基于非靶向代谢组学的中国高血压人群脑卒中发病研究

Stroke has become the leading cause of death in China. Hypertensive population is the most important target for primary prevention of stroke. The mechanism of hypertension related stroke is complicated and different from that of non-hypertension related stroke. The incidence of stroke among Chinese hypertensive patients is significantly higher than western population, which can’t be fully explained by the existing evidence. Recent studies show that metabolic profiles are closely associated with cardiovascular and cerebrovascular diseases. However, there is no metabolomic study on stroke onset among hypertensive patients in the literature. Based on our previous screening results of metabolomics, we plan to perform a 1:1 matched nested case-control study to validate and investigate the association between plasma metabolic profiles and incident stroke among hypertensive patients using our established longitudinal hypertension cohort. UHPLC-MS/MS and ELISA method will be used respectively to perform non-targeted metabolomics and to test markers of inflammation and oxidative stress. We will conduct logistic regression and mediation analysis to screen out the most powerful metabolites for prediction of hypertension related stroke and elucidate the contributions of inflammation and oxidative stress to this process. Cellular and animal models will be used to further investigate the mechanisms. The present study is expected to provide crucial molecularly epidemiologic evidence for primary prevention of stroke in hypertensive population and also to shed a new light on precise management of hypertensive patients.

脑卒中已成为我国居民的首位死因，而高血压人群是脑卒中一级预防最重要的目标人群。高血压所致卒中机制复杂，不同于单纯脑卒中，且中国高血压人群脑卒中发生率明显高于欧美人群，现有证据均不能充分解释这种差异。近期研究表明，基于代谢组学的多种小片段代谢产物与心脑血管疾病发病密切相关。然而，目前国内外尚无高血压人群并发脑卒中的代谢组学研究。本研究在已完成初步代谢组学筛查的基础上，拟利用已有的纵向高血压人群队列，采用1:1匹配巢式病例对照研究，以新发脑卒中为病例组，匹配非脑卒中为对照组，应用UHPLC-MS/MS技术和ELISA法进行血浆非靶向代谢组学及炎症、氧化应激指标检测，通过Logistic回归、中介分析等方法验证并筛选出与高血压脑卒中关联强度最强的代谢产物，阐明炎症及氧化应激在这一过程中的作用，并在细胞和动物模型中验证。为高血压脑卒中的一级预防提供分子流行病学证据，为高血压患者精准管理提供新思路。

在本项目中，我们应用代谢组学技术，筛选出与高血压脑卒中发病关联明显的代谢产物并且发现了多种代谢途径参与其中，同时发现缺血性脑卒中发病的代谢图谱存在不同特点。在传统分析的基础上，应用机器学习分析算法，确定了一组可用于预测高血压脑卒中的血浆代谢物。在人群层面进一步分析发现多种代谢指标与脑卒中发病密切相关。选取鞘脂类代谢物进行深入研究，发现植物鞘氨醇能够改善临床脑卒中症状，并且可能通过抗氧化应激损伤的机制起到保护脑卒中的作用。本项目为高血压脑卒中的防治提供了新思路。