循环的与炎症相关的蛋白质组改善了心血管风险预测. 来自两个大型欧洲队列研究的结果
Ruijie Xie1,2, Sha Sha1,2, Hermann Brenner1
1Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
将与炎症相关的蛋白质添加到SCORE2模型中,显著提高了10年心血管疾病风险的预测. 这种改进的风险分层对于以前没有心血管疾病或糖尿病的个人来说是有价值的.
科学领域:
- 心血管医学 心血管医学
- 生物标志物发现发现
- 风险预测建模风险预测建模
背景情况:
- 炎症是心血管疾病 (CVD) 发展的关键因素.
- 炎症相关蛋白质对主要不良心血管事件 (MACE) 的预测价值需要进一步调查.
- 当前的风险预测模型可能无法完全捕捉与炎症相关的风险.
研究的目的:
- 评估是否结合与炎症相关的蛋白质可以改善SCORE2模型的10年MACE预测.
- 确定特定的与炎症相关的蛋白质,以提高心血管风险评估.
- 在独立的队列中验证增强模型.
主要方法:
- 利用了来自47382名英国生物库和4135名ESTHER研究参与者的数据,这些参与者以前没有心血管疾病或糖尿病.
- 使用Olink®面板测量了C反应蛋白 (CRP) 和73种与炎症相关的蛋白质.
- 使用LASSO回归来选择生物标志物,并使用C指数,NRI和IDI评估模型性能.
主要成果:
- 为了改善预测,选择了七种与炎症相关的蛋白质,不包括CRP.
- 增强的SCORE2模型在内部 (0.716至0.750) 和外部 (0.677至0.713) 验证中显示出显著改善的C指数.
- 净重新分类指数 (NRI) 在风险预测准确度方面显著改善.
结论:
- 整合特定的与炎症相关的蛋白质可以大大提高SCORE2模型的10年MACE风险预测.
- 这种方法为心血管事件风险较高的个体提供了更好的风险分层.
- 测量这些蛋白质可以完善初级预防的临床风险评估策略.
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