This research will identify metabolic, genetic and lifestyle measures that predict, and may determine, the onset of various age-related degenerative diseases. We will establish studies of participants within UK Biobank that have developed these diseases since the baseline assessment and examine how they differ in terms of their genetics, metabolism and lifestyle compared to similar participants who have aged free of these diseases in the same period.
We will also investigate why some participants? physiology appears to age more rapidly than others across the same chronological time period, according to age-related general health measures in the cohort.
Findings could shed new light on the aetiology of several age-related diseases, improve disease risk prediction and/or inform strategies for developing novel treatments. Gathering more information about how the ageing process underlies the development of many chronic, degenerative conditions will also aid efforts to extend both the lifespan and health-span (years spent in good health) of individuals.
We will derive large ?case-cohort? studies of incident cases and characteristic-matched controls for several diseases and conditions of interest. We will then examine which factors measured at baseline are linked to future development of disease, avoiding some biases that affect conventional case-control studies. So-called ?biological ages? will be calculated for the full cohort from baseline health data on several variables, including blood pressure and anthropometry. Genetic data will be used both to understand the genetic contribution underlying diseases and traits, and to aid causal inference when considering how different exposures affect disease risk (?Mendelian randomisation?).
Data on the full cohort are required for several analyses. Several case-cohort sub-sets of data will be derived from these.