Identification and validation of susceptibility modules and hub genes in polyarticular juvenile idiopathic arthritis using WGCNA and machine learning

• Published in: Autoimmunity (Chur, Switzerland) Vol. 58; no. 1; p. 2437239
• Main Authors: Liu, Junfeng, Fan, Jianhui, Duan, Hongxiang, Chen, Guoming, Zhang, Weihua, Wang, Pingxi
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Group 01.12.2025
• Subjects: Arthritis, Juvenile - diagnosis; Arthritis, Juvenile - genetics; Biomarkers; Child; co-expression modules; Computational Biology - methods; Databases, Genetic; Gene Expression Profiling; Gene Ontology; Gene Regulatory Networks; Genetic Predisposition to Disease; Humans; Juvenile rheumatoid arthritis; Machine Learning; Prognosis; prognostic genes; Protein Interaction Maps - genetics; Transcriptome; weighted gene co-expression network analysis; co-expression modules; Juvenile rheumatoid arthritis; weighted gene co-expression network analysis; prognostic genes

Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflammation, swelling, pain, and limited mobility, potentially lead...