Polygenic Risk Scores are increasingly being integrated into clinical practice across healthcare systems in the United States and Europe.
Learn about how PRS is used as a cutting-edge tool for precision genomic risk prediction, empowering healthcare providers to provide better patient outcomes through data-driven disease risk management.
PRS identify more patients at high risk of disease
Polygenic Risk Scores identify significant proportions of patients at high genetic risk for a range of common diseases, including coronary artery disease, breast cancer, prostate cancer, Alzheimer's Diesease and Type 2 Diabetes. Crucially, many of these high genetic risk patients are currently undetected by traditional risk models which fail to account for the critical influence of our genes on disease risk. By relying solely on family history, other clinical risk factors, and occasionally whether an individual carriers a rare pathogenic mutation, many patients at high risk will remain undetected.
Integrating PRS into risk assessments is changing genomic medicine
Current risk assessments used in clinical practice provide patients with an assessment of their risk for complex disease by accounting for a limited set of risk factors, such as smoking status, age, BMI, family history, and in a few cases, presence of rare pathogenic mutations. While these factors play a role in overall risk by additionally taking PRS into account, physicians are able to give patients a more complete and accurate understanding of their individual risk for disease.
What's more, recent research has revealed that an individual's PRS can critically interact with clinical risk factors. For example, PRS modulates the effect on lifetime breast cancer risk conferred by carrying a pathogenic mutation in BRCA1/2 and other moderate impact genes. Another example is LDL cholesterol and PRS for coronary artery disease (CAD), where understanding an individual's overall risk of disease depends on assessing PRS to help define a safe cholesterol level. Accounting for all relevant factors, including PRS, is therefore key to providing patients with a comprehensive assessment of their personalised lifetime risk of disease.
PRS explains the genetic cause of disease
A major limitation of existing genetic assessments for complex diseases is that they are unable to explain the cause of the disease, even when this is genetic. For example, rare pathogenic mutations in major breast cancer susceptibility genes such as BRCA1/2, ATM, CHEK2 and PALB2 explain fewer than 5% of all breast cancer cases. Although not all of the remaining 95% of cases are the result of genetic causes, PRS enables physicians to identify up to 20% of women with breast cancer where high genetic risk has caused her disease. Being able to understand and explain the cause of disease to patients is crucial not only in providing holistic patient care, but also in disease risk management for the patient and their family.
Combining genetic with clinical risk leads to better absolute risk assessment
One of the most revolutionary advances in genomic risk assessment is the ability to integrate a range of factors into absolute risk models. The models developed by Allelica include a range of rare pathogenic mutations and polygenic risk factors, combined with traditional risk factors. Not only does this provide patients with a precise, more complete understanding of their risk, but it also enables physicians to more effectively manage risk in across the lifetime of their patients.
Genetic risk is actionable: with Allelica’s absolute risk calculator, physicians can help patients to visualize how changing modifiable risk factors lowers their absolute disease risk, empowering individuals to use this understanding of their genetics to take control of their health through lifestyle changes and therapeutic interventions.
PRS inform primary prevention strategies
With genomics-integrated disease risk assessments in hand, physicians can improve the prevention of disease in primary care. A critical advantage of PRS integration is its power to inform more appropriate and effective primary prevention in healthcare, ultimately reducing the impact of common disease on patients and their families, accelerating the move to a truly personalized and preventative approach to healthcare.
Downloadable Use Cases 