The UK Government has outlined plans to forward their ambitions to achieve better prevention of disease through harnessing technology and moving towards a new personalised prevention model in a new Green Paper on prevention. These plans include building on the UK’s position as a global leader in genomics in healthcare and using advances in this field to improve approaches towards the prevention of common diseases through the use of polygenic scores.
What are polygenic risk scores?
Science has made considerable progress in identifying common genetic variants/single nucleotide polymorphisms (SNPs) that are associated with different common diseases, such as cardiovascular disease, breast cancer, stroke and psychiatric disorders. Individually, each of these variants has only a small effect on disease risk, and so cannot meaningfully contribute to risk prediction. However, researchers have developed methods to aggregate the impact of multiple SNPs and relay this information in the form of a combined polygenic risk score or PRS. Polygenic scores can be calculated for different diseases, and can be used to assess individual risk for particular diseases.
Making use of polygenic risk scores
Over the past few years, excitement over the potential use of PRS for prevention of common diseases has been increasing. Genetic contributions to disease risk are defined at birth, and remain stable throughout the life-course. There is therefore considerable interest in polygenic scores as a biomarker for earlier identification of those at increased risk prior to manifestation of traditional indicators of clinical disease, such as blood pressure or blood glucose levels.
For example, in cardiovascular disease there is evidence that plaque build-up in the blood vessels (atherosclerosis) can begin at an early age (pre-teen) and stay with individuals for life. Individual genetic information could provide the earliest indication of a predisposition to such a build-up, allowing preventative action to be taken in high-risk individuals from a younger age, perhaps even before plaque build-up begins in childhood. Preventative interventions in individuals considered to be at ‘high-risk’ of disease might include closer monitoring, lifestyle adaptation or use of therapeutics.
Meeting the evidence gap
This scenario is appealing, and using PRS in this way could enable a move towards predictive prevention for common diseases. Nevertheless, it is yet to be demonstrated that using genetic information in the form of a PRS can sufficiently classify individuals for successful identification of these high-risk populations or other ‘currently invisible patient populations’ as suggested in the Green Paper.
Furthermore, assuming this evidence is forthcoming, moving towards this model of prevention will also require consideration of the proposed interventions to be offered to individuals identified as being at elevated risk, and subsequent demonstration of the beneficial health impacts of these interventions.
A PHG Foundation project on polygenic risk scores for cardiovascular disease has carefully examined this emerging area, and we have identified the main areas where further information and evidence is needed prior to clinical implementation. The report will be released in the autumn.
Accelerating detection of disease – carefully
A proposed new Accelerating Detection of Disease challenge was outlined in the Green Paper as an initiative that aims to recruit 5 million healthy participants into a world leading research cohort. The paper states that a key part of this is ‘to offer as many participants as possible their PRS….in order to develop and improve the evidence base for the use of PRS’.
Whilst building an evidence base is a much needed and very welcome goal, plans to return PRS results to research participants seem counter intuitive, as their predictive utility for individuals remains to be determined.
Developing this evidence base will entail careful evaluation of where polygenic risk scores have real value in existing prevention pathways for different common diseases, to ensure that the research cohort is representative enough to enable robust evidence development. Along with efforts to include generally under-represented groups (for example, ensuring an appropriate range of ethnicities), consideration should also be given to other population sub-groups that might benefit from inclusion; for example, younger people (under 40 years old) aren’t currently widely represented in such databases, but could play a vital role in demonstrating real-world utility for PRS in disease prediction and prevention efforts.
As we have said before, whilst this is an exciting area, what is clear is that the exact clinical application of PRS will differ substantially for diseases depending on the underlying genetic contribution of the disease, as well as current clinical and public health practice. Understanding which areas of clinical practice can benefit most from developments in this fast-moving and complex field is the first step to realising its potential. Ultimately, realising the full benefits might in some cases require new models of prevention - but in the short and medium term it makes sense to see how PRS can inform and improve current efforts, and research efforts should take this into account.