An integrative transcriptomic analysis of systemic juvenile idiopathic arthritis for identifying potential genetic markers and drug candidates

Daeun Kim, Jaeseung Song, Sora Lee, Junghyun Jung, Wonhee Jang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

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‐ex-pression 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‐reg-ulated 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‐regu-lated 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.

Original languageEnglish
Article number712
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Molecular Sciences
Volume22
Issue number2
DOIs
StatePublished - 2 Jan 2021

Keywords

  • Drug repositioning
  • Meta‐analysis
  • Systemic juvenile idiopathic arthritis
  • Weighted gene co‐expression network analysis (WGCNA)

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