Neutrophil extracellular traps-associated candidate genes in IgA vasculitis: an exploratory multi-omics analysis...

Neutrophil extracellular traps (NETs) have been implicated in the pathogenesis of IgA vasculitis (IgAV), yet the NET-associated genes and their immune cell-specific contexts remain incompletely defined. This study aimed to exploratorily identify NET-associated candidate genes related to IgAV using an integrated multi-omics approach.

Peripheral-blood bulk transcriptomic data from IgAV patients and healthy controls were analyzed for differential expression. A curated set of 646 NET-associated genes was evaluated using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Differentially expressed genes, NET-related GSEA leading-edge genes, and transcriptome-wide association study (TWAS)-significant genes were intersected to prioritize candidate genes. Genetically supported associations with IgAV susceptibility were assessed using two-sample Mendelian randomization (MR), including cell-type-specific MR. Exploratory immune profiling and intercellular communication analyses were performed using single-sample GSEA and single-cell RNA sequencing (scRNA-seq).

Five NET-associated candidate genes-AGER, TLR2, CXCR2, TEK, and THBD-were consistently prioritized across analyses. MR results indicated that genetically predicted higher expression of AGER, TLR2, and CXCR2 was associated with increased IgAV risk, whereas TEK and THBD showed inverse associations. Single-cell analyses suggested that these genes were mainly expressed in myeloid immune subsets, accompanied by elevated NETosis-related transcriptional signatures. Enhanced activity of immune-related signaling pathways, including MHC-I and MIF, was observed in IgAV samples.

This exploratory multi-omics study identified a set of NET-associated candidate genes showing consistent associations with IgAV. These findings provide a hypothesis-generating framework for understanding NET-related immune processes in IgAV and warrant further validation in larger cohorts and functional studies.