A recent study led by researchers at University College London (UCL) has raised questions about the effectiveness of polygenic risk scores in predicting and screening for common diseases, such as heart disease. These scores estimate an individual’s disease risk based on thousands or even millions of common genetic variants.
Polygenic risk scores have been hailed as potentially transformative tools for disease prediction and prevention, with several companies offering polygenic risk score testing services. The study, published in BMJ Medicine, analyzed 926 polygenic risk scores for 310 diseases and found that, on average, only 11% of individuals who developed a disease were correctly identified, while 5% of those who did not develop the disease tested positive, leading to falser positive than true positive predictions.Â
Lead author Professor Aroon Hingorani from the UCL Institute of Cardiovascular Science noted, “Strong claims have been made about the potential of polygenic risk scores in medicine, but our study shows that this is not justified.” The study found that polygenic risk scores performed poorly when evaluated using the same standards as other medical tests across various common diseases.Â
The researchers used data from an open-access database called the Polygenic Score Catalog to determine the detection rate and false positive rate of these scores if they were used for screening. For diseases like breast cancer and coronary artery disease, the risk scores could only identify 10% and 12% of eventual cases, respectively, with a cutoff leading to 5% of unaffected individuals testing positive.
When the researchers examined how polygenic risk scores would perform alongside conventional screening methods, they found that thousands of individuals would need genetic testing to guide statin prescriptions to prevent one additional heart attack or stroke. In contrast, using age alone as a criterion for statin prescription would be simpler and more effective in preventing cardiovascular events without the need for genetic testing.Â
The study also considered the use of polygenic risk scores as a first-stage screening tool to prioritize individuals for mammography in breast cancer screening. However, this approach was found to miss most women who later developed breast cancer while generating numerous false positives, which would strain healthcare systems.Â
The study’s authors recommend regulating commercial genetic tests based on polygenic risk scores to manage public expectations and prevent overburdening already stretched public health systems with false positive results. They also suggest that consumers of these tests should be provided with information about the detection rate, false positive rate, and the absolute risk with and without a polygenic score result to make informed decisions about the test’s utility.Â
Professor Sir Nick Wald added, “Our results build on evidence that indicates that polygenic risk scores do not have a role in public health screening programs.” It’s important to note that polygenic risk scores are distinct from genetic testing for specific single-gene mutations, such as BRCA1 and BRCA2, which play a critical role in screening for breast and ovarian cancer.
Despite the limitations of polygenic risk scores in screening and prediction, discovering genetic variants associated with disease risk remains crucial for drug development. These variants encode proteins that can be targeted with drugs that have the potential to benefit everyone, regardless of their genetic makeup.Â
Reference Â
Aroon Hingorani et al, Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog, BMJ Medicine (2023). DOI: 10.1136/bmjmed-2023-000554Â
