Zhang Yufeng, Niu Yingzhen, Peng Yonggang, Pan Xueyang, Wang Fei
Department of Orthopedic Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, Hebei 050051, P.R. China.
Department of Tactical Medical Service, Special Medical Service Teaching and Research Section, Army Medical University Non-Commissioned Officer School, Shijiazhuang, Hebei 050051, P.R. China.
Exp Ther Med. 2023 Oct 2;26(5):540. doi: 10.3892/etm.2023.12239. eCollection 2023 Nov.
Osteoarthritis (OA) is a non-inflammatory degenerative joint disease, characterized by joint pain and stiffness. The prevalence of OA increases with age. However, the relationship between biomarkers [collagen type III α1 (COL3A1), COL5A1, COL6A2, COL12A1] and OA remains unclear. The OA subchondral bone dataset GSE51588 was downloaded from the GEO database, and the differentially expressed genes (DEGs) were screened. Weighted gene co-expression network analysis was performed, and a protein-protein interaction network was constructed and further analyzed using Cytoscape and STRING. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and then Gene Set Enrichment Analysis (GSEA) was used to formulate the molecular functions and pathways based on the results of GO and KEGG analyses. Comparative Toxicogenomics Database and TargetScan were used to identify the hub-gene-related diseases and the microRNAs that regulated the central hub genes. Immunohistochemical staining was performed to confirm the expression of related proteins in OA and non-OA tissue samples. A total of 1,679 DEGs were identified. GO analysis showed that the DEGs were primarily enriched in the process of 'immune system', 'extracellular region', 'secretory granule', 'collagen-containing extracellular matrix', 'ECM-receptor, glycosaminoglycan binding' and 'systemic lupus erythematosus'. The results of GSEA were similar to those of GO and KEGG enrichment terms for DEGs. A total of 25 important modules were generated, and two core gene clusters and seven core genes were obtained (COL6A2, COL5A2, COL12A1, COL5A1, COL6A1, LUM and COL3A1). Core genes were expressed differentially between OA subchondral bone and normal tissue samples. The expression levels of COL3A1, COL5A1 and COL6A2 in OA subchondral bone tissue were higher compared with those in normal tissues, but COL12A1 expression was not significantly increased; all stained markers were highly expressed in surrounding tissues of immunohistochemical staining. In conclusion, COL3A1, COL5A1 and COL6A2 may be potential molecular biomarkers for OA.
骨关节炎(OA)是一种非炎性退行性关节疾病,其特征为关节疼痛和僵硬。OA的患病率随年龄增长而增加。然而,生物标志物[III型胶原蛋白α1(COL3A1)、COL5A1、COL6A2、COL12A1]与OA之间的关系仍不清楚。从基因表达综合数据库(GEO)下载OA软骨下骨数据集GSE51588,并筛选差异表达基因(DEG)。进行加权基因共表达网络分析,构建蛋白质-蛋白质相互作用网络,并使用Cytoscape和STRING进一步分析。使用基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析进行功能富集分析,然后基于GO和KEGG分析结果使用基因集富集分析(GSEA)来确定分子功能和途径。使用比较毒理基因组学数据库和TargetScan来识别枢纽基因相关疾病以及调控核心枢纽基因的微小RNA。进行免疫组织化学染色以确认相关蛋白在OA和非OA组织样本中的表达。共鉴定出1679个DEG。GO分析表明,DEG主要富集于“免疫系统”“细胞外区域”“分泌颗粒”“含胶原蛋白的细胞外基质”“细胞外基质受体、糖胺聚糖结合”和“系统性红斑狼疮”过程。GSEA结果与DEG的GO和KEGG富集术语结果相似。共生成25个重要模块,获得两个核心基因簇和7个核心基因(COL6A2、COL5A2、COL12A1、COL5A1、COL6A1、LUM和COL3A1)。核心基因在OA软骨下骨和正常组织样本之间差异表达。与正常组织相比,OA软骨下骨组织中COL3A1、COL5A1和COL6A2的表达水平更高,但COL12A1表达未显著增加;在免疫组织化学染色的周围组织中所有染色标志物均高表达。总之,COL3A1、COL5A1和COL6A2可能是OA潜在的分子生物标志物。