Research Question: How do genetic variation, multi-omics profiles (including transcriptomics, proteomics, metabolomics, microbiome), and environmental/lifestyle exposure risk factors interact to drive the development and co-occurrence (comorbidity) of major chronic diseases (specifically lung diseases, neurodegenerative/psychiatric disorders, cardiovascular diseases, diabetes, kidney diseases, cancers) and influence aging trajectories and mortality?
Objectives: Identify shared molecular pathways underlying chronic disease comorbidities. Investigate the chronic disease Comorbidity axis, including treatment effects and genetic targets. Develop integrated comorbidity prediction models using genetics, exposures, and multi-omics. Assess generalizability of findings across diverse ancestries in UK Biobank.
Scientific Rationale: Chronic diseases cause a global health burden and frequently co-occur, suggesting shared etiologies. While genetics contribute, interactions between genetic variation, environmental exposures, and dynamic molecular processes (reflected in multi-omics) in driving comorbidity remain poorly characterized. Notably, individuals with identical genetic mutations show variable disease severity/progression, highlighting the role of modifiable factors and molecular context. The UK Biobank provides an unprecedented resource to address this complexity through deep phenotyping, genetic data, and emerging multi-omics for ~500,000 individuals. This enables moving beyond single-disease studies to map the interconnected “diseaseome”. A critical gap exists in understanding the lung-brain axis. Observational associations exist, but causal mechanisms, shared pathways, and impacts of lung treatments on neurodegeneration are unclear. Similarly, shared etiology across other chronic diseases requires systematic multi-omics exploration across diverse populations to ensure equitable insights. This project harnesses UK Biobank’s scale and depth to fill these gaps.
