Background: Recent studies have revealed that the nasal microbiota in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is profoundly altered and is correlated with systemic inflammation. However, little is known regarding whether the microbiota can be utilized to predict nasal polyp recurrence. This study is aimed to determine whether altered nasal microbiota constituents could be used as biomarkers to predict CRSwNP recurrence.
Methods: Nasal microbiota constituents were quantified and characterized using bacterial 16S ribosomal RNA gene sequencing. Selected features for least absolute shrinkage and selection operator regression-based predictors were the nasal microbiota community composition and CRSwNP patient clinical characteristics. The primary outcome was recurrence, which was determined post-admission.
Results: By distinguishing recurrence-associated nasal microbiota taxa and exploiting the distinct nasal microbiota abundance between patients with recurrent and non-recurrent CRSwNP, we developed a predictive classifier for the diagnosis of nasal polyps' recurrence with 91.4% accuracy.
Conclusions: Key taxonomical features of the nasal microbiome could predict recurrence in CRSwNP patients. The nasal microbiome is an understudied source of clinical variation in CRSwNP and represents a novel therapeutic target for future prevention and treatment.
Keywords: LASSO; chronic rhinosinusitis with nasal polyps; nasal microbiota; prediction model; recurrence.
© 2021 European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.