基于生物信息学工具的骨关节炎关键基因和通路的鉴定：一项更新分析。
Identification of Key Genes and Pathways in Osteoarthritis via Bioinformatic Tools: An Updated Analysis.
机构信息
Department of Orthopedics, The First Affiliated Hospital of Soochow University, Suzhou, China.
Orthopedic Institute, Soochow University, Suzhou, China.
出版信息
Cartilage. 2021 Dec;13(1_suppl):1457S-1464S. doi: 10.1177/19476035211008975. Epub 2021 Apr 15.
OBJECTIVE
Osteoarthritis (OA) is a severe and common degenerative disease; however, the exact pathology of OA is undefined. Our study is designed to investigate the underlying molecular mechanism of OA with bioinformatic tools.
DESIGN
Three updated GEO datasets: GSE55235, GSE55457, and GSE82107 were selected for data analyzing. R software was utilized to screen and confirm the candidate differentially expressed genes in the development of OA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway were performed to identify the enriched GO terms and signaling pathways. Protein and protein interaction (PPI) models were built to observe the connected relationship among each potential protein.
RESULTS
A total of 113 upregulated genes and 161 downregulated genes were found by integrating 3 datasets. GO enrichment indicated that cell differentiation, cellular response to starvation, and negative regulation of phosphorylation were important biological processes. KEGG enrichment indicated that FoxO, IL-17 signaling pathways, and osteoclast differentiation mainly participated in the progression of OA. Combining the molecular function and PPI results, ubiquitylation was identified as a pivotal bioactive reaction involved in OA.
CONCLUSION
Our study provided updated candidate genes and pathways of OA, which may benefit further research and treatment for OA.
目的
骨关节炎（OA）是一种严重且常见的退行性疾病，但 OA 的确切病理机制尚不清楚。我们的研究旨在利用生物信息学工具探讨 OA 的潜在分子机制。
设计
选择了三个更新的 GEO 数据集：GSE55235、GSE55457 和 GSE82107 进行数据分析。R 软件用于筛选和确认 OA 发生过程中的候选差异表达基因。进行基因本体论（GO）和京都基因与基因组百科全书通路分析，以鉴定富集的 GO 术语和信号通路。构建蛋白质和蛋白质相互作用（PPI）模型，以观察每个潜在蛋白质之间的连接关系。
结果
通过整合三个数据集，共发现 113 个上调基因和 161 个下调基因。GO 富集分析表明，细胞分化、细胞对饥饿的反应和磷酸化的负调控是重要的生物学过程。KEGG 富集表明 FoxO、IL-17 信号通路和破骨细胞分化主要参与 OA 的进展。结合分子功能和 PPI 结果，泛素化被确定为 OA 中涉及的关键生物活性反应。
结论
本研究提供了 OA 的更新候选基因和通路，可能有助于 OA 的进一步研究和治疗。
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