Validation and verification of predictive salivary biomarkers for oral health

Abstract Oral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for ging...

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Autores principales:	Nagihan Bostanci, Konstantinos Mitsakakis, Beral Afacan, Kai Bao, Benita Johannsen, Desirée Baumgartner, Lara Müller, Hana Kotolová, Gülnur Emingil, Michal Karpíšek
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3561b48ac1014f7085591d45faa2eca1
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spelling	oai:doaj.org-article:3561b48ac1014f7085591d45faa2eca12021-12-02T13:18:02ZValidation and verification of predictive salivary biomarkers for oral health10.1038/s41598-021-85120-w2045-2322https://doaj.org/article/3561b48ac1014f7085591d45faa2eca12021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85120-whttps://doaj.org/toc/2045-2322Abstract Oral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for gingivitis and periodontitis, which are major oral health threats, affecting the gums. These need to be verified and validated for their potential use as differentiators of health, gingivitis and periodontitis status, before they are translated to chair-side for diagnostics and personalized monitoring. We aimed to measure 10 candidates using high sensitivity ELISAs in a well-controlled cohort of 127 individuals from three groups: periodontitis (60), gingivitis (31) and healthy (36). The statistical approaches included univariate statistical tests, receiver operating characteristic curves (ROC) with the corresponding Area Under the Curve (AUC) and Classification and Regression Tree (CART) analysis. The main outcomes were that the combination of multiple biomarker assays, rather than the use of single ones, can offer a predictive accuracy of > 90% for gingivitis versus health groups; and 100% for periodontitis versus health and periodontitis versus gingivitis groups. Furthermore, ratios of biomarkers MMP-8, MMP-9 and TIMP-1 were also proven to be powerful differentiating values compared to the single biomarkers.Nagihan BostanciKonstantinos MitsakakisBeral AfacanKai BaoBenita JohannsenDesirée BaumgartnerLara MüllerHana KotolováGülnur EmingilMichal KarpíšekNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nagihan Bostanci Konstantinos Mitsakakis Beral Afacan Kai Bao Benita Johannsen Desirée Baumgartner Lara Müller Hana Kotolová Gülnur Emingil Michal Karpíšek Validation and verification of predictive salivary biomarkers for oral health
description	Abstract Oral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for gingivitis and periodontitis, which are major oral health threats, affecting the gums. These need to be verified and validated for their potential use as differentiators of health, gingivitis and periodontitis status, before they are translated to chair-side for diagnostics and personalized monitoring. We aimed to measure 10 candidates using high sensitivity ELISAs in a well-controlled cohort of 127 individuals from three groups: periodontitis (60), gingivitis (31) and healthy (36). The statistical approaches included univariate statistical tests, receiver operating characteristic curves (ROC) with the corresponding Area Under the Curve (AUC) and Classification and Regression Tree (CART) analysis. The main outcomes were that the combination of multiple biomarker assays, rather than the use of single ones, can offer a predictive accuracy of > 90% for gingivitis versus health groups; and 100% for periodontitis versus health and periodontitis versus gingivitis groups. Furthermore, ratios of biomarkers MMP-8, MMP-9 and TIMP-1 were also proven to be powerful differentiating values compared to the single biomarkers.
format	article
author	Nagihan Bostanci Konstantinos Mitsakakis Beral Afacan Kai Bao Benita Johannsen Desirée Baumgartner Lara Müller Hana Kotolová Gülnur Emingil Michal Karpíšek
author_facet	Nagihan Bostanci Konstantinos Mitsakakis Beral Afacan Kai Bao Benita Johannsen Desirée Baumgartner Lara Müller Hana Kotolová Gülnur Emingil Michal Karpíšek
author_sort	Nagihan Bostanci
title	Validation and verification of predictive salivary biomarkers for oral health
title_short	Validation and verification of predictive salivary biomarkers for oral health
title_full	Validation and verification of predictive salivary biomarkers for oral health
title_fullStr	Validation and verification of predictive salivary biomarkers for oral health
title_full_unstemmed	Validation and verification of predictive salivary biomarkers for oral health
title_sort	validation and verification of predictive salivary biomarkers for oral health
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3561b48ac1014f7085591d45faa2eca1
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Validation and verification of predictive salivary biomarkers for oral health

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