Genetic architecture of cardiac dynamic flow volumes

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 fro...

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Bibliographic Details
Published inNature genetics Vol. 56; no. 2; pp. 245 - 257
Main Authors Gomes, Bruna, Singh, Aditya, O'Sullivan, Jack W, Schnurr, Theresia M, Goddard, Pagé 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
Format Journal Article
LanguageEnglish
Published United States Nature Publishing Group 01.02.2024
Subjects
Aorta
Aortic Valve
Aortic Valve Insufficiency
Automation
Biobanks
Blood flow
Blood Flow Velocity - physiology
Blood pressure
Cardiac function
Connective tissue
Connective tissues
Genes
Genomes
Genotyping
Heart
Heart valves
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Phenotyping
Regurgitation
Software
Velocity
United Kingdom > UK
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Summary: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.
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ISSN:1061-4036
1546-1718
DOI:10.1038/s41588-023-01587-5