Scientific rationale
Cerebrovascular disease (CVD; stroke, small-vessel disease) and neurodegenerative disease (ND; Alzheimer’s, Parkinson’s, other dementias) are leading causes of disability, cognitive decline, and depression in ageing. They share mechanisms such as white-matter damage, neuroinflammation, and network disruption, but also have disease-specific pathways. The UK Biobank’s large, deeply phenotyped cohort with structural MRI, diffusion tensor imaging (DTI), resting-state fMRI, and other imaging-derived phenotypes (IDPs), alongside blood biomarkers, genetics, lifestyle data, and linked health records, enables robust disease-specific analyses and, secondarily, combined analyses to explore overlap.
Research questions
In CVD, which imaging, biological, genetic, and lifestyle factors predict post-stroke cognitive impairment (PSCI), post-stroke depression (PSD), and functional decline?
In ND, which factors predict cognitive decline, depression, and functional deterioration?
Are there shared vs disease-specific predictors, and does combining vascular and neurodegenerative risk profiles improve prediction?
Objectives
Parallel (primary): Build multimodal risk models for PSCI/PSD and ND outcomes; extract and analyse imaging features including infarct location, white-matter hyperintensity (WMH) volume and spatial distribution, cortical and subcortical regional volumes, tract-specific DTI metrics, resting-state network connectivity, and quantitative radiomics features; model cognitive trajectories (including segmented models for stroke); estimate risks using survival analysis; assess the effects of imaging-derived measures; and examine interactions.
Combined (optional): Compare effect sizes, test disease-type × predictor interactions, and evaluate whether combined risk profiles improve prediction.
Impact
Preserves disease specificity while enabling integrated analyses to reveal mechanisms and improve early risk prediction in aging.
