Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular mechanisms in idiopathic pulmonary arterial hypertension (IPAH) pathogenesis remain largely unexplored. This study employed integrated bioinformatics approaches and experimental validation to identify NETs-related biomarkers in IPAH. We performed weighted gene co-expression network analysis (WGCNA) on merged transcriptomic datasets (GSE117261 and GSE48149, comprising 40 IPAH and 34 control samples), identifying a blue module significantly correlated with IPAH status. By intersecting module genes with 69 known NETs-related genes, we obtained 19 differentially expressed NETs-related genes (DE-NRGs) enriched in neutrophil degranulation, interleukin-6 regulation, and NETs formation pathways. Three complementary machine learning algorithms converged on five key biomarkers: CSF3R, MGAM, ITGAM, TLR8 (downregulated), and SELP (upregulated). These biomarkers demonstrated strong diagnostic performance in an independent validation cohort, with an area under the curve greater than 0.8. Immune infiltration analysis revealed significantly decreased neutrophils, macrophages, and myeloid-derived suppressor cells in IPAH patients. Single-cell RNA sequencing validated cell-type-specific expression patterns, with CSF3R predominantly in neutrophils, ITGAM/TLR8 in macrophages, and SELP in endothelial cells. Critically, monocrotaline-induced rat pulmonary arterial hypertension model confirmed significant downregulation of MGAM, CSF3R and ITGAM at protein levels. Our findings establish a NETs-related molecular signature for IPAH diagnosis and reveal impaired neutrophil function as a key pathogenic mechanism in IPAH, providing novel molecular targets for therapeutic intervention and risk stratification. • Integrated machine learning of transcriptomic data identified 5 novel NET-related biomarkers for idiopathic pulmonary arterial hypertension (IPAH). • The diagnostic potency of key biomarkers (MGAM, CSF3R, ITGAM) was confirmed in a rat model, with cell-type-specific expression revealed by scRNA-seq. • Immune profiling uncovered a "high-NET" IPAH subgroup with distinct thromboinflammatory features, aiding precision diagnosis and targeted therapy.