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Abstract Study Objectives: Intermittent hypoxia (IH) mimicking obstructive sleep apnea (OSA) significantly modifies gut microbiota in mice. However, whether these IH-induced gut microbiome changes are reversible after restoring normal oxygenation (the equivalent of effective OSA therapy) is unknown. The aim of this study was to investigate gut microbiota composition and circulating endotoxemia after a post-IH normoxic period in a mouse model of OSA. Methods: Ten mice were subjected to IH (40 sec 21% O2-20 sec 5% O2) for 6 h/day for 6 w and 10 mice breathing normoxic air (NM) were used as controls. After exposures, both groups were subjected to 6 w in normoxia. Microbiome composition of fecal samples was determined by 16S ribosomal RNA (rRNA) pyrosequencing. Bioinformatic analysis was performed by Quantitative Insights into Microbial Ecology. Plasma lipopolysaccharide (LPS) levels were measured by endotoxin assay. Results: After normoxic recovery, the Chao and Shannon indices of each group suggested similar bacterial richness and diversity. 16S rRNA pyrosequencing analysis showed that IH-exposed mice had a significant decrease in the abundance of Bacteroidetes and a significant increase of Firmicutes and Deferribacteres compared to the NM group. After normoxic recovery, circulating LPS concentrations were higher in the IH group (P < 0.009). Moreover, the IH group showed a negative and significant correlation between the abundance of Lactobacillus and Ruminococcus and significant positive correlations between the abundance of Mucispirillum and Desulfovibrio and plasma LPS levels, respectively. Conclusions: Even after prolonged normoxic recovery after IH exposures, gut microbiota and circulating endotoxemia remain negatively altered, suggesting that potential benefits of OSA treatment for reversing OSA-induced changes in gut microbiota may either require a longer period or alternative interventions.

Intestinal microbiota imbalance plays an important role in the progression of obstructive sleep apnea (OSA), and is considered to be the main mediator that triggers metabolic comorbidities. Here, we analyzed the changes in intestinal microbiota in patients with different severities of OSA based on apnea hypopnea index (AHI) classification, and explored the role of intestinal microbiota in the severity of OSA. This study included 19 healthy volunteers and 45 patients with OSA [5 ≤ AHI < 15 (n = 14), 15 ≤ AHI < 30 (n = 13), AHI ≥ 30 (n = 18)]. Relevant sleep monitoring data and medical history data were collected, and microbial composition was analyzed using 16S rRNA high-throughput sequencing technology. The diversity analysis of intestinal microbiota among different groups of people was conducted, including alpha diversity, beta diversity, species diversity, and marker species as well as differential functional metabolic pathway prediction analysis. With the increase of AHI classification, the alpha diversity in patients with OSA significantly decreased. The results revealed that the severity of OSA is associated with differences in the structure and composition of the intestinal microbiota. The abundance of bacteria producing short-chain fatty acids (such as Bacteroides , Ruminococcacea , and Faecalibacterium ) in severe OSA is significantly reduced and a higher ratio of Firmicutes to Bacteroidetes . Random forest analysis showed that Parabacteroides was a biomarker genus with important discriminatory significance. The differential metabolic pathway prediction function shows that the main function of maintaining intestinal microbiota homeostasis is biosynthetic function. Our results show that the differences in the composition of intestinal microbiota in patients with different severities of OSA are mainly related to short-chain fatty acid-producing bacteria. These changes may play a pathological role in OSA combined with metabolic comorbidities.

Purpose of Review With the growing body of research examining the link between sleep disorders, including insomnia and obstructive sleep apnea (OSA), and the gut microbiome, this review seeks to offer a thorough overview of the most significant findings in this emerging field. Recent Findings Current evidence suggests a complex association between imbalances in the gut microbiome, insomnia, and OSA, with potential reciprocal interactions that may influence each other. Notably, specific gut microbiome species, whether over- or under-abundant, have been associated with variation in both sleep and mood in patients diagnosed with, e.g., major depressive disorder or bipolar disorder. Summary Further studies are needed to explore the potential of targeting the gut microbiome as a therapeutic approach for insomnia and its possible effects on mood. The variability in current scientific literature highlights the importance of establishing standardized research methodologies.

