{"title":"Whole-Genome Metagenomic Analysis of the Oral Microbiota in Patients with Obstructive Sleep Apnea Comorbid with Major Depressive Disorder","authors":"Jing Ye, Yunhui Lv, Hui Xie, Kun Lian, Xiufeng Xu","doi":"10.2147/nss.s474052","DOIUrl":null,"url":null,"abstract":"<strong>Background:</strong> Obstructive sleep apnea (OSA) patients commonly experience high rates of depression. This study aims to examine the oral microbiota characteristics of OSA and those with comorbid major depressive disorder (OSA+MDD) patients.<br/><strong>Methods:</strong> Participants were enrolled from Aug 2022 to Apr 2023. Polysomnography, psychiatrist interviews, and scales were used to diagnose OSA and MDD. Oral samples were collected from participants by rubbing swabs on buccal mucosa, palate, and gums. Oral microbiota was analyzed via whole-genome metagenomics and bioinformatic analysis followed sequencing. Venous blood was drawn to detect plasma inflammatory factor levels.<br/><strong>Results:</strong> The study enrolled 33 OSA patients, 28 OSA+MDD patients, and 28 healthy controls. Significant differences were found in 8 phyla, 229 genera, and 700 species of oral microbiota among the three groups. Prevotellaceae abundance in the OSA and OSA+MDD groups was significantly lower than that in healthy controls. Linear discriminant analysis effect size (LEfSe) analysis showed that Streptococcaceae and Actinobacteria were the characteristic oral microbiota of the OSA and OSA+MDD groups, respectively. KEGG analysis indicates 30 pathways were changed in the OSA and OSA+MDD groups compared with healthy controls, and 23 pathways were changed in the OSA group compared with the OSA+MDD group. Levels of IL-6 in the OSA+MDD group were significantly higher than in the healthy group, correlating positively with the abundance of Schaalia, Campylobacter, Fusobacterium, Alloprevotella, and Candidatus Nanosynbacter in the oral, as well as with Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale scores.<br/><strong>Conclusion:</strong> Significant differences in oral microbiota populations and gene function were observed among the three groups. OSA patients were characterized by a decreased abundance of Prevotellaceae and an increased abundance of Streptococcaceae. OSA+MDD patients had an increased abundance of Actinobacteria. IL-6 might regulate the relationship between depression and the oral microbiota in OSA+MDD patients.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature and Science of Sleep","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/nss.s474052","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Obstructive sleep apnea (OSA) patients commonly experience high rates of depression. This study aims to examine the oral microbiota characteristics of OSA and those with comorbid major depressive disorder (OSA+MDD) patients. Methods: Participants were enrolled from Aug 2022 to Apr 2023. Polysomnography, psychiatrist interviews, and scales were used to diagnose OSA and MDD. Oral samples were collected from participants by rubbing swabs on buccal mucosa, palate, and gums. Oral microbiota was analyzed via whole-genome metagenomics and bioinformatic analysis followed sequencing. Venous blood was drawn to detect plasma inflammatory factor levels. Results: The study enrolled 33 OSA patients, 28 OSA+MDD patients, and 28 healthy controls. Significant differences were found in 8 phyla, 229 genera, and 700 species of oral microbiota among the three groups. Prevotellaceae abundance in the OSA and OSA+MDD groups was significantly lower than that in healthy controls. Linear discriminant analysis effect size (LEfSe) analysis showed that Streptococcaceae and Actinobacteria were the characteristic oral microbiota of the OSA and OSA+MDD groups, respectively. KEGG analysis indicates 30 pathways were changed in the OSA and OSA+MDD groups compared with healthy controls, and 23 pathways were changed in the OSA group compared with the OSA+MDD group. Levels of IL-6 in the OSA+MDD group were significantly higher than in the healthy group, correlating positively with the abundance of Schaalia, Campylobacter, Fusobacterium, Alloprevotella, and Candidatus Nanosynbacter in the oral, as well as with Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale scores. Conclusion: Significant differences in oral microbiota populations and gene function were observed among the three groups. OSA patients were characterized by a decreased abundance of Prevotellaceae and an increased abundance of Streptococcaceae. OSA+MDD patients had an increased abundance of Actinobacteria. IL-6 might regulate the relationship between depression and the oral microbiota in OSA+MDD patients.
期刊介绍:
Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep.
Specific topics covered in the journal include:
The functions of sleep in humans and other animals
Physiological and neurophysiological changes with sleep
The genetics of sleep and sleep differences
The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness
Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness
Sleep changes with development and with age
Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause)
The science and nature of dreams
Sleep disorders
Impact of sleep and sleep disorders on health, daytime function and quality of life
Sleep problems secondary to clinical disorders
Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health)
The microbiome and sleep
Chronotherapy
Impact of circadian rhythms on sleep, physiology, cognition and health
Mechanisms controlling circadian rhythms, centrally and peripherally
Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health
Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption
Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms
Epigenetic markers of sleep or circadian disruption.