Identification of molecular mechanisms between depression and outcome in heart failure

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