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pmid:34580642
Identification of Vital Hub Genes and Potential Molecular Pathways of Dermatomyositis by Bioinformatics Analysis.
Xueren Ouyang · Yuning Zeng · Xiaotao Jiang · Hua Xu · Yile Ning
BioMed research international · 2021 doi:10.1155/2021/9991726
Paper
complete
Experiment
partial
Data
partial
Analysis
complete
Execution
absent
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Complete file
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This study was aimed at discovering vital hub genes and potential molecular pathways of DM through bioinformatics analysis, which contributes to identifying potential diagnostic or therapeutic biomarkers and targets. In this study, a total of 915 DEGs in DM samples including 167 upregulated genes and 748 downregulated genes were screened out by the limma package based on the GSE142807 dataset from the Gene Expression Omnibus (GEO) database. Furthermore, the results of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that these downregulated genes were highly associated with the immune-related biological processes and pathways. Therefore, 41 genes closely related to DM were extracted for further study based on the subcluster analysis through the Molecular Complex Detection (MCODE) software plugin in Cytoscape. Ultimately, 10 hub genes (including ISG15, DDX58, IFIT3, CXCL10, and STAT1) were identified as the potential candidate biomarkers and targets. Besides, we found that the identified hub genes directly or indirectly communicated with each other via molecular signaling pathways on the protein and transcription level. In general, under the guidance of bioinformatics analysis, 10 vital hub genes and molecular mechanisms in DM were identified and the expression of proinflammatory factors and interferon family proteins and genes showed high association with DM, which might help provide a theoretical foundation for the development of point-to-point targeted therapy in the future treatment of DM.", "claims": [{"id": "claim-method", "statement": "The DEGs between dermatomyositis samples and healthy samples were filtered out by running the limma package in R (version 3.5.3) [15].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34580642", "locator": "sections[4] \"2.2. 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