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A new study shows CT scans are more effective at estimating heart disease risk during mid-life compared to genetic testing. Urs Siedentop & Co/Stocksy
  • Assessing an individual’s risk of developing cardiovascular disease is essential for prevention.
  • Traditional risk markers, such as blood pressure and cholesterol, are not always accurate measures for predicting heart disease at the individual level.
  • Researchers are exploring new risk markers such as the coronary artery calcium score and the polygenic risk score.
  • A new study suggests that adding the coronary artery calcium score, as opposed to the polygenic risk score, to traditional risk markers can help doctors assess individual coronary heart disease risk more accurately in middle-aged and older adults.

On average, someone in the United States dies of cardiovascular disease (CVD) every 34 seconds.

Yet the World Health Organization (WHO) estimates that over 75% of early cardiovascular disease cases are preventable.

To minimize the risk of heart disease, it’s important for doctors to assess an individual’s risk factors, particularly for coronary heart disease (CHD). This is done using risk models that take into account various factors, including age, sex, blood pressure, cholesterol levels, diabetes status, and smoking status.

Earlier this year, the 20-year results of the Heinz Nixdorf Recall (HNR) study showed that individual risk prediction is improved by the addition of coronary artery calcification to the traditional risk score. However, no studies to date have directly compared coronary artery calcium and polygenic risk scores in the same cohort.

To address this knowledge gap, researchers at Northwestern University Feinberg School of Medicine analyzed data on both risk scores from two cohorts of middle-aged to older adults from the United States and the Netherlands.

They compared the change in coronary heart disease risk prediction when a coronary artery calcium score, a polygenic risk score, or both were added to a traditional risk factor-based model.

The findings were published in JAMA on May 23.

Risk models help doctors to determine whether treatments like lipid-lowering therapy or lowering blood pressure are necessary based on the level of cardiovascular disease risk.

But these conventional risk scores do not always provide accurate estimates and new risk markers for coronary heart disease are being explored.

One such marker is coronary artery calcium (calcium plaque in the walls of coronary arteries), which is a strong predictor of future coronary heart disease and can be detected using computed tomography (CT) scans.

In addition, research has shown that genetics play an important role in the development of coronary heart disease.

Another approach for determining a person’s risk of developing the condition is the use of polygenic risk scores, which calculate coronary heart disease risk based on a person’s genes.

The present study included data from two observational population-based studies involving White individuals ages 45 to 79, who did not have coronary heart disease at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Rotterdam Study (RS), conducted in the U.S. and the Netherlands respectively.

Only individuals of European ancestry were included in the Northwestern study due to previous evidence suggesting that the polygenic risk score performs better in European populations.

Furthermore, participants with missing data or those taking lipid-lowering therapy at the beginning of the study were excluded, resulting in a final analysis population of 1,991 MESA participants and 1,217 RS participants.

Lead researcher Dr. Sadiya S. Khan, an assistant professor of medicine and preventive medicine at Northwestern University, and her team assessed coronary heart disease risk based on traditional risk factors.

They used the 2013 ACC/AHA Pooled Cohort Equations (PCEs) to calculate the predicted 10-year risk of atherosclerotic cardiovascular disease for each participant. This risk prediction model considered factors such as age, sex, smoking status, blood pressure, cholesterol levels, diabetes status, and hypertension treatment.

Then, they evaluated coronary heart disease risk using the coronary artery calcium score and the polygenic risk score for each participant.

In both the MESA and RS studies, the occurrence of coronary heart disease events, including myocardial infarction, angina, resuscitated cardiac arrest, and death from coronary heart disease, was monitored through in-person examinations approximately every 18 months and annual telephone follow-up conversations.

Finally, Dr. Khan and coworkers conducted statistical analyses to examine the association between coronary heart disease risk predictors (PCEs, coronary artery calcium score, and polygenic risk score) and the actual occurrence of coronary heart disease.

The median age was 61 years in MESA and 67 years in RS.

The results showed that both the coronary artery calcium score and the polygenic risk score were significantly associated with a 10-year risk of coronary heart disease: 2.60 times higher risk per standard deviation (SD) increase for coronary artery calcium score, and 1.43 times higher risk per SD increase for polygenic risk score.

The researchers used a statistical measure called the C statistic to assess the ability of the coronary artery calcium score and the polygenic risk score to predict the risk of coronary heart disease. The C statistic for the coronary artery calcium score was 0.76, indicating moderate predictive ability, and for the polygenic risk score, it was 0.69, indicating slightly lower predictive ability.

When the coronary artery calcium score was added to the traditional risk factors, there was a significant improvement in risk prediction (an increase in the C statistic of 0.09).

However, when the polygenic risk score was added, the improvement was smaller (an increase in the C statistic of 0.02). When both scores were added, there was a larger improvement (an increase in the C statistic of 0.10).

The researchers obtained similar results when they repeated the analyses with age-stratified subgroups, and with longer-term follow-up data from the MESA study (median 16.0 years).

Dr. Joseph F. Polak, MPH, professor of radiology at Tufts University School of Medicine, who is involved in the MESA study, said he was not surprised by these results. He explained to Medical News Today:

“This is likely an example of what we commonly refer to as vascular age. Basically, a person is as old as their arteries. In this case, a direct measurement of the ‘age’ of the artery trumps genetics.”

Dr. Raimund Erbel, professor emeritus of medicine and cardiology at Essen University Hospital and the University of Duisburg-Essen, and principal investigator of the Heinz Nixdorf Recall Study, also agreed with the conclusions of this study and described CT as “a wonderful tool for individual cardiovascular[r] risk prediction” in his comments to MNT.

When asked to comment about the implications of these findings, Dr. Erica Spatz, associate professor of cardiology and epidemiology at Yale University, told MNT that “this study validates our current approach to cardiovascular risk assessment, whereby a calcium score can meaningfully up- or down-grade a person’s cardiovascular risk, especially when that risk is greater than 7.5%.”

Dr. Spatz explained that “calcium scores can enhance shared decision-making discussions about how aggressive to be with prevention, including decisions about statins and other lipid-lowering agents, LDL targets, and overall lifestyle goals.”

“Polygenic risk scores are the new kid on the block for risk stratification; they impart additional information about a person’s cardiovascular risk, but we are still trying to figure out their place in clinical practice,” Dr. Spatz added.

Dr. Karol E. Watson, PhD, professor of medicine and cardiology at the David Geffen School of Medicine at the University of California Los Angeles, warned that the findings are “not definitive” since the study is limited to “a specific population” and “specific polygenic risk scores.”

“What this study says is that in white participants enrolled in 2 observational studies, identifying coronary calcium predicted future cardiac events better than our currently available polygenic risk scores. This doesn’t mean that CAC [coronary artery calcium] predicts better than genetics. It only mean[s] that CAC predicted incident events better than the specific polygenic risk scores they used in these specific white populations.”

– Dr. Karol E. Watson, PhD, professor of medicine and cardiology, UCLA

Prof. Dr. Michiel L. Bots, PhD, professor of epidemiology of cardiovascular disease at UMC Utrecht, remarked that evidence of the usefulness of adding the coronary artery calcium score to traditional risk markers “has been available for certainly a decade.”

However, Dr. Bots noted there will always be some low risk individuals who may experience a cardiovascular event, while some higher-risk individuals, such as those with high levels of coronary calcium, may not.