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Reishi, Lingzhi · 2026 · Preprint

High relevance

Exploring the effect and mechanism of Ganoderma lucidum Polysaccharides on improving Paediatric MASLD based on network pharmacology and animal experiment

Ganoderma lucidum

Immune supportEnergy & fatigueMetabolic healthLiver support
SpeciesReishi, Lingzhi
JournalNot listed
Year2026

Key points

  • Abstract Background Paediatric Metabolic dysfunction-associated steatotic liver disease (MASLD) is a metabolic disorder resulting from chronic hepatic steatosis
  • Differentially expressed genes (DEGs) in the GSE185051 dataset and GLP-targeted genes were overlapped to identify candidate genes
  • Results Five key genes (ADRA2A, HTR2A, FGF2, MMP2, and TLR4) were selected as key genes through nine algorithms
  • The binding energy of HTR2A to the GLP component β-glucan was − 6.0 kJ/mol, suggesting a favourable binding effect
  • Western blot and QPCR results showed that the above beneficial effects could be achieved by regulating protein and the mRNA expression levels of ADRA2A, FGF2, MMP2, and TLR4 in the liver
  • Conclusions The study identified four key genes (ADRA2A, FGF2, MMP2, TLR4) play a role in GLP treatment of paediatric MASLD through the application of network pharmacology and Animal experiment

From the paper

Abstract

Abstract Background Paediatric Metabolic dysfunction-associated steatotic liver disease (MASLD) is a metabolic disorder resulting from chronic hepatic steatosis. Ganoderma lucidum polysaccharide (GLP) have several pharmacological effects. However, comprehensive investigations into the mechanistic basis of GLP's therapeutic effects in paediatric MASLD remained limited. This study investigates the underlying mechanisms of GLP in the treatment of pediatric MASLD through an integrated approach combining network pharmacology and Animal experiment. Methods To investigate the underlying mechanisms of Ganoderma lucidum polysaccharide (GLP) in the treatment of pediatric MASLD through an integrated approach combining network pharmacology and animal experiment. Differentially expressed genes (DEGs) in the GSE185051 dataset and GLP-targeted genes were overlapped to identify candidate genes. Intersecting genes from nine Cytohubba algorithms were identified as key genes. GGI network analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) demonstrated pathways influencing paediatric MASLD. Transcription factor (TF) regulation analysis of the key genes was performed, and a molecular regulatory network. Molecular docking was performed for GLP components and key genes. Animal experiments were performed to further substantiate the outcomes. Results Five key genes (ADRA2A, HTR2A, FGF2, MMP2, and TLR4) were selected as key genes through nine algorithms. Pentose and glucuronate interconversion and propanoate metabolism were significantly upregulated in paediatric MASLD patients. The Creb and Atf TF families play crucial roles in regulating key genes. The predicted lncRNA‒miRNA–key gene regulatory network contains 19 miRNAs (such as hsa-mir-15b-5p) and 39 lncRNAs (such as MALAT1). The binding energy of HTR2A to the GLP component β-glucan was − 6.0 kJ/mol, suggesting a favourable binding effect. Animal experiment result showed that GLP treatment could significantly reduce the levels of TG, TC, ALT and AST, alleviate hepatic lipid deposition and reduce pathological injury in MASLD mice. Western blot and QPCR results showed that the above beneficial effects could be achieved by regulating protein and the mRNA expression levels of ADRA2A, FGF2, MMP2, and TLR4 in the liver. Conclusions The study identified four key genes (ADRA2A, FGF2, MMP2, TLR4) play a role in GLP treatment of paediatric MASLD through the application of network pharmacology and Animal experiment. A perspective strategy is provided to offer the scientific foundations and healing mechanism of GLP for paediatric MASLD treatment.

Citation

Jiang T, Zheng X, Ouyang W, Li S (2026). Exploring the effect and mechanism of Ganoderma lucidum Polysaccharides on improving Paediatric MASLD based on network pharmacology and animal experiment. https://doi.org/10.21203/rs.3.rs-8597333/v1

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