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Journal of Chinese Pharmaceutical Sciences ›› 2024, Vol. 33 ›› Issue (11): 1025-1039.DOI: 10.5246/jcps.2024.11.074

• Original articles • Previous Articles     Next Articles

Deciphering the therapeutic mechanisms of Fructus Ligustri Lucidi on diabetic nephropathy via bioinformatics analysis

Qinqing Li1,2, Yanli Xin1, Pulin Liu2, Kaiwen Li1, Caifang Jing1, Xuelan Zhang2,*(), Wenbin He1,*()   

  1. 1 Shanxi Key Laboratory of Traditional Chinese Medicine Encephalopathy, National International Joint Research Center of Molecular Traditional Chinese Medicine, Shanxi University of Chinese Medicine, Taiyuan 030024, Shanxi, China
    2 Shandong University of Traditional Chinese Medicine, Jinan 250355, Shangdong, China
  • Received:2024-06-15 Revised:2024-08-11 Accepted:2024-09-20 Online:2024-12-10 Published:2024-12-10
  • Contact: Xuelan Zhang, Wenbin He
  • Supported by:
    The National Natural Science Foundation of China (Grant No. 81973486, 82173974), the State Administration of Traditional Chinese Medicine Processing Technology Inheritance Project (Grant No. 202259), the National Key Research and Development Plan (Grant No. 2018YFC1707002), the Shanxi Provincial Basic Research Program General Project (Grant No. 202203021211220), and the Study on Processing Synergistic Mechanism of Ligustrum against Diabetic Nephropathy Based on TGFB1/Smads Pathway (Grant No. 2024ZYYA021).

Abstract:

This study aimed to investigate the potential mechanisms underlying the therapeutic effects of Fructus Ligustri Lucidi in the treatment of diabetic nephropathy (DN) through bioinformatics analysis. The research commenced with a comprehensive database search for DN-associated datasets and gene targets of Fructus Ligustri Lucidi. Subsequently, the ssGSEA method was employed to score the drug target gene sets, and based on these scores, subjects were categorized. Further analysis involved differential analysis and enrichment analysis techniques to elucidate differentially expressed genes (DEGs) and associated pathways between the two groups. Based on the ssGSEA scoring results, the data were stratified into two groups: the "High NZZ group" and the "Low NZZ group". Through differential analysis, a total of 18 DEGs were identified, comprising 14 upregulated genes (EGR1, CCL2, CDH6, VCAN-AS1, VCAN, C3, MMP7, RNASE6, C1QC, MOXD1, APOC1, SFRP2, CCL21, and LUM) and four downregulated genes (OTTHUMG00000152025, RERG, B3GALT2, and NELL1). Notably, several genes exhibited concurrent expression patterns in both the DN and High NZZ groups, including VCAN-AS1, CCL21, VCAN, MOXD1, CCL2, SFRP2, MMP7, C3, RNASE6, LUM, C1QC, APOC1, and CDH6. Enrichment analysis revealed significant enrichment in pathways related to "regulation of apoptotic cell clearance" and "granulocyte chemotaxis", among others. These findings highlighted the potential value of Fructus Ligustri Lucidi in the treatment of DN and unveiled novel potential targets for prognosis and therapy in DN patients. This study offered promising avenues for enhancing both the prognosis and treatment outcomes for individuals affected by this condition.

Key words: Diabetic kidney disease, Fructus Ligustri Lucidi, Bioinformatics, Data analysis

Supporting: /attached/file/20241214/20241214114423_929.pdf