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Review

Epigenetic Immunologic Biomarkers in Allergic Rhinitis and CRSwNP: Methylation Signatures and Translational Prospects

Qinghua Liu ORCID ,  Liwei Chen ORCID
    Received: 17 August 2026; Revised: 14 September 2026; Accepted: 17 September 2026; Published: 28 September 2026

    Abstract

    Allergic rhinitis (AR) and chronic rhinosinusitis with nasal polyps (CRSwNP) are distinct inflammatory disorders that may share type 2 immune features but differ in tissue pathology, clinical course, and therapeutic decision-making. This narrative review evaluates epigenetic immunologic biomarkers in the two diseases, with emphasis on deoxyribonucleic acid (DNA) methylation while also considering histone regulation and non-coding ribonucleic acid (RNA) networks. A structured literature search was used to organize evidence by disease, specimen, study design, and degree of clinical validation. Human AR studies provide signals in nasal epithelium, peripheral blood, and immune-cell subsets that relate to allergen exposure, symptom burden, immunoglobulin E (IgE)-associated biology, or treatment-associated changes. In CRSwNP, most epigenetic evidence comes from polyp or bulk sinonasal tissue and identifies methylation, chromatin, and microRNA patterns linked to inflammation and remodeling. These findings are biologically informative, but bulk-tissue signals can be strongly influenced by cell composition, and direct comparison across blood, nasal brushings, polyp tissue, and experimental models is not valid without qualification. No methylation- or RNA-based classifier has yet been prospectively validated to screen for future CRSwNP, replace current type 2 inflammatory markers, or select biologic therapy. Epigenetic enzyme inhibition and RNA delivery remain predominantly preclinical and face substantial challenges in target specificity, delivery, durability, and safety. The most credible path toward translation is therefore disease-specific and tissue-aware: standardized nasal sampling, cell-resolved profiling, independent multicenter validation, longitudinal designs, and demonstration of added value over established clinical biomarkers. Early risk prediction should currently be viewed as a research objective rather than a clinical application.

    Keywords

    References

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