Global Biobanks in Enhancing Risk Prediction and Prevention through Digital Longevity: Narrative Review (Preprint)

UNSTRUCTURED Biobanks are recognised as lucrative health research resources due to their extensive and in-depth data availability, which allows researchers to draw correlations between various genetic, lifestyle, and health information and future disease incidence. As prospective data sources collect genetic and lifestyle information for several hundred thousand participants across various age categories, biobanks are important datasets in designing novel healthcare approaches. Within the realm of cardiometabolic ageing, which refers to the age related decline in the function of cardiovascular and metabolic systems, the conceptualisation of a systems medicine-based approach known as P4 (Predictive, Preventive, Personalised, Participatory) medicine has provided an interesting framework to tackle these metabolic illnesses in tandem with digital longevity tools that serve as vessels to deliver interventions across large populations. Therefore, this review aims to critically discuss how digital longevity informed by biobank data is vital in improving risk prediction, with a focus on cardiometabolic ageing.