Key result
Genome-wide association studies of bi-ventricular heart shape identified 43 significant loci and revealed that genetically predicted shape components are associated with cardiometabolic diseases like atrial fibrillation.
Why the study?
Heart shape captures cardiac structure variation beyond mass and volume, but while observational studies link it to cardiometabolic risks, its genetic basis is less understood.
Observational (n=45,683)
Yes
Effect estimate: OR 1.52
p-value: p=2.32x10^-60
Multidimensional bi-ventricular heart shape phenotypes derived from CMR have a significant genetic basis, with specific shape components genetically linked to cardiometabolic diseases like atrial fibrillation.
Bi-ventricular shape genetics may refine AF risk models; leaves open causal effects and clinical utility pending prospective validation.
Heart shape captures variation in cardiac structure beyond traditional phenotypes of mass and volume. Although observational studies have demonstrated associations with cardiometabolic risk factors and diseases, its genetic basis is less understood. We utilised cardiovascular magnetic resonance images from 45,683 UK Biobank participants to construct a heart shape atlas from bi-ventricular end-diastolic surface mesh models through principal component (PC) analysis. Genome-wide association studies were performed on the first 11 PCs that captured 83.6% of shape variance. We identified 43 significant loci, 14 were previously unreported for cardiac traits. Genetically predicted PCs were associated with cardiometabolic diseases. In particular two PCs (2 and 3) linked with more spherical ventricles being associated with increased risk of atrial fibrillation. Our study explores the genetic basis of multidimensional bi-ventricular heart shape using PCA, reporting new loci and biology, as well as polygenic risk scores for exploring genetic relationships of heart shape with cardiometabolic diseases.
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Burns et al. (2024) conducted an observational in Cardiometabolic diseases and heart shape variation (n=45,683). Principal components (PCs) of bi-ventricular heart shape was evaluated on Association of PC3 (anterior-posterior width) with atrial fibrillation (OR 1.52, p=2.32x10^-60). Genome-wide association studies of bi-ventricular heart shape identified 43 significant loci and revealed that genetically predicted shape components are associated with cardiometabolic diseases like atrial fibrillation.
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