Identification of biomarkers related to neutrophil extracellular traps and potential therapeutic drugs for rheumatoid arthritis using computational analysis.

ABSTRACT:

Background

Neutrophil extracellular traps (NETs) derived from neutrophils are implicated in the pathogenesis of rheumatoid arthritis (RA) pathogenicity, though the underlying mechanisms remain unclear.

Methods

Data were obtained from Gene Expression Omnibus (GEO) database. First, Gene Set Variation Analysis (GSVA) was used to calculate NET scores, and ConsensusClusterPlus was employed to classify RA samples. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to construct co-expression networks. Lasso regression and support vector machine recursive feature elimination (SVM-RFE) were then used to cross-screen biomarkers for RA, with predictive performance evaluated via the timeROC package. Immune infiltration in RA samples was assessed using ssGSEA and

SUBMITTER: Sheng L 

PROVIDER: S-EPMC12522263 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature