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The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals
Aim: To characterize the profile of submucosal microbiome and cytokine levels in peri-implant crevicular fluid (PICF) from clinically healthy implants and peri-implantitis in the same individuals. Material and Methods: A total of 170 patients were screened and, finally, 14 patients with at least one...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572122/ https://www.ncbi.nlm.nih.gov/pubmed/36233685 http://dx.doi.org/10.3390/jcm11195817 |
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author | Song, Lu Jiang, Jimin Li, Jia Zhou, Chuan Chen, Yanqi Lu, Hongye He, Fuming |
author_facet | Song, Lu Jiang, Jimin Li, Jia Zhou, Chuan Chen, Yanqi Lu, Hongye He, Fuming |
author_sort | Song, Lu |
collection | PubMed |
description | Aim: To characterize the profile of submucosal microbiome and cytokine levels in peri-implant crevicular fluid (PICF) from clinically healthy implants and peri-implantitis in the same individuals. Material and Methods: A total of 170 patients were screened and, finally, 14 patients with at least one healthy implant and one peri-implantitis implant were included. Submucosal microbiota and cytokines from 28 implants were analyzed using 16S rRNA gene sequencing and multifactor assays, respectively. Correlations of clinical indexes and microbiota or cytokines were analyzed using Spearman’s correlation coefficient. A random forest classification model was constructed. Results: Peri-implantitis sites harbored higher microbial diversity, as well as more Gram-negative bacteria and anaerobic bacteria, compared with healthy implants sites. The genera of Peptostreptococcaceae XIG-1, Treponema, Porphyromonas, and Lachnospiraceae G-8, as well as the cytokines of IL-17A, IL-6, IL-15, G-CSF, RANTES, and IL-1β were significantly higher in peri-implantitis than healthy implants. Furthermore, these genera and cytokines had positive relationships with clinical parameters, including probing depth (PD), bleeding on probing (BOP), and marginal bone loss (MBL). The classification model picked out the top 15 biomarkers, such as IL-17A, IL-6, IL-15, VEGF, IL-1β, Peptostreptococcaceae XIG-1, Haemophilus, and Treponema, and obtained an area under the curve (AUC) of 0.85. Conclusions: There are more pathogenic bacteria and inflammatory cytokines in peri-implantitis sites, and biomarkers could facilitate the diagnosis of peri-implantitis. |
format | Online Article Text |
id | pubmed-9572122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95721222022-10-17 The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals Song, Lu Jiang, Jimin Li, Jia Zhou, Chuan Chen, Yanqi Lu, Hongye He, Fuming J Clin Med Article Aim: To characterize the profile of submucosal microbiome and cytokine levels in peri-implant crevicular fluid (PICF) from clinically healthy implants and peri-implantitis in the same individuals. Material and Methods: A total of 170 patients were screened and, finally, 14 patients with at least one healthy implant and one peri-implantitis implant were included. Submucosal microbiota and cytokines from 28 implants were analyzed using 16S rRNA gene sequencing and multifactor assays, respectively. Correlations of clinical indexes and microbiota or cytokines were analyzed using Spearman’s correlation coefficient. A random forest classification model was constructed. Results: Peri-implantitis sites harbored higher microbial diversity, as well as more Gram-negative bacteria and anaerobic bacteria, compared with healthy implants sites. The genera of Peptostreptococcaceae XIG-1, Treponema, Porphyromonas, and Lachnospiraceae G-8, as well as the cytokines of IL-17A, IL-6, IL-15, G-CSF, RANTES, and IL-1β were significantly higher in peri-implantitis than healthy implants. Furthermore, these genera and cytokines had positive relationships with clinical parameters, including probing depth (PD), bleeding on probing (BOP), and marginal bone loss (MBL). The classification model picked out the top 15 biomarkers, such as IL-17A, IL-6, IL-15, VEGF, IL-1β, Peptostreptococcaceae XIG-1, Haemophilus, and Treponema, and obtained an area under the curve (AUC) of 0.85. Conclusions: There are more pathogenic bacteria and inflammatory cytokines in peri-implantitis sites, and biomarkers could facilitate the diagnosis of peri-implantitis. MDPI 2022-09-30 /pmc/articles/PMC9572122/ /pubmed/36233685 http://dx.doi.org/10.3390/jcm11195817 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Song, Lu Jiang, Jimin Li, Jia Zhou, Chuan Chen, Yanqi Lu, Hongye He, Fuming The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title | The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title_full | The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title_fullStr | The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title_full_unstemmed | The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title_short | The Characteristics of Microbiome and Cytokines in Healthy Implants and Peri-Implantitis of the Same Individuals |
title_sort | characteristics of microbiome and cytokines in healthy implants and peri-implantitis of the same individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572122/ https://www.ncbi.nlm.nih.gov/pubmed/36233685 http://dx.doi.org/10.3390/jcm11195817 |
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