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Updated: May 5, 2026

Flow Cytometry Analysis of Immune Cells Within Murine Aortas
Published on: July 1, 2011
Integrated bioinformatic analysis of the shared molecular mechanisms between ANCA-associated vasculitis and
Xun Hu1,2, Inmaculada Xu Lou2, Qilan Chen3
1Hangzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310053, China.
Background And Objective:
Accumulated evidence supports the tendency of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis(AAV) to coexist with atherosclerosis (AS). However, the common etiology of these two diseases remains unclear. This study aims to explore the mechanisms underlying the concurrent occurrence of ANCA and AS.
Methods:
Microarray data of AAV and AS were examined in a comprehensive gene expression database. Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis (GEO2R) were performed to identify common genes between AAV and AS. Based on the co-expressed genes, functional enrichment analysis, protein-protein interaction (PPI) network analysis, and identification of hub genes (HGs) were conducted. Subsequently, co-expression analysis of HGs was performed, and their expression and diagnostic value were validated. We further explored immune cell infiltration and analyzed the correlation between HGs and infiltrating immune cells. Finally, the reliability of the selected pathways was verified.
Results:
The results of the common gene analysis suggest that immune and inflammatory responses may be common features in the pathophysiology of AAV and AS. Through the interaction of different analysis results, we confirmed five HGs (CYBB, FCER1G, TYROBP, IL10RA, CSF1R). The CytoHubba plugin and HG validation demonstrated the reliability of the selected five HGs. Co-expression network analysis revealed that these five HGs could influence monocyte migration. Analysis of immune cell infiltration showed that monocytes in ANCA and M0 macrophages in AS constituted a higher proportion of all infiltrating immune cells, with significant differences in infiltration. We also found significant positive correlations between CYBB, FCER1G, TYROBP, IL10RA, CSF1R, and monocytes/M0 macrophages in AAV, as well as between CYBB, FCER1G, TYROBP, IL10RA, CSF1R, and M0 macrophages in AS.
Conclusion:
These five HGs can promote monocyte differentiation into macrophages, leading to the concurrent occurrence of AAV and AS. Our study provides insights into the mechanisms underlying the coexistence of AAV and AS.
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