By analyzing millions of small genetic differences across a person’s genome, researchers can calculate a polygenic risk score and estimate the probability that a person will develop a particular disease during their lifetime. Over the past decade, scientists have developed risk scores for dozens of diseases, including heart disease, kidney disease, diabetes, and cancer. The hope is that patients will one day be able to use this information to lower their high risk of disease. However, it has been difficult to determine whether such tests would work effectively in all populations and how they could guide clinical decision-making.

Now, a team of researchers from MIT and Harvard’s Broad Institute, in collaboration with 10 academic medical centers across the country, has conducted 10 such tests for use in clinical research. In a study published in natural medicine, the team outlined how they selected, optimized, and validated tests for 10 common diseases, including heart disease, breast cancer, and type 2 diabetes. They also tailored the test for use on people with non-European ancestry.

Researchers collaborated with the National Electronic Medical Records and Genomics (eMERGE) Network to study how patients’ genetic data can be integrated with electronic medical records to improve clinical care and health outcomes. Ten collaborating medical centers enrolled 25,000 participants, and researchers at Broad Clinical Lab, a subsidiary of the Broad Institute, administered polygenic risk score testing to those participants.

“There is a lot of ongoing conversation and debate about polygenic risk scores and their utility and applicability in clinical practice,” said Broad Clinical Institute Chief Scientific Officer and Broad Institute Scientist said Niall Lennon, lead author of the new paper. paper. “With this study, we have taken the first step toward demonstrating the potential strength and power of these scores in diverse populations. In the future, this type of information will be used in preventive medicine and We hope that we can help people take actions that lower their blood pressure’s risk of disease. ”

What’s the score?

Most polygenic risk scores have been developed based on genetic data primarily from people of European ancestry, raising questions about whether the scores are applicable to people of other ancestry.

To optimize polygenic risk scores for a diverse population, Lennon and his colleagues first scoured the literature for polygenic risk scores that had been tested on people with at least two different genetic ancestries. Ta. They also looked for scores that indicate a patient’s risk of a disease that can be reduced through treatment, screening, and/or lifestyle changes.

“It was important that we didn’t give people consequences that were beyond their control,” Lennon said.

The research team targeted the polygenic risk score for atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. diseases were selected.

For each condition, the researchers identified a precise spot in the genome to analyze to calculate the risk score. They verified that they could accurately genotype all of these spots by comparing the test results to the whole genome sequence of each patient’s blood sample.

Finally, the researchers wanted to make the polygenic risk score work across different genetic ancestry. By analyzing data from the National Institutes of Health’s “All of Us” research program, which collects health information from 1 million people of various backgrounds across the United States, they determined how much genetic variation exists among populations. We researched how different they are. The team used that information to create a model for adjusting health outcomes. A person’s polygenic risk score according to their genetic ancestry.

“While it is not possible to correct for all biases in risk scores, it is possible to ensure that people who belong to a high-risk group for a given disease are identified as high-risk, regardless of their genetic ancestry. We can do that,” Lennon explained.

Once this optimization was complete, Lennon’s team at Broad Clinical Labs ended up creating 10 tests that are now being used to calculate risk scores for the 25,000 people enrolled in the eMERGE study. . In collaboration with eMERGE collaborators, they also plan detailed follow-up studies to analyze how polygenic risk scores impact patient health care.

“Ultimately, the network wants to know what it means for a person to receive information that they are at increased risk for one of these diseases,” Lennon said.