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Observational Cohort Study Links Dynamic Cardiac Shape to Cardiometabolic Disease Risk in UK Biobank

Observational Cohort Study Links Dynamic Cardiac Shape to Cardiometabolic Disease Risk in UK Biobank
Photo by Ben Maffin / Unsplash
Key Takeaway
Note dynamic cardiac shape features may improve prediction of incident cardiometabolic disease beyond standard CMR measures.

This publication is an abstract reporting an observational cohort study utilizing UK Biobank data. The study population comprised 36,992 participants. The primary exposure involved biventricular cardiac dynamic shape derived from CMR, alongside genetic loci and polygenic risk scores. The main outcome focused on association with incident cardiometabolic diseases.

Analysis identified 14 dynamic cardiac shape principal components capturing 83.3% of total dynamic cardiac shape variance. All 14 principal components were associated with at least one incident cardiometabolic disease. The strongest disease associations were observed for incident ischemic heart disease, heart failure, and atrioventricular block. Incorporating dynamic shape principal components improved prediction of incident ischemic heart disease beyond standard CMR measures.

Genetic analysis identified 75 genetic loci, including 14 previously unreported for cardiac traits. Polygenic risk scores derived from dynamic shape loci were significantly associated with multiple outcomes, most prominently heart failure. Mendelian randomization identified significant causal relationships between several principal components and cardiometabolic disease. However, genetic associations generally indicate association rather than causation.

The authors note that dynamic cardiac shape features capture aspects of cardiac structure and function not fully represented by standard CMR measures. Limitations were not reported in the abstract. Practice relevance suggests these features provide new insights into the genetic architecture of cardiac remodeling. Clinicians should interpret findings cautiously given the observational nature and lack of reported limitations.

Study Details

EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
Background: Genetic studies using cardiac magnetic resonance (CMR) imaging have identified loci related to cardiac shape, but most focus on static morphology. The value of a dynamic cardiac shape atlas capturing both shape and function remains unknown. Methods: A dynamic shape atlas comprising CMR-derived shape models at end-diastole and end-systole was combined with genetic and outcome data in 36,992 UK Biobank participants. Dynamic shape principal components (PCs) describing >1% of variance were characterized, and tested for associations with prevalent and incident cardiometabolic diseases, including ischemic heart disease (IHD), heart failure (HF), significant atrioventricular block (AVB), and atrial fibrillation (AF), and independent predictive power alongside standard CMR measures. Genome-wide association studies (GWAS) were performed to identify candidate genes and biological pathways, and polygenic risk scores (PRS) were assessed for disease associations. Mendelian randomization (MR) was performed to test causality of observed disease associations. Results: We identified 14 dynamic cardiac shape PCs capturing 83.3% of total dynamic cardiac shape variance. These PCs captured distinct functional remodeling patterns such as variation in annular plane systolic excursion, while remaining only modestly correlated with standard CMR measures. All 14 PCs were associated with at least one incident cardiometabolic disease, with the strongest associations observed for incident IHD, HF, and AVB. Notably, incorporating dynamic shape PCs improved the prediction of incident IHD beyond standard CMR measures. GWAS identified 75 genetic loci associated with dynamic shape, including 14 previously unreported for cardiac traits, and candidate genes demonstrated enrichment in pathways related to cardiac development and contractile function. PRS derived from dynamic shape loci were significantly associated with multiple outcomes, most prominently HF. MR identified significant causal relationships between several PCs and cardiometabolic disease. Conclusions: Dynamic cardiac shape features capture aspects of cardiac structure and function not fully represented by standard CMR measures. These features are strongly associated with incident cardiometabolic disease and provide new insights into the genetic architecture of cardiac remodeling. Keywords: biventricular, dynamic cardiac shape and function, cardiometabolic disease, genome-wide association study
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