Identification and validation of immune-associated NETosis subtypes and biomarkers in anti-neutrophil cytoplasmic antibody associated glomerulonephritis

作者：Tao Mi, Yiqing He, Lijuan Li, Yuyan Li, Wenwen Liao, Haihang Nie, Gao Ping · 发表于：Frontiers in Immunology · 年份：2023 · DOI：10.3389/fimmu.2023.1177968 · 被引用次数：16 · 研究领域：Neutrophil, Myeloperoxidase and Oxidative Mechanisms、Vasculitis and related conditions、Inflammasome and immune disorders

Background: NETosis is a new form of cell death, marked by DNA chromatin release from dead neutrophils. While it aids in microbe defense, it may worsen inflammation in autoimmune diseases, causing tissue harm. The impact of NETosis on Anti-neutrophil Cytoplasmic Antibody-associated Glomerulonephritis (ANCA-GN) remains unexplored and requires investigation. Methods: First, a weighted gene co-expression network analysis (WGCNA) was conducted to uncover differential expression of neutrophil extranuclear trap-associated genes (DE-NETs) in ANCA-GN. The NETosisScore model was established through the single sample gene set enrichment analysis (ssGSEA), which categorized all patients into high-risk and low-risk groups. The accuracy of model was assessed by ROC curve. The biological function of various subgroups was explored through Gene Set Variation Analysis (GSVA), while the abundance of immune cell infiltration was measured with CIBERSORT. Furthermore, the key NETosis-related genes (NRGs) were identified using three machine learning algorithms, and their relationship with renal function was analyzed through the NephroseqV5 database. Through the application of qPCR and immunohistochemical staining techniques, the mRNA and protein expression levels of NRGs were determined in patients with ANCA-GN and control. Results: A NETosisScore model was developed from 18 DE-NETs using the ssGSEA algorithm. The model's ability to predict ANCA-GN patients with a ROC AUC of 0.921. The high-risk g...