Anterior Nares Diversity and Pathobionts Represent Sinus Microbiome in Chronic Rhinosinusitis

Abstract

It is generally believed that the microbiome plays a role in the pathophysiology of chronic rhinosinusitis (CRS), though its exact contribution to disease development and severity remains unclear. Here, samples were collected from the anterior nares, nasopharynx, and maxillary and ethmoid sinuses of 190 CRS patients and from the anterior nares and nasopharynx of 100 controls. Microbial communities were analyzed by Illumina sequencing of the V4 region of 16S rRNA. The phenotype and patient characteristics were documented, and several serum inflammatory markers were measured. Our data indicate a rather strong continuity for the microbiome in the different upper respiratory tract (URT) niches in CRS patients, with the microbiome in the anterior nares being most similar to the sinus microbiome. Bacterial diversity was reduced in CRS patients without nasal polyps compared to that in the controls but not in CRS patients with nasal polyps. Statistically significant differences in the presence/absence or relative abundance of several taxa were found between the CRS patients and the healthy controls. Of these, Dolosigranulum pigrum was clearly more associated with URT samples from healthy subjects, while the Corynebacterium tuberculostearicum, Haemophilus influenzae/H. aegyptius, and Staphylococcus taxa were found to be potential pathobionts in CRS patients. However, CRS versus health as a predictor explained only 1 to 2% of the variance in the microbiome profiles in an adonis model. A history of functional endoscopic sinus surgery, age, and sex also showed a minor association. This study thus indicates that functional studies on the potential beneficial versus pathogenic activity of the different indicator taxa found here are needed to further understand the pathology of CRS and its different phenotypes. (This study has been registered at ClinicalTrials.gov under identifier NCT02933983.)IMPORTANCE There is a clear need to better understand the pathology and specific microbiome features in chronic rhinosinusitis patients, but little is known about the bacterial topography and continuity between the different niches of the upper respiratory tract. Our work showed that the anterior nares could be an important reservoir for potential sinus pathobionts. This has implications for the diagnosis, prevention, and treatment of CRS. In addition, we found a potential pathogenic role for the Corynebacterium tuberculostearicum, Haemophilus influenzae/H. aegyptius, and Staphylococcus taxa and a potential beneficial role for Dolosigranulum Finally, a decreased microbiome diversity was observed in patients with chronic rhinosinusitis without nasal polyps compared to that in healthy controls but not in chronic rhinosinusitis patients with nasal polyps. This suggests a potential role for the microbiome in disease development or progression of mainly this phenotype.

Keywords: chronic rhinosinusitis; microbiome; sinus pathobionts; upper respiratory tract.

Copyright © 2019 De Boeck et al.

Figures

FIG 1

Bacterial profiles and diversity of the different URT sites sampled in CRS patients. (A) Dominant genera in the anterior nares, nasopharynx, and maxillary and ethmoid sinus samples. The order of the samples is determined by hierarchical clustering on pooled samples per participant. (B) Comparison of the inverse Simpson index (top) and richness (bottom) of the different URT sites sampled in CRS patients at the ASV level. P values (determined by unpaired Welch t tests with the Holm-Bonferroni correction for multiple testing) of less than 0.05 were considered significant. Asterisks represent statistically significant differences between the niches. ***, P ≤ 0.001; ****, P ≤ 0.0001. (C) Bray-Curtis dissimilarities as an indicator of intrapersonal and interpersonal differences between the nose, nasopharynx, and maxillary and ethmoid sinuses at the ASV level; horizontal bars represent median dissimilarity values.

FIG 2

Comparison of alpha diversity measures in the anterior nares (left) and nasopharynx (right) between healthy controls, CRSsNP patients, and CRSwNP patients. Asterisks represent statistically significant differences between the niches (determined by unpaired Welch t tests with the Holm-Bonferroni correction for multiple testing). *, P ≤ 0.05; **, P ≤ 0.01.

FIG 3

Differences in the presence/absence and relative abundance of the most prevalent taxa in CRS patients versus healthy controls (CON). (A) Correlation between the presence of ASVs in healthy controls and CRS patients in the anterior nares (left) and the nasopharynx (right). A Fisher exact test was used to test for the significance of ASVs that were more present in healthy controls or CRS patients (P ≤ 0.05). Only ASVs with a significant presence and more than 25% presence under at least one of the conditions are shown with a name label. (B) Correlation between the mean relative abundance of ASVs in the anterior nares (left) and the nasopharynx (right) of healthy controls and CRS patients. Only ASVs with a mean relative abundance of greater than 30% under at least one of the conditions are shown with a name label.

FIG 4

Associations between the nasopharyngeal microbiome profiles of CRS patients (n = 172) and covariates. Adonis tests were performed for each covariate for either all CRS subjects (left), only the CRSsNP subjects (middle), or only the CRSwNP subjects (right). The bars represent the effect sizes of the covariates (R2 values); statistical significance (P < 0.05) is indicated with an asterisk. Covariates are colored based on the metadata category. The numbers depicted next to each bar represent the number of subjects used in the adonis model.

FIG 5

Associations of numerical (A) and categorical (B) microbiome covariates with microbiome-based subject clusters. (A) Box plot visualization of age, IFN-γ concentration, IL-5 concentration, periostin concentration, and 22-item Sino-Nasal Outcome Test (SNOT-22) and Visual Analog Scale (VAS) scores for the six microbiome clusters. (B) Mosaic plot showing the association of the categorical variables with the microbiome clusters. The surface of each colored area is proportional to the number of subjects that it represents. Significance tests of associations of the covariates with the microbiome were performed using the adonis model.

FIG 6

Graphical summary of the URT sampling sites and patient covariates, sample processing, and main findings of this study.