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Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting

BACKGROUND: Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive ma...

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Autores principales: Andörfer, Leonie, Holtfreter, Birte, Weiss, Stefan, Matthes, Rutger, Pitchika, Vinay, Schmidt, Carsten Oliver, Samietz, Stefanie, Kastenmüller, Gabi, Nauck, Matthias, Völker, Uwe, Völzke, Henry, Csonka, Laszlo N., Suhre, Karsten, Pietzner, Maik, Kocher, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278731/
https://www.ncbi.nlm.nih.gov/pubmed/34256740
http://dx.doi.org/10.1186/s12916-021-02035-z
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author Andörfer, Leonie
Holtfreter, Birte
Weiss, Stefan
Matthes, Rutger
Pitchika, Vinay
Schmidt, Carsten Oliver
Samietz, Stefanie
Kastenmüller, Gabi
Nauck, Matthias
Völker, Uwe
Völzke, Henry
Csonka, Laszlo N.
Suhre, Karsten
Pietzner, Maik
Kocher, Thomas
author_facet Andörfer, Leonie
Holtfreter, Birte
Weiss, Stefan
Matthes, Rutger
Pitchika, Vinay
Schmidt, Carsten Oliver
Samietz, Stefanie
Kastenmüller, Gabi
Nauck, Matthias
Völker, Uwe
Völzke, Henry
Csonka, Laszlo N.
Suhre, Karsten
Pietzner, Maik
Kocher, Thomas
author_sort Andörfer, Leonie
collection PubMed
description BACKGROUND: Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss. METHODS: We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models. RESULTS: We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation. CONCLUSIONS: Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-02035-z.
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spelling pubmed-82787312021-07-15 Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting Andörfer, Leonie Holtfreter, Birte Weiss, Stefan Matthes, Rutger Pitchika, Vinay Schmidt, Carsten Oliver Samietz, Stefanie Kastenmüller, Gabi Nauck, Matthias Völker, Uwe Völzke, Henry Csonka, Laszlo N. Suhre, Karsten Pietzner, Maik Kocher, Thomas BMC Med Research Article BACKGROUND: Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss. METHODS: We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models. RESULTS: We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation. CONCLUSIONS: Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-02035-z. BioMed Central 2021-07-14 /pmc/articles/PMC8278731/ /pubmed/34256740 http://dx.doi.org/10.1186/s12916-021-02035-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Andörfer, Leonie
Holtfreter, Birte
Weiss, Stefan
Matthes, Rutger
Pitchika, Vinay
Schmidt, Carsten Oliver
Samietz, Stefanie
Kastenmüller, Gabi
Nauck, Matthias
Völker, Uwe
Völzke, Henry
Csonka, Laszlo N.
Suhre, Karsten
Pietzner, Maik
Kocher, Thomas
Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title_full Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title_fullStr Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title_full_unstemmed Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title_short Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
title_sort salivary metabolites associated with a 5-year tooth loss identified in a population-based setting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278731/
https://www.ncbi.nlm.nih.gov/pubmed/34256740
http://dx.doi.org/10.1186/s12916-021-02035-z
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