Posted on January 10, 2024

By Krystal Redman (KR), DrPH, MHA, (they/she), Executive Director

The Polygenic Risk Score: Necessary but Not Sufficient for Targeting Prevention Strategies

In the session titled Prevention, Early Detection, and Interception, Dr. Suzette Delaloge, MD, MSc, Head of Interception Programme, Institut Gustave Roussy Villejuif, Ile-de-France, France, provided a presentation titled What Is Polygenic Risk Score & How Is It Used?

The overarching question asked during this session was, “Can we predict the risk of cancer and aggressive cancer?” Dr. Delaloge began by giving an in-depth presentation on polygenic risk scores (PRS) and how they could potentially be used in “preventative” decision-making. And, of course, I intentionally placed the word in quotes as we know at BCAction and within the breast cancer movement that prevention is not an individualized treatment plan and decision. We understand that prevention has everything to do with addressing the root cause of the disease AND that working to prevent breast cancer through lifestyle choices ignores the hard fact that we don’t all share equal access to those choices. Importantly, making healthy choices and trying to shop our way to prevention are not going to address the environmental links to the breast cancer epidemic. Nonetheless, the presenter of this session began by discussing PRS and their use.

What is the PRS?

The PRS is a tool used in genetics to estimate an individual’s genetic predisposition to a particular trait or disease. In the context of breast cancer risk prediction, a PRS is used to assess the combined effects of multiple genetic variants associated with breast cancer.

Here’s how PRS is generally used in breast cancer risk prediction:

  1. Genetic Variants: Numerous genetic variants, often single nucleotide polymorphisms (SNPs), have been identified through genome-wide association studies as being associated with an increased or decreased risk of breast cancer.
  2. Weighted Score: Each genetic variant is assigned a weight based on its strength of association with breast cancer. The combined value of these weighted variants is calculated to generate an individual’s PRS.
  3. Population Risk: The individual’s PRS is then compared to that of the general population to assess whether that individual has a higher or lower genetic risk of developing breast cancer compared to the average.
  4. Integration With Other Risk Factors: The PRS is often used in combination with other risk factors, such as family history, hormonal factors, and lifestyle factors, to provide a more comprehensive assessment of breast cancer risk.
  5. Clinical Application: The PRS is increasingly being integrated into breast cancer risk prediction models to provide more personalized risk assessments. This information can be valuable for guiding screening recommendations, “prevention” strategies, and decision-making regarding interventions.

While complex diseases have been shown to be linked to numerous DNA variants that either increase or decrease the risk, a PRS provides an assessment of disease risk relative to that of the general population.

Dr. Delaloge stated that “the relative impact of one SNP (a type of genetic variation that occurs when a single nucleotide [A, T, C, or G] in the DNA sequence is altered) is small. The combined effect of multiple risk variants as captured by the PRS may be much greater and therefore provide risk discrimination that is clinically useful.”

Breast cancer PRS are among the most promising regarding potential clinical utility

Having more SNPs in the PRS modestly improves the prediction; however, adding clinical data to the PRS increases the discrimination! (Risk Score Discrimination: This refers to the ability of a model to effectively distinguish between different levels of risk based on certain criteria.)

Dr. Delaloge also clarified that the finding “SNPs improve risk score discrimination in most models” suggests that SNPs have a positive impact on the ability of various models to differentiate or discriminate between different risk scores. In the context of genetics or medical research, this statement might mean that incorporating information about SNPs into risk assessment models enhances the models’ ability to discriminate or predict risk more accurately. This could be relevant in areas such as disease risk prediction, where understanding genetic variations can contribute to a more comprehensive risk assessment.

Dr. Delaloge further stated that only PRS313 was associated with more favorable tumor features in studies conducted by the Breast Cancer Association Consortium (BCAC) and the MINDACT trial. PRS313 is a PRS composed of 313 common genetic variants and was linked to more favorable characteristics in breast cancer in the context of those studies. In my review of the ethnic demographics of this study, it is clear that these studies mostly recruited white participants, which causes concern that findings may not be readily applicable to other ethnic groups. For wider generalizability, the studies need to account for ethnic differences.

What is the proposed solution? Population-specific design of clinical studies is required for a valid estimation of breast cancer risk. The proposed strategy is to extend current screening to PRS-defined highest-risk quintiles for all cancers. Further, data on clinical utility may be obtained from randomized controlled trials such as the WISDOM Study and MyPeBS.

However, beyond the use of PRS in screening, can prevention be stratified by PRS? Based on the above findings, the presenter proposes the use of PRS in prescribing prevention medication and asserts that PRS may help refine cancer risk assessment in moderate gene carriers.

The major remaining gaps are related to the partial transferability of these findings across ethnicities and, consequently, the risk of inequity. More research is needed to exploit the functional effect of PRS on breast cancer risk for a more personalized approach to prevention in the future.

Dr. Delaloge suggested that PRS may be useful in determining lifestyle changes — for instance, exercising more, consuming less sugar, etc. The presenter’s overall recommendation was to combine PRS with mammography data, and then determine the need for in-clinic counseling and genetic testing based on PRS score and mammography/imagery data.

While the PRS can be a powerful tool, it has limitations. It does not account for all possible genetic and environmental factors, and its predictive value may vary among different communities and populations. Additionally, PRS is just one component of a comprehensive breast cancer risk assessment.

It’s important to note that PRS is primarily used in research and, to some extent, in clinical settings. The field of genetics and risk prediction is dynamic, with ongoing research to identify new genetic variants and improve the accuracy of risk assessments. Individuals concerned about breast cancer risk, especially those with a family history or other risk factors, should consult with healthcare professionals, such as genetic counselors or oncologists, who can provide personalized risk assessments and guidance based on a combination of genetic, familial, and clinical factors. But it is not enough to rely on risk stratification tools to target “prevention strategies.”

Working to prevent breast cancer through lifestyle choices ignores the hard fact that we don’t all share equal access to those choices, and making healthy choices and trying to shop our way to prevention are not going to address the environmental links to the breast cancer epidemic. If we are to address the root causes of this disease, it is imperative that we pursue the large-scale systemic changes that are necessary. This disease is not going to be prevented by eating better and working out. If we are going to talk about prevention, then let’s truly talk about it!