Association of obstructive sleep apnea severity with the composition of the upper airway microbiome

Microbial dysbiosis in obstructive sleep apnea: a systematic review and meta-analysis

Background

The association between the microbiota and obstructive sleep apnea (OSA) remains understudied. In this study, we conducted a comprehensive systematic review and meta-analysis of studies investigating the diversity and relative abundance of microbiota in the gut, respiratory tracts and oral cavity of patients with OSA, aiming to provide an in-depth characterization of the microbial communities associated with OSA.

Methods

A comprehensive literature search across PubMed, the Cochrane Library, Web of Science, and Embase databases were conducted to include studies published prior to Dec 2024 that compared the gut, respiratory and oral microbiota between individuals with and without OSA. The findings regarding alpha-diversity, beta-diversity, and relative abundance of microbiota extracted from the included studies were summarized. This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and the study protocol was registered with PROSPERO (CRD42024525114).

Results

We identified a total of 753 articles, out of which 27 studies were ultimately included in the systematic review, involving 1,381 patients with OSA and 692 non-OSA populations, including 1,215 OSA patients and 537 non-OSA populations in adults and 166 OSA patients and 155 non-OSA populations in children. The results of alpha diversity revealed a reduction in the Chao1 index (SMD = -0.40, 95% CI = -0.76 to -0.05), Observed species (SMD = -0.50, 95% CI = -0.89 to -0.12) and Shannon index (SMD = -0.27, 95% CI = -0.47 to -0.08) of the gut microbiota in patients with OSA. Beta diversity analysis indicated significant differences in the gut, respiratory and oral microbial community structure between individuals with OSA and those without in more than half of the included studies. Furthermore, in comparison to the non-OSA individuals, the gut environment of patients with OSA exhibited an increased relative abundance of phylum Firmicutes, along with elevated levels of genera Lachnospira; conversely, there was a decreased relative abundance of phylum Bacteroidetes and genus Ruminococcus and Faecalibacterium. Similarly, within the oral environment of OSA patients, there was an elevated relative abundance of phylum Actinobacteria and genera Neisseria, Rothia, and Actinomyces.

Conclusion

Patients with OSA exhibit reduced diversity, changes in bacterial abundance, and altered structure in the microbiota, especially in the gut microbiota. The results of this study provide basic evidence for further exploration of microbiome diagnostic markers and potential intervention strategies for OSA.

Robust phylogenetic tree-based microbiome association test using repeatedly measured data for composition bias

BACKGROUND

The effects of microbiota on the host phenotypes can differ substantially depending on their age. Longitudinally measured microbiome data allow for the detection of the age modification effect and are useful for the detection of microorganisms related to the progression of disease whose identification change over time. Moreover, longitudinal analysis facilitates the estimation of the within-subject covariate effect, is robust to the between-subject confounders, and provides better evidence for the causal relationship than cross-sectional studies. However, this method of analysis is limited by compositional bias, and few statistical methods can estimate the effect of microbiota on host diseases with repeatedly measured 16S rRNA gene data. Herein, we propose mTMAT, which is applicable to longitudinal microbiome data and is robust to compositional bias.

RESULTS

mTMAT normalized the microbial abundance and utilized the ratio of the pooled abundance for association analysis. mTMAT is based on generalized estimating equations with a robust variance estimator and can be applied to repeatedly measured microbiome data. The robustness of mTMAT against compositional bias is underscored by its utilization of abundance ratios.

CONCLUSIONS

With extensive simulation studies, we showed that mTMAT is statistically relatively powerful and is robust to compositional bias. mTMAT enables detection of microbial taxa associated with host diseases using repeatedly measured 16S rRNA gene data and can provide deeper insights into bacterial pathology.

OSA Is Associated With the Human Gut Microbiota Composition and Functional Potential in the Population-Based Swedish CardioPulmonary bioImage Study

BACKGROUND

OSA is a common sleep-breathing disorder linked to increased risk of cardiovascular disease. Intermittent upper airway obstruction and hypoxia, hallmarks of OSA, have been shown in animal models to induce substantial changes to the gut microbiota composition, and subsequent transplantation of fecal matter to other animals induced changes in BP and glucose metabolism.

RESEARCH QUESTION

Does OSA in adults associate with the composition and functional potential of the human gut microbiota?

STUDY DESIGN AND METHODS

We used respiratory polygraphy data from up to 3,570 individuals 50 to 64 years of age from the population-based Swedish Cardiopulmonary bioimage Study combined with deep shotgun metagenomics of fecal samples to identify cross-sectional associations between three OSA parameters covering apneas and hypopneas, cumulative sleep time in hypoxia, and number of oxygen desaturation events with gut microbiota composition. Data collection about potential confounders was based on questionnaires, onsite anthropometric measurements, plasma metabolomics, and linkage with the Swedish Prescribed Drug Register.

RESULTS

We found that all three OSA parameters were associated with lower diversity of species in the gut. Furthermore, in multivariable-adjusted analysis, the OSA-related hypoxia parameters were associated with the relative abundance of 128 gut bacterial species, including higher abundance of Blautia obeum and Collinsella aerofaciens. The latter species was also independently associated with increased systolic BP. Furthermore, the cumulative time in hypoxia during sleep was associated with the abundance of genes involved in nine gut microbiota metabolic pathways, including propionate production from lactate. Finally, we observed two heterogeneous sets of plasma metabolites with opposite association with species positively and negatively associated with hypoxia parameters, respectively.

INTERPRETATION

OSA-related hypoxia, but not the number of apneas/hypopneas, is associated with specific gut microbiota species and functions. Our findings lay the foundation for future research on the gut microbiota-mediated health effects of OSA.

Changes in the oral and nasal microbiota in pediatric obstructive sleep apnea

Background

Several clinical studies have demonstrated that pediatric obstructive sleep apnea (OSA) is associated with dysbiosis of airway mucosal microbiota. However, how oral and nasal microbial diversity, composition, and structure are altered in pediatric OSA has not been systemically explored.

Methods

30 polysomnography-confirmed OSA patients with adenoid hypertrophy, and 30 controls who did not have adenoid hypertrophy, were enrolled. Swabs from four surface oral tissue sites (tongue base, soft palate, both palatine tonsils, and adenoid) and one nasal swab from both anterior nares were collected. The 16S ribosomal RNA (rRNA) V3-V4 region was sequenced to identify the microbial communities.

Results

The beta diversity and microbial profiles were significantly different between pediatric OSA patients and controls at the five upper airway sites. The abundances of Haemophilus, Fusobacterium, and Porphyromonas were higher at adenoid and tonsils sites of pediatric patients with OSA. Functional analysis revealed that the differential pathway between the pediatric OSA patients and controls involved glycerophospholipids and amino acid metabolism.

Conclusions

In this study, the oral and nasal microbiome of pediatric OSA patients exhibited certain differences in composition compared with the controls. However, the microbiota data could be useful as a reference for studies on the upper airway microbiome.