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How does the environment interact with genes to cause and worsen disorders related to abnormal inflammation?

Safe People

Organisation name

University of Birmingham

Organisation sector

Academic Institute

Applicant name(s)

Archana Sharma-Oates

Funders/ Sponsors

Safe Projects

Project ID

OFHS240134

Lay summary

Our overall aims are to better understand how an individual’s genes, environment, and everyday lifestyles (including diet, air quality, and physical activity) work together to influence the chances of developing long-term diseases. This knowledge will help us identify early warning signs of illness and support more personalised ways to prevent and treat disease in different groups of people. We plan to use computer models to find early biological warning signs (biomarkers) and environmental and lifestyle risk factors that could help identify who is more likely to develop certain illnesses. This information can support better prevention and public health messaging. In this study, we will: • Investigate how environmental factors such as where we live (including exposure to pollution) and lifestyle choices (e.g. smoking, diet, and exercise) influence the risk of developing inflammation-related diseases. • Use computer models to combine genetic information (i.e. the DNA sequence), lifestyle, air pollution and health data to better understand who may be more vulnerable to these diseases. These objectives will help create more personalised prevention and treatment plans, especially for people from deprived and minority ethnic communities who are often underrepresented in research and may face different health risks. Chronic inflammation plays a central role in the development and progression of a wide range of diseases, including cancer, cardiovascular and autoimmune conditions as well as ageing. While genetic differences affect how susceptible someone is to disease, there is growing evidence that environmental and lifestyle factors, such as diet, exercise, pollution, and socioeconomic status, play an important role by influencing inflammation and overall disease risk. However, we do not fully understand how our genes interact with external factors, such as diet, pollution, and lifestyle, though we know that these factors can be changed to improve our health. This study aims to discover how inherited genetic differences, together with environmental factors including lifestyle and behaviours, affect the risk of developing diseases linked to increased inflammation, or if they worsen the symptoms of these diseases. By identifying reliable genetic markers and understanding how they work, we aim to uncover early signs of disease and find new targets for treatment.

Public benefit statement

Inflammation-related diseases are common and affect people of all ages and backgrounds, but we still do not fully understand why some people get more severe illness or respond differently to treatment. One challenge is that research often includes fewer people from deprived communities and ethnic minority backgrounds, even though they may be more affected by certain conditions or risk factors like pollution, diet, or lifestyle. By studying how genetics, lifestyle, and environment influence different groups of people, we hope to find better ways to identify those most at risk. This research could lead to fairer and more personalised healthcare. For example, if we discover genetic differences linked to inflammation-related diseases, we could develop better screening tools and treat them earlier. Understanding how factors like pollution or diet interact with a person’s genes could also help create better prevention plans. Ultimately, our goal is to improve early diagnosis and treatment. Instead of using a one-size-fits-all approach, we want to predict who is more likely to develop disease and tailor treatments to each person’s needs, making care more precise and effective for everyone.

Request category type

Public Health Research

Other approval committees

Project start date

02/02/2026

Latest approval date

22/01/2026

Safe Data

Dataset(s) name

Safe Setting

Access type

TRE

Safe Outputs

Link to research outputs