ArticleFrontiers in molecular biosciences2021
Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 6 citations in OpenAlex.
- Identification and experimental validation of CD74, PGLYRP1, and TXN as potential biomarkers in rheumatoid arthritis: an integrative bulk and ScRNA-seq study.Frontiers in immunology · 2026Article
- Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization.Molecular medicine (Cambridge, Mass.) · 2025Article
- Human Umbilical Cord Mesenchymal Stem Cell-Derived Exosomes Loaded Mir-29-3p Targets AhR to Improve Juvenile Idiopathic Arthritis via Inhibiting the Expression of IL-22 in CD4Stem cell reviews and reports · 2025Article
- Biomarkers in Systemic Juvenile Idiopathic Arthritis, Macrophage Activation Syndrome and Their Importance in COVID Era.International journal of molecular sciences · 2022Review
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systemic juvenile idiopathic arthritis (sJIA) is a rare and serious type of JIA characterized by an unknown etiology and atypical manifestations in the early stage, and early diagnosis and effective treatment are needed. We aimed to identify diagnostic biomarkers, immune cells and pathways involved in sJIA pathogenesis as well as potential treatment targets. The GSE17590, GSE80060, and GSE112057 gene expression profiles from the Gene Expression Omnibus (GEO) database were screened to obtain differentially expressed genes (DEGs) between sJIA and healthy controls. Common DEGs were subjected to pathway enrichment analysis; a protein-protein interaction network was constructed, and hub genes were identified. In addition, functional annotation of hub genes was performed with GenCLiP2. Immune infiltration analysis was then conducted with xCell, and correlation analysis between immune cells and the enriched pathways identified from gene set variation analysis was performed. The Connectivity Map database was used to identify candidate molecules for treating sJIA patients. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was carried out, and the GEO dataset GSE8361 was applied for validation of hub gene expression levels in blood samples from healthy individuals with sJIA. A total of 73 common DEGs were identified, and analysis indicated enrichment of neutrophil and platelet functions and the MAPK pathway in sJIA. Six hub genes were identified, of which three had high diagnostic sensitivity and specificity; ARG1 and PGLYRP1 were validated by qRT-PCR and microarray data of the GSE8361 dataset. We found that increased megakaryocytes and decreased Th1 cells correlated positively and negatively with the MAPK pathway, respectively. Furthermore, MEK inhibitors and some kinase inhibitors of the MAPK family were identified as candidate agents for sJIA treatment. Our results indicate two candidate markers for sJIA diagnosis and reveal the important roles of platelets and the MAPK pathway in the pathogenesis of sJIA, providing a new perspective for exploring potential molecular targets for sJIA treatment.
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