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LONDON — Some hearts are round, others more elongated, and as it turns out, these differences aren’t just simple curiosities. Scientists have discovered that your heart’s unique shape could be a crystal ball for predicting future health problems.
Published in Nature Communications, researchers analyzed detailed heart scans from over 45,000 participants to create the first comprehensive “heart shape atlas,” revealing that cardiac geometry could be as important as traditional measures like heart size and blood pressure in predicting health outcomes.
The study, led by researchers from multiple institutions in the United Kingdom, used advanced artificial intelligence and imaging techniques to examine the intricate variations in heart shape across thousands of participants in the UK Biobank project. Their findings suggest that seemingly subtle differences in cardiac geometry could help identify individuals at higher risk for conditions like atrial fibrillation (an irregular heartbeat) and heart failure before traditional warning signs appear.
Think of it like analyzing the aerodynamics of different car designs. Just as a vehicle’s shape affects its performance and efficiency, the precise three-dimensional geometry of your heart influences how effectively it can pump blood throughout your body.
The researchers discovered that heart shape characteristics are significantly influenced by genetics – much like how your height or eye color is inherited from your parents. They identified 43 specific locations in the human genome that affect heart shape, with 14 of these genetic regions never before linked to cardiac function.
One of the most intriguing findings involved heart “sphericity” – essentially how round or football-shaped the heart appears. The study found that people with more spherical hearts had a higher risk of developing atrial fibrillation, one of the most common heart rhythm disorders.
The research team used cardiovascular magnetic resonance (CMR) imaging – essentially highly detailed 3D heart scans – to create precise digital models of each participant’s heart. They then applied sophisticated mathematical techniques to identify the most important patterns of shape variation across the population.
These shape patterns, called principal components, captured different aspects of cardiac geometry. The first component related to overall heart size, while others described characteristics like the length from base to apex, width, and the relative orientation of the heart’s right and left chambers.
Importantly, the study found that these shape features were associated with various cardiovascular diseases in ways that couldn’t be predicted by traditional measurements alone. For example, variations in the heart’s lateral width were linked to multiple conditions, including heart failure, cardiomyopathy, and diabetes.
The researchers also developed genetic risk scores based on their findings, which could potentially help doctors identify patients at higher risk for specific heart conditions based on their DNA, even before any physical symptoms appear. These genetic markers worked consistently across different ethnic groups, suggesting their potential utility for diverse populations.
The implications of this research are significant for preventive cardiology. Currently, doctors primarily rely on measures like heart size, blood pressure, and various blood tests to assess cardiovascular risk. This study suggests that analyzing heart shape could add another crucial layer of information, potentially allowing for earlier and more precise intervention strategies.
“This study provides new information on how we think about heart disease risk,” says study co-author Patricia B. Munroe, Professor of Molecular medicine at Queen Mary, in a statement. “We’ve long known that size and volume of the heart matter, but by examining shape, we’re uncovering new insights into genetic risks. This discovery could provide valuable additional tools for clinicians to predict disease earlier and with more precision.”
While additional research is needed to fully understand the clinical implications, this study represents a significant step forward in our understanding of heart health. It demonstrates that when it comes to the heart, shape matters – and sometimes, what makes a heart different is exactly what makes it telling.
Paper Summary
Methodology
The researchers analyzed CMR images from 45,683 UK Biobank participants using automated image analysis software. They created detailed 3D models of each participant’s heart and used a statistical technique called principal component analysis to identify the main patterns of shape variation. The team then performed genetic analyses to identify DNA variations associated with these shape patterns and examined their relationships with various cardiovascular diseases.
Key Results
The study identified 11 principal components that explained 83.6% of heart shape variation in the population. They found 43 genetic regions significantly associated with heart shape, with 14 being previously unknown. Shape variations were significantly associated with various cardiovascular diseases, particularly atrial fibrillation and heart failure. Genetic risk scores based on these findings showed consistent predictive value across different ethnic groups.
Study Limitations
The study primarily included participants of European ancestry, limiting its generalizability to other populations. The shape analysis was based on automated computer measurements, which could introduce some technical variations. Additionally, the findings are observational, meaning they show associations but cannot prove direct cause-and-effect relationships.
Discussion & Takeaways
This research introduces a new way of thinking about cardiac risk assessment by incorporating 3D shape analysis. It suggests that heart shape could be an important early indicator of cardiovascular disease risk, potentially allowing for earlier intervention. The genetic findings provide new insights into how heart shape develops and could lead to new therapeutic targets.
Funding & Disclosures
The study was supported by multiple institutions including the Wellcome Trust, the Engineering and Physical Sciences Research Council, the Medical Research Council, and the National Institute for Health Research. One researcher reported receiving consulting fees from various pharmaceutical companies, while the remaining authors declared no competing interests.
