The future, now: Revolutionising disease prevention through predictive genomics

It has been 70 years since the discovery of the DNA double helix and 20 years since the completion of the Human Genome Project - both seminal moments in the field of genomics. These advances paved the way for us to be able to utilise the power of the human genome to deliver personalised medicine, such as cell and gene therapies, and understand how a patient may respond to a particular therapy. This has huge value for the individuals being treated for a disease, but what of the wider public health potential for genomics?

At Thermo Fisher Scientific, we believe that using genomics to predict a person’s risk of disease could be the catalyst needed to revolutionise approaches to both disease prevention and public health. This is of course a bold claim, so, to begin to frame my argument, it’s important to first start with the need.

Addressing unmet needs, improving patient outcomes

Health systems in the UK, Europe, and the US have been created to focus on the individual and not the population, so the focus is treatment, rather than prevention. In 2020, European nations spent the equivalent of 11% of their GDP on healthcare,¹ with as little as 0.37% allocated to preventive healthcare.² When you consider that the most prevalent chronic, non-communicable diseases (NCDs) alone cost economies as much as US$2 trillion per year,³ and as many as 80% of all heart disease, stroke, and type 2 diabetes cases, and at least a third of cancer cases may be preventable - one can see the opportunity in front of us to improve patient outcomes.⁴

The individual and societal burden of chronic conditions increases year-on-year, so, whilst the further reduction of environmental risks (i.e., pollution, radiation, climate change) remains vital, it can be argued that exploring other ways to help people remain healthier for longer has incredible value, also. One such approach is the use of polygenic risk scores, which is a component of predictive genomics that calculates a person’s risk of developing a particular disease.

Polygenic risk scores - stratifying the population

As all humans have near-identical DNA sequences across the estimated six billion-letter code for their genome, genetic variants can increase the risk of developing a disease. Polygenic risk scores are calculated using data from large-scale genomic studies, powered to find genomic variants by comparing groups with a certain disease to a group without the disease. Polygenic risk scores are not diagnostic tools (they indicate relative not absolute risk),⁵ however, they can help to “stratify the population” and identify individuals with a higher-than-normal risk of developing diseases, often plotted on a bell curve. It must be noted that, as these scores are based on data sets, they do not indicate hereditary disease, so they should be used in conjunction with other testing methods in those with familial history of certain diseases. Also, as 95% of the genome-wide association studies undertaken have been in people of European descent,⁶ studies from more diverse populations are needed to identify certain genetic variations.

The value of calculating a person’s polygenic risk score is that earlier risk identification allows for an opportunity for that individual to then adapt or change their behaviour or take other steps to reduce their risk of disease. Action is required when someone is found to be at high-risk of developing a disease, but encouragingly, data from Finland suggests that polygenic risk scores can be a driver of positive behavioural change. In a study of over 7,000 people who were given their polygenic risk scores and followed for 18 months, one in five who were identified as at high risk of cardiovascular disease had engaged with their doctor, 12.4% had lost weight, 14.2% had stopped smoking, and 15.4% had signed-up for health coaching.⁷ At a societal level, polygenic risk scores could one day improve the accuracy of existing screening programmes, support risk identification for diseases for which no large-scale population screening initiatives exist, and help countries enhance their disease prevention strategies and policies.

Empowering and enabling people to take better control of their health could be a significant cost saving. However, the long-term socio-economic effectiveness of polygenic risk scores needs to be established. Large-scale research projects are ongoing that are expected to generate this evidence.

From drug discovery to clinical through validation

With healthcare systems in many parts of the world already stretched, predictive genomics provides new opportunities to improve the sustainability of public health services. Its translational application in precision medicine to develop targeted cancer therapies, and in medical care to identify infectious diseases, could possibly transform our approach to treating and managing these diseases.

To take us from drug discovery to clinical through validation, we need to prioritise improving proteogenomic capabilities in hospitals, investing in state-of-the-art equipment, such as automated flow cytometry and immunoassay systems, especially to improve cancer care. These methods have the potential to be integrated into therapeutic trials and support clinical care across the board. To safeguard for the future and prepare for emerging infectious diseases, we must also shift the healthcare model from reactive to pre-emptive. Continuing to strengthen the national infrastructure of advanced proteomics capabilities, such as advanced cryoEM, mass spectrometry, and mass-spectrometry-based interactomics capabilities, will enable rapid translational research outcomes that complement existing genomics programmes to prepare us for new and emerging infectious disease.

Of course, more still needs to be understood as to the viability of these measures, but with research progressing at speed and increasing levels of investment, predictive genomics is here to stay. And I, for one, am excited.