血蛋白与 carotid 斑块相关,并预测发生的动脉样硬化心血管事件
Andrea Baragetti1, Liliana Grigore2, Elena Olmastroni1
1Department of Pharmacological and Biomolecular Sciences "Rodolfo Paoletti", University of Milan, Milan, Italy.
血蛋白质学可以识别心动脉斑块的数量,并改善对健康个体动脉样硬化心血管疾病 (ASCVD) 的预测. 这种基于血液的标记物为传统成像方法提供了一个有希望的替代方案.
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
- 人工智能在医学中的应用
背景情况:
- 非侵入性动脉成像面临挑战,原因是运营商之间的变化和组织障碍.
- 血蛋白质组学为评估动脉斑块负担和心血管风险提供了一个潜在的替代方案.
- 确定可靠的生物标志物对于早期检测和预防动脉样硬化心血管事件 (ASCVD) 至关重要.
研究的目的:
- 为了识别与动脉斑块的存在和数量相关的血蛋白.
- 为了确定血蛋白是否可以预测明显健康的受试者中发生的ASCVD.
- 评估血蛋白质组学对风险分层中已确定的风险因素的附加值.
主要方法:
- 在PLIC研究中的664名受试者中分析了368种蛋白质的血水平.
- 人工智能 (AI) 是一种人工智能. 用于在22年内聚集与动脉斑块存在,数量和发生ASCVD相关的蛋白质.
- 进行了带超声波成像,以评估斑块的存在和数量.
主要成果:
- 97种蛋白质与存在3个或更多的动脉斑块 (AUC=0.683) 有意义地相关.
- 在A.I.I.中. 确定了87种蛋白质,在与经典风险因素相结合时,显著改善了3+斑块的检测 (AUC=0.918) 和预测发生的ASCVD (AUC=0.739).
- 确定的主要生物途径包括白细胞化学反应/迁移和白细胞间/细胞因子信号传递.
结论:
- 血蛋白质学可以有效地表明动脉斑块的数量.
- 蛋白质基因分析提高了在看似健康的个体中ASCVD发病率的预测.
- 这种方法提供了一种新的基于血液的方法来评估心血管风险.
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