23 September 2019
It is widely recognised that genetic information is useful in the care and management of people with rare diseases, cancer and inherited forms of other common diseases. Efforts have been ongoing for some time now to harness knowledge about genetics in the prevention of common diseases such as cardiovascular disease, diabetes and obesity.
Genetic contributions to disease risk are defined at birth, and remain stable throughout the life-course. There is therefore considerable interest in using genetic factors 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. This could help instigate preventative measures much earlier on, or create more efficient and targeted prevention programmes through better identification of those at increased risk.
Recent advances in research on polygenic scores and their application to risk stratification have created renewed interest in the use of genetic information in prevention of common diseases. The debate thus far has been largely polarised, with strong proponents and critics about the utility of such information. In our report we look specifically at polygenic scores and cardiovascular disease to explore their potential for prevention.
The report outlines the science that underlies polygenic scores, and their potential applications. It also provides an overview of the current state of cardiovascular disease prevention, and considers the evidence for the implementation. We conclude that, whilst there is indeed potential in the field, it remains under development.
Initial indications are that polygenic scores for coronary artery disease (CAD) can improve population stratification, and hence potentially support more effective prevention. Stratification can be an important mechanism for informing prevention, by allowing interventions to be targeted towards those at greatest risk of disease, and is established practice in cardiovascular disease prevention efforts. However, it has yet to be demonstrated that the ability to better stratify using genomic information can also lead to better health outcomes.
It is hoped that our ability to better accumulate and analyse vast amounts of data (including, but not limited to, genetic data) will lead to more effective public health practice, through enabling more accurate identification of at-risk individuals at an earlier time point, targeting interventions at those at greater risk and offering more tailored interventions. This approach is sometimes referred to as precision public health, and forms part of personalised prevention (which combines prevention efforts at the individual level with stratified population level approaches).
Genetics is seen as having a central role to play, as evidenced by the recent government green paper on prevention. However, achieving this goal is not an easy task, especially when there is concern that this can divert attention from more ‘traditional’ population-wide public health efforts. Bridging this gap and the ongoing debate requires taking an evidence-based approach to identify where we have most to gain from genomics. There are certainly opportunities for genomics to contribute to public health, and it can complement existing efforts.
Research shows that, to gain the most from genomic risk information, it needs to be combined with other forms of support both at the individual and population level. Going forward, it is therefore important to realise that having the healthiest possible populations is reliant on having both population-wide and precision elements to public health.