Identification of the shared molecular mechanisms between major depressive disorder and COVID-19 from postmortem brain transcriptome analysis

Objectives: This study aims to investigate the molecular mechanisms underlying the interaction of major depressive disorder (MDD) and COVID-19, and on this basis, diagnostic biomarkers and potential therapeutic drugs are further explored.Methods: Differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify common key genes involved in the pathogenesis of COVID-19 and MDD. Correlations with clinical features were explored. Detailed mechanisms were further investigated through protein interaction networks, GSEA, and immune cell infiltration analysis. Finally, Enrichr's Drug Signature Database and Coremine Medical were used to predict the potential drugs associated with key genes.Results: The study identified 18 genes involved in both COVID-19 and MDD. Four key genes (MBP, CYP4B1, ERMN, and SLC26A7) were selected based on clinical relevance. A multi-gene prediction model showed good diagnostic efficiency for the two diseases: AUC of 0.852 for COVID-19 and 0.915 for MDD. GO and GSEA analyses identified specific biological functions and pathways associated with key genes in COVID-19 (axon guidance, metabolism, stress response) and MDD (neuron ensheathment, biosynthesis, glutamatergic neuron differentia-tion). The key genes also affected immune infiltration. Potential therapeutic drugs, including small molecules and traditional Chinese medicines, targeting these genes were identified.Conclusion: This study provides insights into the complex biological mechanisms underlying COVID-19 and MDD, develops an effective diagnostic model, and predicts potential therapeutic drugs, which may contribute to the prevention and treatment of these two prevalent diseases.

Automated summary

This study investigates the molecular mechanisms underlying the interaction between major depressive disorder (MDD) and COVID-19, and explores diagnostic biomarkers and potential therapeutic drugs. It identifies common key genes involved in both COVID-19 and MDD, and selects four key genes based on clinical relevance. A multi-gene prediction model shows good diagnostic efficiency for COVID-19 and MDD. The study also identifies specific biological functions and pathways associated with key genes, and predicts potential therapeutic drugs targeting these genes.