Understanding the link between genetics, cholesterol and coronary artery disease

Cardiovascular disease is the leading cause of death worldwide, with recent estimates putting the global death toll at around 18 million each year. It is also a major burden on populations and health systems, contributing to a reduction in the quality of life for millions of people and treatment costs of billions of dollars. We know a lot about the drivers of cardiovascular disease (CVD). Years of research have implicated the key roles that physical activity, cholesterol control, BMI, smoking and associated diseases like diabetes play in an individual’s risk of suffering the adverse effects of CVD.

There is also a genetic component to heart disease. Family history of CVD is widely used as a risk factor and several well-known pathogenic variants influence risk. Recently, genome-wide association studies have identified thousands of genome-wide variants that are associated with cardiovascular disease risk, and seminal papers from Khera and colleagues at the Broad Institute and Inouye and colleagues at the University of Cambridge have developed Polygenic Risk Scores (PRS) for Coronary Artery Disease (CAD) — a subset of CVD — showing the potential for genome-wide assays of variation to be used to identify those individuals at high risk of CAD.

Building on this work, we developed a new PRS for CAD that had just been published in Circulation. The aim of this work was to explore how PRS — which is not routinely measured — and clinical risk factors — which are — work together to determine an individual’s risk for CAD. Our new PRS outperformed those of these two leading groups, and we used the PRS to stratify the population into high, intermediate and low PRS groups. Crucially, we found that the effect of Low-Density Lipoprotein Cholesterol (LDL-C) on an individual’s risk of heart attack depends on their polygenic background. Technically, we found a statistically significant interaction between LDL-C and PRS.

Our finding shows that the effect of LDL-C on an individual’s risk of developing a heart attack differs based on their underlying genetics. Those in the highest PRS group, who had LDL-C between 130 and 160 mg/dL, for example, had the same increased risk as individuals with hypercholesterolemia (LDL-C>190 mg/dL) and average PRS.

Our paper shows the effect of LDL-C on CAD risk is different depending on whether an individual has Low, Intermediate or High PRS (Figure from Bolli et al 2021)

What this means is that LDL-C on its own is not enough to identify individuals at high risk of CAD. Moreover, there is no one safe level of LDL-C: the same level of LDL-C will affect people differently, depending on their genes. So LDL-C measurement is a blunt instrument, but it’s one that can be sharpened by PRS to provide precision to medicine and to identify individuals who are at high risk of disease but who are unaware and invisible to current risk assessment strategies. And, although other clinical risk factors can affect an individual’s CAD risk, in our study, LDL-C was the only one which we found interacted with PRS.

Although more work is needed to understand the mechanism behind this interaction, one avenue to explore relates to recent work that showed that individuals with high PRS are more affected by atherosclerotic than those with ‘normal’ CAD PRS levels.

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