Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis - Sun, Pengcheng; Wang, Yi; Liu, Xing; Li, Zhuqing; Cui, Diankun; Li, Qianru; Wang, Qi; Wang, Ji (Frontiers in Genetics, 2024)
Background: Allergic rhinitis (AR) is a widespread allergic disease that results from genetic and environmental factors. Pollen is a common allergen which can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons to investigate their relationship with asthma. Methods: We downloaded DNA methylation and gene expression data from the GEO database (GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis. We incorporated data on AR combined with asthma (GSE101720) to identify genes that promote the transformation of AR to asthma. We also utilized data on olive pollen allergy (GSE54522) to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1. Results: We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. ZNF667-AS1 was further validated in GSE54522. WGCNA identified 17 modules, among which the blue module (ZNF667-AS1's module) showed significant correlation with pollen allergy. The pathway analysis on the blue module genes identified a prominent cluster of pathways including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in TLR and MAPK signaling. Conclusions: We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.