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Chinese Journal of Obesity and Metabolic Diseases(Electronic Edition) ›› 2025, Vol. 11 ›› Issue (02): 104-110. doi: 10.3877/cma.j.issn.2095-9605.2025.02.004

• Article • Previous Articles    

The Translational Genomics Study on the Gene Expression of Lipid Metabolism Induced by High-Fat Diet in Obesity Based on Bioinformatics

Zhong Ren1, Mengyuan Luo2, Zehui Yan3,4,*()   

  1. 1Changchun Infectious Disease Hospital, Orthopedics & General Surgery, Changchun 130000, China
    2College of Pharmacy, Chengdu University, Chengdu 610100
    3Health of College, Yantai Nanshan University, Yantai 265713
    4School of Public Health, China Medical University, Shenyang, 110122, China
  • Received:2024-11-28 Online:2025-05-30 Published:2025-09-06
  • Contact: Zehui Yan

Abstract:

Objective

This study aimed to investigate the physiological and metabolic changes induced by a high-fat diet in mice using bioinformatics methods, and to reveal the underlying molecular interaction mechanisms through systematic analysis of differential gene expression.

Methods

Gene expression data were retrieved from the GEO database, and the chip dataset GSE136821 was selected for analysis. Differentially expressed genes (DEGs) in mouse liver tissue were identified using several Bioconductor R packages (such as org.Mm.eg.db, Limma, and clusterProfiler). GO functional annotation and KEGG pathway enrichment analyses were performed on these DEGs. The top 200 DEGs were further used to construct a protein–protein interaction (PPI) network via the STRING online database, and high-degree hub genes were subsequently identified using Cytoscape.

Results

A total of 1 169 DEGs were identified, with 755 genes upregulated and 414 genes downregulated in the high-fat diet group. GO enrichment analysis revealed that these DEGs are involved in biological processes such as lipid metabolism, fatty acid metabolism, and regulation of inflammatory responses, and they exhibit various molecular functions including NAD(P)+ nucleosidase activity, lipase activity, and lipid transporter activity. KEGG pathway analysis further demonstrated significant enrichment of DEGs in several key biological pathways, notably the PI3K-Akt signaling pathway, PPAR signaling pathway, and cholesterol metabolism-related pathways. PPI network analysis further identified PPARγ, Src, and Manf as critical regulatory nodes, suggesting their important roles in high-fat diet-induced obesity and lipid metabolism dysregulation.

Conclusions

A high-fat diet significantly alters the expression of genes related to lipid metabolism and inflammatory regulation in the mouse liver. Key genes such as PPARγ, Src, and Manf interact to form a complex regulatory network.

Key words: Bioinformatics, Obesity, Lipid metabolism, Differential gene

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