Nasal Mucosal Transcriptomic Markers in Airway Disease

Abstract

Understanding the molecular underpinnings of airway diseases has become increasingly possible with the advent of transcriptomic profiling technologies. Nasal mucosal transcriptomic markers offer a non-invasive window into the pathophysiology of both upper and lower airway diseases, including asthma, chronic rhinosinusitis, and allergic rhinitis. This review synthesizes current evidence regarding the utility of nasal transcriptomic biomarkers, elucidates their clinical relevance, examines their role in diagnosis and management, and discusses emerging advances and future directions. Through an in-depth exploration of transcriptomic signatures, we highlight the potential for precision medicine approaches in airway disease management.

Introduction

The respiratory tract, from the nasal mucosa to the bronchioles, shares a continuum of epithelial and immunological features, which has led to the concept of a united airway. Nasal mucosal transcriptomic analysis leverages high-throughput RNA sequencing and gene expression profiling to assess disease-associated molecular changes. As the nasal epithelium is easily accessible, it serves as a surrogate for the lower airways, providing a practical approach for biomarker discovery and disease monitoring in clinical and research settings. This review aims to present the current landscape of nasal mucosal transcriptomic markers in airway diseases, with a focus on their scientific rationale, clinical implications, and integration into future therapeutic paradigms.

Epidemiology / Disease Burden

Airway diseases, including asthma, chronic rhinosinusitis (CRS), and allergic rhinitis (AR), affect hundreds of millions globally, with significant morbidity and healthcare burdens. Asthma alone accounts for approximately 300 million cases worldwide, while AR prevalence exceeds 10-30% in many populations. CRS, often under-diagnosed, impacts quality of life and is associated with increased healthcare utilization. The high prevalence and chronicity of these diseases underscore the need for improved diagnostic and prognostic tools. Transcriptomic profiling of nasal mucosa offers a promising avenue to address current limitations in phenotyping, risk stratification, and personalized therapy.

Pathophysiology

The pathogenesis of airway diseases involves complex interactions between genetic susceptibility, environmental exposures, and immune dysregulation. Transcriptomic studies have revealed distinct and overlapping gene expression signatures in the nasal mucosa of patients with asthma, CRS, and AR. Notably, increased expression of type 2 inflammation-related genes (e.g., IL-4, IL-5, IL-13, periostin) is observed in allergic and eosinophilic phenotypes. Upregulation of interferon signaling pathways is characteristic of viral-induced exacerbations. Additionally, epithelial barrier dysfunction, highlighted by altered expression of tight junction and mucin genes, is a shared feature contributing to chronic inflammation and susceptibility to environmental insults. These insights support the concept of the nasal mucosa as a mirror of lower airway inflammation and underscore its value in disease characterization.

Risk Factors

Genetic predisposition, atopy, environmental allergens, pollutants, respiratory infections, and smoking are established risk factors for airway diseases. Transcriptomic profiling has identified gene-environment interactions that modulate disease risk and severity. For instance, polymorphisms in IL-33 and TSLP genes influence Th2-driven transcriptomic signatures in the nasal mucosa. Early-life viral infections, particularly with rhinovirus and respiratory syncytial virus, induce persistent transcriptional alterations that predispose to asthma development. Environmental factors such as air pollution and occupational exposures can drive specific transcriptomic changes linked to neutrophilic inflammation and remodeling. Recognizing these risk-associated transcriptomic patterns can inform individualized prevention and management strategies.

Clinical Features

Airway diseases present with overlapping symptoms, including nasal congestion, rhinorrhea, sneezing, cough, wheezing, and dyspnea. However, clinical heterogeneity is pronounced, and traditional diagnostic criteria often fail to capture underlying molecular endotypes. Nasal transcriptomic markers have been associated with specific clinical phenotypes, such as eosinophilic versus neutrophilic inflammation, steroid responsiveness, and risk of exacerbations. For example, periostin and CCL26 expression in nasal epithelium correlates with severe, refractory disease and predicts response to biologic therapies. The integration of transcriptomic data with clinical assessment enhances precision in phenotyping and guides targeted interventions.

Diagnosis

Current diagnostic approaches for airway diseases rely on clinical evaluation, imaging, and conventional biomarkers (e.g., blood eosinophils, FeNO). Nasal transcriptomic profiling offers a minimally invasive alternative for molecular diagnosis and endotyping. RNA sequencing or targeted gene panels from nasal brushings can distinguish between type 2-high and type 2-low inflammation, identify viral versus bacterial triggers, and predict disease exacerbations. Studies have demonstrated high concordance between nasal and bronchial gene expression profiles, supporting the utility of nasal sampling as a surrogate for lower airway pathology. This approach may reduce the need for invasive procedures, particularly in pediatric and difficult-to-access populations.

Treatment & Management

Management of airway diseases encompasses pharmacologic therapy (e.g., inhaled corticosteroids, leukotriene modifiers, biologics), allergen avoidance, and management of comorbidities. Transcriptomic markers enable stratification of patients based on molecular endotypes, allowing for tailored therapy. For instance, identification of type 2-high inflammation in nasal mucosa guides the use of anti-IL-5 or anti-IL-4/IL-13 biologics. Monitoring transcriptomic changes during therapy provides early markers of response or resistance, facilitating timely adjustments in management. In CRS, transcriptomic profiling assists in distinguishing between eosinophilic and non-eosinophilic forms, informing surgical decision-making and adjunctive therapy selection.

Recent Advances / Emerging Therapies

Advances in single-cell RNA sequencing, spatial transcriptomics, and machine learning have expanded our understanding of cellular heterogeneity and molecular networks in the nasal mucosa. Recent studies have identified novel biomarkers, such as TSLP and oncostatin M, associated with corticosteroid resistance and tissue remodeling. Integration of transcriptomic markers with proteomic and metabolomic data enables comprehensive multi-omics endotyping for precision medicine. Emerging therapies targeting upstream regulators of inflammation, such as epithelial cytokines and kinase inhibitors, are being guided by transcriptomic insights. Non-invasive monitoring using nasal brushings is being explored in clinical trials as a surrogate endpoint for evaluating treatment efficacy.

Guideline Recommendations

International guidelines, including GINA and EPOS, recognize the need for improved molecular phenotyping in airway disease management. While routine clinical use of transcriptomic markers is not yet standard practice, expert panels endorse their integration in research protocols and precision medicine trials. Recommendations include the validation of nasal transcriptomic biomarkers for diagnosis, monitoring, and therapeutic stratification, particularly in severe, refractory, or complex cases. Ongoing development of standardized sampling and analytic protocols is critical for translation into routine care.

Conclusion

Nasal mucosal transcriptomic markers represent a transformative advance in the understanding and management of airway diseases. They provide mechanistic insights, enhance diagnostic precision, and enable individualized therapy. Ongoing research and technological innovation will continue to refine their clinical utility, paving the way toward integrated, omics-driven approaches in respiratory medicine. For clinicians, embracing transcriptomic biomarkers offers the potential to improve outcomes and usher in a new era of personalized airway disease management.