Amit V. Khera, MD, MSc, associate director of the Precision Medicine Unit at the Massachusetts General Hospital Center for Genomics Medicine and the Cardiovascular Disease Initiative at the Broad Institute, discusses the potential impact of polygenic scores.
Until recently, genetic research has focused heavily on mutations in a single gene to predict susceptibility to disease. But this monogenic approach identifies only small numbers of people at risk. For example, a familial hypercholesterolemia mutation triples the risk for coronary artery disease but is found in only 0.4% of the population. So researchers are investigating a new way to assess genetic risk that may have broader impact: polygenic scores, which are based on millions of genetic variants identified through large genome-wide association studies (GWAS). By scanning genotype arrays from an individual, researchers can see which variants are present and calculate that person’s polygenic risk of disease.
Amit V. Khera, MD, MSc, the associate director of the Precision Medicine Unit at the Massachusetts General Hospital Center for Genomics Medicine and the Cardiovascular Disease Initiative at the Broad Institute, is currently working with Sekar Kathiresan, MD, to better understand monogenic and polygenic drivers of cardiovascular health. Dr. Khera answered three questions about what a polygenic score is, how it could potentially improve patient care, and how it may influence drug development.
Interview edited and condensed for clarity.
The polygenic model recognizes that most diseases are caused by the cumulative effect of multiple genetic variations. Each of these variants may affect risk by only a small amount, but in aggregate, their clinical impact can be substantial. A polygenic score is an estimate of a person’s cumulative genetic susceptibility to a given disease.
What is striking is that these individuals often fly under the radar in clinical practice. Patients can have a high polygenic score for heart disease, yet their cholesterol levels and other traditional risk factors may be normal.
For example, in a paper published last year, we analyzed data from the UK Biobank, which includes clinical and genetic information about hundreds of thousands of participants. We found that 8% had a polygenic score that conferred triple the normal risk of coronary artery disease. Yet their cholesterol, blood pressure, and other conventional risk factors were similar to the other participants.
In a study of people hospitalized at an early age for heart attacks, we found that nearly one in five had a polygenic score that more than tripled their heart attack risk. Yet, they could not be identified based on conventional risk factors.
Fortunately, DNA is not destiny. A polygenic score offers an opportunity to really impact someone’s health. You can quantify a person’s polygenic score at birth. If we disclose the risk, we might be able to empower patients to make changes that improve their chances of remaining healthy. For example, research shows that people at high polygenic risk for coronary artery disease can reduce their risk and even avoid heart disease by adopting a healthy lifestyle or taking a statin to lower cholesterol.
One barrier to making this actionable is that patients aren’t familiar with the concept of polygenic scores. That’s why we’re working to build a preventive genomics clinic at Mass. General, which will have physicians and genetic counselors equipped to counsel patients at high polygenic risk about how to prevent disease in the future.
Another big challenge is the lack of diversity in genetic studies, which overwhelmingly involve people of European descent. As a result, polygenic scores are somewhat more accurate for white people than for Asians, African-Americans, and other ethnic groups.
Drug development targets one specific pathway that is being perturbed in a disease. That’s not possible with polygenic risk, which involves multiple pathways that differ among individuals.
But the polygenic model offers some advantages. We are now doing molecular profiling of people who are either at very low or very high polygenic risk for a disease to find biomarkers that distinguish them from other people. This could have implications for clinical trial design in the future.
Think about Alzheimer’s disease. We understand a lot about the biology of the disease, but essentially, all of the drugs have failed in clinical trials. The leading hypothesis is that we are intervening too late, and if we could identify people at risk earlier, then maybe the drugs would show a benefit. A polygenic score is one mechanism to identify people at risk decades before they develop the disease. We’re not there yet, but the field is moving fast.
Continue the conversation with us @HMS_ExecEd or with Dr. Khera @amitvkhera.
— Ann MacDonald