美国斯坦福大学Euan A. Ashley小组揭示心脏动态血流量的基因结构。相关论文于2023年12月11日在线发表于国际学术期刊《自然—遗传学》。

研究人员开发的DeepFlow是一种深度学习系统，用于从相位对比心脏磁共振成像中提取心脏血流量和体积。混合线性模型适用于英国生物库中的37653 人，从而揭示了从主动脉前向速度到主动脉瓣反流率的心脏动态血流量之间的全基因组显著关联。孟德尔随机化揭示了主动脉根部大小在主动脉瓣反流中的因果作用。

在最重要的致病变异中，定位基因（靠近 ELN、PRDM6 和 ADAMTS7）与结缔组织和血压途径有关。研究人员展示了规模化的DeepFlow心流表型与基因分型数据相结合，并加强了结缔组织基因、血压和瓣根大小对主动脉瓣功能的贡献。

据介绍，心脏血流量是决定人类健康的关键因素。然而，由于从心脏成像中大规模捕捉动态血流量的技术难题，对其基因结构的定义受到了限制。

附：英文原文

Title: Genetic architecture of cardiac dynamic flow volumes

Author: Gomes, Bruna, Singh, Aditya, OSullivan, Jack W., Schnurr, Theresia M., Goddard, Pag C., Loong, Shaun, Amar, David, Hughes, J. Weston, Kostur, Mykhailo, Haddad, Francois, Salerno, Michael, Foo, Roger, Montgomery, Stephen B., Parikh, Victoria N., Meder, Benjamin, Ashley, Euan A.

Issue&Volume: 2023-12-11

Abstract: Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

DOI: 10.1038/s41588-023-01587-5

Source: https://www.nature.com/articles/s41588-023-01587-5