An Integrative Transcriptomic Analysis of Systemic Juvenile Idiopathic Arthritis for Identifying Potential Genetic Markers and Drug Candidates

• Published in: International journal of molecular sciences 2021-01, Vol.22 (2), p.712
• Main Authors: Kim, Daeun, Song, Jaeseung, Lee, Sora, Jung, Junghyun, Jang, Wonhee
• Format: Article
• Language: English
• Subjects: Arthritis; Arthritis, Juvenile - drug therapy; Arthritis, Juvenile - genetics; Cytokines; Datasets; DNA microarrays; Down-Regulation - genetics; Drug development; Drug Discovery - methods; drug repositioning; Fever; Gene clusters; Gene expression; Gene Expression Profiling - methods; Gene Expression Regulation - genetics; Gene Regulatory Networks - genetics; Genes; Genetic markers; Genetic Markers - genetics; Humans; Joint diseases; Meta-analysis; Microarray Analysis - methods; Mortality; Network analysis; Pathogenesis; Principal components analysis; systemic juvenile idiopathic arthritis; TNF inhibitors; Transcriptome - genetics; Tumor necrosis factor-TNF; Up-Regulation - genetics; weighted gene co-expression network analysis (WGCNA)
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms22020712

Systemic juvenile idiopathic arthritis (sJIA) is a rare subtype of juvenile idiopathic arthritis, whose clinical features are systemic fever and rash accompanied by painful joints and inflammation. Even though sJIA has been reported to be an autoinflammatory disorder, its exact pathogenesis remains unclear. In this study, we integrated a meta-analysis with a weighted gene co-expression network analysis (WGCNA) using 5 microarray datasets and an RNA sequencing dataset to understand the interconnection of susceptibility genes for sJIA. Using the integrative analysis, we identified a robust sJIA signature that consisted of 2 co-expressed gene sets comprising 103 up-regulated genes and 25 down-regulated genes in sJIA patients compared with healthy controls. Among the 128 sJIA signature genes, we identified an up-regulated cluster of 11 genes and a down-regulated cluster of 4 genes, which may play key roles in the pathogenesis of sJIA. We then detected 10 bioactive molecules targeting the significant gene clusters as potential novel drug candidates for sJIA using an in silico drug repositioning analysis. These findings suggest that the gene clusters may be potential genetic markers of sJIA and 10 drug candidates can contribute to the development of new therapeutic options for sJIA.