Cargando…

Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction

OBJECTIVES: The purpose of this study was to evaluate available evidence on the association between the human oral microbiota and coronavirus disease 2019 (COVID-19) and summarize relevant data obtained during the pandemic. METHODS: We searched EMBASE, PubMed, and the Cochrane Library for human stud...

Descripción completa

Detalles Bibliográficos
Autores principales: Tan, Li, Zhong, Meng-Mei, Liu, Qiong, Chen, Yun, Zhao, Ya-Qiong, Zhao, Jie, Dusenge, Marie Aimee, Feng, Yao, Ye, Qin, Hu, Jing, Ou-Yang, Ze-Yue, Zhou, Ying-Hui, Guo, Yue, Feng, Yun-Zhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10282655/
https://www.ncbi.nlm.nih.gov/pubmed/37351182
http://dx.doi.org/10.3389/fcimb.2023.1193340
_version_ 1785061174241394688
author Tan, Li
Zhong, Meng-Mei
Liu, Qiong
Chen, Yun
Zhao, Ya-Qiong
Zhao, Jie
Dusenge, Marie Aimee
Feng, Yao
Ye, Qin
Hu, Jing
Ou-Yang, Ze-Yue
Zhou, Ying-Hui
Guo, Yue
Feng, Yun-Zhi
author_facet Tan, Li
Zhong, Meng-Mei
Liu, Qiong
Chen, Yun
Zhao, Ya-Qiong
Zhao, Jie
Dusenge, Marie Aimee
Feng, Yao
Ye, Qin
Hu, Jing
Ou-Yang, Ze-Yue
Zhou, Ying-Hui
Guo, Yue
Feng, Yun-Zhi
author_sort Tan, Li
collection PubMed
description OBJECTIVES: The purpose of this study was to evaluate available evidence on the association between the human oral microbiota and coronavirus disease 2019 (COVID-19) and summarize relevant data obtained during the pandemic. METHODS: We searched EMBASE, PubMed, and the Cochrane Library for human studies published up to October 2022. The main outcomes of the study were the differences in the diversity (α and β) and composition of the oral microbiota at the phylum and genus levels between patients with laboratory-confirmed SARS-CoV-2 infection (CPs) and healthy controls (HCs). We used the Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA) database, Protein−protein interaction (PPI) network (STRING) and Gene enrichment analysis (Metascape) to evaluate the expression of dipeptidyl peptidase 4 (DPP4) (which is the cell receptor of SARS CoV-2) in oral tissues and evaluate its correlation with viral genes or changes in the oral microbiota. RESULTS: Out of 706 studies, a meta-analysis of 9 studies revealed a significantly lower alpha diversity (Shannon index) in CPs than in HCs (standardized mean difference (SMD): -0.53, 95% confidence intervals (95% CI): -0.97 to -0.09). Subgroup meta-analysis revealed a significantly lower alpha diversity (Shannon index) in older than younger individuals (SMD: -0.54, 95% CI: -0.86 to -0.23/SMD: -0.52, 95% CI: -1.18 to 0.14). At the genus level, the most significant changes were in Streptococcus and Neisseria, which had abundances that were significantly higher and lower in CPs than in HCs based on data obtained from six out of eleven and five out of eleven studies, respectively. DPP4 mRNA expression in the oral salivary gland was significantly lower in elderly individuals than in young individuals. Spearman correlation analysis showed that DPP4 expression was negatively correlated with the expression of viral genes. Gene enrichment analysis showed that DPP4-associated proteins were mainly enriched in biological processes, such as regulation of receptor-mediated endocytosis of viruses by host cells and bacterial invasion of epithelial cells. CONCLUSION: The oral microbial composition in COVID-19 patients was significantly different from that in healthy individuals, especially among elderly individuals. DPP4 may be related to viral infection and dysbiosis of the oral microbiome in elderly individuals.
format Online
Article
Text
id pubmed-10282655
