Cargando…

The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis

INTRODUCTION: Despite decades of research, systemic autoimmune diseases (SADs) continue to be a major global health concern and the etiology of these diseases is still not clear. To date, with the development of high-throughput techniques, increasing evidence indicated a key role of oral microbiome...

Descripción completa

Detalles Bibliográficos
Autores principales: Gao, Lu, Cheng, Zijian, Zhu, Fudong, Bi, Chunsheng, Shi, Qiongling, Chen, Xiaoyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277227/
https://www.ncbi.nlm.nih.gov/pubmed/35844967
http://dx.doi.org/10.3389/fdata.2022.927520
_version_ 1784745910348021760
author Gao, Lu
Cheng, Zijian
Zhu, Fudong
Bi, Chunsheng
Shi, Qiongling
Chen, Xiaoyan
author_facet Gao, Lu
Cheng, Zijian
Zhu, Fudong
Bi, Chunsheng
Shi, Qiongling
Chen, Xiaoyan
author_sort Gao, Lu
collection PubMed
description INTRODUCTION: Despite decades of research, systemic autoimmune diseases (SADs) continue to be a major global health concern and the etiology of these diseases is still not clear. To date, with the development of high-throughput techniques, increasing evidence indicated a key role of oral microbiome in the pathogenesis of SADs, and the alterations of oral microbiome may contribute to the disease emergence or evolution. This review is to present the latest knowledge on the relationship between the oral microbiome and SADs, focusing on the multiomics data generated from a large set of samples. METHODOLOGY: By searching the PubMed and Embase databases, studies that investigated the oral microbiome of SADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and Sjögren's syndrome (SS), were systematically reviewed according to the PRISMA guidelines. RESULTS: One thousand and thirty-eight studies were found, and 25 studies were included: three referred to SLE, 12 referred to RA, nine referred to SS, and one to both SLE and SS. The 16S rRNA sequencing was the most frequent technique used. HOMD was the most common database aligned to and QIIME was the most popular pipeline for downstream analysis. Alterations in bacterial composition and population have been found in the oral samples of patients with SAD compared with the healthy controls. Results regarding candidate pathogens were not always in accordance, but Selenomonas and Veillonella were found significantly increased in three SADs, and Streptococcus was significantly decreased in the SADs compared with controls. CONCLUSION: A large amount of sequencing data was collected from patients with SAD and controls in this systematic review. Oral microbial dysbiosis had been identified in these SADs, although the dysbiosis features were different among studies. There was a lack of standardized study methodology for each study from the inclusion criteria, sample type, sequencing platform, and referred database to downstream analysis pipeline and cutoff. Besides the genomics, transcriptomics, proteomics, and metabolomics technology should be used to investigate the oral microbiome of patients with SADs and also the at-risk individuals of disease development, which may provide us with a better understanding of the etiology of SADs and promote the development of the novel therapies.
format Online
Article
Text
id pubmed-9277227
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-92772272022-07-14 The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis Gao, Lu Cheng, Zijian Zhu, Fudong Bi, Chunsheng Shi, Qiongling Chen, Xiaoyan Front Big Data Big Data INTRODUCTION: Despite decades of research, systemic autoimmune diseases (SADs) continue to be a major global health concern and the etiology of these diseases is still not clear. To date, with the development of high-throughput techniques, increasing evidence indicated a key role of oral microbiome in the pathogenesis of SADs, and the alterations of oral microbiome may contribute to the disease emergence or evolution. This review is to present the latest knowledge on the relationship between the oral microbiome and SADs, focusing on the multiomics data generated from a large set of samples. METHODOLOGY: By searching the PubMed and Embase databases, studies that investigated the oral microbiome of SADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and Sjögren's syndrome (SS), were systematically reviewed according to the PRISMA guidelines. RESULTS: One thousand and thirty-eight studies were found, and 25 studies were included: three referred to SLE, 12 referred to RA, nine referred to SS, and one to both SLE and SS. The 16S rRNA sequencing was the most frequent technique used. HOMD was the most common database aligned to and QIIME was the most popular pipeline for downstream analysis. Alterations in bacterial composition and population have been found in the oral samples of patients with SAD compared with the healthy controls. Results regarding candidate pathogens were not always in accordance, but Selenomonas and Veillonella were found significantly increased in three SADs, and Streptococcus was significantly decreased in the SADs compared with controls. CONCLUSION: A large amount of sequencing data was collected from patients with SAD and controls in this systematic review. Oral microbial dysbiosis had been identified in these SADs, although the dysbiosis features were different among studies. There was a lack of standardized study methodology for each study from the inclusion criteria, sample type, sequencing platform, and referred database to downstream analysis pipeline and cutoff. Besides the genomics, transcriptomics, proteomics, and metabolomics technology should be used to investigate the oral microbiome of patients with SADs and also the at-risk individuals of disease development, which may provide us with a better understanding of the etiology of SADs and promote the development of the novel therapies. Frontiers Media S.A. 2022-06-29 /pmc/articles/PMC9277227/ /pubmed/35844967 http://dx.doi.org/10.3389/fdata.2022.927520 Text en Copyright © 2022 Gao, Cheng, Zhu, Bi, Shi and Chen. 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 Big Data
Gao, Lu
Cheng, Zijian
Zhu, Fudong
Bi, Chunsheng
Shi, Qiongling
Chen, Xiaoyan
The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title_full The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title_fullStr The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title_full_unstemmed The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title_short The Oral Microbiome and Its Role in Systemic Autoimmune Diseases: A Systematic Review of Big Data Analysis
title_sort oral microbiome and its role in systemic autoimmune diseases: a systematic review of big data analysis
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277227/
https://www.ncbi.nlm.nih.gov/pubmed/35844967
http://dx.doi.org/10.3389/fdata.2022.927520
work_keys_str_mv AT gaolu theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT chengzijian theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT zhufudong theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT bichunsheng theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT shiqiongling theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT chenxiaoyan theoralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT gaolu oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT chengzijian oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT zhufudong oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT bichunsheng oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT shiqiongling oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis
AT chenxiaoyan oralmicrobiomeanditsroleinsystemicautoimmunediseasesasystematicreviewofbigdataanalysis