Department of Orthopedics, The First People's Hospital of Dali City, Dali, Yunnan 671000, China.
Department of the Basic Medicine, The Kunming Medical University, Kunming, Yunnan 650500, China.
Comput Math Methods Med. 2022 Jul 11;2022:8953807. doi: 10.1155/2022/8953807. eCollection 2022.
Increasing evidence has suggested that obesity affects the occurrence and progression of osteoarthritis (OA). However, the underlying molecular mechanism that obesity affects the course of OA is not fully understood and remains to be studied.
The gene expression profiles of the GSE117999 and GSE98460 datasets were derived from the Gene Expression Omnibus (GEO) database. Firstly, we explored the correlation between obesity and OA using chi-square test. Next, weighted gene coexpression network analysis (WGCNA) was executed to identify obesity patients with OA- (obesity OA-) related genes in the GSE117999 dataset by "WGCNA" package. Moreover, differential expression analysis was performed to select the hub genes by "limma" package. Furthermore, ingenuity pathway analysis (IPA) and functional enrichment analysis ("clusterProfiler" package) were conducted to investigate the functions of genes. Finally, the regulatory networks of hub genes and protein-protein interaction (PPI) network were created by the Cytoscape 3.5.1 software and STRING.
A total of 15 differentially expressed obesity OA-related genes, including 9 lncRNAs and 6 protein coding genes, were detected by overlapping 66 differentially expressed genes (DEGs) between normal BMI samples and obesity OA samples and 451 obesity OA-related genes. Moreover, CCR10, LENG8, QRFPR, UHRF1BP1, and HLA-DRB4 were identified as hub genes. IPA results indicated that the hub genes were noticeably enriched in antimicrobial response, inflammatory response, and humoral immune response. PPI network showed that CCR10 interacted more with other proteins. Gene set enrichment analysis (GSEA) indicated that the hub genes were related to protein translation, cancer, chromatin modification, antigen processing, and presentation.
Our results further demonstrated the role of obesity in OA and might provide new targets for the treatment of obesity OA.
越来越多的证据表明肥胖会影响骨关节炎（OA）的发生和发展。然而，肥胖影响 OA 病程的潜在分子机制尚不完全清楚，有待进一步研究。
从基因表达综合数据库（GEO）中获取 GSE117999 和 GSE98460 数据集的基因表达谱。首先，我们使用卡方检验探讨肥胖与 OA 之间的相关性。接下来，我们使用“WGCNA”包在 GSE117999 数据集中进行加权基因共表达网络分析（WGCNA），以识别肥胖 OA 相关基因。此外，我们使用“limma”包进行差异表达分析，以筛选出枢纽基因。然后，我们进行了 Ingenuity 通路分析（IPA）和功能富集分析（“clusterProfiler”包），以研究基因的功能。最后，我们使用 Cytoscape 3.5.1 软件和 STRING 创建了枢纽基因的调控网络和蛋白质-蛋白质相互作用（PPI）网络。
通过重叠正常 BMI 样本和肥胖 OA 样本之间的 66 个差异表达基因（DEGs）和 451 个肥胖 OA 相关基因，我们共检测到 15 个差异表达的肥胖 OA 相关基因，包括 9 个 lncRNAs 和 6 个蛋白质编码基因。此外，我们还鉴定出 CCR10、LENG8、QRFPR、UHRF1BP1 和 HLA-DRB4 等枢纽基因。IPA 结果表明，这些枢纽基因明显富集在抗菌反应、炎症反应和体液免疫反应中。PPI 网络显示，CCR10 与其他蛋白质的相互作用更多。基因集富集分析（GSEA）表明，这些枢纽基因与蛋白质翻译、癌症、染色质修饰、抗原加工和呈递有关。
我们的研究结果进一步证实了肥胖在 OA 中的作用，并为肥胖 OA 的治疗提供了新的靶点。
