Microbial-Metabolite Signatures Are Associated With Glucocorticoid Responsiveness in Chronic Rhinosinusitis With Nasal Polyps.

BACKGROUND

Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) exhibit heterogeneous responses to oral glucocorticoids (GCs), but the biological basis of this variability remains unclear.

OBJECTIVE

To identify gut microbiome‒plasma metabolomic signatures associated with GC responsiveness in CRSwNP patients and to compare their predictive value with that of conventional clinical indicators.

METHODS

Patients with CRSwNP aged 18-65 years with bilateral nasal polyps and a nasal polyp score (NPS) ≥ 2 on at least one side were enrolled, together with septoplasty controls without sinonasal disease. GC responsiveness was defined as the change in endoscopic NPS after 2 weeks of oral methylprednisolone. Fecal shotgun metagenomic and untargeted plasma metabolomics were performed.

RESULTS

Twenty-six CRSwNP patients and 30 controls were included. At baseline, GC responders had significantly greater tissue eosinophilic inflammation, whereas GC non-responders had higher NPS. Responders exhibited distinct baseline gut microbial and plasma metabolic profiles, characterized by the enrichment of Bacteroides caccae, Microbacterium flavum, and Mucilaginibacter rigui, and markedly elevated levels of lupinisoflavone N, CAY10622, kanzonol V, and D-sorbitol. These baseline features were positively correlated with tissue eosinophilic inflammation. After treatment, reductions in Lund-Mackay CT total score, ethmoid/maxillary sinus CT score ratio, NPS, tissue eosinophilic inflammation, and tissue IL-6 mRNA levels were significantly greater in GC responders. Tissue eosinophil count was the strongest conventional predictor (AUC = 0.885), while the integrated multiomics model achieved an AUC of 0.899, showing only marginal improvement.

CONCLUSION

Gut microbiome-plasma metabolomic signatures capture the systemic immunometabolic context of GC therapy and are linked to GC responsiveness in CRSwNP, explaining interindividual treatment efficacy differences.