动脉动脉病的血清蛋白质分析:一个人口结局研究
Nicholas Cauwenberghs1, Astrid Verheyen1, František Sabovčik1
1Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Belgium.
Atherosclerosis
|October 25, 2023
概括
循环中的蛋白质可以预测动脉样硬化心血管疾病 (ASCVD) 事件. 基于蛋白质的现象组确定了高风险个体,补充了当前的ASCVD风险评分策略.
科学领域:
- 心血管疾病研究研究
- 蛋白质组学和生物标志物发现发现
- 血管健康 血管健康
背景情况:
- 亚临床血管疾病检测对于预测动脉样硬化心血管疾病 (ASCVD) 至关重要.
- 循环蛋白提供了潜在的生物标志物,可以改善ASCVD风险预测.
- 动脉病变是潜在血管疾病的关键指标.
研究的目的:
- 使用蛋白质组数据识别与动脉动脉病相关的蛋白质.
- 开发一种基于蛋白质的分类器,用于预测ASCVD事件.
- 探索基于蛋白质的现象组在风险分层中的实用性.
主要方法:
- 在491名参与者的蛋白质组数据上应用特征选择和无监督聚类.
- 利用部分最小方形 (PLS) 将蛋白质与动脉内膜介质厚度 (cIMT) 联系起来.
- 使用高斯混合物建模用于ASCVD事件预测的衍生蛋白质基现象组.
主要成果:
- 确定了与cIMT相关的19种蛋白质;11种用于聚类.
- 根据蛋白质配置文件确定了两个不同的现象组.
- 第二个现象组显示不良的脂质样本,更高的cIMT,ASCVD事件的风险增加了2.05倍.
结论:
- 基于蛋白质的表观分组有效地识别了未来ASCVD事件的高风险个体.
- 这种方法可以补充现有的ASCVD风险分层策略.
- 聚焦蛋白质组分析为血管疾病预测提供了宝贵的见解.
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