ArticlePediatric rheumatology online journal2023
Identification of key biomarkers in RF-negative polyarticular and oligoarticular juvenile idiopathic arthritis by bioinformatic analysis.
Article in Pediatric rheumatology online journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveJuvenile idiopathic arthritis (JIA) is a broad term used to describe arthritis of unknown origin. JIA commonly persists into adulthood, often causing substantial morbidity such as restricted joint function, which can lead to challenges in employment and independence. This study aims to identify diagnostic biomarkers and investigate the role of immune cells in the pathogenesis of rheumatoid factor-negative polyarticular juvenile idiopathic arthritis (RF-negative pJIA) and oligoarticular juvenile idiopathic arthritis (oJIA).
methodsWe retrieved a JIA dataset from the GEO database and conducted an analysis of differentially expressed genes (DEGs). Subsequently, functional enrichment analysis was performed on the DEGs. Weighted gene co-expression network analysis (WGCNA) was utilized to identify key modules. Additionally, we constructed a protein‒protein interaction network to identify hub genes that serve as signature genes. Furthermore, we employed CIBERSORT to classify immune cell infiltration.
resultsFrom the GSE20307 dataset, we identified a total of 1438 DEGs in RF-negative pJIA and 688 DEGs in oJIA. WGCNA clustered the data into 6 modules in pJIA and 4 modules in oJIA. Notably, the ME5 and ME2 modules exhibited significant associations with pJIA and oJIA, respectively. In both pJIA and oJIA, we identified six hub genes, four of which demonstrated high diagnostic sensitivity and specificity in pJIA, while five showed high diagnostic sensitivity and specificity in oJIA. CIBERSORT analysis suggested the potential involvement of these signature genes in immune cell infiltration.
conclusionIn this study, we identified JUN, CXCL8, SOCS3, and KRAS as biomarkers for RF-negative pJIA and JUN, CXCL8, SOCS3, PTGS2, and NFKBIA as biomarkers for oJIA. Furthermore, our findings suggest that Tfh cells may play a role in the early onset of both RF-negative pJIA and oJIA.
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