Dental, oral pH, orthodontic and salivary values in children with obstructive sleep apnea

Oral microbiota in obstructive sleep apnea patients: a systematic review

PURPOSE

Evidence suggests that patients with obstructive sleep apnea (OSA) are at increased risk of suffering from periodontitis, a chronic inflammatory disease of the tooth-supporting tissues associated with a dysbiotic oral microbiota. This systematic review aims to explore the current literature about the composition of the oral microbiota in patients with OSA compared to those without OSA.

METHODS

Medline, Embase, and Cochrane Library were searched in May 2022 to identify original articles investigating the oral microbiota composition and/or oral microbiome (any microbiological technique) of patients with OSA (adults or children) vs. controls. Case report, reviews, and animal studies were excluded.

RESULTS

Of over 279 articles initially identified, 8 were selected, of which 3 dealt with pediatric patients. Overall, 344 patients with OSA and 131 controls were included. Five studies used salivary samples, 2 oral mucosal swabs, and 1 subgingival plaque sample. With different methods to characterize oral microbiota, 6/8 studies observed significant differences between patients with OSA patients and controls in the composition and relative abundance of several bacteria species/genera linked to periodontitis.

CONCLUSION

Within the limitations of the available literature, the present systematic review indicates that OSA and related conditions (e.g., mouth breathing) are associated with different oral microbiota compositions, which may underlie the association between OSA and periodontitis.

Whole-genome metagenomic analysis of the oral microbiota in patients with obstructive sleep apnea

PURPOSE

The oral microbiota is closely associated with systemic health, but few studies have investigated the oral microbiota in patients with obstructive sleep apnea (OSA). This study aimed to identify the variation of oral microbiota among patients with severe OSA, and the change of oral microbiota after treatment with continuous positive airway pressure (CPAP).

METHODS

Participants were enrolled in the study from November 2020 to August 2021. Sleep parameters using full nocturnal polysomnography (PSG) were collected on healthy controls, patients with severe OSA, and patients with severe OSA after CPAP treatment for 3 months. Oral samples were also collected by rubbing disposable medical sterile swabs on the buccal mucosa. Routine blood tests and biochemical indicators were measured using the fully automated biochemical analyzer. Oral microbial composition of oral samples were determined using whole-genome metagenomic analysis in all participants. Correlations were analyzed between the oral microbiota and blood lipids.

RESULTS

Study enrollment included 14 participants, 7 healthy controls and 7 patients with severe OSA. At the species level, the relative abundances of Prevotella, Alloprevotella, Bacteroides, Veillonella_tobetsuensis, Candidatus saccharimonas, and Leptotrichia in the groups with severe OSA were significantly lower than those in the healthy controls (P both < 0.05). The abundances of Capnocytophaga, Veillonella, Bacillus_anthracis, Eikenella, and Kingella were significantly higher whereas the abundances of Gordonia and Streptococcus were significantly lower in the group with severe OSA compared to the severe OSA-CPAP group (P < 0.05 for both). According to the Kyoto Encyclopedia of Genes and Genomes (KEGG), 4 pathways changed in the group with severe OSA compared with healthy controls (P both < 0.05). Pathways related to Novobiocin biosynthesis, 2-Oxocarboxylic acid metabolism, and Histidine metabolism were enriched in the patients with severe OSA. Nine pathways showed significant differences with regard to the relative abundances of phenylalanine metabolism; alanine, aspartate, and glutamate metabolism; one carbon pool by folate; monobactam biosynthesis; 2-oxocarboxylic acid metabolism; arginine biosynthesis and vitamin B6 metabolism; novobiocin biosynthesis; and arginine and proline metabolism, which were significantly higher in the group with severe OSA compared to the severe OSA-CPAP group (P both < 0.05). The Spearman correlation analysis between blood lipid parameters and oral microbiota components showed that negative correlations were observed between total cholesterol and Streptomyces (r =  - 0.893, P = 0.007), and high-density lipoprotein cholesterol (HDL-C) and Gordonia (r = - 0.821, P = 0.023); positive correlations were observed between HDL-C and Candidatus saccharimonas (r = 0.929, P = 0.003), and low-density lipoprotein cholesterol (LDL-C) and Capnocytophaga (r = 0.893, P = 0.007).

CONCLUSION

There was an apparent discrepancy of the oral microbiota and metabolic pathways between the group with severe OSA and controls, and CPAP significantly changed oral microbial abundance and metabolic pathways in patients with severe OSA. Correlation analysis showed that these oral bacteria were strongly correlated with the blood lipids level.

Obstructive Sleep Apnea, Metabolic Dysfunction, and Periodontitis-Machine Learning and Statistical Analyses of the Dental, Oral, Medical Epidemiological (DOME) Big Data Study

This study aimed to analyze the associations of obstructive sleep apnea (OSA) with dental parameters while controlling for socio-demographics, health-related habits, and each of the diseases comprising metabolic syndrome (MetS), its consequences, and related conditions. We analyzed data from the dental, oral, and medical epidemiological (DOME) cross-sectional records-based study that combines comprehensive socio-demographic, medical, and dental databases of a nationally representative sample of military personnel for one year. Analysis included statistical and machine learning models. The study included 132,529 subjects; of these, 318 (0.2%) were diagnosed with OSA. The following parameters maintained a statistically significant positive association with OSA in the multivariate binary logistic regression analysis (descending order from highest to lowest OR): obesity (OR = 3.104 (2.178-4.422)), male sex (OR = 2.41 (1.25-4.63)), periodontal disease (OR = 2.01 (1.38-2.91)), smoking (OR = 1.45 (1.05-1.99)), and age (OR = 1.143 (1.119-1.168)). Features importance generated by the XGBoost machine learning algorithm were age, obesity, and male sex (located on places 1-3), which are well-known risk factors of OSA, as well as periodontal disease (fourth place) and delivered dental fillings (fifth place). The Area Under Curve (AUC) of the model was 0.868 and the accuracy was 0.92. Altogether, the findings supported the main hypothesis of the study, which was that OSA is linked to dental morbidity, in particular to periodontitis. The findings highlight the need for dental evaluation as part of the workup of OSA patients and emphasizes the need for dental and general medical authorities to collaborate by exchanging knowledge about dental and systemic morbidities and their associations. The study also highlights the necessity for a comprehensive holistic risk management strategy that takes systemic and dental diseases into account.

