ArticleBioMed research international2021
Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- KLRB1 gene in tumor immune regulation and disease prognosis: a multidimensional role review.Discover oncology · 2026Review
- Exploration of common genomic signatures of systemic juvenile idiopathic arthritis and Kawasaki disease.Clinical rheumatology · 2025Article
- Article
- Identification and validation of miR-29b-3p and LIN7A as important diagnostic markers for bone non-union by WGCNA.Journal of cellular and molecular medicine · 2024Article
- Biomarkers in Systemic Juvenile Idiopathic Arthritis, Macrophage Activation Syndrome and Their Importance in COVID Era.International journal of molecular sciences · 2022Review
- Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study.RMD open · 2022Article
- Implications of SARS-CoV-2 Infection in Systemic Juvenile Idiopathic Arthritis.International journal of molecular sciences · 2022Review
- Identification of Up-Regulated ANXA3 Resulting in Fracture Non-Union in Patients With T2DM.Frontiers in endocrinology · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systemic juvenile idiopathic arthritis (sJIA) is a severe autoinflammatory disorder with a still not clearly defined molecular mechanism. To better understand the disease, we used scattered datasets from public domains and performed a weighted gene coexpression network analysis (WGCNA) to identify key modules and hub genes underlying sJIA pathogenesis. Two gene expression datasets, GSE7753 and GSE13501, were used to construct the WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to the genes and hub genes in the sJIA modules. Cytoscape was used to screen and visualize the hub genes. We further compared the hub genes with the genome-wide association study (GWAS) genes and used a consensus WGCNA to verify that our conclusions were conservative and reproducible across multiple independent datasets. A total of 5,414 genes were obtained for WGCNA, from which highly correlated genes were divided into 17 modules. The red module demonstrated the highest correlation with the sJIA module (
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