Metabolic syndrome (MetS) is a complex disorder characterized by obesity, dyslipidaemia, hypertension, and impaired glucose regulation, all of which substantially increase the risk of cardiovascular and metabolic diseases. Despite its global prevalence, the precise biological mechanisms and druggable targets underlying MetS remain insufficiently characterized.
This project aims to integrate large-scale genomic, biochemical, and clinical data from the UK Biobank to identify novel therapeutic targets and molecular pathways involved in metabolic dysregulation. Specifically, we will (1) perform genome-wide and phenome-wide association analyses to map loci associated with key MetS traits; (2) apply Mendelian randomization to prioritize causal biomarkers and pathways; and (3) integrate multi-omic and functional annotation resources to identify tractable targets and potential repurposing opportunities.
Through this approach, we aim to bridge population-scale genetic evidence with translational insight into therapeutic development. The expected outcome is a prioritized list of candidate targets and biological mechanisms that may inform precision medicine and the development of new interventions for metabolic disorders.