Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2018
Pediatric Obstructive Sleep Apnea is Associated With Changes in the Oral Microbiome and Urinary Metabolomics Profile: A Pilot Study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Xu Huajun, Li Xiaoyan, Zheng Xiaojiao, Xia Yunyan, Fu Yiqun, Li Xinyi, Qian Yingjun, Zou Jianyin, Zhao Aihua, Guan Jian, Gu Meizhen, Yi Hongliang, Jia Wei, Yin Shankai
Аннотация
STUDY OBJECTIVES: Several cross-sectional studies have reported associations between oral diseases and obstructive sleep apnea (OSA). However, there have been no reports regarding the structure and composition of the oral microbiota with simultaneous evaluation of potential associations with perturbed metabolic profiles in pediatric OSA.
METHODS: An integrated approach, combining metagenomics based on high-throughput 16S rRNA gene sequencing, and metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry, was used to evaluate the oral microbiome and the urinary metabolome.
RESULTS: 16S rRNA gene sequencing indicated that the oral microbiome composition was significantly perturbed in pediatric OSA compared with normal controls, especially with regard to Firmicutes, Proteobacteria, Bacteroidetes, Fusobacteria, and Actinobacteria. Moreover, metabolomics profiling indicated that 57 metabolites, 5 of which were metabolites related to the microflora of the digestive tract, were differentially present in the urine of pediatric patients with OSA and controls. Co-inertia and correlation analyses revealed that several oral microbiome changes were correlated with urinary metabolite perturbations in pediatric OSA. However, this correlation relationship does not imply causality.
CONCLUSIONS: High-throughput sequencing revealed that the oral microbiome composition and function were significantly altered in pediatric OSA. Further studies are needed to confirm and determine the mechanisms underlying these findings.
METHODS: An integrated approach, combining metagenomics based on high-throughput 16S rRNA gene sequencing, and metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry, was used to evaluate the oral microbiome and the urinary metabolome.
RESULTS: 16S rRNA gene sequencing indicated that the oral microbiome composition was significantly perturbed in pediatric OSA compared with normal controls, especially with regard to Firmicutes, Proteobacteria, Bacteroidetes, Fusobacteria, and Actinobacteria. Moreover, metabolomics profiling indicated that 57 metabolites, 5 of which were metabolites related to the microflora of the digestive tract, were differentially present in the urine of pediatric patients with OSA and controls. Co-inertia and correlation analyses revealed that several oral microbiome changes were correlated with urinary metabolite perturbations in pediatric OSA. However, this correlation relationship does not imply causality.
CONCLUSIONS: High-throughput sequencing revealed that the oral microbiome composition and function were significantly altered in pediatric OSA. Further studies are needed to confirm and determine the mechanisms underlying these findings.