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Profiles of immune infiltration in seasonal allergic rhinitis and related genes and pathways

免疫系统 免疫学 外周血单个核细胞 CD8型 流式细胞术 生物 T细胞 医学 遗传学 体外
作者
Suizi Zhou,Chaozheng Zhou,Xinyue Wang,Peng Luo,Anqi Lin,Yi Cui,Qianhui Qiu
出处
期刊:International Immunopharmacology [Elsevier]
卷期号:120: 110174-110174 被引量:1
标识
DOI:10.1016/j.intimp.2023.110174
摘要

Seasonal allergic rhinitis (SAR) is a chronic inflammatory disease for which the molecular mechanism is unclear. Whole blood, CD4+ T cells in peripheral blood mononuclear cells (PBMCs), and CD4+ T cells in nasal mucosa from SAR-related datasets (GSE43497, GSE50223, and GSE49782) were downloaded from the Gene Expression Omnibus (GEO) database. Differences in SAR-associated immune cell infiltration in the PBMCs were analyzed using the CIBERSORT algorithm. Differential gene expression analysis was conducted between different groups. Gene set enrichment analysis (GSEA) was performed using the clusterProfiler package to explore functional changes in signaling pathways. There was a significant increase in the proportion of CD8+ T cells and a significant decrease in the proportion of neutrophils in the whole blood of SAR patients after allergen challenge compared to SAR patients after diluent challenge. This pattern was also found in SAR patients compared to healthy controls (HCs) by flow cytometry. The NF-κB and Toll-like receptor signaling pathways were enriched in SAR patients following allergen challenge. The expression of CD4+ T cell marker genes and associated cytokines significantly differed between allergen-treated SAR patients, diluent-treated SAR patients and HCs. We also observed heightened CD4+ T cell related genes, cytokines and pathways activation in the nasal mucosa region of SAR patients after allergen challenge. Our analysis revealed that T cell receptor signaling pathways, T helper 1 (Th1) /T helper 2 (Th2) cell differentiation may contribute to the development of SAR. The present study is the first bioinformatic analysis to quantify immune cell infiltration and identify underlying SAR mechanisms from combined microarray data and provides insight for further research into the molecular mechanisms of SAR.
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