Mendelian Randomization Identifies IL-4, IL-6, CCL19, and DNER as Potential Causal Inflammatory Proteins in Allergic Rhinitis: Evidence Partially Supported by Transcriptomics and Protein Interaction Analysis

孟德尔随机化分析鉴定出IL-4、IL-6、CCL19和DNER是过敏性鼻炎中潜在的致病炎症蛋白:转录组学和蛋白质相互作用分析部分支持了这一发现。

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Abstract

Background Inflammatory proteins play a significant role in the pathogenesis of allergic rhinitis (AR), but the causal relationships remain unclear. We aimed to identify potential causal circulating inflammatory proteins contributing to the development of AR. Methods We employed Mendelian randomization (MR) analysis to determine the causal relationship between 91 circulating inflammatory proteins and AR. Inverse variance weighted (IVW) was the main analytic pipeline, followed by sensitivity analysis. The genome-wide association study (GWAS) summary datasets for AR and circulating inflammatory proteins were used for the analysis. The AR dataset comprised 12,240 cases and 392,069 controls, while the summary datasets for 91 plasma proteins contained 14,824 participants. Subsequent to the MR analysis, bioinformatic analysis was employed to probe differences in specific gene expression levels and to construct a network of associated proteins. Results The results of the MR analysis indicated that four inflammatory proteins had a causal effect on AR, including interleukin-4 (IL-4), interleukin-6 (IL-6), Chemokine (C-C motif) ligand 19 (CCL19), and Delta/Notch-like epidermal growth factor (EGF)-related receptor (DNER). Through differential gene expression analysis, IL4 mRNA expression was significantly elevated in AR patients compared to healthy controls. Protein-protein interaction (PPI) analysis via the STRING database revealed that IL-6, IL-4, and CCL19 constituted a densely connected network. Conclusion Our study supports the involvement of four circulating inflammatory proteins (IL-4, IL-6, CCL19, and DNER), especially IL-4, in susceptibility to AR. These findings highlight IL-4, IL-6, CCL19, and DNER as promising immunotherapeutic targets, providing mechanistic insights for developing novel diagnostics and biologic therapies for AR management.

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