Bioinformatics screening of key genes for endoplasmic reticulum stress in osteoarthritis and experimental validation
- VernacularTitle:骨关节炎内质网应激关键基因的生物信息学筛选及实验验证
- Author:
Maochen HAO
1
;
Chao MA
;
Kai LIU
;
Kexin LIU
;
Lingting MENG
;
Xingru WANG
;
Jianzhong WANG
Author Information
- Publication Type:Journal Article
- Keywords: osteoarthritis; endoplasmic reticulum; WGCNA; machine learning; human synoviocytes; immune infiltration analysis; biomarkers; experimental validation; cell experiment; differential genes
- From: Chinese Journal of Tissue Engineering Research 2025;29(26):5632-5641
- CountryChina
- Language:Chinese
- Abstract: BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.
