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摘要
Background: Osteoarthritis (OA) is the most common chronic disorder of joints; however, the key genes and transcription factors (TFs) associated with OA are still unclear. Through bioinformatics tools, the study aimed to understand the mechanism of genes associated with the development of OA. @@@ Methods: Four gene expression profiling datasets were used to identify differentially expressed genes (DEGs) between OA and healthy control samples by a meta-analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed with Multifaceted Analysis Tool for Human Transcriptome (MATHT). Subsequently, a protein-protein interaction (PPI) network was constructed for these DEGs. Significant network modules were identified using ReactomeFIViz, and the pathway of each module was enriched using MATHT. In addition, TFs in the DEGs were identified. @@@ Results: In total, 690 DEGs were identified between OA and healthy control samples, including 449 upregulated and 241 downregulated DEGs. Additionally, 622 nodes and 2752 interactions constituted the PPI network, including 401 upregulated and 221 downregulated DEGs. Among them, FOS, TWIST1, POU2F1, SMARCA4, and CREBBP were also identified as TFs. RT-PCR results showed that the expression levels of Fos, Twist1, Pou2f1, Smarca4, and Crebbp decreased in mice with OA. In addition, FOS, TWIST1, SMARCA4, and CREBBP were involved in the positive regulation of transcription from the RNA polymerase II promoter. @@@ Conclusions: TWIST1, POU2F1, SMARCA4, and CREBBP may play an important role in OA pathology.
- 出版日期2018-3-7
- 单位山东中医药大学
