Predicting healthy ageing and age-related disorders using the UK Biobank Database
Approved Research ID: 91331
Approval date: March 2nd 2023
Globally, the older adult population (people > 65 years of age) is increasing, and it is estimated that by 2030, 1 in 6 people will be over the age of 60 (WHO, 2021). Given this increase in the older adult demographic, and our desire to live longer and to enjoy a high quality of life in old age, an important goal for the global community is to learn how to age healthily and to avoid age-related decline and impairment.
There are a wide range of potential predictors of healthy ageing and age-related problems (e.g., in relation to cognitive, physical and mental health) and given the complexity of these topics and the substantial variance that can be seen across individuals, much more investigation is needed to identify these. The UK Biobank provides a unique resource to identify such factors given the detailed datasets which are available and the very large number of individuals who have been recruited.
Our project aims to investigate the range of predictors (e.g., lifestyle, metabolic, brain and body imaging, and genetic) and how these work both in isolation and together to increase risk of cognitive problems (e.g., in memory, attention), physical problems (e.g., osteoporosis, falls), and mental health problems (e.g., depression, suicidal ideation). Often research has focused on single predictors, whereas we will incorporate a range of different datatypes (e.g., metabolomics, genetics and neuroimaging) in our predictions and will investigate how these interact.
We will also focus on developing novel predictors which will be created from the available data. For example, we will develop our own brain imaging metrics to use in our models and afterwards will make these available to other UK Biobank researchers.
As we will first investigate individual predictors and will later investigate how these interact, the project is expected to last 3 years. We have a multidisciplinary team who have expertise in psychology, nutrition/exercise/physical health, biology/pharmacy, biomedical engineering and data science. Together we are well placed to investigate the predictors of age-related problems and interactions between these.
Through our research on predictors of cognitive and physical ageing, and age-related mental health problems we expect to generate substantial public health impact. Members of the public will have a better understanding of the key contributors to these age-related problems and as a result should be able to identify which risk factors apply to them, and which may be modified.