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Differences in salivary microbiome among children with tonsillar hypertrophy and/or adenoid hypertrophy.
- Source :
-
MSystems [mSystems] 2024 Oct 22; Vol. 9 (10), pp. e0096824. Date of Electronic Publication: 2024 Sep 17. - Publication Year :
- 2024
-
Abstract
- Children diagnosed with severe tonsillar hypertrophy display discernible craniofacial features distinct from those with adenoid hypertrophy, prompting illuminating considerations regarding microbiota regulation in this non-inflammatory condition. The present study aimed to characterize the salivary microbial profile in children with tonsillar hypertrophy and explore the potential functionality therein. A total of 112 children, with a mean age of 7.79 ± 2.41 years, were enrolled and divided into the tonsillar hypertrophy (TH) group ( n = 46, 8.4 ± 2.5 years old), adenoid hypertrophy (AH) group ( n = 21, 7.6 ± 2.8 years old), adenotonsillar hypertrophy (ATH) group ( n = 23, 7.2 ± 2.1 years old), and control group ( n = 22, 8.6 ± 2.1 years old). Unstimulated saliva samples were collected, and microbial profiles were analyzed by 16S rRNA sequencing of V3-V4 regions. Diversity and composition of salivary microbiome and the correlation with parameters of overnight polysomnography and complete blood count were investigated. As a result, children with tonsillar hypertrophy had significantly higher α-diversity indices ( P <0.05). β-diversity based on Bray-Curtis distance revealed that the salivary microbiome of the tonsillar hypertrophy group had a slight separation from the other three groups ( P <0.05). The linear discriminant analysis effect size (LEfSe) analysis indicated that Gemella was most closely related to tonsillar hypertrophy, and higher abundance of Gemella , Parvimonas , Dialister , and Lactobacillus may reflect an active state of immune regulation. Meanwhile, children with different degrees of tonsillar hypertrophy shared similar salivary microbiome diversity. This study demonstrated that the salivary microbiome in pediatric tonsillar hypertrophy patients had different signatures, highlighting that the site of upper airway obstruction primarily influences the salivary microbiome rather than hypertrophy severity.IMPORTANCETonsillar hypertrophy is the most frequent cause of upper airway obstruction and one of the primary risk factors for pediatric obstructive sleep apnea (OSA). Studies have discovered that children with isolated tonsillar hypertrophy exhibit different craniofacial morphology features compared with those with isolated adenoid hypertrophy or adenotonsillar hypertrophy. Furthermore, characteristic salivary microbiota from children with OSA compared with healthy children has been identified in our previous research. However, few studies provided insight into the relationship between the different sites of upper airway obstruction resulting from the enlargement of pharyngeal lymphoid tissue at different sites and the alterations in the microbiome. Here, to investigate the differences in the salivary microbiome of children with tonsillar hypertrophy and/or adenoid hypertrophy, we conducted a cross-sectional study and depicted the unique microbiome profile of pediatric tonsillar hypertrophy, which was mainly characterized by a significantly higher abundance of genera belonging to phyla Firmicutes and certain bacteria involving in the immune response in tonsillar hypertrophy, offering novel perspectives for future related research.<br />Competing Interests: The authors declare no conflict of interest.
- Subjects :
- Humans
Male
Female
Child
RNA, Ribosomal, 16S genetics
RNA, Ribosomal, 16S analysis
Child, Preschool
Bacteria classification
Bacteria isolation & purification
Bacteria genetics
Hypertrophy microbiology
Adenoids microbiology
Adenoids pathology
Microbiota
Saliva microbiology
Palatine Tonsil microbiology
Palatine Tonsil pathology
Subjects
Details
- Language :
- English
- ISSN :
- 2379-5077
- Volume :
- 9
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- MSystems
- Publication Type :
- Academic Journal
- Accession number :
- 39287377
- Full Text :
- https://doi.org/10.1128/msystems.00968-24