The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis

The results of this update of the 2011 Cochrane review on the impact of communicating genetic risks of disease on risk-reducing behaviour comes as no surprise to our group, the PHG Foundation, who have been working in the area of genetic and genomic technologies for almost two decades. We know that there is a paucity of evidence linking risk communication, genomic or otherwise, and the motivation of sustained behaviour change and that the quality of existing evidence is poor. In other contexts, we know that motivating behaviour change is extraordinarily difficult, and there appears to be no reason to suppose that genomic information is endowed with greater influencing power for any given level of risk than other types of information.
Furthermore, as the authors point out, when it comes to assessing the impact of communicating predictive genetic information, the quality of the evidence presented is poor, the studies selected for review typically have poor or flawed study design or utilise outcomes or timings of outcome assessment that are insufficiently robust. Additionally, the criteria for inclusion of research within the review required that each study adopted a randomised controlled trial design, meaning that the results represent population level data rather than individual level data, which in the context of attempting to assess an intrinsically individualised approach is problematic.
As an organisation committed to making the best use of biomedical science to improve health, we consider that genomics has an important role to play in this endeavour as one of a number of relevant biomarkers of common, complex disease susceptibility. Collective use of these biomarkers will enable the development of a molecular taxonomy of disease that can in turn drive the development of more accurately tailored and targeted interventions offered to population subgroups and individuals. We strongly agree with the authors that DNA tests ‘may have a role in stratifying populations by risk, to enable clinical and behavioural interventions to be targeted at those at increased risk’. Preventive interventions might include screening tests and surveillance, drug treatments or even occasionally screening.
However, it is now widely accepted in the field of personalised medicine that for common complex diseases, genomic information alone will be insufficient to either motivate behaviour change, or (more realistically) to stratify populations to receive more rational and targeted interventions. Apart from anything else, inclusion of genetic data alongside other personal, physiological or biomarker data adds little to the accuracy of the risk prediction for these diseases and the size of effect is small. Thus for an individual the eventual risk estimate will only be slightly increased or slightly decreased. Why then would these small differences intrinsically motivate significant changes in behaviour? The public has more sense than to react differently just because of the ‘genomic’ origins of the information when the absolute risk estimates are very similar.
In this sense, this paper tackles a question that is no longer considered of central relevance within the field. We, and others working in this area anticipate that any potential future utility of genomic information in preventing or treating disease will arise from the appropriate matching of individuals or groups of individuals (classified on the basis of genomic and a host of other biomarkers and environmental factors) with interventions known to be most effective in these groups.
Rather than dismissing the role of genomics and personalised medicine more widely on the basis of sparse and poor quality evidence relating to a question of only marginal relevance to the endeavour at hand, we suggest that health policy makers should focus on generating robust evidence on how genomic and other personal physiological and environmental information could be optimised to guide clinical and behavioural interventions; increase transparency around what is known about the scientific validity and clinical utility of genomics (especially in direct-to-consumer contexts) and develop more nuanced approaches that acknowledge the potential impact of both genomic and other risk information in empowering individuals to improve their health.
Progress is dogged by a determination amongst both personalised medicine evangelists and sceptics to present genomic analysis in polarised ‘all or nothing’ terms. As we learn more about the widely varying contribution of genomics to disease it becomes ever clearer to us at the PHG Foundation that a more balanced and nuanced approach to its role in prevention is essential. The construction and demolition of ‘straw man’ arguments of the type described in this article are not helpful in encouraging such a balanced approach to health policy making. Instead, as health policy researchers and advisers we should be seeking to critically evaluate and, where the evidence warrants it, support the work of those researchers and clinicians aiming to develop personalised medicine approaches in the areas in which its potential benefits are most urgently sought and required, such as rare diseases and cancer.
As better quality evidence accrues in the future that addresses the potential role for genomics in ‘personalising prevention’ for common chronic diseases it will of course be important to evaluate this evidence and consider its implications for health policy. It is hard, however, to see the value in undertaking such evaluation prematurely, as it risks undermining the current efforts within the field of biomedical and clinical research to develop this evidence base more fully.