心脏衰老的遗传学意味着特定器官的变异
James Brundage1, Joshua P Barrios1,2, Geoffrey H Tison1,2,3,4
1Division of Cardiology, University of California San Francisco, San Francisco, CA, USA.
medRxiv : the preprint server for health sciences
|August 16, 2024
概括
一个新的深度学习模型使用心脏特定的MRI数据准确估计心脏衰老加速. 这种心脏衰老加速是遗传的,与生活方式,遗传学和不良健康结果有关.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 遗传学 遗传学 是一个
背景情况:
- 心脏衰老在个体之间有所不同,这引起了对估计心脏衰老加速的兴趣.
- 现有的心脏年龄估计方法缺乏特异性或特征丰富性,阻碍了对遗传贡献的研究.
- 心脏蒙面MRI的深度学习 (DL) 为精确的心脏衰老评估提供了一个潜在的解决方案.
研究的目的:
- 开发和验证基于视频的DL模型,以估计心脏衰老加速,使用心脏蒙面心脏MRI数据.
- 研究心脏衰老加速与心脏功能,生活方式因素,血清蛋白质和大脑MRI特征的关联.
- 探索心脏衰老加速的遗传性和遗传基础.
主要方法:
- 一个基于视频的DL模型被训练在来自61,691名英国生物库参与者的心脏MRI数据上,不包括非心脏像素.
- 心脏衰老加速的计算是预测心脏年龄和日历年龄之间的差异.
- 用全基因组关联研究 (GWAS) 和门德尔随机化来确定遗传位置和蛋白质关联.
主要成果:
- DL模型解释了71.1%的日历年龄差异,平均绝对误差为3.3年.
- 心脏衰老加速与不良的心脏几何学,功能障碍,生活方式因素,特定的血清蛋白质和大脑MRI发现相关.
- 发现心脏衰老加速是遗传的 (h2g 26.6%),GWAS确定了24个相关的位置,21个是心脏衰老加速的新型.
结论:
- 一种新的DL方法提供了一种特定于心脏的衰老指标.
- 心脏衰老加速受遗传,生活方式和环境因素的影响,并与心血管疾病和死亡率的风险增加有关.
- 这些发现强调了心脏和血管特异性因素在心脏衰老中的重要性.
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