HAMILTON, ON — A new study suggests that a polygenic risk score based on 182 genetic variants that are weakly associated with CAD can help predict whether a person has a high risk for early-onset coronary disease.[1]
The test would detect five times as many patients as would a genetic test for familial hypercholesterolemia (FH), according to the authors of a report, led by Dr Sébastien Thériault (Laval University, Quebec City, QC), published January 8 in Circulation: Genomic and Precision Medicine.
“What is quite exciting to me as a clinician is that the number of people with this high polygenic score is actually much higher than the number of people with one of these [FH] mutations for an equal risk of disease,” senior author, Dr Guillaume Paré (McMaster University, Hamilton, ON), told theheart.org | Medscape Cardiology.
Dr Guillaume Paré
In the study, 1 in 53 people in the cohort had a polygenic risk score associated with a 3.7-fold increased risk for early-onset CAD, the same risk increase associated with the presence of an FH variant, which has a 1 in 256 prevalence, according to report.
“This test is identifying a larger segment of the population than just the people who have classical hypercholesterolemia,” agreed Dr Kiran Musunuru (University of Pennsylvania, Philadelphia), who is executive editor of the journal publishing the report, in an interview.
And, importantly, “it’s capturing a different segment of the population who may have increased risk of heart attack for reasons other than cholesterol,” Musunuru said.
The researchers acknowledge that the findings would need confirmation in other studies but say this type of polygenetic risk score could potentially be part of the clinical workup for patients with early-onset CAD.
Because it is “independent of known risk factors,” they write, the risk score “could be used to better stratify a patient’s risk and guide management.” It also might heighten patients’ motivation to follow secondary prevention recommendations or increase screening of relatives.
In an accompanying editorial,[2] Dr Themistocles L Assimes (Stanford University School of Medicine, Palo Alto, CA) and Dr David M Herrington (Wake Forest School of Medicine, Winston-Salem, NC) caution that the study “highlights how much more needs to be done to translate knowledge of genetic risk into our ultimate goal of eradication of cardiovascular disease.”
This genetic risk score, they write, “is not the first, nor will it be the last to demonstrate incremental risk prediction over earlier risk models. The challenge now is less about finding additional improvements in prediction and more about whether clinicians and patients armed with this additional information are able to make decisions that produce fewer events.”
A 182-Variant Genetic Risk Score
The researchers calculated a genetic risk score based on the presence of 182 independent high-risk variants in 111,418 participants in the UK Biobank cohort, who were aged 40 to 69 years when recruited from 2006 to 2010.
Of those in the cohort, 96 persons (77 men and 19 women) were identified with early-onset obstructive CAD, defined as self-reported MI or angina and a history of coronary revascularization at age 40 years or younger for men and 45 years or younger for women.
The early-onset CAD group, compared with the remaining participants, who acted as controls, showed a significantly higher mean multigene genetic risk score (11.21 vs 10.88; P<0.0001).
The researchers then applied the genetic risk scoring to a “local cohort” of 30 patients recruited at the Hamilton Health Sciences Heart Investigation Unit between 2014 and 2016. These patients had early-onset CAD as defined for the UK Biobank cohort and were of European descent, but they didn’t have secondary potential causes of CAD, such as insulin-requiring diabetes, chronic kidney disease, morbid obesity, or use of corticosteroids, cocaine, or amphetamine.
Compared with the controls from the UK Biobank cohort, patients in the local cohort also had a significantly higher mean multigene genetic risk score (11.23 vs 10.88; P=0.001).
Seven participants in the local cohort had a genetic risk score that was associated with a more than 2-fold greater risk for early-onset CAD; one of them showed a 6.1-fold increased risk.
Future Clinical Implications
This is a proof-of-concept study, and the group believes that the polygenic risk score can be improved further to make it more predictive, Paré said. With the current findings and other research, he said, the test could potentially become part of routine screening in clinical practice.
Most individuals with a high genetic score also had a high burden of classical risk factors for CAD, according to Paré. “To me that also shows that probably having a genetic predisposition by itself might not be quite sufficient in most individuals, and I think that also stresses the importance of not neglecting classic risk factors and healthy lifestyle, despite the genetic risk,” he added.
He called that “a hopeful message” because it means that if someone who has “bad luck in the genetic lottery” adopts healthy lifestyle habits, “there’s a lot that someone can do to minimize that risk.”
On the other hand, some patients with early-onset CAD without classic risk factors, apart from smoking, had a very high multigene risk score.
As a provider, if the risk score is known for such a patient, Musunuru said, “you could say, ‘Look, you have a very compelling reason not to smoke; you’re at high genetic risk. It doesn’t mean that you are necessarily going to get the disease, but if you want to avoid getting a heart attack, you’re going to have to pay very close attention to diet and lifestyle. Don’t go anywhere near tobacco; don’t even be exposed to second-hand smoke.'”
As for future use of the genetic risk score, potentially “we could measure this in individuals as part of preventative screening,” Paré said. “If we do find that someone has this high polygenetic burden, we make sure we treat this person aggressively in terms of prevention of having a heart attack in their 30s, 40s, or 50s.”
The study was funded by the Canadian Institutes of Health Research, a Canada Research Chair in Genetic and Molecular Epidemiology, and a CISCO Professorship in Integrated Health Biosystems. The authors, editorialists, and Musunuru have no relevant financial disclosures.
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