Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
Nat Cardiovasc Res. 2024 Feb;3(2):130-139. doi: 10.1038/s44161-024-00422-2. Epub 2024 Feb 12.
Myocardial infarction is a leading cause of death globally but is notoriously difficult to predict. We aimed to identify biomarkers of an imminent first myocardial infarction and design relevant prediction models. Here, we constructed a new case-cohort consortium of 2,018 persons without prior cardiovascular disease from six European cohorts, among whom 420 developed a first myocardial infarction within 6 months after the baseline blood draw. We analyzed 817 proteins and 1,025 metabolites in biobanked blood and 16 clinical variables. Forty-eight proteins, 43 metabolites, age, sex and systolic blood pressure were associated with the risk of an imminent first myocardial infarction. Brain natriuretic peptide was most consistently associated with the risk of imminent myocardial infarction. Using clinically readily available variables, we devised a prediction model for an imminent first myocardial infarction for clinical use in the general population, with good discriminatory performance and potential for motivating primary prevention efforts.
心肌梗死是全球范围内主要的致死原因,但它的发生很难预测。我们旨在寻找即将发生的首次心肌梗死的生物标志物,并设计相关的预测模型。在这里,我们构建了一个新的由来自六个欧洲队列的 2018 名无先前心血管疾病的个体组成的病例对照队列研究,其中 420 名个体在基线血液采集后 6 个月内发生了首次心肌梗死。我们分析了生物银行血液中的 817 种蛋白质和 1025 种代谢物以及 16 个临床变量。48 种蛋白质、43 种代谢物、年龄、性别和收缩压与即将发生的首次心肌梗死风险相关。脑利钠肽与即将发生的心肌梗死风险最密切相关。我们使用临床上易于获得的变量,为一般人群中即将发生的首次心肌梗死设计了一种预测模型,该模型具有良好的判别性能,并有潜力激发初级预防工作。