Integrated network pharmacology and transcriptomics to reveal the mechanism of Passiflora against depressive disorder: An observational study

整合网络药理学和转录组学揭示西番莲抗抑郁症的机制:一项观察性研究

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Abstract

Relevant studies have pointed out that Passiflora could relieve depressive disorder (DD) related symptoms, such as anxiety and insomnia, but its mechanism in DD has not been reported. In this study, DD-related transcriptome data was extracted from the Gene Expression Omnibus (GEO) database. Subsequently, 50 differentially expressed genes (DEGs) were screened by "limma," and the enrichment analysis of these DEGs revealed that they were associated with neuro-inflammatory-related signaling pathways, including IL-17, TNF, NF-kappa B, etc signaling pathways. Then, CCDC58, CXCL5, EGR1, LOC101929855, SCML1, and THBS1 were screened as biomarkers of DD by the least absolute shrinkage and selection operator (LASSO) analysis. Moreover, Harmaline, Harmine, Quercetin, and Kaempferol were the key chemically active ingredients of Passiflora. Noticeable, THBS1 and Quercetin were connected closely. In addition, the quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the key biomarkers (EGR1 and THBS1) were significantly lowly expressed in DD samples. In summary, we identified 2 key biomarkers of DD and 4 key chemically active ingredients of Passiflora. The potential mechanism of antidepressant effect of DD associated with neuro-inflammatory responses and neurotransmitter function. These might related to the synergistic activity of its key active ingredients with TNF-α, IL-1β, IL-6, etc, which work with EGR1 and THBS1 to regulate IL-17, NF-kappa B, TNF, etc signaling pathways. These findings might help to deepen the understanding of the mechanism of Passiflora in clinical treatment of DD.

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