Exploring internal and external exposome: behavioural, social, biological and genetic markers contribution to risk of cardiometabolic and respiratory conditions

The exposome concept builds upon the accumulating evidence that lifestyle factors, environmental factors (including exposure to air pollution, noise, green space) as well as social factors complement genetics to understand individual predisposition and risk of chronic diseases. The exposome is defined as external stressors (i.e. non genetic factors) that affect health in the life course. Characterising and understanding the exposome relies on the identification of social, environmental, behavioural, and biological determinants of health and on the exploration of the way they (separately, and jointly) affect health.
We propose to use the non-genetic information collected within the UK Biobank, together with socio-economic variables, environmental descriptors to define and characterise the UK Exposome and its health social consequences.
We will employ advanced statistical models and machine learning tools to identify pools of UK biobank participants sharing similar exposure experiences in the life course. These exposures will include behavioral (e.g. diet, smoking, physical activity), environmental (e.g. air pollution, noise, availability of green space), demographic, and social factors, and we will investigate which and how these variables differ across the different groups of participants.
We will subsequently investigate how these discriminatory exposome features affect health, in particular mortality form and incidence of cardiometabolic diseases. We will quantify the added information brought about by these external factors to explain and possibly predict individual risks over and above (i) established risk factors, (ii) combination of biochemistry biomarkers, and (ii) established genetic risk scores.
We will also explore changes in time of these factors using the repeated measurements available in the UK Biobank population. We will evaluate if a change in these factors are likely to induce a change in the risk. The availability of time-resolved measurement of these factors will also be instrumental in addressing the temporality, hence giving indication on the causality, of events leading to higher risks of cardiometabolic conditions.
UK Biobank, due to its size and characterisation offers a unique high-resolution view to generate hypotheses on the main determinants of cardiometabolic health. These will be further validated and refined in a collection of EU cohorts (as part of H2020 initiatives this research stems from).
We expect to provide actionable information on the effect of healthy living conditions. We plan to analyse life course trajectories in biological, physiological social and health status at an unprecedented scale.