A new polygenic risk score for early prediction of coronary artery disease (CAD)

What is Coronary Artery Disease?

Coronary Artery Disease (CAD) is a medical condition that affects the coronary arteries, which are responsible for supplying oxygenated blood to the heart muscle. CAD occurs when these arteries become narrowed or blocked by a buildup of plaque, consisting of cholesterol, fat, calcium, and other substances. This process, known as atherosclerosis, restricts the flow of blood to the heart, depriving it of the necessary oxygen and nutrients.

The narrowing of the coronary arteries can lead to various symptoms, including chest pain or discomfort, known as angina. The severity of angina can range from mild discomfort to intense pressure or squeezing sensations in the chest. CAD can also cause shortness of breath, fatigue, and in some cases, lead to heart attacks or myocardial infarctions, which occur when the blood supply to the heart is completely blocked.

Early detection and prevention are crucial in managing CAD. Regular medical check-ups, screening tests, and risk assessments can help identify individuals at risk, enabling healthcare professionals to intervene and implement appropriate measures to prevent or manage the progression of CAD.

Now, researchers have developed a new polygenic risk score to to predict CAD even before onset. According to results published in Nature Medicine, this method outperformed all previously published methods for assessing CAD risk 1.

What is a Polygenic Risk Score?

A polygenic risk score (PRS) is a numerical representation that combines information from multiple genetic variants associated with a particular trait or disease. It is calculated based on an individual’s genetic profile, usually obtained through genome-wide association studies (GWAS).

The PRS is used to estimate an individual’s genetic predisposition or risk for developing a specific condition or trait by considering the cumulative effects of multiple genetic variants. PRS can be used in research studies, clinical settings, or population screening to assess an individual’s relative risk or likelihood of developing a certain disease or trait based on their genetic makeup.

A new polygenic risk score for CAD

Previously, clinicians have used genetic information to assess the risk of CAD.

In the new method, called GPSMult, researchers combined genetic data from five different ancestral groups across 269,000 CAD cases. They then took into account ten risk factors for CAD to calculate a new polygenic risk score. These risk factors included diabetes, blood pressure and lipid concentrations, among others 1.

GPSMult was strongly associated with CAD in a group of people of European ancestry. It identified 20% of the population with a three times higher risk and 13.9% with a three times lower risk compared to the average.

GPSMult also predicted the risk of future CAD events in healthy individuals, improving the accuracy of risk assessment. The researchers also validated GPSMult across different ethnic groups. They found that it outperformed all previously published methods for assessing CAD risk. They claim that their work demonstrates the potential of using genetic data from diverse populations to improve the prediction of CAD risk.