伴腹型肥胖的颅内动脉粥样硬化患者ECE-1基因多态性的机制研究及机器学习模型的建立

颅内动脉粥样硬化（ICAS）为中国人群脑卒中主要病因。伴腹型肥胖的ICAS患者，在中国发生率高，存在多种血管代谢危险聚集，严重危害人类健康，但发病机制及影响因素未完全明确。内皮素转化酶-1（ECE-1）可调节血管张力，上调氧化应激，诱发炎症，引起内皮功能障碍，重塑血管，具有多种生物学作用。我们认为ECE-1基因多态性与伴腹型肥胖的ICAS发生发展存在关联，但具体机制尚欠明确。本课题通过纳入不同人群，采用LDR-PCR进行基因分型，结合Real-time PCR，ELISA等实验技术，研究ECE-1基因多态性与伴腹型肥胖的ICAS患者及预后的联系并探讨其机制。另外通过大数据分析，结合机器学习技术对伴有腹型肥胖的ICAS患者的危险因素进行分析，构建预测模型和评估体系。研究成果有望用于筛选相关疾病的高危因素和易感人群，为脑血管病防治提供新思路。

Intracranial atherosclerosis (ICAS) is the main cause of stroke in Chinese population. The incidence of ICAS patients with central obesity is high in China, and there are multiple vascular metabolism risk clusters, which seriously endanger human health. But the pathogenesis and influencing factors are not completely clear. Endothelin converting enzyme-1 (ECE-1) have many biological functions involved in regulating vascular tension, up-regulating oxidative stress to induce vascular inflammation, remodeling blood vessels, and affecting endothelial dysfunction. We assured that ECE-1 gene polymorphism is related to the occurrence and development of ICAS with central obesity, but the mechanism is still unclear. In this study, LDR-PCR genotyping was performed, and Real-time PCR, ELISA and other techniques were combined to study the association between ECE-1 gene polymorphism and ICAS with central obesity. In addition, in order to build the predictive model and evaluation system, the risk factors of ICAS patients with central obesity were analyzed by machine learning. The research results are expected for screening high-risk groups and susceptible individuals of ICAS in patients with central obesity, providing strategy for the prevention and treatment of cerebrovascular diseases.