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pmid:33855867
Identification of Key Genes and Pathways in Osteoarthritis via Bioinformatic Tools: An Updated Analysis.
Yijian Zhang · Tianfeng Zhu · Fan He · Angela Carley Chen · Huilin Yang · Xuesong Zhu
Cartilage · 2021 doi:10.1177/19476035211008975
Paper
complete
Experiment
complete
Data
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Analysis
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Execution
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Complete file
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Our study is designed to investigate the underlying molecular mechanism of OA with bioinformatic tools.\nDESIGN: 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.\nRESULTS: 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. 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