Chu Zhen-Chen, Cong Ting, Zhao Jian-Yu, Zhang Jian, Lou Zhi-Yuan, Gao Yang, Tang Xin
Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Dalian Medical University, Dalian, Liaoning, China.
Front Med (Lausanne). 2023 Jul 3;10:1219830. doi: 10.3389/fmed.2023.1219830. eCollection 2023.
Osteoarthritis (OA) refers to a commonly seen degenerative joint disorder and a major global public health burden. According to the existing literature, osteoarthritis is related to epigenetic changes, which are important for diagnosing and treating the disease early. Through early targeted treatment, costly treatments and poor prognosis caused by advanced osteoarthritis can be avoided.
This study combined gene differential expression analysis and weighted gene co-expression network analysis (WGCNA) of the transcriptome with epigenome microarray data to discover the hub gene of OA. We obtained 2 microarray datasets (GSE114007, GSE73626) in Gene Expression Omnibus (GEO). The R software was utilized for identifying differentially expressed genes (DEGs) and differentially methylated genes (DMGs). By using WGCNA to analyze the relationships between modules and phenotypes, it was discovered that the blue module (MEBlue) has the strongest phenotypic connection with OA (cor = 0.92, p = 4e-16). The hub genes for OA, also known as the hub methylated differentially expressed genes, were identified by matching the MEblue module to differentially methylated differentially expressed genes. Furthermore, this study used Gene set variation analysis (GSVA) to identify specific signal pathways associated with hub genes. qRT-PCR and western blotting assays were used to confirm the expression levels of the hub genes in OA patients and healthy controls.
Three hub genes were discovered: HTRA1, P2RY6, and RCAN1. GSVA analysis showed that high HTRA1 expression was mainly enriched in epithelial-mesenchymal transition and apical junction; high expression of P2RY6 was mainly enriched in the peroxisome, coagulation, and epithelial-mesenchymal transition; and high expression of RCAN1 was mainly enriched in epithelial-mesenchymal-transition, TGF-β-signaling, and glycolysis. The results of the RT-qPCR and WB assay were consistent with the findings.
The three genes tested may cause articular cartilage degeneration by inducing chondrocyte hypertrophy, regulating extracellular matrix accumulation, and improving macrophage pro-inflammatory response, resulting in the onset and progression of osteoarthritis. They can provide new ideas for targeted treatment of osteoarthritis.
骨关节炎(OA)是一种常见的退行性关节疾病,也是全球主要的公共卫生负担。根据现有文献,骨关节炎与表观遗传变化有关,这对该疾病的早期诊断和治疗很重要。通过早期靶向治疗,可以避免晚期骨关节炎导致的昂贵治疗和不良预后。
本研究将转录组的基因差异表达分析和加权基因共表达网络分析(WGCNA)与表观基因组微阵列数据相结合,以发现骨关节炎的关键基因。我们在基因表达综合数据库(GEO)中获得了2个微阵列数据集(GSE114007、GSE73626)。利用R软件鉴定差异表达基因(DEGs)和差异甲基化基因(DMGs)。通过使用WGCNA分析模块与表型之间的关系,发现蓝色模块(MEBlue)与骨关节炎的表型联系最强(cor = 0.92,p = 4e - 16)。通过将MEblue模块与差异甲基化差异表达基因进行匹配,鉴定出骨关节炎的关键基因,也称为关键甲基化差异表达基因。此外,本研究使用基因集变异分析(GSVA)来鉴定与关键基因相关的特定信号通路。采用qRT-PCR和蛋白质印迹分析来确认关键基因在骨关节炎患者和健康对照中的表达水平。
发现了三个关键基因:HTRA1、P2RY6和RCAN1。GSVA分析表明,HTRA1高表达主要富集在上皮-间质转化和顶端连接;P2RY6高表达主要富集在过氧化物酶体、凝血和上皮-间质转化;RCAN1高表达主要富集在上皮-间质转化、TGF-β信号传导和糖酵解。RT-qPCR和WB检测结果与上述发现一致。
所检测的这三个基因可能通过诱导软骨细胞肥大、调节细胞外基质积累和改善巨噬细胞促炎反应,导致关节软骨退变,从而引发骨关节炎并使其进展。它们可为骨关节炎的靶向治疗提供新思路。