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. 2019 Sep 17;3(3):2473974X19875100.
doi: 10.1177/2473974X19875100. eCollection 2019 Jul-Sep.

Analysis of Sinonasal Microbiota in Exacerbations of Chronic Rhinosinusitis Subgroups

Laura J Vandelaar  1 , Blake Hanson  2   3 , Michael Marino  4 , William C Yao  1 , Amber U Luong  1 , Cesar A Arias  2   3 , Vijay Ramakrishnan  5 , Martin J Citardi  1
Affiliations

Analysis of Sinonasal Microbiota in Exacerbations of Chronic Rhinosinusitis Subgroups

Laura J Vandelaar et al. OTO Open. .

Abstract

Objective: Microbiome analyses now allow precise determination of the sinus microbiota of patients with exacerbations of chronic rhinosinusitis (CRS). The aim of this report is to describe the sinus microbiota of acute exacerbations in CRS clinical subgroups (with nasal polyps [CRSwNP], without nasal polyps [CRSsNP], and allergic fungal rhinosinusitis [AFRS]).

Study design: Retrospective chart review.

Setting: Tertiary rhinology practice.

Subjects and methods: A retrospective review was performed of all patients whose sinus microbiota were assayed via a commercially available microbiome technology during an acute CRS exacerbation during the 2-year period ending December 31, 2016. All samples were sinus aspirates collected under endoscopic visualization in clinic.

Results: Samples from a total of 134 patients (65 CRSsNP, 55 CRSwNP, and 14 AFRS) were reviewed. The observed richness (number of taxa >2% relative abundance) ranged between 1 and 11 taxa, with an average of 3 taxa per specimen. The most common bacteria in all groups were Staphylococcal spp (including Staphylococcus aureus), Streptococcus spp, Pseudomonas spp, and Escherichia spp. S aureus had an increased prevalence in CRSsNP and AFRS as compared with CRSwNP. Otherwise, the sinus microbiota were markedly similar among all 3 clinical subgroups.

Conclusions: Many bacterial types are identified during acute CRS exacerbation according to DNA-based detection techniques. Bacterial richness was remarkably low in all samples. Few differences in the patterns among clinical subgroups were observed. Further investigation is warranted to determine the clinical significance of these observations and their role in current clinical algorithms.

Keywords: 16S rRNA; bacteria; chronic rhinosinusitis; culture; microbiome; sinusitis.

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Figures

Figure 1.
Figure 1.
Heat map of prevalence for detected bacterial taxa, stratified by clinical subgroup. AFRS, allergic fungal rhinosinusitis; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps.
Figure 2.
Figure 2.
Box and whisker plots of relative abundance, stratified by primary diagnosis and bacterial taxa. AFRS, allergic fungal rhinosinusitis; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps.
Figure 3.
Figure 3.
Ordination of samples by primary diagnosis. A Bray-Curtis dissimilarity matrix was used to generate a principal component analysis showing that the samples do not cluster by primary diagnosis. The primary bacterial drivers of variability within these samples were Pseudomonas spp, Streptococcus spp, and Staphylococcus aureus. AFRS, allergic fungal rhinosinusitis; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps.
Figure 4.
Figure 4.
Alpha diversity metrics stratified by clinical subgroup. AFRS, allergic fungal rhinosinusitis; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps.
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References

    1. Ramakrishnan VR, Hauser LJ, Feazel LM, Ir D, Robertson CE, Frank DN. Sinus microbiota varies among chronic rhinosinusitis phenotypes and predicts surgical outcome. J Allergy Clin Immunol. 2015;136:334-342.e1. - PubMed
    1. Psaltis AJ, Wormald PJ. Therapy of sinonasal microbiome in CRS: a critical approach. Curr Allergy Asthma Rep. 2017;17:59. - PubMed
    1. Ramakrishnan VR, Hauser LJ, Frank DN. The sinonasal bacterial microbiome in health and disease. Curr Opin Otolaryngol Head Neck Surg. 2016;24:20-25. - PMC - PubMed
    1. Hauser LJ, Feazel LM, Ir D, et al. Sinus culture poorly predicts resident microbiota. Int Forum Allergy Rhinol. 2015;5:3-9. - PubMed
    1. Jervis Bardy J, Psaltis AJ. Next generation sequencing and the microbiome of chronic rhinosinusitis: a primer for clinicians and review of current research, its limitations, and future directions. Ann Otol Rhinol Laryngol. 2016;125:613-621. - PubMed