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Genomics of long-term health conditions

Safe People

Organisation name

University of Leicester

Organisation sector

3

Applicant name(s)

Chiara Batini

Funders/ Sponsors

Safe Projects

Project ID

OFHS240217

Lay summary

Almost half the global population has two or more long-term health conditions, affecting people’s quality of life and leading to substantial demand on healthcare services. Whether people develop long-term conditions is influenced by many factors, including genetics. We can think of our genetic code, or DNA, as being made up of a series of letters. Changes even to one “letter” can increase risk of disease. These effects are usually small, but across our whole genetic code can add up to have a larger effect. We will use health and genetic data from Our Future Health to investigate the genetics behind long-term conditions, including lung, heart, kidney and liver disease, diabetes, hormonal conditions, mental health, and chronic pain. This will help understand their biology, identify new medicines and ultimately improve treatment options. We will aim to: (1) test findings from existing genetic studies of long-term conditions,), and (2) undertake new studies to identify undiscovered genetic effects. We will look at single “letters” and at “risk scores” that add up changes across the whole genetic code. Importantly, Our Future Health will enable us to study the genetics of long-term conditions in populations which have not been adequately represented in studies to date. Long-term conditions, individually and together, impose a significant health burden. Genetic association studies can reveal important information about the biology underlying long-term conditions, which may be shared or distinct, and provide evidence to improve treatment and prevention. We will study the genetics of long-term conditions using data from DNA, linked healthcare records, questionnaires and clinically-relevant measures. We will include lung, heart, kidney and liver disease, diabetes, other hormonal conditions, mental health, conditions that can co-occur with them such as pain, conditions that are at risk of becoming long-term, and response to treatment (e.g. blood pressure and lipid-lowering drugs). Most genetic studies so far have been in people of European ancestry, while we aim to include all Our Future Health participants. This will enable us to replicate and validate existing findings (for example, disease-relevant genetic variants identified by genetic association studies, or associations of genetic risk scores with disease), particularly in populations which have not been well-represented in studies to date. It will also enable new genetic association studies. Results from such studies can be meta-analysed (combined) with results from other large studies, giving us more statistical power (ability to discover small genetic effects which can nevertheless give important clues about-biological-function).

Public benefit statement

Long-term conditions have very substantial impacts on patients, carers and health services. The impact falls unfairly on people who are already disadvantaged: people with the lowest incomes are four times more likely to have multiple long-term conditions, meaning that they spend more years living with ill health, as well as dying younger. People from minority ethnicities are also more likely to experience multiple long-term conditions. Genetic evidence substantially increases the chances of success for drugs in development. This can boost opportunities for new treatments in long-term conditions where current treatments can only manage symptoms rather than modifying the course of the disease. It is essential that genetic studies contributing to drug discovery represent people from all ethnic groups, to ensure that treatments work effectively for all. Another benefit is improved risk prediction to identify individuals at higher risk of disease and offer personalised strategies for prevention and early treatment. Use of genetic risk scores will require testing in clinical settings to come to fruition, but many non-genetic risk scores are widely used, for example, to predict risk of cardiovascular disease. Testing risk prediction in diverse individuals will ensure that this can be delivered for all.

Request category type

Public Health Research

Other approval committees

Project start date

15/03/2025

Latest approval date

23/02/2025

Safe Data

Dataset(s) name

Safe Setting

Access type

TRE

Safe Outputs

Link to research outputs