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Study highlights the potential of polygenic risk scoring
There are well-known risk factors for several of the most common health disorders these days—BRCA mutations can increase your chances of breast cancer, high cholesterol boosts the likelihood of heart disease and high blood sugar could put you at risk for diabetes. Doctors use such lifestyle and genetic risk factors to advise preventive measures, but what if there was a way to predict the likelihood of diseases in advance of the development of symptoms?
A team of scientists from the Broad Institute of MIT and Harvard, Massachusetts General Hospital (MGH) and Harvard Medical School are looking to answer just that question, and have a new approach to genome analysis that could be a solution. They used polygenic risk factor screening to determine individuals' likelihoods of developing any of five diseases, and recently published their work in a Nature Genetics article titled “Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.”
“We’ve known for long time that there are people out there at high risk for disease based just on their overall genetic variation,” said senior author Sekar Kathiresan, who is director of the Cardiovascular Disease Initiative at the Broad Institute, director of the Center for Genomic Medicine at MGH and a professor of medicine at Harvard Medical School. “Now, we’re able to measure that risk using genomic data in a meaningful way. From a public health perspective, we need to identify these higher-risk segments of the population so we can provide appropriate care.”
Kathiresan led this study, along with with Amit V. Khera, a cardiologist at MGH and junior faculty member in Kathiresan’s lab, and Mark Chaffin, a computational biologist in Kathiresan’s lab, both of whom were first authors on the paper.
Per a Broad Institute press release by Karen Zusi, the research team distilled data from large-scale genome-wide association studies (GWAS) in search of genetic variants linked to any of five diseases: coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease (IBD) or breast cancer. The genes highlighted for each disease were processed with a computational algorithm to aggregate information from all gene variants into a single polygenic risk score. The algorithms were then evaluated against data pulled from the UK Biobank for more than 400,000 individuals.
“Over the last 10 years, we've been able to find many variants that affect people's risk for diseases such as heart attack,” Khera explained in a Broad Institute video. “But it's important to note that any one variant typically increases your risk by maybe 2 or 3 percent, so its power in prediction is actually quite modest. We then asked the question, what if you combined all the common variants that are present in the population? And it turns out that if we combine all 6.6 million variants together and weight them appropriately, we're able to get what we call a polygenic risk score. So polygenic risk score is really aggregating information from all these sites of DNA information that we're born with into a single risk factor.”
In looking at breast cancer risk, the team found that of the screened individuals with the highest polygenic risk scores, 19 percent had breast cancer, compared to about 4 percent among the other test subjects.
In the case of coronary artery disease, the results showed that 8 percent of the individuals from the UK Biobank were more than three times as likely to develop coronary artery disease. Eleven percent of individuals with the highest polygenic scores had coronary artery disease, compared to only 0.8 percent of those with the lowest scores. The press release also noted that according to Khera, individuals with high risk scores didn't always present with traditional signs of coronary artery disease such as hypertension.
“These individuals, who are at several times the normal risk for having a heart attack just because of the additive effects of many variations, are mostly flying under the radar,” he remarked. “If they came into my clinical practice, I wouldn’t be able to pick them out as high risk with our standard metrics. There’s a real need to identify these cases so we can target screening and treatments more effectively, and this approach gives us a potential way forward.”
As noted in a press release penned by the Broad's Leah Eisenstadt, Kathiresan predicts polygenic risk scoring for heart attack risk could be clinically available in roughly a year, and could perhaps be widely adopted in less than 10 years.
“Ultimately, this is a new type of genetic risk factor,” he said. “We envision polygenic risk scores as a way to identify people at high or low risk for a disease, perhaps as early as birth, and then use that information to target interventions—either lifestyle modifications or treatments—to prevent disease. For heart attack, I foresee that each patient will have the opportunity to know his or her polygenic risk number in the near future, similar to way they can know their cholesterol number right now.”
More work needs to be done to fully determine the efficacy and potential of this approach. For one thing, the authors pointed out that their results were based on data from the United Kingdom, and therefore was limited to people of European descent. According to Eisenstadt's piece, “As of 2009, 96 percent of GWAS participants were of European descent; that number fell to 81 percent in 2016, mostly due to the inclusion of participants of East Asian descent, but there is still a lack of African and Hispanic representation.”
“Lack of diversity is the primary scientific and ethical limitation we currently face in translating these polygenic risk scores into the clinical space,” postdoctoral researcher Alicia Martin commented in a Broad Institute press release. Martin and Broad institute member Mark Daly, co-director of the Broad’s Medical and Population Genetics Program, are hoping to tackle this issue by running GWAS studies on more diverse populations.
Still, despite the work that needs to be done to fine-tune this screening approach, the authors are strongly in support of polygenic risk scoring going mainstream.
“A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies,” they write in the paper's abstract. “Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation ... We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.”