Coronary Artery Disease: Predicting risk through genetics

5 min readJun 22, 2020

Within the last two decades, and upon completion of the world’s largest biological project in 2003, interest in the human genome and its effect on health and disease risk has soared. Mapping of the human DNA sequence has allowed for the identification of fundamental errors in the genetic code that facilitated the prediction and thus preventative treatment of disease.

Coronary artery disease (CAD) is the most prevalent form of heart disease across the globe with more than 18 million people over the age of 20 living with the condition. CAD presents with multiple complications and places a significant burden on community and healthcare. The primary target is prevention of the disease in high risk individuals, with current risk factors for diagnosis including hypertension, hyperlipidemia, diabetes, overweight or obesity, smoking history, low physical activity levels, nutrient-poor diet and chronic stress.

Family history of CAD is another well recognised factor that is used to identify those at a higher risk of its development, with 40–60% of cases being suggested as a risk relating to shared environment and genetic heritability. It is this genetic heritability of CAD that offers an interesting perspective on how to further go about predicting at-risk populations, and implementing primary prevention strategies to reduce the incidence of disease.

We know that genetic inheritance plays a role in lifetime risk of disease, however, it is rare to observe isolated high risk genetic mutations. More common are genetic variants that confer small risks, which when considered in isolation may not present much clinical relevance, but what about when we look at these variants in an individual collectively?

While genes don’t dictate the disease, and we need to consider traditional risk factors of disease, the study of genetic variants in an individual with high risk of CAD may provide direction for targeted therapeutic interventions and promote change in lifestyle patterns as a means to reduce the risk of developing the disease in addition to improving outcomes associated with the condition.

Polygenic Risk Score in CAD

Typically, genetic variants have been found to only explain around 20% of CAD heritability based on risk allele loci as observed from information supplied by large genome-wide association studies (GWAS). It has, however, been purported that there is an unexplained portion of risk that still needs to be taken into account in at-risk populations, or to discover true risk in certain individuals that may not necessarily present with clinical risk.

Polygenic Risk Score (PRS) provides a more accurate measure of an individual’s genetic predisposition to disease. Because diseases are often polygenic, in that a large number of genetic variants may contribute to its development, it is necessary to be able to identify what the association is to a specific variant and classify it according to the degree of risk it represents.

PRS allows for consideration of many common variants, which cumulatively, predict high risk of disease in a much larger population when compared to taking only the rare monogenic mutations into account. PRS may also provide information relating to the prediction of CAD events in presence of traditional risk factors, which include poor lifestyle and non-optimal low density lipoprotein cholesterol. Additionally, research has shown that this type of aggregated risk score may help to determine the risk of recurrent events in CAD patients, and improve the identification of patients who may respond to pharmaceutical treatments such as statins or blood-thinning medication versus those who would not.

Datasets are ever expanding, which allows for millions of variants to be assessed in very large populations and a greater number of disease-associated variants to be identified. This expansion has been shown to allow for a far more accurate development of PRSs, predicting CAD better than the traditional risk factors considered in isolation.

The population under the curve

Using PRS, it has been proposed that as much as 8% of the population has a greater than three-fold risk of CAD, which would have been difficult to predict as many of these individuals do not present with any of the high-risk mutations or clinical factors that precede a diagnosis. With PRS, many common variants of small effect are collectively taken into account, which allows many more people to be categorized as at-risk. Preventative interventions, such as pharmaceutical and dietary/lifestyle changes that influence common CAD risk factors like hyperlipidemia and hypertension, for example, may be implemented early, which not only attenuates the higher cumulative risk of more serious outcomes, but does so in a more cost effective manner by sparing long-term, more intensive medical care.

Even in the event of insignificant clinical findings, those individuals who currently fly under the radar but who have a very high genetic risk of CAD, may benefit from early and intensive preventative therapies as a means to reduce the incident rate of the disease.

The PRS system also allows for simultaneous calculation of risk by taking rare monogenic mutations into account, and in doing so, provides clinical evidence for therapeutic interventions, even aggressive forms of treatment, should they be deemed necessary based on an individual’s requirements and genetic variability.

With PRS being based on DNA and not on traditional risk factors, risk can be quantified at any stage of life in an individual, which provides greater potential for early screening, and thus early intervention of prevention well before traditional risk factors may become obvious.

Taking into account the sum of the effect of specific variant alleles in an individual, which have previously been detected using data collected and analysed through GWAS, the PRS is computed and compared to those of an entire population. When considered alongside established conventional risk factors for CAD, an individual’s fixed nature germline DNA may be leveraged to predict or anticipate their trajectory of their lifetime CAD risk. For a condition that has proven preventative measures, PRS allows for the implementation of early interventions and strategic management of this chronic and devastating disease.

Originally published at on June 22, 2020.




Allelica is a Software Genomics Company developing algorithms and digital tools to accelerate the integration of Polygenic Risk Score in the clinical practice