Liu Xiao-Yang, Yu Qiu-Ping, Guo Si-Qin, Chen Xu-Ming, Zeng Wei-Nan, Zhou Zong-Ke
Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, #37 Guoxue Road, Chengdu, 610041, People's Republic of China.
Health Management Center, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China.
J Orthop Surg Res. 2024 Oct 1;19(1):618. doi: 10.1186/s13018-024-05109-9.
Muscle atrophy is a typical affliction in patients affected by knee Osteoarthritis (KOA). This study aimed to examine the potential pathogenesis and biomarkers that coalesce to induce muscle atrophy, primarily through the utilization of bioinformatics analysis.
Two distinct public datasets of osteoarthritis and muscle atrophy (GSE82107 and GSE205431) were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA) to probe for common differentially expressed genes (DEGs) and conduct transcription factor (TF) enrichment analysis from such genes. Venn diagrams were used to identify the target TF, followed by the construction of a protein-protein interaction (PPI) network of the common DEGs governed by the target TF. Hub genes were determined through the CytoHubba plug-in whilst their biological functions were assessed using GSEA analysis in the GTEx database. To validate the study, reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Flow Cytometry techniques were employed.
A total of 138 common DEGs of osteoarthritis and muscle atrophy were identified, with 16 TFs exhibiting notable expression patterns in both datasets. Venn diagram analysis identified early growth response gene-1 (EGR1) as the target TF, enriched in critical pathways such as epithelial mesenchymal transition, tumor necrosis factor-alpha signaling NF-κB, and inflammatory response. PPI analysis revealed five hub genes, including EGR1, FOS, FOSB, KLF2, and JUNB. The reliability of EGR1 was confirmed by validation testing, corroborating bioinformatics analysis trends.
EGR1, FOS, FOSB, KLF2, and JUNB are intricately involved in muscle atrophy development. High EGR1 expression directly regulated these hub genes, significantly influencing postoperative muscle atrophy progression in KOA patients.
肌肉萎缩是膝骨关节炎(KOA)患者的一种典型病症。本研究旨在主要通过生物信息学分析,探究导致肌肉萎缩的潜在发病机制和生物标志物。
对两个不同的骨关节炎和肌肉萎缩公共数据集(GSE82107和GSE205431)进行差异基因表达分析和基因集富集分析(GSEA),以探寻共同的差异表达基因(DEGs),并对这些基因进行转录因子(TF)富集分析。使用韦恩图确定目标TF,随后构建由目标TF调控的共同DEGs的蛋白质-蛋白质相互作用(PPI)网络。通过CytoHubba插件确定枢纽基因,同时使用GTEx数据库中的GSEA分析评估其生物学功能。为验证该研究,采用了逆转录实时定量聚合酶链反应(qRT-PCR)、酶联免疫吸附测定(ELISA)和流式细胞术技术。
共鉴定出138个骨关节炎和肌肉萎缩的共同DEGs,其中16个TF在两个数据集中均表现出显著的表达模式。韦恩图分析确定早期生长反应基因-1(EGR1)为目标TF,其富集于上皮-间质转化、肿瘤坏死因子-α信号通路NF-κB和炎症反应等关键通路。PPI分析揭示了五个枢纽基因,包括EGR1、FOS、FOSB、KLF2和JUNB。验证测试证实了EGR1的可靠性,证实了生物信息学分析趋势。
EGR1、FOS、FOSB、KLF2和JUNB与肌肉萎缩的发展密切相关。高EGR1表达直接调控这些枢纽基因,显著影响KOA患者术后肌肉萎缩的进展。