Research Outline
This study investigates the interplay of gout, CVD, and OA using UK Biobank multi-omics data (genomic/proteomic/clinical/lifestyle). We aim to discover shared immune-metabolic biomarkers and therapeutic targets for preventing CVD/OA in gout patients, while exploring exercise’s role in modulating disease pathways.
Research Questions:
1. What shared immune-metabolic biomarkers act as therapeutic targets for gout, CVD, and OA?
2. What factors elevate CVD/OA risk in gout patients, and how to target them?
3. How does exercise modulate immune-metabolic pathways to reduce CVD/OA risk?
4. Can multi-omics identify proteins/metabolites driving CVD/OA progression?
5. Can LSTM models integrate multi-omics data to predict CVD/OA risks?
Objectives:
1. Identify immune-metabolic biomarkers via multi-omics analysis
2. Decipher mechanisms linking gout to CVD/OA comorbidity
3. Develop therapies targeting key immune-metabolic proteins
4. Assess lifestyle impacts on metabolic pathways and risks
5. Build multi-omics ML models for risk prediction
Scientific Rationale:
Gout shares inflammatory pathways with CVD (urate crystals accelerate atherosclerosis) and OA (chronic joint inflammation). Identifying biomarkers enables targeted therapies, while understanding exercise’s metabolic effects informs personalized prevention strategies.
