Investigating genetic drivers of juvenile dermatomyositis pathogenesis using bioinformatics methods.

Juvenile dermatomyositis (JDM) is a chronic autoimmune disease. The pathogenic mechanisms remain ill-defined. The purpose of this study was to identify key genes related to JDM. Microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEG) were identified. Then, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and protein-protein interaction (PPI) network were carried out. In addition, the hub genes were selected by cytoHubba. The expression profile and diagnostic capacity (receiver-operator curve [ROC]) of interested hub genes were verified. Gene set enrichment analysis (GSEA) was also carried out. Moreover, the signature of hub genes was then used as a search query to explore the Connectivity Map (CMAP). A total of 128 DEG were identified. The enriched functions and pathways of the DEG include response to virus, negative regulation of cell migration, cadmium ion transmembrane transport, defense response to Gram-negative bacterium, positive regulation of megakaryocyte differentiation, and negative regulation of angiogenesis. Twenty-one hub genes were identified. The expression levels of the interested genes were also confirmed. ROC analysis confirmed that the expression of these genes can distinguish JDM from controls. GSEA showed that these genes are mainly related to "inflammatory response", "complement", "interferon-α response", "IL6/JAK/STAT3 signaling", "TGF-β signaling", "IL2/STAT5 signaling" and "TNF-α signaling via NF-κB". The CMAP research found some compounds with the potential to counteract the effects of the dysregulated molecular signature in JDM. In this study, bioinformatics methods were used to identify DEG, which helps us understand the molecular mechanisms of JDM and provide candidate targets for diagnosis and treatment of JDM.