Whole-Genome Metagenomic Analysis of the Oral Microbiota in Patients with Obstructive Sleep Apnea Comorbid with Major Depressive Disorder

IF 3 2区 医学 Q2 CLINICAL NEUROLOGY Nature and Science of Sleep Pub Date : 2024-07-29 DOI:10.2147/nss.s474052
Jing Ye, Yunhui Lv, Hui Xie, Kun Lian, Xiufeng Xu
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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.

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阻塞性睡眠呼吸暂停合并重度抑郁症患者口腔微生物群的全基因组元基因组分析
背景:阻塞性睡眠呼吸暂停(OSA)患者通常有较高的抑郁症发病率。本研究旨在检测 OSA 患者和合并重度抑郁症(OSA+MDD)患者的口腔微生物群特征:方法:从 2022 年 8 月至 2023 年 4 月招募参与者。采用多导睡眠图、精神科医生访谈和量表来诊断 OSA 和 MDD。用棉签擦拭参与者的口腔黏膜、上颚和牙龈,收集口腔样本。在测序后,通过全基因组元基因组学和生物信息分析对口腔微生物群进行分析。抽取静脉血检测血浆炎症因子水平:研究共纳入 33 名 OSA 患者、28 名 OSA+MDD 患者和 28 名健康对照组。结果发现,三组患者口腔微生物群的 8 个门、229 个属、700 个种存在显著差异。OSA组和OSA+MDD组的前胡科丰度明显低于健康对照组。线性判别分析效应大小(LEfSe)分析显示,链球菌属和放线菌属分别是OSA组和OSA+MDD组的特征性口腔微生物群。KEGG分析表明,与健康对照组相比,OSA组和OSA+MDD组有30条通路发生了变化,与OSA+MDD组相比,OSA组有23条通路发生了变化。OSA+MDD组的IL-6水平明显高于健康组,与口腔中的沙雷氏菌、弯曲杆菌、镰刀菌、异型伏特氏菌和纳米拟杆菌的丰度以及汉密尔顿焦虑评分量表和汉密尔顿抑郁评分量表的评分呈正相关:结论:三组患者的口腔微生物群和基因功能存在显著差异。OSA 患者的特点是普雷沃特氏菌(Prevotellaceae)数量减少,链球菌(Streptococcaceae)数量增加。OSA+MDD患者的放线菌数量增加。IL-6可能会调节OSA+MDD患者抑郁与口腔微生物群之间的关系。
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来源期刊
Nature and Science of Sleep
Nature and Science of Sleep Neuroscience-Behavioral Neuroscience
CiteScore
5.70
自引率
5.90%
发文量
245
审稿时长
16 weeks
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.
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