亚洲印第安人冠状动脉疾病的多基因风险评分评估
Madhusmita Rout1, Gurleen Kaur Tung1, Jai Rup Singh2
1Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA.
Journal of cardiovascular translational research
|April 24, 2024
概括
对冠状动脉疾病 (CAD) 的多基因风险评分 (PRS) 模型在针对特定祖先量身定制时表现更好. 亚洲印度 (AI) 和南亚 (SA) 衍生模型,或组合模型,显示出比欧洲衍生模型更好的预测和可运输性.
科学领域:
- 遗传学 是一个遗传学.
- 心血管疾病研究研究
- 人口健康 人口健康
背景情况:
- 多基因风险评分 (PRS) 对于预测冠状动脉疾病 (CAD) 风险至关重要.
- 目前的PRS模型主要来自欧洲祖先种群,这限制了它们在不同种群中的适用性.
- 跨不同祖先的PRS的可运输性和预测性要求进行彻底的评估.
研究的目的:
- 在亚洲印第安人 (AI) 队列中评估冠状动脉疾病 (CAD) 的各种多基因风险评分 (PRS) 模型的性能和可运输性.
- 为了比较来自欧洲 (EU),南亚 (SA) 和人工智能祖先的PRS模型的预测准确度.
- 评估包括临床风险得分和人口特异性遗传多样性的对PRS表现的影响.
主要方法:
- 使用来自13,974名AI祖先受试者的培训和测试集对PRS模型的性能评估.
- 在不同的PRS模型 (EU,SA,AI,EU+AI) 之间比较预测性绩效指标 (例如,极端四分位数中的效率).
- 在PRS模型中评估临床风险得分和人群特定变异的增量值.
主要成果:
- 来自AI和SA祖先的PRS模型,以及EU+AI组合模型,与欧盟衍生模型相比,显示出优异的预测性能和可运输性.
- 人工智能和欧盟+人工智能模型的预测性能分别比欧盟模型高18%和22%.
- 与欧盟模型相比,人工智能和欧盟+人工智能模型在识别高CAD风险的个体方面效率高2.6至4.6倍. 临床风险评分没有显著改变遗传模型的性能.
结论:
- 由亚洲印第安人 (AI) 和南亚人 (SA) 遗传数据衍生或包括的多基因风险评分模型显著改善了冠状动脉疾病 (CAD) 风险预测和AI群体的可运输性.
- 将特定种群的遗传多样性和风险因素纳入PRS模型对于完善风险分层和提高临床效用至关重要.
- 开发特定于祖先或基于祖先的PRS模型对于在不同人群中进行公平有效的心血管疾病风险评估至关重要.
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