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pmid:35003257
Identification of Latent Diagnostic Biomarkers and Biological Pathways in Dermatomyositis Based on WGCNA.
Shaxi Ouyang · Yifang Liu · Changjuan Xiao · Qinghua Zeng · Xun Luo · Xiaofang Hu · Shuoshan Xie
Journal of oncology · 2021 doi:10.1155/2021/1920111
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Experiment
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Data
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Analysis
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Complete file
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This research is designed to probe the latent pathogenesis of dermatomyositis, identify potential biomarkers, and reveal the pathogenesis of dermatomyositis through information biology analysis of gene chips.\nMETHODS: In this study, we utilised the GSE14287 and GSE11971 datasets rooted in the Gene Expression Omnibus (GEO) databank, which included a total of 62 DM samples and 9 normal samples. The datasets were combined, and the differentially expressed gene sets were subjected to weighted gene coexpression network analysis, and the hub gene was screened using a protein interaction network from genes in modules highly correlated with dermatomyositis progression.\nRESULTS: A total of 3 key genes-myxovirus resistance-2 (MX2), oligoadenylate synthetase 1 (OAS1), and oligoadenylate synthetase 2 (OAS2)-were identified in combination with cell line samples, and the expressions of the 3 genes were verified separately. The results showed that MX2, OAS1, and OAS2 were highly expressed in LPS-treated cell lines compared to normal cell lines. The results of pathway enrichment analysis of the genes indicated that all 3 genes were enriched in the cytosolic DNA signalling and cytokine and cytokine receptor interaction signalling pathways; the results of functional enrichment analysis showed that all 3 were enriched in interferon-α response and interferon-γ response functions.\nCONCLUSIONS: This is important for the study of the pathogenesis and objective treatment of dermatomyositis and provides important reference information for the targeted therapy of dermatomyositis.", "claims": [{"id": "claim-method", "statement": "Differential analysis of normal and dermatomyositis samples in the GEO dataset was performed using the “limma” package in R v4.0.4; differential analysis of normal and dermatomyositis model cell samples was performed using the DEseq2 package in R v4.0.4.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35003257", "locator": "sections[6] \"2.4. 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