APR 06, 2022

Mobile App Predicts Genetic Risks for Coronary Artery Disease

WRITTEN BY: Ryan Vingum

Coronary artery disease (CAD) is the most common form of heart disease, affecting about 18 million adult Americans each year. There are numerous causes of CAD and heart disease, including diet and lifestyle factors. 

There is also a genetic component to CAD, with some people simply having a higher genetic propensity to plaque and cholesterol building up in arteries. In response, significant advances have been made in recent years to map the specific genes associated with CAD and the nature of the risk they pose.

A new study published in Nature Digital Medicine outlines efforts to create a mobile app that uses genetic information to predict a user's genetic risk for CAD.

Using the wide availability of online genetic testing services, the application pulls data from sources like 23AndMe to build a comprehensive genetic risk factor analysis. Upon creating this genetic analysis, the app shares a user's risk factor, noting whether their risk is high or low. 

The goal is to encourage users to take action as soon as possible. That’s why researchers believe their work could contribute to the early detection of CAD. This is crucial; while CAD affects a lot of people, many don’t know it. For some people, in fact, the first signs of CAD may be a heart attack. Early detection could allow for more timely therapeutic interventions to prevent heart attacks or strokes. 

According to the study published in Nature, that appears to be the case. Following about 721 people, researchers tried to gauge how effective the app was at encouraging users with high genetic risks to take action. A year after receiving their genetic profile, researchers followed up with users to see what they did with that information.

They found that among people with high genetic risk factors for CAD (compared to the low risk users) there was twice the rate of starting new statin treatment, indicating the app could be having a positive effect on promoting early interventions.

Sources: Medgadget; AHA; Nature Digital Medicine