Researchers optimize genetic testing of diverse populations to address health disparities

To prevent new genomic technologies from contributing to health disparities, the scientific team has devised a new way to improve genetic testing methods called polygenic risk scores. Because polygenic risk scores are not valid for all populations, researchers recalibrated these genetic tests using ancestrally diverse genomic data.

As reported in natural medicineoptimized testing allows for a more accurate assessment of disease risk across diverse populations.

Genetic testing looks for small differences between a person's genome, known as genomic variations. Polygenic risk scores are tools that evaluate many genomic variations across the genome to determine a person's risk of disease. As the use of polygenic risk scores increases, one of the major concerns is that the genomic datasets used to calculate the scores often significantly overrepresent people of European descent.

“Recently, an increasing number of studies have incorporated multi-ancestral genomic data into the development of polygenic risk scores,” said Dr. Niall Lennon, a scientist at the Broad Institute in Cambridge, Massachusetts, and lead author of this publication. said. “However, there are still gaps in genetic ancestry representation in many of the scores developed to date.”

These “gaps” or missing data can lead to erroneous results. This means that a person may be at high risk for a disease but not receive a high-risk score because the genomic variation is not expressed. Although health disparities are often due to systemic discrimination rather than genetics, these spurious results may mean that inequitable genetic tools can exacerbate existing health disparities.

In the new study, researchers used health records and ancestrally diverse genomic data from the All of Us Research Program, an initiative that collects health data from more than 1 million people from diverse backgrounds. , improved existing polygenic risk scores.

The “All of Us” dataset represents approximately three times as many individuals with non-European ancestry compared to other major datasets previously used to calculate polygenic risk scores. It also included eight times as many individuals with ancestry spanning two or more world populations. Robust representation of these individuals is important because they are more likely than other groups to receive misleading results from polygenic risk scores.

Researchers selected polygenic risk scores for 10 common health conditions, including breast cancer, prostate cancer, chronic kidney disease, coronary heart disease, asthma, and diabetes. Polygenic risk scores are particularly useful for assessing the risk of conditions that result from a combination of several genetic factors, as is the case for ten selected conditions. Many of these health conditions are also associated with health disparities.

Researchers assembled an ancestrally diverse cohort of people with and without each disease from the All of Us data. Genomic variations in these cohorts allowed researchers to recalibrate polygenic risk scores for individuals with non-European ancestry.

The researchers used the optimized score to analyze disease risk in a group of 2,500 ancestrally diverse people. About one in five participants were found to be at high risk for at least one of the 10 diseases.

Most importantly, these participants had a wide range of ancestry backgrounds, showing that the recalibrated polygenic risk score was not biased towards people of European descent and is valid for all populations. .

“Our model significantly increases the likelihood that people in the high-risk end of the distribution will receive a high-risk outcome, regardless of their genetic ancestry,” Dr. Lennon said. “The diversity of the All of Us dataset was key to doing this.”

However, these optimized scores alone cannot address health disparities. “Polygenic risk score results are only useful for patients who can take steps to prevent disease or detect disease early, and people with less access to health care may need more frequent screening.” It will also be difficult to receive recommended follow-up activities such as Dr. Lennon.

Still, this study is an important step toward the routine use of polygenic risk scores in clinical practice to benefit everyone. His 2,500 participants in this study are just the beginning stages of an improved polygenic risk score. NIH's Electronic Medical Records and Genomics (eMERGE) Network will continue this research by enrolling a total of 25,000 participants from an ancestrally diverse population in the next phase of the study.