Objective This study investigates the role of gut microbiota and metabolites as biomarkers in the diagnosis and assessment of Obstructive Sleep Apnea (OSA) by analyzing the correlation between microbiota and metabolomics in the host's gut under conditions of chronic intermittent hypoxia (CIH). Methods We analyzed the composition and function of gut microorganisms and metabolites in OSA and CIH mouse models using 16S rRNA sequencing combined with targeted metabolomics to evaluate the association between clinical indicators and severity of OSA and gut flora and metabolites. Results Compared with normal controls, we found: (1) The apnea hypoventilation index (AHI) and fasting blood glucose were higher in the moderate and severe OSA groups, the eosinophilia score (EP) and neutrophil percentage were significantly higher in the severe OSA group, and the percentage of lymphocytes in the blood count and platelet pressures were lower in the moderate group ( P  < 0.05).(2) The OSA and CIH groups showed an increase in the abundance of Firmicutes and Tenotrophomonas , and a decrease in the abundance of Bacteroidota and Ligilactobacillus ( P  < 0.05).(3) The OSA and CIH groups had elevated Nervonic acid and Erucic acid and decreased Arachidonic acid ( P  < 0.05). In addition, correlation analysis showed that: There was a negative correlation between Coprobacillus and percentage of lymphocytes, and Bacteroidota and EP and AHI;and a positive correlation between Lactococcus and Neutrophils, Arachidonic acid and width of erythrocyte distribution, and Erucic and Neuronic acids and AHI ( P  < 0.05). Conclusion The CIH condition can lead to microbial and metabolite alterations, which correlate with disease severity and clinical indicators, and is expected to be a new biomarker for the diagnosis and assessment of severity of OSA.

Obstructive sleep apnea syndrome (OSAS) is prevalent among children and is associated with elevated blood pressure (BP), posing a risk for future hypertension and cardiovascular diseases. While the roles of gut microbiota and systemic inflammation in OSAS pathogenesis are recognized in adults and animal models, their impact on pediatric BP remains less understood. This cross-sectional study explored the relationships between polysomnographic parameters, gut microbiota, systemic inflammation, and BP in 60 children with OSAS. Significant associations between specific microbial profiles—including beta diversity and 31 marker microbes—and BP variations were observed. These microbial profiles correlated with significant alterations in systemic inflammation markers like interleukin-17 and tumor necrosis factor-α. Notably, the relative abundance of Acinetobacter was related to fluctuations in these inflammatory markers and BP levels. The research further highlighted the unique microbial and cytokine profiles exhibited by children with different BP levels, indicating a substantial role of gut microbiota and systemic inflammation in influencing pediatric cardiovascular health. The findings suggest integrating gut microbiota management into comprehensive cardiovascular risk strategies for children with OSAS. This initiative underscores the need for further investigations to decode the mechanisms behind these associations, which could lead to innovative treatments for pediatric OSAS.

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. To evaluate whether the composition of the nasal microbiota is associated with obstructive sleep apnea and inflammatory biomarkers. 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. 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. 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.

Objective To explore the changes and potential mechanisms of microbiome in different parts of the upper airway in the development of pediatric OSA and observe the impact of surgical intervention on oral microbiome for pediatric OSA. Methods Before adeno-tonsillectomy, we collected throat swab samples from different parts of the oropharynx and nasopharynx of 30 OSA patients and 10 non-OSA patients and collected throat swab samples from the oropharynx of the above patients one month after the adeno-tonsillectomy. The 16 S rRNA V3–V4 region was sequenced to identify the microbial communities. The correlation analysis was conducted based on clinical characteristics. Results There was a significant difference of alpha diversity in different parts of the upper airway of pediatric OSA, but this difference was not found in children with non-OSA. Beta diversity was significantly different between non-OSA and pediatric OSA. At the genus level, the composition of flora in different parts is different between non-OSA and pediatric OSA. The correlation analysis revealed that the relative abundance of Neisseria was significantly correlated with obstructive apnea hypopnea index. Furthermore, the functional prediction revealed that pathways related to cell proliferation and material metabolism were significantly different between non-OSA and pediatric OSA. Besides, the adeno-tonsillectomy has minimal impact on oral microbiota composition in short term. Conclusion The changes in upper airway microbiome are highly associated with pediatric OSA. The relative abundance of some bacteria was significantly different between OSA and non-OSA. These bacteria have the potential to become new diagnostic and early warning biomarkers.

