Screening and validation of glucose metabolism genes in osteoarthritis

doi:10.12307/2025.633

Abstract

Abstract: BACKGROUND: Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body. Glucose metabolism disorder can lead to a range of health problems. At present, the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.
OBJECTIVE: To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods, and to verify them by cell experiments in vitro, so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.
METHODS: Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database. The genes related to both osteoarthritis and glucose metabolism were obtained. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to screen the functions and pathways of these genes. To further investigate the interactions between these genes, a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes (Hub genes) for osteoarthritis glucose metabolism. In addition, CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set. Finally, the expression of Hub gene was verified by cell experiment in vitro.
RESULTS AND CONCLUSION: A total of 134 osteoarthritis glucose metabolism-related genes were obtained. GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances, the positive regulation of inflammatory reaction, the reaction of lipopolysaccharide and so on. KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway, interleukin-17 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Macrophages, monocytes, resting natural killer cells, regulatory T cells, and CD8+ T cells were the main infiltrating cells obtained by immune infiltration analysis. In vitro cell experiments showed that the expression of Hub genes SERPINF1, TAC1, GLUL, APOE, and TMEM176A in the experimental group was significantly different from that in the control group. The mRNA expression of HLA-DRA was not statistically significant. The results show that SERPINF1, TAC1, Glul, APOE, and TMEM176A may be the key genes of glucose metabolism in osteoarthritis, and may be potential new targets for the prevention and treatment of osteoarthritis.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: osteoarthritis, glucose metabolism, bioinformatics, differentially expressed genes, PPI network, immune infiltration, enrichment analysis, engineered tissue construction

CLC Number:

Liu Kexin, Ma Chao, Liu Kai, Hao Maochen, Wang Xingru, Meng Lingting, Dong Mei, Wang Jianzhong . Screening and validation of glucose metabolism genes in osteoarthritis[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(20): 4181-4189.

Figures/Tables 8

2.1 数据集获取在GEO数据库中获取符合筛选条件的数据集GSE98918，该数据集包含12例骨关节炎患者的半月板组织和12例非骨关节炎(关节镜下半月板部分切除术)患者的半月板组织。 2.2 数据处理及差异基因筛选运用R语言对GSE98918数据集进行差异表达基因的数据标准化预处理，标准化结果以箱式图呈现(图1)。使用R语言中的“limma”包，并且设定筛选条件为：P < 0.05且|log2FC|> 1，获得266个差异表达基因，其中上调基因145个、下调基因121个。使用“ggplot2”工具包绘制火山图(图2)及“pheatmap”工具包绘制热图(图3)。 2.3 交集基因通过查询GeneCards数据库，得到了10 899个与葡萄糖代谢相关的基因。与之前得到的骨关节炎差异表达基因进行交集分析后，发现有134个基因与骨关节炎和葡萄糖代谢相关，绘制韦恩图(图4)。 2.4 GO和KEGG通路富集分析对134个与骨关节炎和葡萄糖代谢相关基因进行了GO和KEGG富集分析，GO富集分析的结果显示：骨关节炎葡萄糖代谢相关基因在生物学过程中主要参与对有毒物质的反应、炎症反应的正调节、中性粒细胞迁移、血小板脱颗粒、对脂多糖的反应、参与炎症反应的白细胞迁移等过程；细胞组分显示其主要存在于含胶原蛋白的细胞外基质、分泌性颗粒腔、细胞质囊泡腔、胶原蛋白三聚体、网格蛋白包被的内吞囊泡、血小板α颗粒腔等；分子功能上，其在与酰胺结合、肽结合、构成细胞外基质结构成分、有机酸结合、钙依赖性蛋白结合、抗氧化活性、脂多糖结合、长链脂肪酸结合、淀粉样蛋白-β结合中发挥作用(图5)。根据KEGG富集分析结果显示：骨关节炎葡萄糖代谢相关基因在磷脂酰肌醇3-激酶-蛋白激酶B (phosphatidylinositol 3 kinase-protein"

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