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Lookup NU author(s): Professor Heather Cordell, Professor Bernard Keavney
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2020, The Author(s).Blood flow in the vasculature can be characterised by dimensionless numbers commonly used to define the level of instabilities in the flow, for example the Reynolds number, Re. Haemodynamics play a key role in cardiovascular disease (CVD) progression. Genetic studies have identified mechanosensitive genes with causal roles in CVD. Given that CVD is highly heritable and abnormal blood flow may increase risk, we investigated the heritability of fluid metrics in the ascending aorta calculated using patient-specific data from cardiac magnetic resonance (CMR) imaging. 341 participants from 108 British Caucasian families were phenotyped by CMR and genotyped for 557,124 SNPs. Flow metrics were derived from the CMR images to provide some local information about blood flow in the ascending aorta, based on maximum values at systole at a single location, denoted max, and a ‘peak mean’ value averaged over the area of the cross section, denoted pm. Heritability was estimated using pedigree-based (QTDT) and SNP-based (GCTA-GREML) methods. Estimates of Reynolds number based on spatially averaged local flow during systole showed substantial heritability (hPed2=41%[P=0.001], hSNP2=39%[P=0.002]), while the estimated heritability for Reynolds number calculated using the absolute local maximum velocity was not statistically significant (12–13%; P > 0.05). Heritability estimates of the geometric quantities alone; e.g. aortic diameter (hPed2=29%[P=0.009], hSNP2=30%[P=0.010]), were also substantially heritable, as described previously. These findings indicate the potential for the discovery of genetic factors influencing haemodynamic traits in large-scale genotyped and phenotyped cohorts where local spatial averaging is used, rather than instantaneous values. Future Mendelian randomisation studies of aortic haemodynamic estimates, which are swift to derive in a clinical setting, will allow for the investigation of causality of abnormal blood flow in CVD.
Author(s): McGurk KA, Owen B, Watson WD, Nethononda RM, Cordell HJ, Farrall M, Rider OJ, Watkins H, Revell A, Keavney BD
Publication type: Article
Publication status: Published
Journal: Scientific Reports
Year: 2020
Volume: 10
Issue: 1
Print publication date: 01/12/2020
Online publication date: 01/09/2020
Acceptance date: 25/06/2020
Date deposited: 03/12/2020
ISSN (electronic): 2045-2322
Publisher: Nature Publishing Group
URL: https://doi.org/10.1038/s41598-020-71354-7
DOI: 10.1038/s41598-020-71354-7
PubMed id: 32873833
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