PRS Only Marginally Better than Established Methods of Predicting Heart Disease

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Unrecognizable businessman having chest pain and heart attack

A research study conducted at UT Southwestern Medical Center and published this week in JAMA suggests that using polygenic risk scores (PRS) to determine which patients have the highest risk of developing coronary heart disease (CHD), did not improve prediction compared with conventional risk assessment tools.

Identifying elevated risk for CHD as early as possible can help patients avoid potentially fatal events, such as heart attacks, through lifestyle changes and preventive treatments like cholesterol-lowering statins. According to the American Heart Association, CHD is the leading cause of death worldwide, killing an estimated 3.8 million men and 3.4 million women each year.

The study was led by Thomas J. Wang, M.D., the Donald W. Seldin Distinguished Chair in Internal Medicine at UT Southwestern, who noted his research was suggested by an August 2018 paper published in Nature Genetics that detailed how genetic variations of individuals at more than 6 million points in their DNA were associated with those who had already suffered a heart attack. But while the study looked back at events that had already taken place, Wang said the study was inconclusive as to whether examination of these variations could also be predictive of future events and whether there is a greater value in PRS than more traditional risk assessment tools.

“Genetics is an important determinant of familial diseases and a key tool for understanding human biology, and the idea that genetics may also be important for predicting common diseases has been a source of excitement over the past several years,” noted Wang.

To conduct the study, Wang and colleagues collected data from two long-running, longitudinal studies of heart disease and heart health: the Atherosclerosis Risk in Communities (ARIC) study and the Multi-Ethnic Study of Atherosclerosis (MESA). Due to the fact that the PRS calculator for CHD/ was developed using genetic data from people of European descent, the team only included this population in their study.

Using this framework, they extracted data on more than 7,300 patients ranging from 45 to 79 years old and ran their information through a risk calculation tool developed collaboratively by the American College of Cardiology and the American Heart Association—known as the 2013 ACC/AHA Pooled Cohort Equations—and the polygenic risk calculator for these study volunteers at baseline. They then compared how these two methods of determining risk identified which individuals experienced cardiac events over an average of about 15 years.

While the results showed a strong association between polygenic risk scores and CHD, with those scoring highest on this calculator at baseline most likely to experience cardiac events over the follow-up period, the results were roughly the same using the ACC/AHA calculator. Although the polygenic risk calculator reclassified about 5% of individuals to a higher or lower risk category, many of these classifications didn’t match who developed CHD or not.

“As an everyday clinical tool for predicting cardiovascular risk, human genetics isn’t there yet,” Wang concluded. “We should not lose sight of traditional risk factors for assessing risk of cardiovascular disease, counseling about that risk, and strategizing on reducing it.”

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