Current clinical management of multimorbidity remains reactive and symptom-focused due to limited understanding of cross-disease mechanisms. The UK Biobank’s multi-omics data (genomics, proteomics, imaging) and longitudinal phenotyping uniquely enable us to distinguish genetic predisposition from environmental mediation through instrumental variable analysis and resolve cytokine/neurotransmitter crosstalk between neuropsychiatric-chronic disease pairs via multi-layer network modeling. The paradigm shift from single-disease to pathway-centric frameworks could reveal novel prevention targets reducing comorbidity incidence, enable risk-stratified treatment matching using predictive algorithms and provide biological evidence for environmental policy interventions.
Our study aims to unveil potential causal factors and genetic biomarkers associated with neuropsychiatric disorders and chronic diseases, elucidate the underlying molecular mechanisms, thus propose novel preventive strategies. Additionally, our team aims to explore the underlying genetic landscape and biological correlations in order to uncover shared biological pathways and therapeutic targets for multimorbidity patterns and subsequently guiding clinical decision-making. Also, data models will be developed utilizing genetic biomarkers previously discovered and clinical features to facilitate disease diagnosis and predict treatment responsiveness in patients. This endeavor holds promise for enhancing disease management, minimizing notable side effects, and reducing healthcare costs linked to ineffective treatment protocols.
