous proteins and 14 belonged to the members of the human core urinary protein group. Functional annotation analysis showed that ellagic acid may activate the renin-angiotensin system through inflammatory response, the coagulation cascade and the activation of platelets, leading to the occurrence of plasma hypercoagulable state. Finally, comparing the differential proteins at each time point, it was found that 10 of the 74 differential proteins appeared at three time points, and one of them was related to the pathogenesis of hypercoagulable state. Eleven proteins were present at two consecutive time points, and four of them were associated with hypercoagulable state. It can be speculated that these 21 differentially expressed proteins present at two time points or more can be used as biomarkers at different stages of the pathogenesis of plasma hypercoagulable state.