ArticleFrontiers in genetics2024
Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis.
Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Genetic mechanisms of pollinosis: interactions between genes and environmental factors.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Review
- Inhalant Mediated Allergy: Immunobiology, Clinical Manifestations and Diagnosis.Clinical reviews in allergy & immunology · 2025Review
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Authors and funding
8 authors.
Funding
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Abstract
Background: Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%-40% of the global population. Pollen is a common allergen, and exposure to pollen 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 using bioinformatics analysis and to investigate their relationship with asthma. Methods: We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis 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 related to the key methylation-driven gene Results: We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that Conclusion: 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.
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