Scientists at the Broad Institute have discovered that it isn’t enough just to test for mutations to find coronary artery disease, breast cancer or colorectal cancer—instead, it’s also critical to test for the many small changes across the genome to produce polygenic risk scores (PRS).
The findings are presented in a new study, published Aug. 20 in Nature Communications, and led by the Broad Institute of MIT and Harvard, Massachusetts General Hospital, and by San Francisco-based genetic testing company, Color.
Amit Khera, M.D., associate director of the Broad Institute’s Program in Medical and Population Genetics and leader of a research group within the Center for Genomic Medicine at Massachusetts General Hospital and senior author on the study, said he will soon begin offering patients testing based on the findings.
Khera is working with a team of geneticists and genetic counselors in the hospital’s Preventive Genomics Clinic to offer a clinical test developed by Color that assesses both monogenic and polygenic risk for heart disease.
“This research has real clinical implications for genome interpretation,” Khera said. “We’ve found that the traditional approach of only looking for monogenic risk variants misses an important part of the picture. A person’s polygenic risk also plays a crucial role in predicting the development of disease. I suspect that evaluating both will soon become standard in clinical practice.”
For the study, researchers focused on breast cancer, coronary artery disease, and colorectal cancer because each disease is associated with what the Centers for Disease Control and Prevention considers a tier 1 genomic condition, meaning there are specific genetic mutations associated with higher risk for developing the condition, according to researchers.
“The relationship between the mutations that cause these three genomic conditions and the risk of developing each disease is relatively well understood,” authors of the study said. “But until now, few researchers have investigated how the interplay between these monogenic variants and someone’s polygenic risk affects the likelihood of developing disease.”
For the study, researchers reviewed genetic information from 80,928 individuals who either participated in case-controlled Color or U.K. Biobank studies, to find the presence of monogenic variants and a patient’s polygenic risk. The risk score was determined to “significantly affect” the likelihood of developing a disease associated with a tier 1 genomic condition.
“Think about a monogenic variant as a brick,” said Julian Homburger, a Color data scientist and co-first author of the paper. “A polygenic risk score, then, is like stacking sheets of paper. You can still get to the same size—in this case, the likelihood of developing a disease—it’s just a different mechanism. And, what we show is that if you have both of these, they stack on top of each other and contribute to an even greater risk.”
Alicia Zhou, CSO at Color and co-author of the paper said the next logical step after testing patients is to monitor them closely, with earlier and more frequent screening. “The current approach to screening for genomic conditions is fairly crude,” she said. “With better information about the risk of genomic diseases, we can refine screening and treatment for people, and hopefully improve patient outcomes.”