ArticlePathophysiology : the official journal of the International Society for Pathophysiology2026
Nasal Cytology as a Local Biomarker of Airway Inflammation: A Paradigm Shift in Precision Medicine.
Article in Pathophysiology : the official journal of the International Society for Pathophysiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Biomarker-driven approaches have markedly improved the stratification and management of airway inflammatory diseases. However, in everyday clinical practice, these strategies still rely mainly on systemic indicators, which often provide only an indirect view of the inflammatory processes occurring within the airway mucosa. This limitation becomes particularly evident in chronic conditions such as chronic rhinosinusitis with nasal polyps (CRSwNP), where local inflammatory patterns may not relate to circulating biomarkers. Nasal cytology represents a simple, non-invasive, and reproducible technique that allows direct evaluation of the cellular components of the nasal mucosa. By identifying distinct inflammatory patterns, it offers a real-time snapshot of the local inflammatory microenvironment, bringing the clinician closer to the site of disease. In this hypothesis, we propose that airway inflammation is primarily driven by local cytological patterns. In particular, we suggest that the interaction between eosinophils and mast cells constitutes a key pathogenic axis underlying disease activity, severity, and progression. From a pathophysiological perspective, eosinophils may reflect a more chronic component of inflammation, whereas mast cells are more closely associated with active and dynamic phases of the disease. Their coexistence may therefore identify a state of amplified inflammatory activity, often associated with more severe clinical phenotypes. We further propose that integrating cytological findings into clinical-cytological grading (CCG) systems could improve patient stratification and support more personalized therapeutic strategies. This model is readily testable in current clinical and research settings and may contribute to a progressive shift toward the use of local biomarkers in precision medicine.
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