A multilayer network analysis of cardiovascular-depression comorbidity reveals symptom-specific molecular biomarkers

Background. Cardiovascular diseases (CVD) and depression frequently co-occur, yet the biological mechanisms underpinning this comorbidity remain poorly understood. This may reflect complex, non-linear associations across multiple biological pathways. We aimed to identify molecular biomarkers linking depressive symptoms and cardiovascular phenotypes using a network-based integrative approach.
Methods. Data were obtained from the Young Finns Study (N = 1,686; mean age = 37.7 years; 58.3% female), including 21 depressive symptoms (Beck Depression Inventory), 17 CVD-related indicators, 6 risk factors, 228 metabolomic, and 437 lipidomic variables. Mutual information was used to capture both linear and non-linear associations among variables. A multipartite projection network was constructed to quantify how depressive symptoms and cardiovascular phenotypes are biologically connected via shared metabolites and lipids. Biomarkers were ranked by their contribution to these projected associations. Results were validated in an independent cohort from the UK Biobank.
Results. Specific depressive symptoms – crying, appetite changes, and loss of interest in sex – showed strong projected associations with diastolic blood pressure, systolic blood pressure, and cardiovascular health scores. Key mediators included creatinine, valine, leucine, phospholipids in very large HDL, triglycerides in small LDL, and apolipoprotein B. Important lipid mediators included sphingomyelins, phosphatidylcholines, triacylglycerols, and diacylglycerols. Replication analysis in the UK Biobank identified many overlaps in metabolite profiles, supporting generalizability.
Conclusions. This network-based analysis revealed symptom-specific biological pathways linking CVD and depression. The identified biomarkers may offer insights into shared mechanisms and support future prevention and treatment strategies for cardiometabolic–psychiatric comorbidity.