Volume 39 Issue 4
Apr.  2023
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Article Navigation >  Journal of Nanjing University of traditional Chinese Medicine  > 2023  >  39(4): 346-358
WAN Hao-ting, LIU Qing, LIU Lu-yao, XIE Lin-tong, ZHU Hui, LIU Xiao. Mechanism of Fangji Huangqi Tang against Nephrotic Syndrome Based on Network Pharmacology and Transcriptomics Methods[J]. Journal of Nanjing University of traditional Chinese Medicine, 2023, 39(4): 346-358. doi: 10.14148/j.issn.1672-0482.2023.0346
Citation: WAN Hao-ting, LIU Qing, LIU Lu-yao, XIE Lin-tong, ZHU Hui, LIU Xiao. Mechanism of Fangji Huangqi Tang against Nephrotic Syndrome Based on Network Pharmacology and Transcriptomics Methods[J]. Journal of Nanjing University of traditional Chinese Medicine, 2023, 39(4): 346-358. doi: 10.14148/j.issn.1672-0482.2023.0346
shu

Mechanism of Fangji Huangqi Tang against Nephrotic Syndrome Based on Network Pharmacology and Transcriptomics Methods

doi: 10.14148/j.issn.1672-0482.2023.0346
  • 1.

    School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China

  • 2.

    Jiangsu Key Laboratory of Chinese Medicine Processing, Nanjing 210023, China

  • 3.

    Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing, Nanjing University of Chinese Medicine, Nanjing 210023, China

  • Received Date: 2022-11-01
    Available Online: 2023-04-17
    Abstract
  •   OBJECTIVE  To explore the mechanism of Fangji Huangqi Tang (FHT) in the treatment of nephrotic syndrome (NS) based on transcriptomics and network pharmacology.  METHODS  Intersection target genes of network pharmacology and transcriptomics were collected for GO/KEGG functional enrichment analysis. Protein-protein interactions (PPI) were constructed and network topology analysis was performed to identify potential core targets. The pathway-target network map was constructed to identify the key signaling pathways. Finally, real-time quantitative PCR (qPCR), western blot and immunofluorescence staining were used to verify the mRNA and protein expression levels of core targets in kidney tissues of rats.  RESULTS  Seven potential core targets AKT1, AMPK, CPT1B, NF-κB1, P53, TGF-β1 and TLR4 were identified by PPI analysis. The main signaling pathways were AMPK, PI3K-Akt, PPAR, NF-κB, TGF-β, P53, MAPK, JAK-STAT and FoxO. In animal experiments, FHT significantly down-regulated the mRNA and protein expression levels of AKT1, CPT1B, NF-κB1, P53, TGF-β1, TLR4 (P < 0.05), and up-regulated the mRNA and protein expression levels of AMPK (P < 0.05).  CONCLUSION  From the perspective of network pharmacology and transcriptomics, the overall regulation features of multi-component, multi-target and multi-pathway of FHT against NS were preliminaries elaborated, which could provide the basis and reference for subsequent pharmacological research and clinical application of FHT.

     

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