The Power of Polygenic Risk Scores in Personalised Medicine

Polygenic risk score (PRS) is an important and increasingly discussed topic in the field of genetics. It has the potential to revolutionize personalized medicine by providing valuable insights into an individual’s genetic risk for certain diseases. PRS is calculated using a combination of independent risk variants associated with a particular disorder, as identified through genome-wide association studies (GWAS) [1].

In the past decade, GWAS has shed light on the role of inherited variants in numerous non-communicable polygenic disorders, including heart disease, cancer, and even personality traits and talents. Unlike single variants, which do not account for disease onset, PRS takes into consideration the cumulative effect of multiple risk alleles or mutations carried by an individual for a specific disease. This personalized score offers a unique disease risk assessment tailored to each person’s genetic makeup [2].

It is crucial to note that while an individual may have an increased risk for one disease, they may have a low or average risk for other conditions. PRS serves as a valuable tool in routine healthcare practices, enabling the identification and prediction of medical conditions. For instance, by incorporating PRS and genome analysis, some women may discover they have a high genetic risk score for breast cancer even before the age of 47, the current threshold for mammogram screening [2]. This empowers them to take early interventions and make personalized decisions regarding further testing.

Research on heart disease involving 290,000 participants revealed that PRS identified 8% of them as having three times the normal risk of experiencing a heart attack. Unfortunately, this elevated risk would not have been detected through normal clinical practice without genetic testing [3]. Similarly, in the case of Alzheimer’s Disease, PRS modification could lead to a difference of up to ten years in disease onset between individuals with the lowest and highest PRS values [4].

It is essential to acknowledge that PRS only assesses genetic inheritance and does not account for other factors such as age, previous illnesses, environment, and lifestyle, which also contribute to disease risk [2]. Furthermore, interpreting PRS results can be complex and may require input from genetic counselors or medical professionals with expertise in genetics. Additionally, PRS values may differ among different populations. Non-European populations, for instance, have distinct ancestry and carry different genetic variations that can impact their PRS values [5]. As more GWAS studies are conducted, PRS will provide a more accurate estimate of an individual’s risk.

Despite these challenges, PRS holds immense potential for advancing the fields of genetics and personalized medicine. By providing a more nuanced understanding of an individual’s genetic risk profile, PRS can facilitate early detection and treatment of diseases, ultimately leading to improved health outcomes. However, it is important to approach PRS with caution and ensure its ethical and responsible use to maximize benefits while minimizing potential harm.

References
  1. Centre for Disease Control and Prevention (2016). Polygenic Risk Scores, CDC, Retrieved from: https://www.cdc.gov/genomics/disease/polygenic.htm.
  2. Lewis, C. M., & Vassos, E. (2020). Polygenic risk scores: from research tools to clinical instruments. Genome medicine, 12(1), 1-11.
  3. Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., ... & Kathiresan, S. (2018). Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nature genetics, 50(9), 1219-1224.
  4. Desikan, R. S., Fan, C. C., Wang, Y., Schork, A. J., Cabral, H. J., Cupples, L. A., ... & Dale, A. M. (2017). Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score. PLoS medicine, 14(3), e1002258.
  5. Hao, L., Kraft, P., Berriz, G. F., Hynes, E. D., Koch, C., Korategere V Kumar, P., ... & Lebo, M. S. (2022). Development of a clinical polygenic risk score assay and reporting workflow. Nature medicine, 28(5), 1006-1013.