Metabolic cardiovascular diseases (MCVD) represent a category of cardiovascular pathologies primarily driven by metabolic disorders, with shared underlying conditions including insulin resistance, dyslipidemia, and systemic inflammation. Approximately one-third of adults worldwide suffer from some form of MCVD, which accounts for the highest mortality burden among chronic non-communicable diseases. Although these diseases exhibit heterogeneity in clinical manifestations, they share core mechanisms such as oxidative stress, endothelial dysfunction, and immunometabolic dysregulation. Current research predominantly focuses on individual disease types, leaving the common molecular pathways and cross-omics regulatory networks within the broader MCVD spectrum inadequately characterized. However, MCVD arises from complex interactions between genetic susceptibility and environmental metabolic stressors. Their development and progression are not only influenced by classical cardiovascular risk factors but are also centrally regulated by metabolic biological processes such as glucose homeostasis, fatty acid oxidation, and inflammasome activation. Recent advances in multi-omics technologies provide unprecedented opportunities to elucidate the systems biology of MCVD. The large-scale multi-omics data from the UK Biobank enable cross-dimensional data integration and causal inference within the same cohort. This study will develop polygenic risk scores (PRS) and environmental risk scores (ERS), combined with metabolic pathway enrichment analysis and network medicine models, to reveal universal intervention strategies targeting core metabolic mechanisms-such as nutritional modulation, exercise prescriptions, and metabolic reprogramming drugs-ultimately alleviating the global health burden imposed by MCVD.
