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...
| Publicado en: | Psychological Medicine Vol. 55; pp. 1 - 13 |
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| Formato: | research tables/charts Journal Article |
| Publicado: |
Cambridge University Press
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191245152&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191245152 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00332917 6Q3 jtl: Psychological Medicine issn: 00332917 maglogo: N pubinfo: dt: 2025 vid: 55 pid: 15979 pub: Cambridge University Press artinfo: ui: 191245152 191245152 191245152 10.1017/S0033291725102109 191245152 ppf: 1 ppct: 12 formats: tig: atl: A multilayer network analysis of cardiovascular–depression comorbidity reveals symptom-specific molecular biomarkers. aug: sug: subj: Comorbidity Biological Markers Blood Cardiovascular Diseases Metabolism Depression Metabolism Phenotype Risk Assessment Human Male Female Adult Psychological Tests Metabolomics Crying Sexual Desire Disorders Eating Disorders Diastolic Pressure Systolic Pressure Creatinine Valine Leucine Phospholipids Triglycerides Apolipoproteins Phosphatidylcholines Finland Descriptive Statistics Funding Source Adult: 19-44 years Male Female ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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