Objective Depression in chronic heart failure (HF) leads to worse outcomes. Analysing proteomic profile might explain the underlying molecular pathomechanisms. Methods Depressiveness was assessed by the Patient-Health-Questionnaire-9 (PHQ-9) in the MyoVasc study (NCT04064450; N = 3289), a prospective cohort study on chronic HF. Total of 358 proteins was quantified in EDTA plasma by targeted immuno-PCR (Olink, Sweden). Elastic net linear regression was used to identify proteins associated with somatic and cognitive component of PHQ-9. Subsequent pathway analysis was conducted with STRING. Based on the selected proteins, protein scores for PHQ-9 were generated with linear regression and evaluated for the prediction of outcome. Results PHQ-9 scores and protein biomarkers were available in 2725 participants (AHA Stages A-D). 29 proteins (10-fold CV R2 = 0.08) and 75 proteins (10-fold CV R2 = 0.09) were identified for cognitive and somatic dimension of PHQ-9. Protein-protein network analyses revealed that the selected proteins are involved in inflammatory and metabolic pathways. In Cox regression analyses, the somatic PHQ-9 protein score was a predictor of all-cause death (HR 1.43, 95% CI: 1.24-1.66, p <0.0001) and worsening of HF (WoHF) (HR 1.19,95% CI 1.05-1.35, p = 0.0066), independent of age, sex, clinical profile and medication. The cognitive PHQ-9 protein score was as well predictive of all-cause death (HR 1.52, 95% CI: 1.21-1.91, p = 0.00027), but less predictive of WoHF (HR 1.03. 95% CI: 0.84-1.26, p = 0.77). Conclusions Molecular mechanisms associated with dimensions of depressiveness in the context of heart failure were identified. These mechanisms were prognostic for worsening of HF and death, indicating their clinical relevance.