Abstract:
OBJECTIVE To investigate the impact of serum metabolic profiles on depression pathogenesis and elucidate the regulatory mechanisms of Zhizichi Decoction (ZZCD) in modulating metabolic disturbances.
METHODS The association between 1 400 serum metabolites and the risk of depression was analyzed by Mendelian randomization (MR), and the effect size was integrated by meta-analysis to enhance the robustness of causal inference. Metabolic pathway enrichment analysis was performed for metabolites with significant causal association.To validate MR findings, a chronic social defeat stress (CSDS) mouse model treated with the traditional Chinese herbal formula ZZCD was employed, analyzing behavioral outcomes and serum metabolic profiles.
RESULTS The causal associations between six metabolites and depression onset were confirmed, identifying 10-undecenoate (11:1n1) and sphingomyelin (d18:1/14:0, d16:1/16:0) as consistent risk factors, and X-18779 levels and the serine to alpha-ketobutyrate ratio as protective factors. Meta-analysis revealed consistent effect directions across independent cohorts, further supporting causal inferences. Pathway enrichment analysis demonstrated that depression-associated metabolites were predominantly enriched in sphingolipid metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, and caffeine metabolism. Among the three identified metabolites linked to lipid metabolism, two metabolites were associated with increased depression risk. Notably, ZZCD downregulated key risk metabolites (e.g., 10-undecenoate and sphingomyelin) and alleviated depressive-like behaviors in mouse models. Mechanistic pathway analysis suggested that ZZCD exerts therapeutic effects by modulating neuroinflammation and gut microbiota-related metabolic pathways.
CONCLUSION These findings collectively indicate that circulating metabolites may have causal implications for depression risk, with ZZCD potentially targeting specific metabolic pathways for therapeutic intervention. This study provides novel insights into early prediction and intervention strategies for depression, integrating genetic, metabolic, and traditional Chinese medicine perspectives.
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