While lifestyle choices and environment can impact risk, genes are often what most affect how likely a person is to develop a disease. People commonly have different versions of a gene throughout a population, and some of these versions are associated with an increase in disease risk. Polygenic risk scores consider these gene variations and can provide a measurement of a person's risk for a specific disease. This can give people a better idea of how likely they are to develop a specific condition so they can take steps to prevent it, diagnose it earlier, and decide how to treat it. In this blog, we'll provide an overview of polygenic risk scores and how they support treatment development and personalised healthcare.
Understanding polygenic risk scores
DNA is composed of four chemical bases: adenine (A), thymine (T), cytosine (C), and guanine (G). Everybody possesses nearly identical DNA sequences within their genome, which is made up of approximately 3.2 billion base pairs. However, genomic variations do occur at specific points within our DNA, which is what makes us different from each other. The order and number of the bases determine the information content of each gene; genomic variants occur where this code diverges among individuals.
Each individual's genome contains roughly 4 million of these variants. Some may be exclusive to a specific person, while others are shared among a larger population. These variants can either heighten the risk of developing certain diseases, mitigate such risk, or have no impact on disease susceptibility.
Scientists often classify genetic diseases into two categories: single-gene diseases and complex diseases. Single-gene diseases trace their origins to variants in a single gene. For example, cystic fibrosis results from mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene on chromosome 7. Complex diseases, on the other hand, arise from numerous genomic variants combined with environmental factors like diet, sleep, stress, or smoking. These are often referred to as "polygenic" diseases due to their multifactorial nature.
While not in widespread clinical use yet, polygenic risk scores are used to determine a person's risk of developing one of these complex diseases. The essential concept is to combine the effect of thousands of genetic variants with individually small influences to create a composite score. Scientists will consider all variants relating to a particular condition to work out how many of them add to the person's risk and how many do not. They can then provide a score, which is essentially a measurement of the likelihood of whether someone will develop the disease or not. Knowing how likely a disease is helps people take steps to prevent it or find it earlier when it is easier to treat. Polygenic risk scores can also be combined with other factors to help predict how a disease will progress and how well a patient will respond to a treatment.
Benefits and potential pitfalls
Knowing polygenic risk scores not only predicts disease risk, but also drives diagnostic refinement, encourages risk-reducing behaviours, and improves population screening. On the drug development side, understanding the genetic links to disease susceptibility is critical in identifying therapeutic targets. Using polygenic risk scores offers a promising way to support drug development for more personalised medicines.
However, there are concerns about the reliability and precision of polygenic risk scores in clinical settings. Because there are many variants which may be linked to undiscovered diseases and there are diseases with a lack of related variants, polygenic risk scores are limited in what they can tell us. Additionally, there is a risk of misinterpretation and misuse of polygenic risk scores, both within the medical community and society at large. Risks include not properly communicating the limits of polygenic risk scores, not providing appropriate counselling and action steps, and the potential for genetic discrimination.
To leverage the potential benefits of polygenic risk scores responsibly and ethically, certain key issues need to be addressed. This includes the development of best practices, effective risk communication, and regulatory frameworks that ensure the judicious use of polygenic risk scores in medical practice and beyond.
Case in point: Cardiovascular disease
Cardiovascular diseases, particularly coronary artery disease, are great examples of conditions wherein polygenic risk scores can be very useful. These complex conditions are influenced by numerous genomic variants dispersed across the genome. For example, researchers have identified approximately 60 genomic variants associated with coronary artery disease, and they do not cluster on a specific chromosome.
In the context of cardiovascular disease, polygenic risk scores have provided valuable insights into predictive biomarkers. A study by Khera et al. in 2018, involving over 250,000 individuals from the UK Biobank, revealed that 8% of the population had polygenic risk scores indicating a threefold or greater increased risk of coronary artery disease.
Integrating polygenic risk scores with conventional risk factors, like blood pressure and cholesterol levels, also enhances screening for coronary artery disease and stroke. For example, incorporating polygenic risk scores has been shown to improve the detection rate of at-risk individuals and prevent additional cardiovascular events. In the pursuit of cardiovascular drug development and other medicines, polygenic risk scores offer the potential to refine risk assessment, guide treatment choices, and optimise prevention strategies, ultimately leading to improved patient outcomes.
The future of drug development with polygenic risk scores
By identifying individuals at higher risk for diseases based on their genetic profiles, polygenic risk scores can lead to more targeted, effective, and personalised therapies. While polygenic risk scores can be incredibly helpful for drug development, their uptake within the development phase is currently hindered by challenges. Aside from the previously noted issues around reliability, communication, and discrimination, information about how each genetic change affects disease risk also comes from large-scale genetic studies like genome-wide association studies (GWAS), which leads to several issues. For instance, diversity within these studies is limited, and information derived from one population might not be universally applicable. However, if research is more inclusive for communities underrepresented in research, this could help us understand variations better and make polygenic risk scores more useful across populations.
It's likely that polygenic risk scores will become a more routine part of clinical practice, but it'll be important to address issues like access, insurance coverage, and the responsible sharing of results across healthcare systems. However, as we collect more information from genetic testing and research and we learn more about the links between variants and disease, polygenic risk scores are poised to play a pivotal role in shaping the personalised medicine of the future.
Conclusion
In summary, polygenic risk scores can be really insightful for understanding a person's disease risk. This can help them, in partnership with their healthcare provider, to take proactive steps towards disease prevention, early diagnosis, and tailored treatment. While polygenic risk scores are likely to play a greater role in drug development in the future, there are challenges hindering their uptake.
Diversity, data quality, and regulatory considerations are among the hurdles that must be addressed to make polygenic risk scores a routine part of clinical practice. Aside from this, polygenic risk scores don't take into account other factors that can influence disease risk, so should be used in conjunction with other tests and surveys to ensure a comprehensive view of a patient's overall health to determine actual risk.
To learn more about polygenic risk scores and other foundational elements of genetics, please download our guide: "Genetics essentials for clinical research professionals."