Purpose This study investigated variations in gut microbiota among severe obstructive sleep apnea (OSA) patients and changes in gut microbiota after continuous positive airway pressure (CPAP) treatment. Method From November 2020 to August 2021, laboratory-based polysomnography (PSG) was used to measure sleep parameters in healthy controls, severe OSA patients, and severe OSA patients treated with CPAP for three months. A fully automated biochemical analyzer was used to evaluate routine blood tests and biochemical indicators. Whole-genome metagenomic analysis was used to determine the microbial composition of gut samples from all participants. The relationships between gut microbiota and hypertension were examined using correlation analysis. Result The relative abundances of Bacteroides , Firmicutes , and Parabacteroides were significantly lower at the species level. Enterobacterales and Turicibacter were significantly higher in participants with severe OSA than healthy controls. Negative correlations were identified between Bacteroides coprocola and systolic blood pressure (SBP) (r =  − 0.710, P  = 0.003) and diastolic blood pressure (DBP) (r =  − 0.615, P  = 0.015). Conversely, a positive correlation was found between Escherichia coli and SBP (r = 0.568, P  = 0.027). Conclusion The metabolic pathways and gut microbiota differed significantly between the control group and individuals with severe OSA. Additionally, CPAP therapy substantially changed the metabolic pathways and gut microbial composition among patients diagnosed with severe OSA. Correlation analysis further revealed a strong association between Escherichia coli , Bacteroides coprocola , and blood pressure levels.

Patients with obstructive sleep apnea (OSA) have increased mortality from chronic inflammatory and cardiovascular diseases. Excess catecholamine exposure contributes to the disease associations of OSA, but the underlying mechanism is unknown. This study tested the hypothesis that increased catecholamine exposure is associated with Enterobacteriaceae abundance in OSA. We compared urinary norepinephrine and the fecal microbiota in 24 patients with OSA and 23 controls. Urinary norepinephrine was elevated in OSA patients, consistent with increased sympathetic activation in those patients. OSA patients did not show changes in the community structure of the microbiome or in Enterobacteriaceae abundance compared to controls. Longitudinal changes in Enterobacteriaceae abundance in OSA patients were significantly associated with within-subject changes in norepinephrine, but this association was absent in controls. These results provide a preliminary association between norepinephrine exposure and Enterobacteriaceae in patients with disordered sleep.

Obstructive sleep apnea (OSA) and periodontitis have demonstrated epidemiological and clinical associations. This study aimed to characterize salivary microbiome alterations in patients with OSA, periodontitis, and their comorbidity (OSA+PD), and to explore potential microbial markers. This cross-sectional study included 125 adults divided into four groups: healthy controls (H, n=26), patients with OSA (OSA/O, n=42), patients with periodontitis (PD/P, n=15), and patients with OSA and periodontitis (OSA+PD/OP, n=42). Participants underwent nocturnal polysomnography and comprehensive periodontal examinations. Saliva samples were collected and analyzed using 16S ribosomal DNA gene sequencing to evaluate microbial distribution and community structure across groups. Receiver operating characteristic (ROC) curves were generated for key taxa combining with clinical indicators, and the area under the curve (AUC) values were calculated to assess diagnostic relevance. Oral microbial diversity was significantly altered in OSA, PD, and OSA+PD groups. Alpha diversity was reduced in all patient groups compared to healthy controls, with the periodontitis group showing the highest diversity and evenness. Beta diversity revealed that periodontitis having the strongest impact and the comorbid group exhibiting intermediate characteristics between OSA and periodontitis. Key taxa, including , , , , and , exhibited significant intergroup differences. BugBase phenotype analysis revealed an increased abundance of aerobic and a reduced presence of anaerobic microbial profiles in the OSA and OSA+PD groups. Additionally, and were more abundant in the OSA group, regardless of periodontal status. Receiver operating characteristic (ROC) analysis indicated that and reliably differentiated between OSA and OSA+PD (AUC=0.715, 0.702) and also between periodontitis and OSA+PD ( : AUC=0.879). OSA is associated with distinct changes in salivary microbiota, including reduced microbial richness and altered functional profiles, which may contribute to early periodontal dysbiosis. has been identified as a potential microbial biomarker for OSA-related periodontitis, while and may play a key role in periodontitis-related OSA. However, as this is a cross-sectional study, causal relationships and the predictive value of microbial biomarkers remain to be confirmed in longitudinal studies. These results highlight the need for integrated management of OSA and periodontitis and suggest microbial profiling as a useful diagnostic tool.