Early Childhood Caries and Sleep Disorders

Obstructive sleep-disordered breathing (oSDB) comprises a set of breathing disturbances when the individual is asleep due to partial or complete upper airway obstruction. Modifying or risk factors are the anatomy, the size and shape of the airway, muscle tone, central nervous system responses to hypoxia, etc. In children, this is associated with poor school performance and reduced memory and learning abilities. In addition, increased levels of blood and lung pressure and cardiac alterations have been reported in children with sleep disturbances. On the other hand, Early Childhood Caries (ECC) is defined as the presence of one or more decayed primary teeth (cavities) of children under the age of 5. This study aimed to establish the possible relationship between sleep disorders and ECC by means of validated surveys and determined whether the results obtained coincide with the available literature. Our results found that up to 24.5% of children with a high risk of caries present regular nasal congestion, while this finding is only present among 6% of children with a low risk of caries (p = 0.041). The dmft index remains significantly linked to this occasional congestion, but the association depends on the patient's level of risk (p = 0.008); increasing with a high increasing risk of caries. As a conclusion, the risk of early childhood caries could correlate to a specific sleep change such as occasional snoring.

Changes in oral pH before and after placing preformed metal crowns in primary dentition of Mexican children

BACKGROUND: Prefabricated metal crowns (PMCs) have been widely used in pediatric dentistry due to their great success in various clinical situations. However, it is important to know the local effects, such as changes in pH in the oral environment. OBJECTIVE: To evaluate the pH variations before and after placement of PMCs. METHODS: A quasi-experimental study (before and after) was performed with 32 pediatric patients who needed rehabilitation with PMCs at a pediatric dentistry clinic in a public university. Measurements were made using a pH potentiometer before PMC placement, one week after, and one month after placement. ANOVA and Pearson correlation were performed in SPSS. RESULTS: The average age of the participants was 5.9 ± 1.6 years, and 53.1% were female. The average pH before, one week after, and one month after crown placement was 7.46 ± 0.37, 7.00 ± 0.32, and 7.1 ± 0.19, respectively. Significant differences (p< 0.05) were observed between the three pH measurements. We found differences when comparing the basal pH values to those at one week (p= 0.001) and one month (p= 0.002). CONCLUSION: Although there were statistically significant differences in the pH change values before and after the placement of crowns, these differences may not have a clinical impact.

Characteristics of salivary microbiota in children with obstructive sleep apnea: A prospective study with polysomnography

Objectives

The present study aimed to investigate the characteristics of salivary microbiota of children with obstructive sleep apnea (OSA) and to assess longitudinal alterations in salivary microbiota before and after adenotonsillectomy.

Methods

A set of cross-sectional samples consisted of 36 OSA children (17 boys and 19 girls, 7.47 ± 2.24 years old) and 22 controls (9 boys and 13 girls, 7.55 ± 2.48 years old) were included in the study, among which eight OSA children (five boys and three girls, 8.8 ± 2.0 years old) who underwent treatment of adenotonsillectomy were followed up after 1 year. Saliva samples were collected, and microbial profiles were analyzed by bioinformatics analysis based on 16S rRNA sequencing.

Results

In cross-sectional samples, the OSA group had higher α-diversity as estimated by Chao1, Shannon, Simpson, Pielou_e, and observed species as compared with the control group (p &lt; 0.05). β-Diversity based on the Bray–Curtis dissimilarities (p = 0.004) and Jaccard distances (p = 0.001) revealed a significant separation between the OSA group and control group. Nested cross-validated random forest classifier identified the 10 most important genera (Lactobacillus, Escherichia, Bifidobacterium, Capnocytophaga, Bacteroidetes_[G-7], Parvimonas, Bacteroides, Klebsiella, Lautropia, and Prevotella) that could differentiate OSA children from controls with an area under the curve (AUC) of 0.94. Linear discriminant analysis effect size (LEfSe) analysis revealed a significantly higher abundance of genera such as Prevotella (p = 0.027), Actinomyces (p = 0.015), Bifidobacterium (p &lt; 0.001), Escherichia (p &lt; 0.001), and Lactobacillus (p &lt; 0.001) in the OSA group, among which Prevotella was further corroborated in longitudinal samples. Prevotella sp_HMT_396 was found to be significantly enriched in the OSA group (p = 0.02) with significantly higher levels as OSA severity increased (p = 0.014), and it had a lower abundance in the post-treatment group (p = 0.003) with a decline in each OSA child 1 year after adenotonsillectomy.

Conclusions

A significantly higher microbial diversity and a significant difference in microbial composition and abundance were identified in salivary microbiota of OSA children compared with controls. Meanwhile, some characteristic genera (Prevotella, Actinomyces, Lactobacillus, Escherichia, and Bifidobacterium) were found in OSA children, among which the relationship between Prevotella spp. and OSA is worth further studies.