Scientific Rationale
CVDs are complex conditions that may be intricately linked to a multifaceted interplay of genetic, lifestyle, clinical, and multi-omics data. For instance, Takotsubo syndrome, characterized by stress-triggered reversible myocardial injury, provides a unique opportunity to study the environmental stress-molecular response-cardiovascular outcome” cascade. Its clinical overlap with classic CVDs suggests shared pathological mechanisms.
Previous studies have revealed that certain genetic mutations can significantly influence the susceptibility to CVDs, while lifestyle factors such as diet, physical activity, and smoking habits also play crucial roles in its development. Additionally, clinical parameters like blood pressure, cholesterol levels, and diabetes status are well-established risk indicators. The integration of multi-omics data, including genomics, proteomics, and metabolomics, provides a comprehensive view of the underlying biological mechanisms. Given the complexity of CVDs and the wealth of information available in the UK Biobank database, it is essential to leverage this valuable resource for in-depth exploration. The UK Biobank’s proteomics, metabolomics, and genomics datasets enable cross-omics analyses, overcoming the fragmentation of single-omics studies. This multi-omics integration strategy not only deepens our understanding of the biological underpinnings of CVDs but also provides a foundation for developing universal prevention strategies across diseases, ultimately reducing the global burden of cardiovascular diseases.
By utilizing the UK Biobank’s resources, this study addresses critical gaps in understanding shared risk mechanisms in CVDs. The discovery of shared biomarkers could lead to early warning tools for cross-CVD risk stratification. Clarifying gene-environment interactions may guide personalized lifestyle interventions for high-risk
