Research Questions
Can patterns in blood-based biomarkers and brain imaging data from the UK Biobank help identify early warning signs of neurodegenerative diseases such as Alzheimer’s and Parkinson’s?
How can artificial intelligence (AI) models combine genetic, imaging, and biochemical data to better predict who is at risk of cognitive decline?
Are changes in blood lipids-such as cholesterol-related molecules-linked to changes in brain structure or memory performance over time?
Objectives
Biomarker Discovery: Use UK Biobank blood assay and imaging data to identify lipid-related biomarkers that are associated with early signs of cognitive decline or brain atrophy.
AI-Based Risk Prediction: Develop AI models that combine brain scans, genetics, and clinical data to predict the likelihood of disease progression over a five-year period.
Mechanistic Insights: Investigate associations between lipid metabolism, brain structure (e.g., hippocampal volume), and cognitive outcomes to better understand disease mechanisms.
Scientific Rationale
Lipid metabolism plays a crucial role in brain health. Disruptions in cholesterol balance and related pathways may contribute to diseases like Alzheimer’s and Parkinson’s. By analyzing UK Biobank’s large dataset-which includes blood biomarkers, brain scans, genetics, and cognitive testing-we aim to uncover early warning signs of disease and build models to help predict who is most at risk. This could guide future approaches to prevention and personalized treatment.