A new type of genetic test known as a polygenic risk score could change the way clinicians detect and treat chronic illnesses. But to be widely used, genomic findings in large populations first need to be translated into valid clinical tests for individual patients. Then physicians need meaningful interpretations of test data to help make clinical decisions about patient care.
In a study published in Nature Medicine, researchers report details of how they set up a genetic assay for six common diseases and developed explanatory reports to help bridge the gap between science and clinical care.
The assay and reports were created for the GenoVA study, a clinical trial that aims to determine whether polygenic risk scores (PRSs), also known as polygenic scores (PGSs), could be used effectively in a primary care setting. The randomized trial will enroll 1,000 patients at the Veterans Affairs Boston Healthcare System and will follow them for 2 years.
The authors report early data from the new laboratory test. For the 227 participants enrolled so far, 11% had a high risk for atrial fibrillation, 7% were at risk for coronary artery disease, 8% for type 2 diabetes, 6% for colorectal cancer, 15% of men had an increased prostate cancer risk, and 13% of women were at increased risk for breast cancer.
Polygenic scores are promising for informing screening and treatment decisions, with the goal of preventing chronic disease. Jason Vassy, MD, of Brigham and Women’s Hospital and VA Boston, says, “It is important to think of PRS as one risk factor for disease, not a diagnostic test or an indication that an individual will certainly develop the disease.”
He continues, “Most diseases have complex, multifactorial etiologies, and a high PRS is just one piece of the puzzle. PRSs do not replace the traditional risk factors we usually think about in clinical medicine, such as diet and exercise to prevent type 2 diabetes and smoking cessation to lower cardiovascular disease risk.”
Currently, clinical genetic testing is typically performed when a patient is suspected of having a specific disease or a family history of a condition, such as sickle cell disease or breast cancer. Tests for these types of conditions are often monogenic, detecting only select mutations.
PRS tests have the potential to inform clinical decisions years before patients become symptomatic. The PRS testing in this study combines large quantities of genetic information to assess a patient’s risk for multiple conditions. The risk for common chronic conditions can involve hundreds to millions of small genetic variations. Alone, these variations have minimal impact on a person’s risk for disease, but together they can lead to an increased risk for specific conditions.
Certain PRS tests are currently available from direct-to-consumer laboratories, in oncology, and through some clinical trials, but they’re not commonly used in general practice.
Dr. Vassy and colleagues developed and validated PRSs for atrial fibrillation, coronary artery disease, type 2 diabetes, breast cancer, colorectal cancer, and prostate cancer at the Mass General Brigham Laboratory for Molecular Medicine.
The team calculated the final PRS on the basis of individual patient genotyping combined with statistical population models.
In the GenoVA study, adults aged 50-70 years who have no previous history of disease provide saliva or blood for PRS testing at the Boston VA. Participants are stratified by risk result and are randomly assigned to receive test results either immediately or after 24 months.
Enrollees are then followed for 2 years to observe how they and their primary care providers use risk score information and whether any preventive measures or other clinical tests are employed. Guidelines are provided to patients and clinicians throughout the study, along with genetic counseling. Ultimately, the study seeks to determine whether PRS implementation improves health outcomes.
Study participants are from diverse backgrounds: 52% of the first 227 patients report non-White, non-Hispanic ethnicity. To adjust for the fact that most genomic research to date has been based on European populations, researchers used statistical methods to calculate scores across racial groups.