在心房风险预测中结合多基因和临床风险得分:对人口查的影响
Louise Segan1, William Wing Ho Ho2, Rose Crowley1
1The Baker Heart and Diabetes Research Institute, Melbourne, Victoria, Australia; The Alfred Hospital, Melbourne, Victoria, Australia; University of Melbourne, Melbourne, Victoria, Australia; Monash University, Melbourne, Victoria, Australia.
Heart rhythm
|April 27, 2025
概括
将多基因风险评分 (PRS) 与临床因素相结合,显著改善了心房动 (AF) 风险预测. 这种综合方法增强了AF的早期检测和有针对性的干预措施.
科学领域:
- 心血管遗传学 心血管遗传学
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 心房动 (AF) 的风险受临床因素和遗传倾向的影响.
- 目前的AF临床风险模型可能无法完全捕捉个体风险.
- 多基因风险评分 (PRS) 提高AF预测的实用性需要进一步研究.
研究的目的:
- 评估AF特异性多基因风险评分 (AF-PRS) 的预测性能.
- 评估AF-PRS与发生性AF的确定的临床风险得分 (HARMS2-AF和CHARGE-AF) 之间的相互作用.
- 为了确定是否将AF-PRS与临床分数结合起来,可以在英国大型生物库队列中改善AF风险预测.
主要方法:
- 利用了来自285,734名英国生物库参与者的全基因组测序数据.
- 计算了AF-PRS并将参与者分为低风险,中等风险和高风险组.
- 使用回归分析来评估AF-PRS与HARMS2-AF和CHARGE-AF分数相结合对事件AF风险的影响.
主要成果:
- 高AF-PRS独立地与增加事件AF风险相关 (HR 2.75).
- 将AF-PRS与HARMS2-AF得分相结合,使曲线下的面积 (AUC) 从0.828提高到0.839.
- 将AF-PRS与CHARGE-AF得分相结合,使AUC从0.808提高到0.828,并有显著的净重新分类.
结论:
- 遗传风险 (AF-PRS) 和临床风险得分的结合显著提高了AF风险预测.
- 将多基因风险评分纳入临床模型可以改善人口查策略.
- 这种综合方法有潜力开发有针对性的干预措施,以减少AF发生率.
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