Background. Juvenile dermatomyositis (JDM) is an immune-mediated disease characterized by chronic organ inflammation. The pathogenic mechanisms remain ill-defined. Methods. Raw microarray data of JDM were obtained from the gene expression omnibus (GEO) database. Based on the GSE3307 dataset with 39 samples, weighted correlation network analysis (WGCNA) was performed to identify key modules associated with pathological state. Functional enrichment analyses were conducted to identify potential mechanisms. Based on the criteria of high connectivity and module membership, candidate hub genes were selected. A protein-protein interaction network was constructed to identify hub genes. Another dataset (GSE11971) was used for the validation of real hub genes. Finally, the real hub genes were used to screen out smallmolecule compounds via the Connectivity map database. Results. Three modules were considered as key modules for the pathological state of JDM. Functional enrichment analysis indicated that responses to interferon and metabolism were dysregulated. A total of 45 candidate hub genes were selected according to the pre-established criteria, and 20 genes could differentiate JDM from normal controls by validation of another external dataset (GSE11971). These real hub genes suggested the pivotal role of mitochondrial dysfunction and interferon signature in JDM. Furthermore, drug repositioning highlighted the importance of acacetin, helveticoside, lanatoside C, deferoxamine, LY-294002, tanespimycin and L01AD from downregulated genes with the potential to perturb the development of JDM, while betonicine, felodipine, valproic acid, trichostatin A and sirolimus from upregulated genes provided potentially therapeutic goals for JDM. Conclusions. There are 20 real hub genes associated with the pathological state of JDM, suggesting the pivotal role of mitochondrial dysfunction and interferon signature in JDM. This analysis predicted several kinds of small-molecule compounds to treat JDM. Q. 2020. Co-expression network analysis reveals the pivotal role of mitochondrial dysfunction and interferon signature in juvenile dermatomyositis. PeerJ 8:e8611 http://doi.Burrows FJ, Fritz LC, Feinstein DL. 2006. The heat-shock protein 90 inhibitor 17allylamino-17-demethoxygeldanamycin suppresses glial inflammatory responses and ameliorates experimental autoimmune encephalomyelitis. Journal of Neurochemistry Drinkard BE, Hicks J, Danoff J, Rider LG. 2003. Fitness as a determinant of the oxygen uptake/work rate slope in healthy children and children with inflammatory myopathy. Canadian Journal of Applied Physiology 28:888-897 DOI 10.1139/h03-063. Feldman BM, Rider LG, Reed AM, Pachman LM. 2008. Juvenile dermatomyositis and other idiopathic inflammatory myopathies of childhood. . 2016. Vasculopathy-related clinical and pathological features are associated with severe juvenile dermatomyositis. Rheumatology 55:470-479 DOI 10.1093/rheumatology/kev359. Greenberg SA. 2010. Dermatomyositis and type 1 interferons. Current Rheumatology