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pmid:34552988
Identification of Key Genes and Immune Infiltrate in Nonalcoholic Steatohepatitis: A Bioinformatic Analysis.
Zhen-Yu Jiang · Yi Zhou · Lu Zhou · Shao-Wei Li · Bang-Mao Wang
BioMed research international · 2021 doi:10.1155/2021/7561645
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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The discovery of new biomarkers would aid in the treatment of NASH.\nMETHODS: Data GSE89632 were downloaded from the Gene Expression Omnibus (GEO) database, and R package \"limma\" was used to identify differentially expressed genes (DEGs) for NASH vs. normal tissues. The STRING database was used to construct a protein-protein interaction (PPI) network, and the Cytoscape software program (Version 3.80) was used to visualize the PPI network and identify key genes. The immune infiltration of NASH was determined using the R package \"CIBERSORT\".\nRESULTS: We screened 41 DEGs. GO and KEGG enrichment analyses of the DEGs revealed the enrichment of pathways related to NAFLD steatosis and inflammation. A PPI network analysis was also performed on the DEGs, and seven genes (MYC, CXCL8, FOS, SOCS1, SOCS3, IL6, and PTGS2) were identified as hub genes. An immune infiltration assessment revealed that macrophages M2, memory resting CD4+ T cells, and γΔ T cells play important roles in the immune microenvironment of NASH, which may be mediated by the seven identified hub genes.", "claims": [{"id": "claim-method", "statement": "We downloaded the gene expression matrix of GSE89632 and the annotation file of GPL14951. First, we replace the ID of the probe with the gene symbol, and if they have the same probe, the max one will be retained. According to the aim of our study, we retained expression profiling data for only 24 HCs and 19 NASH patients. As the data had already been processed in a “quantile normalized” fashion, we proceeded directly to the next analysis. 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