Identification of Potential Therapeutic Target Genes in Osteoarthritis

Yang Hu; Yinteng Wu; Fu Gan; Mingyang Jiang; Dongxu Chen; Mingjing Xie; Yiji Jike; Zhandong Bo

doi:10.1155/2022/8027987

Identification of Potential Therapeutic Target Genes in Osteoarthritis

Evid Based Complement Alternat Med. 2022 Aug 13:2022:8027987. doi: 10.1155/2022/8027987. eCollection 2022.

Authors

Yang Hu¹, Yinteng Wu¹, Fu Gan², Mingyang Jiang¹, Dongxu Chen³, Mingjing Xie¹, Yiji Jike¹, Zhandong Bo¹

Affiliations

¹ Department of Orthopedics, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
² Department of Urology Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, China.
³ Department of Joint Surgery and Sports Medicine, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin 541002, China.

Abstract

Objective: Osteoarthritis (OA), also known as joint failure, is characterized by joint pain and, in severe cases, can lead to loss of joint function in patients. Immune-related genes and immune cell infiltration play a crucial role in OA development. We used bioinformatics approaches to detect potential diagnostic markers and available drugs for OA while initially exploring the immune mechanisms of OA.

Methods: The training set GSE55235 and validation set GSE51588 and GSE55457 were obtained from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified by the limma package. Gene set enrichment analysis (GSEA) was performed on the GSE55235 dataset using the cluster profiler package. At the same time, DEGs were analyzed by gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, protein-protein interaction (PPI) analysis was performed on the common DEGs of the three datasets using the STRING database. Proteins with direct linkage were identified as hub genes, and the relation of hub genes was subsequently analyzed using the GOSemSim package. Hub genes' expression profiles and diagnostic capabilities (ROC curves) were analyzed and validated using three datasets. In addition, we performed RT-qPCR to validate the levels of hub genes. The immune microenvironment was analyzed using the CIBERSORT package, and the relationship between hub genes and immune cells was evaluated. In addition, we used a linkage map (CMAP) database to identify available drug candidates. Finally, the GSEA of hub genes was used to decipher the potential pathways corresponding to hub genes.

Results: Three hub genes (CX3CR1, MYC, and TLR7) were identified. CX3CR1 and TLR7 were highly expressed in patients with OA, whereas the expression of MYC was low. The results of RT-qPCR validation were consistent with those obtained using datasets. Among these genes, CX3CR1 and TLR7 can be used as diagnostic markers. It was found that CX3CR1, MYC, and TLR7 affect the immune microenvironment of OA via different immune cells. In addition, we identified a potential drug for the treatment of OA. Altogether, CX3CR1, MYC, and TLR7 affect the immune response of OA through multiple pathways.

Conclusion: CX3CR1, MYC, and TLR7 are associated with various immune cells and are the potential diagnostic markers and therapeutic targets for OA.