The composition and functional protein subsystems of the human nasal microbiome in granulomatosis with polyangiitis: a pilot study.

BACKGROUND: Ear, nose and throat involvement in granulomatosis with polyangiitis (GPA) is frequently the initial disease manifestation. Previous investigations have observed a higher prevalence of Staphylococcus aureus in patients with GPA, and chronic nasal carriage has been linked with an increased risk of disease relapse. In this cross-sectional study, we investigated changes in the nasal microbiota including a detailed analysis of Staphylococcus spp. by shotgun metagenomics in patients with active and inactive granulomatosis with polyangiitis (GPA). Shotgun metagenomic sequence data were also used to identify protein-encoding genes within the SEED database, and the abundance of proteins then correlated with the presence of bacterial species on an annotated heatmap. RESULTS: The presence of S. aureus in the nose as assessed by culture was more frequently detected in patients with active GPA (66.7%) compared with inactive GPA (34.1%). Beta diversity analysis of nasal microbiota by bacterial 16S rRNA profiling revealed a different composition between GPA patients and healthy controls (P = 0.039). Beta diversity analysis of shotgun metagenomic sequence data for Staphylococcus spp. revealed a different composition between active GPA patients and healthy controls and disease controls (P = 0.0007 and P = 0.0023, respectively), and between healthy controls and inactive GPA patients and household controls (P = 0.0168 and P = 0.0168, respectively). Patients with active GPA had a higher abundance of S. aureus, mirroring the culture data, while healthy controls had a higher abundance of S. epidermidis. Staphylococcus pseudintermedius, generally assumed to be a pathogen of cats and dogs, showed an abundance of 13% among the Staphylococcus spp. in our cohort. During long-term follow-up of patients with inactive GPA at baseline, a higher S. aureus abundance was not associated with an increased relapse risk. Functional analyses identified ten SEED protein subsystems that differ