Dataset Information

Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA).

ABSTRACT:

Background

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.

Methods

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.

Results

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.

Conclusion

Our results further demonstrated the role of obesity in OA and might provide new targets for the treatment of obesity OA.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC9293492 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA).

Zhou Quan Q Sun Huan H Jia Jin J Jiang Jun-Liang JL Li Tao T Wu Zhao-Xiang ZX Chen Zhong Z

Computational and mathematical methods in medicine 20220711

<h4>Background</h4>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.<h4>Methods</h4>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, weig ...[more]

PMID: 35860189

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Dataset Information

Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA).

Background

Methods

Results

Conclusion

Publications

Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA).

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