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-102826552023-06-22 Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction Tan, Li Zhong, Meng-Mei Liu, Qiong Chen, Yun Zhao, Ya-Qiong Zhao, Jie Dusenge, Marie Aimee Feng, Yao Ye, Qin Hu, Jing Ou-Yang, Ze-Yue Zhou, Ying-Hui Guo, Yue Feng, Yun-Zhi Front Cell Infect Microbiol Cellular and Infection Microbiology OBJECTIVES: The purpose of this study was to evaluate available evidence on the association between the human oral microbiota and coronavirus disease 2019 (COVID-19) and summarize relevant data obtained during the pandemic. METHODS: We searched EMBASE, PubMed, and the Cochrane Library for human studies published up to October 2022. The main outcomes of the study were the differences in the diversity (α and β) and composition of the oral microbiota at the phylum and genus levels between patients with laboratory-confirmed SARS-CoV-2 infection (CPs) and healthy controls (HCs). We used the Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA) database, Protein−protein interaction (PPI) network (STRING) and Gene enrichment analysis (Metascape) to evaluate the expression of dipeptidyl peptidase 4 (DPP4) (which is the cell receptor of SARS CoV-2) in oral tissues and evaluate its correlation with viral genes or changes in the oral microbiota. RESULTS: Out of 706 studies, a meta-analysis of 9 studies revealed a significantly lower alpha diversity (Shannon index) in CPs than in HCs (standardized mean difference (SMD): -0.53, 95% confidence intervals (95% CI): -0.97 to -0.09). Subgroup meta-analysis revealed a significantly lower alpha diversity (Shannon index) in older than younger individuals (SMD: -0.54, 95% CI: -0.86 to -0.23/SMD: -0.52, 95% CI: -1.18 to 0.14). At the genus level, the most significant changes were in Streptococcus and Neisseria, which had abundances that were significantly higher and lower in CPs than in HCs based on data obtained from six out of eleven and five out of eleven studies, respectively. DPP4 mRNA expression in the oral salivary gland was significantly lower in elderly individuals than in young individuals. Spearman correlation analysis showed that DPP4 expression was negatively correlated with the expression of viral genes. Gene enrichment analysis showed that DPP4-associated proteins were mainly enriched in biological processes, such as regulation of receptor-mediated endocytosis of viruses by host cells and bacterial invasion of epithelial cells. CONCLUSION: The oral microbial composition in COVID-19 patients was significantly different from that in healthy individuals, especially among elderly individuals. DPP4 may be related to viral infection and dysbiosis of the oral microbiome in elderly individuals. Frontiers Media S.A. 2023-06-07 /pmc/articles/PMC10282655/ /pubmed/37351182 http://dx.doi.org/10.3389/fcimb.2023.1193340 Text en Copyright © 2023 Tan, Zhong, Liu, Chen, Zhao, Zhao, Dusenge, Feng, Ye, Hu, Ou-Yang, Zhou, Guo and Feng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cellular and Infection Microbiology
Tan, Li
Zhong, Meng-Mei
Liu, Qiong
Chen, Yun
Zhao, Ya-Qiong
Zhao, Jie
Dusenge, Marie Aimee
Feng, Yao
Ye, Qin
Hu, Jing
Ou-Yang, Ze-Yue
Zhou, Ying-Hui
Guo, Yue
Feng, Yun-Zhi
Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title_full Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title_fullStr Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title_full_unstemmed Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title_short Potential interaction between the oral microbiota and COVID-19: a meta-analysis and bioinformatics prediction
title_sort potential interaction between the oral microbiota and covid-19: a meta-analysis and bioinformatics prediction
topic Cellular and Infection Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10282655/
https://www.ncbi.nlm.nih.gov/pubmed/37351182
http://dx.doi.org/10.3389/fcimb.2023.1193340
work_keys_str_mv AT tanli potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT zhongmengmei potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT liuqiong potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT chenyun potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT zhaoyaqiong potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT zhaojie potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT dusengemarieaimee potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT fengyao potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT yeqin potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT hujing potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT ouyangzeyue potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT zhouyinghui potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT guoyue potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction
AT fengyunzhi potentialinteractionbetweentheoralmicrobiotaandcovid19ametaanalysisandbioinformaticsprediction