Can Heart Shape Predict Risk for Cardiovascular Diseases? Study Sheds Light

Published On 2024-11-18 03:00 GMT   |   Update On 2024-11-18 03:00 GMT
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A new multi-national study has revealed that the shape of the heart is influenced in part by genetics and may help predict the risk of cardiovascular diseases.
Researchers are first to examine the genetic basis of the heart's left and right ventricles using advanced 3D imaging and machine learning.
By studying both ventricles together, the team was able to capture the more intricate, multi-dimensional aspects of the heart shape.
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This new approach of exploring shape has led to the discovery of new heart-associated genes and provided a better understanding of the biological pathways linking heart shape to cardiovascular disease.
Genetic information related to heart shape can provide a risk score for heart disease, offering potentially early and more tailored assessment in clinical settings.
The team used cardiovascular MRI images from over 40,000 individuals from the UK Biobank, a large-scale biomedical database and research resource containing genetic and health information from half a million UK participants, to create 3D models of the ventricles.
Through statistical analysis, they identified 11 shape dimensions that describe the primary variations in heart shape.
Subsequent genetic analysis found 45 specific areas in the human genome linked to different heart shapes.
Fourteen of these areas had not been previously known to influence heart traits.
This study sets an important foundation for the exploration of genetics in both ventricles," said Dr Richard Burns, Statistical Geneticist at Queen Mary.
"The study confirms that combined cardiac shape is influenced by genetics, and demonstrates the usefulness of cardiac shape analysis in both ventricles for predicting individual risk of cardiometabolic diseases alongside established clinical measures."
Reference: 

Burns, R., Young, W.J., Aung, N. et al. Genetic basis of right and left ventricular heart shape. Nat Commun 15, 9437 (2024). https://doi.org/10.1038/s41467-024-53594-7

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Article Source : Nature Communications

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