NSGC’s PRS Practice Resource: Your PRS one-stop shop

Emma Perez, Genetic Counselor

Allelica
3 min readFeb 3, 2023

This year was kicked off by the publication of the NSGC Practice Resource for Clinical Counseling/Translation of Polygenic Scores, put together by Wand et al. — a stellar team of leaders in the PRS field. With the increasing use of PRS in the research and clinical setting, this resource has the goal of increasing genetic counselors’ and other healthcare providers’ understanding and comfort with PRS in personalized medicine.

The paper begins with a detailed yet simplified description of PRS development and validation methods and emphasizes that PRS are most appropriate for diseases with higher heritability. (Heritability is a term that describes how well the differences in people’s genes explain for differences in their traits — including disease risk). Applying PRS to conditions with higher heritability makes intuitive sense because we know that genetics is is one of the factors that contributes to the risk.

When thinking about assessing PRS performance, although there exists no threshold for good versus acceptable performance of a PRS, it’s very important that those developing PRS be transparent with their metrics. PRS studies and reports should include information about the datasets used in validation including case/control counts specific to ancestry group, and performance metrics such as AUC, confidence intervals, odds ratios, etc. (Wand et al., 2021).

One of the key points was that clinical utility from prospective studies has not been demonstrated for all disease areas at this time, however the authors discuss the personal utility of PRS, where there is existing data to demonstrate positive outcomes. Research demonstrating improved clinical outcomes, such as disease prevention and/or earlier diagnosis is crucial to define clinical utility, is on-going. For example, the NIH-funded eMERGE study recently published their marker paper in Genetics in Medicine that aims to inform the benefits of integrated genetic risk assessment into routine health care (Linder et al., 2023).

One of the main counseling points when discussing PRS with patients is to make clear that PRS is not deterministic and there are many other factors that can contribute to disease risk. If someone is at the top end of a PRS distribution, this will not always lead to disease and so PRS will never be close to 100% penetrant like some other monogenic conditions.

Ideally, we would communicate absolute risk with patients, but unfortunately this is easier said than done as it requires population data with age, sex, and racial group prevalence and/or validated integrated risk models. When communicating relative risk to patients, it will be critical to contextualize this with population prevalence. For example, if a 50-year-old woman has a 2-times increased risk to develop atrial fibrillation based on a PRS score, the risk increases from 0.1% to 0.2% because the prevalence for a 50-year-old woman is only 0.1%.

A final and most essential issue covered by the authors is a review of the ELSI (ethical, legal, and social implications) surrounding PRS, with a focus on how to further prevent healthcare disparities in communities of color when implementing PRS. A key point articulated is the difference between genetic ancestry and race which are often conflated, and there are clear recommendations for next steps that the genetics community can take to improve the performance of PRS, but also the field of genomics as a whole.

The many nuances of PRS described in this practice resource make it all the more important that PRS clinical reporting is thoughtfully executed. The first time a provider reads about PRS in a clinical setting may very well be through a patient report that is in the medical record. It is imperative that these reports not only provide results, but act as a resource for patients and providers.

For more information on polygenic risk score testing and result communication, get in touch with Allelica at info@allelica.com.

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Allelica

Allelica is a Software Genomics Company developing algorithms and digital tools to accelerate the integration of Polygenic Risk Score in the clinical practice