researcher Rutgers University New Jersey uses artificial intelligence (AI) to predict when a patient will develop atrial fibrillation (AFib), heart failure, or other cardiovascular disease, and genomics.[1] What is the key to team effort? Evaluation of DNA samples.
Heart disease is the leading cause of death in the United States, accounting for approximately 1 in 5 deaths. According to the CDC—and given its high heritability, a better understanding of the exact role genetics plays could hone our predictions of whether a person is likely to develop heart disease during their lifetime.
The study’s authors began by identifying genes associated with an increased risk of specific cardiovascular complications.they We collected DNA from 10 healthy participants and 61 participants with known heart failure, AFib, or other cardiovascular disease. Ultimately, they found 7 genes highly correlated with heart failure (correlation coefficients ranging from 0.4 to 0.8), 7 genes highly correlated with AFib (correlation coefficients ranging from 0.4 to 0.9), and Seven genes highly correlated with other cardiovascular diseases (correlation scores ranging from 0.5 to 0.8).
The team then used this knowledge to develop an AI model that could predict when patients would be at higher risk for these conditions.
“The successful execution of our model predicted highly significant cardiovascular disease gene associations associated with demographic variables such as race, gender and age.” first author Zeeshan Ahmed,PhD,of Rutgers Institute Health, Healthcare Policy, Aging ResearchSaid and statement.
