In a recent study published in the journal Nature Communications, researchers found hundreds of new links between people’s DNA and the heart’s electrical activity.
The results could one day lead to advanced screening methods to discern who is at greatest risk of developing the disease, and could help reveal new genetic targets for research and drug development.
The study is from the Queen Mary University of London and Harvard. One author is Professor Patricia Munroe.
Over the past 10 years, researchers have identified many genetic factors that contribute to—or protect against—the onset of specific heart diseases.
However, it has been difficult to find genetic factors associated with arrhythmias—one of the most common forms of heart disease where the heart beats abnormally.
In the study, the team looked at data from 293,051 people across the world.
They examined the individual genomes and their measurements on an electrocardiogram—one of the oldest and most widely used heart diagnostic tests.
They specifically checked the length of time between two points on the electrocardiogram read-out known as the “PR interval,” which is linked to a number of common electrical disorders such as atrial fibrillation and other arrhythmias.
The findings reported 202 locations in the genome with links to this type of electrical activity in the heart—141 of which had not been previously identified.
This more than triples the number of known genetic regions linked to this type of electrical activity and explains about 62 percent of its heritability.
This is the largest global study to test the genetic basis of the PR interval—a well-established electrocardiogram risk marker for heart disease and mortality.
The insights provide new knowledge on biological processes relating to the heart’s electrical activity and potential avenues of drug research for preventing and treating heart conditions.”
The findings suggest that an individual’s inherited predisposition to heart disease is not the result of single-gene mutations, but rather a cumulative effect of many variants across the genome.
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