Cardiovascular ageing, including both cardiac and vascular ageing, is marked by ventricular remodeling, impaired diastolic function, myocardial fibrosis, arterial stiffening, and reduced vascular compliance. These age-related changes accumulate gradually and strongly influence the risk of cardiovascular disease (CVD) such as myocardial infarction, stroke, atrial fibrillation, and heart failure. While conventional risk factors explain part of this burden, cardiovascular ageing represents an integrative biological process that may provide earlier and more precise markers of disease risk. Understanding its determinants and consequences is critical for improving prevention and risk stratification. The UK Biobank provides a unique opportunity to address these questions, with its scale, long follow-up, and integration of multimodal data, including cardiac MRI, aortic imaging, vascular function, biomarkers, and multi-omics layers (genomics, epigenomics, metabolomics). This project will define cardiovascular ageing signatures, evaluate their associations with incident CVD, identify genetic, metabolic, lifestyle, and environmental factors contributing to accelerated ageing, and test whether multimodal signatures improve prediction beyond established models. Prospective associations will be estimated using Cox proportional hazards models, while multimodal integration will apply statistical and machine learning approaches to derive composite signatures. Predictive value will be assessed using discrimination, calibration, and reclassification metrics. By clarifying how cardiovascular ageing contributes to CVD, this study aims to refine risk prediction and highlight modifiable factors that could help delay disease and reduce its public health burden. All analyses will be conducted within the UK Biobank Research Analysis Platform in accordance with governance policies.
