Recent findings by the Smidt Heart Institute based on deep learning analysis of medical images suggest, that one’s likelihood of developing atrial fibrillation and heart muscle disease can be predicted by the shape of their heart as well as certain genetic indicators.
What Determines Heart Shape?
It’s crucial to first understand what affects how your heart is shaped. Although age, lifestyle choices, and underlying medical issues can all have an impact, heredity still plays a significant role in determining the shape of your heart. While some people may have normal longer hearts shaped like the traditional Valentine’s heart, and others may have unusual round hearts shaped like baseballs shaped hearts.
The Impact of Heart Shape on Health
According to recent studies, your general health may be impacted by the structure of your heart. Discovering whether you’re susceptible to two prevalent heart conditions is possible by analyzing your heart’s shape, as suggested by medical experts. The study found that people whose hearts are longer and shaped more like the traditional Valentine’s Day heart are less likely to develop heart failure and atrial fibrillation later in life than those whose hearts are round, like baseballs. Hence, examining the shape of your heart could provide valuable insights into your risk of developing such conditions.
The study published in Med—Cell Press utilized sophisticated imaging analysis and deep learning techniques to examine the genetic makeup of the heart’s structure. The outcomes were quite revealing.
Why Does Heart Shape Matter?
According to research, atrial fibrillation, a disorder in which the heart beats irregularly, has been linked to a 31% greater chance of development in people with spherical hearts. Additionally, these people had a 24% increased chance of developing the cardiac illness cardiomyopathy.
After analyzing cardiac MRI scans of 38,897 healthy individuals in the UK Biobank, researchers made an important discovery regarding the risk of cardiac conditions. By utilizing computational models on the same dataset, the researchers were able to identify specific genetic indicators in the heart that are associated with these conditions.
By studying spherical traits at a genetic level, researchers have discovered a correlation between four specific genes and the development of cardiomyopathy. These genes are PLN, ANGPT1, PDZRN3, and HLA DR/DQ. The researchers found that the first three genes were likewise associated with an increased incidence of atrial fibrillation.
Atrial fibrillation, the most frequently occurring type of irregular heart rhythm, significantly raises the likelihood of an individual experiencing a stroke. By 2030, it’s predicted that 12.1 million Americans will have this ailment, which is on the increase.
Cardiomyopathy is a type of cardiac muscle disease that makes the heart work harder to pump blood throughout the body, which might eventually cause heart trouble. The four primary kinds of cardiomyopathy, namely dilated, hypertrophic, arrhythmogenic, and restrictive, impact nearly one in every 500 grown-ups.
Cedars-Sinai heart specialists have discovered that the shape of an individual’s heart transforms over the course of time, becoming more circular as time passes, particularly following a significant cardiac incident such as a heart attack.
The initial indication of a disease could be a transformation in the form of the heart. To prevent two diseases that have the potential to alter one’s life drastically, it is imperative to comprehend how the heart changes in response to illness, in conjunction with dependable and user-friendly imaging techniques that reinforce this understanding.
The results offer additional insight into the possible utilization of cardiac imaging for the identification and prevention of various illnesses. The authors also highlighted the significance of conducting more research in this area.
Conclusion
The availability of big biobanks containing cardiac imaging data has revolutionized the way we analyze and characterize variations in cardiac structure and function. We can now measure cardiac metrics more quickly and completely than ever before because of recent technological developments like deep learning and computer vision. This could prove invaluable in identifying genetic variations that impact the heart, potentially decades before any observable symptoms of heart disease manifest.
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Dr. Tamanna Anwar is a Scientist and Co-founder of the Centre of Bioinformatics Research and Technology (CBIRT). She is a passionate bioinformatics scientist and a visionary entrepreneur. Dr. Tamanna has worked as a Young Scientist at Jawaharlal Nehru University, New Delhi. She has also worked as a Postdoctoral Fellow at the University of Saskatchewan, Canada. She has several scientific research publications in high-impact research journals. Her latest endeavor is the development of a platform that acts as a one-stop solution for all bioinformatics related information as well as developing a bioinformatics news portal to report cutting-edge bioinformatics breakthroughs.
