Distinct Metabolomic and Clinical Phenotypes of Depression in Heart Failure　- Pilot Exploratory Analysis

Depression is common among patients with heart failure (HF) and worsens prognosis, but its metabolic heterogeneity remains unclear.

Fifty HF patients completed the Patient Health Questionnaire-9 (PHQ-9) and underwent metabolomic profiling of 163 metabolites. Depressed patients (PHQ-9 score ≥5; n=26) were stratified using k-means clustering. Spearman's correlation with false discovery rate (FDR) correction (FDR <0.05) and bootstrap-validated least absolute shrinkage and selection operator (LASSO) regression (1,000 iterations) were applied to identify robust predictors of PHQ-9 scores. Two subtypes emerged. Cluster 1 (n=19) was characterized by elevated HbA1c; in this cluster, glycerol was the only metabolite significantly correlated with PHQ-9 scores. Cluster 2 (n=7) exhibited a cardiorenal phenotype, with elevated B-type natriuretic peptide (BNP) levels and a reduced estimated glomerular filtration rate. In Cluster 2, PHQ-9 scores were significantly positively correlated with BNP and metabolites related to methyl-group metabolism, specifically N,N-dimethylglycine (DMG), betaine, and 1-methylhistidine/3-methylhistidine. Bootstrap-validated LASSO identified BNP and DMG as the most robust predictors of depression severity in this specific cluster.

Depression in HF is metabolically heterogeneous. Cluster 1 is characterized by glycerol-linked lipid dysregulation. In contrast, Cluster 2 is associated with cardiac stress and alterations in methylation pathways, potentially linking metabolic dysfunction to neurotransmitter imbalances. These preliminary findings highlight the potential need for phenotype-specific therapeutic strategies to effectively manage depression in HF patients.