New York: Scientists have used Big Data to identify more than 150 as-yet unknown genetic risk factors for atrial fibrillation, an advance that could potentially improve early detection and treatment.
Atrial fibrillation — an irregular, often rapid heart rate affecting more than 30 million people worldwide — increases one’s risk for blood clots, stroke, heart failure and death.
For the study, published in Nature Genetics, the team performed one large genome-wide association study (GWAS) comprising data from six smaller studies and identified 151 candidate genes for atrial fibrillation.
Many of the genes identified are important for foetal development of the heart. It implies that genetic variation predisposes the heart to atrial fibrillation during foetal development or that the genetic variation could reactivate genes in the adult heart that normally only function during foetal development.
“We are hopeful that additional molecular biology experiments will determine how to create sustained regular heart rhythms by studying the genes we and others have identified,” said Cristen Willer, associate professor at the University of Michigan (U-M).
If atrial fibrillation is detected early, it is possible to prevent complications such as stroke and heart failure. Current treatment options for atrial fibrillation are limited however, include serious side effects, and are rarely curative.
By identifying genes important for atrial fibrillation, researchers constructed a risk score to help identify high-risk individuals and monitor them accordingly, which “may have important implications for precision health and prevention of cardiovascular disease”, Willer said.
Of the 151 genes identified as important for atrial fibrillation, 32 are likely to interact with existing drugs not necessarily developed to treat atrial fibrillation.
This study lays the groundwork for follow-up experiments to test whether any of the identified drugs could prevent or terminate atrial fibrillation, the researchers said.