Abstract
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 ({hbox {h}}^{2}_{Ped} = 41% ,[hbox {P}=0.001], {hbox {h}}^{2}_{SNP} = 39%, [hbox {P}=0.002]), while the estimated heritability for Reynolds number calculated using the absolute local maximum velocity was not statistically significant (12–13%; hbox {P}>0.05). Heritability estimates of the geometric quantities alone; e.g. aortic diameter ({hbox {h}}^{2}_{Ped} = 29%, [hbox {P}=0.009], {hbox {h}}^{2}_{SNP} = 30%, [hbox {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.
Highlights
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
Flow metrics were derived from the cardiac magnetic resonance (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
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
Summary
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. = 30% [P = 0.010] ), were 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. Phase contrast magnetic resonance (MR) imaging offers a verified means of measuring blood flow rate in the great and peripheral arteries based on the phase-shift of magnetic moments acting on particles as they move through a magnetic field g radient[4,5], with a generally accepted accuracy of within 5% While these measurements have some limitations, MR images are increasingly used to generate accurate patient-specific geometries for use in computational fluid dynamics (CFD), to enable a more detailed investigation of the haemodynamics[6,7,8], the process of segmentation, preparation and iterative solution can be time-consuming and resource intensive
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