Seung-No Hong1, Kang Jin Kim2, Min-Gyung Baek3, Hana Yi4, Seung Hoon Lee5, Dong-Young Kim6, Chul Hee Lee6, Chol Shin7, Chae-Seo Rhee6,8. 1. Department of Otorhinolaryngology, Seoul National University College of Medicine, Boramae Medical Center, Seoul, Korea. 2. Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Korea. 3. Department of Public Health Sciences, Korea University, Seoul, Korea. 4. School of Biosystems and Biomedical Sciences, Korea University, Seoul, Korea. 5. Department of Otorhinolaryngology, Korea University College of Medicine, Korea University Ansan Hospital, Ansan, Korea. 6. Department of Otorhinolaryngology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea. 7. Division of Pulmonary, Sleep, and Critical Care Medicine, Department of Internal Medicine, Korea University College of Medicine, Korea University Ansan Hospital, Ansan, Korea. 8. Sensory Organ Research Institute, Medical Research Center, Seoul National University, Seoul, Korea.
Abstract
STUDY OBJECTIVES: Although the airway mucosal system plays a pivotal role in the pathogenesis of obstructive sleep apnea (OSA), the underlying disease mechanism remains unclear. The microbiome greatly impacts human health and disease, particularly in the mucosa, where it can have direct interactions. In this study, we aimed to analyze the microbiome composition in the upper airway mucosa of individuals with and without OSA to identify potential disease severity-related microbial signatures. METHODS: This population-based cohort study involved 92 participants (mean age = 62.7 ± 5.8 years; male-to-female ratio = 0.74) who underwent a physical examination and sleep study. Upper airway swab samples were collected from the nasopharyngeal mucosa to evaluate the microbiome based on 16S rRNA gene pyrosequencing. The relationship between microbiome composition and sleep parameters was explored through bioinformatics analysis. RESULTS: The average apnea-hypopnea index was 7.75 ± 6.5 events/h. Proteobacteria, Firmicutes, and Actinobacteria were the predominant phyla in the nasopharyngeal microbiota in all participants. Simpson diversity indexes were higher in patients with OSA (0.6435 ± 0.2827) than in the control patients (0.6095 ± 0.2683); however, the difference was not significant (P = .1155). Specific anaerobes negatively correlated with the lowest oxygen saturation level during sleep (sum of powered score (1) = -117.47; P = .0052). CONCLUSIONS: The upper airway microbiome of older patients with mild-moderate OSA exhibited minor differences in composition compared with that of individuals without OSA, possibly owing to environmental changes in the upper airway mucosa resulting from recurrent airway obstruction and intermittent hypoxia in patients with OSA. CITATION: Hong S-N, Kim KJ, Baek M-G, et al. Association of obstructive sleep apnea severity with the composition of the upper airway microbiome. J Clin Sleep Med. 2022;18(2):505-515.
STUDY OBJECTIVES: Although the airway mucosal system plays a pivotal role in the pathogenesis of obstructive sleep apnea (OSA), the underlying disease mechanism remains unclear. The microbiome greatly impacts human health and disease, particularly in the mucosa, where it can have direct interactions. In this study, we aimed to analyze the microbiome composition in the upper airway mucosa of individuals with and without OSA to identify potential disease severity-related microbial signatures. METHODS: This population-based cohort study involved 92 participants (mean age = 62.7 ± 5.8 years; male-to-female ratio = 0.74) who underwent a physical examination and sleep study. Upper airway swab samples were collected from the nasopharyngeal mucosa to evaluate the microbiome based on 16S rRNA gene pyrosequencing. The relationship between microbiome composition and sleep parameters was explored through bioinformatics analysis. RESULTS: The average apnea-hypopnea index was 7.75 ± 6.5 events/h. Proteobacteria, Firmicutes, and Actinobacteria were the predominant phyla in the nasopharyngeal microbiota in all participants. Simpson diversity indexes were higher in patients with OSA (0.6435 ± 0.2827) than in the control patients (0.6095 ± 0.2683); however, the difference was not significant (P = .1155). Specific anaerobes negatively correlated with the lowest oxygen saturation level during sleep (sum of powered score (1) = -117.47; P = .0052). CONCLUSIONS: The upper airway microbiome of older patients with mild-moderate OSA exhibited minor differences in composition compared with that of individuals without OSA, possibly owing to environmental changes in the upper airway mucosa resulting from recurrent airway obstruction and intermittent hypoxia in patients with OSA. CITATION: Hong S-N, Kim KJ, Baek M-G, et al. Association of obstructive sleep apnea severity with the composition of the upper airway microbiome. J Clin Sleep Med. 2022;18(2):505-515.
Authors: Benjamin G Wu; Imran Sulaiman; Jing Wang; Nan Shen; Jose C Clemente; Yonghua Li; Robert J Laumbach; Shou-En Lu; Iris Udasin; Oanh Le-Hoang; Alan Perez; Shahnaz Alimokhtari; Kathleen Black; Michael Plietz; Akosua Twumasi; Haley Sanders; Patrick Malecha; Bianca Kapoor; Benjamin D Scaglione; Anbang Wang; Cameron Blazoski; Michael D Weiden; David M Rapoport; Denise Harrison; Nishay Chitkara; Eugenio Vicente; José M Marin; Jag Sunderram; Indu Ayappa; Leopoldo N Segal Journal: Am J Respir Crit Care Med Date: 2019-01-01 Impact factor: 21.405