Research Questions:
1.What are the key genetic, molecular, and environmental factors contributing to neurodegenerative disease (ND) risk and progression?
2.How do multi-omics (genomics, transcriptomics, proteomics, metabolomics) interact with neuroimaging markers (e.g., brain atrophy, white matter integrity) in ND pathogenesis?
3.Can environmental exposures (e.g. air pollution, diet, Heavy metal exposure) and chronic diseases modify ND risk through epigenetic or neuroinflammatory pathways?
4.Are there potential intervention targets (e.g., pharmacological, lifestyle, drug-assisted therapy and non-drug-assisted therapy) that could mitigate ND risk based on UK Biobank’s longitudinal data?
Objectives:
1.Integrate multi-omics data (genomics, transcriptomics, proteomics, metabolomics) with neuroimaging (MRI, DTI) to identify ND-associated biomarkers.
2.Assess environmental contributions (e.g., pollution, smoking, physical activity, and lifestyle) using UKB’s extensive exposure data.
3.Apply AI/ML approaches (e.g., deep learning, causal inference) to model ND risk and progression.
4.dentify modifiable factors (e.g., drug repurposing, dietary patterns) (such as dietary patterns, drug-assisted therapy and non-drug-assisted therapy) for potential interventions.
Scientific Rationale:
Neurodegenerative diseases (NDs) like Alzheimer’s and Parkinson’s arise from complex interactions between genetic, molecular, and environmental factors, but prior studies have lacked integrative approaches. The UK Biobank’s multi-omics, neuroimaging, and longitudinal health data enable a systems-level investigation-linking exposures (e.g., pollution, diet) to biological mechanisms (e.g., epigenetic changes, protein dysregulation) and clinical outcomes (e.g., brain atrophy). This holistic approach can uncover causal pathways and identify interventions (e.g., repurposed drugs, lifestyle modifications) to shift ND management from symptom treatment to early, mechanism-based prevention.