TY - JOUR
T1 - Severe obstructive sleep apnea is associated with alterations in the nasal microbiome and an increase in inflammation
AU - Wu, Benjamin G.
AU - Sulaiman, Imran
AU - Wang, Jing
AU - Shen, Nan
AU - Clemente, Jose C.
AU - Li, Yonghua
AU - Laumbach, Robert J.
AU - Lu, Shou En
AU - Udasin, Iris
AU - Le-Hoang, Oanh
AU - Perez, Alan
AU - Alimokhtari, Shahnaz
AU - Black, Kathleen
AU - Plietz, Michael
AU - Twumasi, Akosua
AU - Sanders, Haley
AU - Malecha, Patrick
AU - Kapoor, Bianca
AU - Scaglione, Benjamin D.
AU - Wang, Anbang
AU - Blazoski, Cameron
AU - Weiden, Michael D.
AU - Rapoport, David M.
AU - Harrison, Denise
AU - Chitkara, Nishay
AU - Vicente, Eugenio
AU - Marin, José M.
AU - Sunderram, Jag
AU - Ayappa, Indu
AU - Segal, Leopoldo N.
N1 - Publisher Copyright:
Copyright © 2019 by the American Thoracic Society
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Rationale: Obstructive sleep apnea (OSA) is associated with recurrent obstruction, subepithelial edema, and airway inflammation. The resultant inflammation may influence or be influenced by the nasal microbiome. Objectives: To evaluate whether the composition of the nasal microbiota is associated with obstructive sleep apnea and inflammatory biomarkers. Methods: Two large cohorts were used: 1) a discovery cohort of 472 subjects from the WTCSNORE (Seated, Supine and Post-Decongestion Nasal Resistance in World Trade Center Rescue and Recovery Workers) cohort, and 2) a validation cohort of 93 subjects rom the Zaragoza Sleep cohort. Sleep apnea was diagnosed using home sleep tests. Nasal lavages were obtained from cohort subjects to measure: 1) microbiome composition (based on 16S rRNA gene sequencing), and 2) biomarkers for inflammation (inflammatory cells, IL-8, and IL-6). Longitudinal 3-month samples were obtained in the validation cohort, including after continuous positive airway pressure treatment when indicated. Measurements and Main Results: In both cohorts, we identified that: 1) severity of OSA correlated with differences in microbiome diversity and composition; 2) the nasal microbiome of subjects with severe OSA were enriched with Streptococcus, Prevotella, and Veillonella; and 3) the nasal microbiome differences were associated with inflammatory biomarkers. Network analysis identified clusters of cooccurring microbes that defined communities. Several common oral commensals (e.g., Streptococcus, Rothia, Veillonella, and Fusobacterium) correlated with apnea-hypopnea index. Three months of treatment with continuous positive airway pressure did not change the composition of the nasal microbiota. Conclusions: We demonstrate that the presence of an altered microbiome in severe OSA is associated with inflammatory markers. Further experimental approaches to explore causal links are needed.
AB - Rationale: Obstructive sleep apnea (OSA) is associated with recurrent obstruction, subepithelial edema, and airway inflammation. The resultant inflammation may influence or be influenced by the nasal microbiome. Objectives: To evaluate whether the composition of the nasal microbiota is associated with obstructive sleep apnea and inflammatory biomarkers. Methods: Two large cohorts were used: 1) a discovery cohort of 472 subjects from the WTCSNORE (Seated, Supine and Post-Decongestion Nasal Resistance in World Trade Center Rescue and Recovery Workers) cohort, and 2) a validation cohort of 93 subjects rom the Zaragoza Sleep cohort. Sleep apnea was diagnosed using home sleep tests. Nasal lavages were obtained from cohort subjects to measure: 1) microbiome composition (based on 16S rRNA gene sequencing), and 2) biomarkers for inflammation (inflammatory cells, IL-8, and IL-6). Longitudinal 3-month samples were obtained in the validation cohort, including after continuous positive airway pressure treatment when indicated. Measurements and Main Results: In both cohorts, we identified that: 1) severity of OSA correlated with differences in microbiome diversity and composition; 2) the nasal microbiome of subjects with severe OSA were enriched with Streptococcus, Prevotella, and Veillonella; and 3) the nasal microbiome differences were associated with inflammatory biomarkers. Network analysis identified clusters of cooccurring microbes that defined communities. Several common oral commensals (e.g., Streptococcus, Rothia, Veillonella, and Fusobacterium) correlated with apnea-hypopnea index. Three months of treatment with continuous positive airway pressure did not change the composition of the nasal microbiota. Conclusions: We demonstrate that the presence of an altered microbiome in severe OSA is associated with inflammatory markers. Further experimental approaches to explore causal links are needed.
KW - Biomarkers
KW - Chronic rhinosinusitis
KW - Inflammation
KW - Microbiome
UR - http://www.scopus.com/inward/record.url?scp=85059243686&partnerID=8YFLogxK
U2 - 10.1164/rccm.201801-0119OC
DO - 10.1164/rccm.201801-0119OC
M3 - Article
C2 - 29969291
AN - SCOPUS:85059243686
SN - 1073-449X
VL - 199
SP - 99
EP - 109
JO - American Journal of Respiratory and Critical Care Medicine
JF - American Journal of Respiratory and Critical Care Medicine
IS - 1
ER -