I. Research Questions
1. How can we develop a metabolomics-specific foundation model to capture the complex relationships between metabolites and aging/disease outcomes?
2. Can a foundation model effectively predict biological age and disease risk by integrating multimodal data, including metabolic profiles and environmental factors?
3. What are the key metabolic pathways driving population-specific aging patterns, particularly influenced by diet and environmental exposures?
II. Objectives
1. Develop a metabolomics-specific foundation model to harmonize heterogeneous data and capture complex aging patterns.
2. Fine-tune the model for biological age estimation and disease risk stratification using UK Biobank data.
3. Identify key metabolic pathways driving population-specific aging patterns using interpretability techniques.
III. Scientific Rationale
1. Data Heterogeneity: Existing metabolomics studies are hindered by data heterogeneity. A foundation model can harmonize diverse datasets, improving generalizability.
2. UK Biobank Data: The UK Biobank’s extensive longitudinal data provides a unique opportunity to develop a robust model for aging and disease prediction.
3. Clinical Relevance: Fine-tuning the model for biological age and disease risk will provide actionable insights for early detection and personalized interventions.
IV. Plan for Disseminating Our Findings
We will disseminate our findings through high-impact SCI publications and presentations at international conferences to engage the academic community. In addition, we will develop and release an open-source web tool based on our findings, enabling the public and researchers to explore and apply the model. Our goal is to make our results accessible through both academic and public channels, ensuring broad impact and contributing to the field.