Previous gene expression analyses seeking genes specific to antineutrophil cytoplasmic antibody-associated vasculitis (AAV) have been limited due to crude cell separation and the use of microarrays. This study aims to identify AAV-specific gene expression profiles in a way that overcomes those limitations. Blood samples were collected from 26 AAV patients and 28 healthy controls (HCs). Neutrophils were isolated by negative selection, whereas 19 subsets of peripheral blood mononuclear cells were sorted by fluorescence assisted cell sorting. RNA-sequencing was then conducted for each sample, and iterative weighted gene correlation network analysis (iterativeWGCNA) and random forest were consecutively applied to identify the most influential gene module in distinguishing AAV from HCs. Correlations of the identified module with clinical parameters were evaluated, and the biological role was assessed with hub gene identification and pathway analysis. Particularly, the module's association with neutrophil extracellular trap formation, NETosis, was analyzed. Finally, the module's overlap with GWAS-identified autoimmune disease genes (GADGs) was assessed for validation. A neutrophil module (Neu_M20) was ranked top in the random forest analysis among 255 modules created by iterativeWGCNA. Neu_M20 correlated with disease activity and neutrophil counts but not with the presence of antineutrophil cytoplasmic antibody. The module comprised pro-inflammatory genes, including those related to NETosis, supported by experimental evidence. The genes in the module significantly overlapped GADGs. We identified the distinct group of pro-inflammatory genes in neutrophils, which characterize AAV. Further investigations are warranted to confirm our findings as they could serve as novel therapeutic targets. •Expression profile of a gene module in neutrophils characterizes AAV.•The module eigengene correlates with disease activity and neutrophil counts.•The module comprises pro-inflammatory genes, including those related to NETosis.•Genes in the module overlap autoimmune disease genes identified by GWAS.