GRS, also known as polygenic risk scores, are instruments used to measure an individual’s genetic susceptibility to particular diseases or disorders. They are developed by evaluating a person’s genetic data, generally through genome-wide association studies (GWAS), to find genetic variations linked to a specific condition.
A recent study examined 926 polygenic risk scores for 310 illnesses. It discovered that just 11% of persons who acquire the disease are diagnosed on average, while 5% of people who do not develop the disease test positive. Unaffected people frequently outnumber those who are affected, resulting in considerably more false positive forecasts than actual positive predictions.
According to a new study lead by UCL (University College London) researchers, polygenic risk scores, which quantify a person’s illness risk based on thousands or millions of common genetic variants, perform poorly in screening and prediction of common diseases such as heart disease.
Polygenic risk scores, it has been suggested, will revolutionize the prognosis and prevention of common diseases. Companies that provide polygenic risk score testing services have already emerged. Testing for polygenic risk scores is also one of the goals of the national Our Future Health project.
The new study, published in BMJ Medicine, looked at 926 polygenic risk scores for 310 diseases. It found that, on average, only 11% of individuals who develop a disease are identified, while at the same time 5% of people who do not develop the disease test positive. Unaffected people usually outnumber those affected which results in far more false than true positive predictions.
Polygenic risk scores appear appealing because genotyping is now inexpensive, the same for all diseases, and is performed only once because a person’s genotype does not change. These features, however, are meaningless if the test is useless.
Dr Jasmine Gratton
Lead author Professor Aroon Hingorani (UCL Institute of Cardiovascular Science) said: “Strong claims have been made about the potential of polygenic risk scores in medicine, but our study shows that this is not justified.
“We found that, when held to the same standards as employed for other tests in medicine, polygenic risk scores performed poorly for prediction and screening across a range of common diseases.”
For the new study, researchers examined data from the Polygenic Score Catalog, an open-access database, to establish what the detection rate and false positive rate of the scores would be if utilized in screening. The risk scores indicated just 10% and 12% of eventual cases of breast cancer and coronary artery disease, respectively, using a cut-off that resulted in 5% of unaffected persons testing positive.
The researchers also looked into how polygenic risk scores would function when combined with traditional screening approaches. They discovered that, when combined with traditional risk variables, several thousand people would need to have a polygenic risk score performed to guide statin prescriptions in order to avoid one more heart attack or stroke. The researchers emphasized that without the requirement for genetic testing, using age alone as a guide to statin prescription would be easier and more successful at preventing heart attacks and strokes.
They also discovered that using polygenic risk scores as first-stage screening to determine who should be prioritized for mammography would miss the majority of women who eventually developed breast cancer and result in many false positives, increasing the load on healthcare systems.
Co-author Professor Sir Nicholas Wald (UCL Institute of Health Informatics) said: “It has been suggested that polygenic risk scores could be introduced early on to help prevent breast cancer and heart disease but, in the examples we looked at, we found that the scores contributed little, if any, health benefit while adding cost and complexity.”
In the paper, the researchers suggest regulation of commercial genetic tests based on polygenic risk scores to “protect the public from unrealistic expectations and already stretched public health systems from becoming overburdened by the management of false positive results.”
Consumers of commercial polygenic risk score tests, according to the researchers, should be informed of the detection rate and false positive rate of the polygenic risk scores, as well as the absolute risk with and without a polygenic score result, in order to properly determine if the test is effective.
“Polygenic risk scores appear appealing because genotyping is now inexpensive, the same for all diseases, and is performed only once because a person’s genotype does not change,” stated co-author Dr Jasmine Gratton (UCL Institute of Cardiovascular Science). These features, however, are meaningless if the test is useless.”
Sir Nick Wald, professor of epidemiology, said: “Our results build on evidence that indicates that polygenic risk scores do not have a role in public health screening programs.”
According to the researchers, the performance of polygenic risk scores is unlikely to alter significantly because the variations with the greatest influence have already been found. Polygenic risk scores should not be confused with genetic testing for specific gene variants such as BRCA1 and BRCA2, which are significant in breast and ovarian cancer screening.
The scientists emphasized that discovering variants associated with a higher risk of disease is still critical for medication development because the variants encode proteins that can be targeted with treatments that would be effective for everyone regardless of genetic makeup.
