Polygenic Risk Scores Predict Heart Disease Across Diverse Populations

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NGS technology has enabled researchers to epidemiologically analyze DNA sequences by quickly deciphering mass quantities of genetic information in a short amount of time. [Heart illustration: iStock/SvetaP DNA double helix: iStock/Kagenmi]

A new study confirms that the whole-genome approach for predicting heart disease in people who have never had a heart attack works and can be used in populations other than the ones used to develop them. The methods involve calculating a polygenic risk score (PRS) based millions of variants identified by genome-wide association studies of people with known heart disease.

According to the study’s authors, findings like this are critical to the eventual widespread clinical use of PRSs for assigning heart disease risk and implementing prevention strategies. The researchers point out that the availability of large human genetic datasets, such as the UK Biobank, now allows for using data from more than 100,000 individuals to perform genome-wide association studies (GWAS), create PRSs, and validate them.

In the current study, researchers tested two previously published PRSs for coronary artery disease (CAD) based on GWAS data from European populations on a different, though ancestrally related, population.

“Our results indicate that CAD PRS developed in European-ancestry individuals perform quite well in the genetically and environmentally homogenous French-Canadian population. How well these same PRS would predict CAD in a more diverse European-ancestry population, or in a population living in a very different environment, remain critical open questions for further investigation,” the authors wrote in the paper published in the 11 June 2019 edition of Circulation: Genomic and Precision Medicine, an American Heart Association journal.

First published last year, PRSs for heart disease are simple and relatively inexpensive to use in a clinical setting. Heart disease in particular seems to be a good use of PRS because early detection can allow for the use of interventions, like statins and aspirin, for prevention.

“PRSs, built using very large data sets of people with and without heart disease, look for genetic changes in the DNA that influence disease risk, whereas individual genes might have only a small effect on disease predisposition,” said Guillaume Lettre, Ph.D., in a press release. Lettre is the lead author of the study and an associate professor at the Montreal Heart Institute and Université de Montréal in Canada. “The PRS is like having a snapshot of the whole genetic variation found in one’s DNA and can more powerfully predict one’s disease risk. Using the score, we can better understand whether someone is at higher or lower risk to develop a heart problem.”

The researchers calculated both GPSCAD and metaGRSCAD in French-Canadian individuals from three cohorts totaling 3639 heart disease cases and 7382 controls. Both GPSCAD and metaGRSCAD are published GWAS-based methods for calculating polygenic risk scores. GPSCAD is based on 6.6 million genetic variants, while metaGRSCAD is based on 1.7 million.

The researchers validated previous findings that these PRSs could predict heart disease. However, they found that the PRSs did not do as well in predicting heart attacks in people who had previously had one. The authors speculate that PRS performance could have been impact by the facts that many of the participants in their study were older and 76 percent of them were already on statins.

Lettre and his colleagues acknowledged in the press release that more research needs to be done before PRSs for heart disease can go mainstream. The next step, they said, is to test the genetic scoring systems long term in large clinical studies. The question will be whether or not managing and treating people based on individual PRSs improves heart health outcomes. Future research will also need to look at how best to combine PRSs with other known risk factors in treating patients.

The authors also wrote that the utility of PRSs is likely to increase as the research community continues to improve methods and gain access to large GWAS carried out in populations of different ethnic backgrounds.

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