Chronological age is an imperfect proxy for health, as individuals of the same age can differ substantially in disease risk, functional decline, and clinical outcomes. This project aims to investigate whether circulating proteomic profiles are associated with biological ageing processes and whether such associations provide insight into future disease risk at population scale.
Using UK Biobank data, we will analyse large-scale blood-based proteomic measurements alongside longitudinal health records, demographic factors, and lifestyle variables. The primary research objectives are: (i) to identify proteome-based indicators associated with biological ageing; (ii) to examine how these indicators relate to the incidence and progression of age-associated diseases; and (iii) to assess whether proteomic information adds predictive value beyond established clinical and epidemiological risk factors.
The project will apply statistical and machine-learning approaches to integrate multiple circulating proteins into composite indicators. These indicators will be evaluated for associations with outcomes including all-cause mortality and major categories of chronic disease such as cardiometabolic, neurodegenerative, inflammatory, and neoplastic conditions. Analyses will explore potential modification by sex and lifestyle factors where appropriate.
The scientific rationale is that circulating proteins reflect downstream biological processes influenced by environmental exposures and physiological state. Proteomic profiles may therefore capture aspects of ageing-related biology, including immune function, metabolic regulation, and tissue homeostasis, that are not fully represented by conventional risk markers.
This research seeks to contribute to population-level understanding of molecular processes associated with ageing and disease risk, and to evaluate the role of proteomic data in epidemiological research and health risk stratification.