Research Questions
1.Epidemiology and Trajectories: It remains unclear whether subthreshold depression independently predicts CVD and how different symptom trajectories shape risk.
2.Biological Mechanisms: Inflammatory and metabolic pathways are implicated, but causal evidence is limited; large-scale proteomic and metabolomic approaches are underused.
3.Neuroimaging Markers: Brain structural and functional alterations observed in major depression are unexplored in subthreshold depression and their role in CVD development.
4.Lifestyle Factors: The influence of smoking, alcohol, diet, activity, and sleep on the depression-CVD link is insufficiently studied.
Objectives
1.Prospective associations: Assess longitudinal CVD risk across depression spectrum using time-updated measures.
2.Mediation analysis: Quantify inflammatory and metabolic contributions and examine heterogeneity by sex and depression subtype.
3.Molecular features: Identify proteomic/metabolomic signatures, protein-metabolite networks, and predictive markers.
4.Neuroimaging integration: Examine structural MRI and resting-state fMRI markers of subthreshold depression, and test whether brain alterations mediate or moderate the depression-CVD link.
5.Trajectory modeling: Apply latent class growth analysis to characterize depressive symptom trajectories and their associations with neuroimaging alterations and CVD outcomes.
6.Lifestyle interactions: Test whether a composite lifestyle score modifies depression-CVD risk, highlighting intervention targets.
Scientific Rationale
This study will test whether subthreshold depression predicts CVD and explore underlying pathways. By integrating inflammatory, metabolic, proteomic, metabolomic, and neuroimaging data, along with symptom trajectories and lifestyle factors, it aims to identify high-risk subgroups. Findings may guide early detection, biomarkers, and lifestyle-based prevention.
