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

BACKGROUND

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

METHODS AND

RESULTS

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.

CONCLUSIONS

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.