基于蛋白质基的方法预测不同心血管疾病和痴呆症
Frederick K Ho1, Patrick B Mark2, Jennifer S Lees2,3
1School of Health and Wellbeing (F.K.H., J.P.P., R.J.S.), University of Glasgow, UK.
Circulation
|November 14, 2024
概括
血蛋白生物标志物显著提高心血管疾病风险预测. 与传统风险评分相比,蛋白质组学方法提高了主要心血管不良事件和其他结果的预测准确性.
科学领域:
- 心血管疾病研究
- 蛋白质组学和生物标志物的发现
- 医学中的预测建模
背景情况:
- 在预测心血管疾病 (CVD) 风险方面,研究了个别的血蛋白生物标志物.
- 基于蛋白质组学的综合方法有助于更好地预测各种心血管结果.
研究的目的:
- 研究血蛋白质学方法对预测主要心血管不良事件 (MACE) 和其他心血管结果的有用性.
- 开发和验证基于蛋白质的风险预测模型,并将其性能与已确定的风险得分进行比较.
主要方法:
- 使用了51,859名英国生物库参与者的数据.
- 通过蛋白质组学数据和临床因素进行了全暴露组关联研究,并开发了预测模型.
- 使用分割样本测试与PREVENT风险评分对蛋白质模型进行了验证.
主要成果:
- 像NT-proBNP,proADM,GDF-15,WFDC2和IGFBP4这样的蛋白质与MACE有很强的关联.
- 与PREVENT得分相比,蛋白质模型显示了MACE的净重新分类和c统计的改善.
- 对包括ASCVD,心肌梗塞,中风,心力衰竭和痴呆症在内的各种次要结果观察到更高的预测准确度.
结论:
- 有针对性的血蛋白生物标志物的测量显著改善了总和个体心血管事件的预测.
- 这项研究提供了应用向蛋白质组学的概念证明,用于预测一系列心血管结果.
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