Detailed Information on Publication Record
2021
Validation and verification of predictive salivary biomarkers for oral health
BOSTANCI, N., K. MITSAKAKIS, B. AFACAN, K. BAO, B. JOHANNSEN et. al.Basic information
Original name
Validation and verification of predictive salivary biomarkers for oral health
Authors
BOSTANCI, N. (guarantor), K. MITSAKAKIS, B. AFACAN, K. BAO, B. JOHANNSEN, D. BAUMGARTNER, L. MULLER, Hana KOTOLOVÁ (203 Czech Republic, belonging to the institution), G. EMINGIL and Michal KARPÍŠEK (203 Czech Republic, belonging to the institution)
Edition
Nature Scientific Reports, London, NATURE RESEARCH, 2021, 2045-2322
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
30104 Pharmacology and pharmacy
Country of publisher
Germany
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 4.996
RIV identification code
RIV/00216224:14160/21:00121412
Organization unit
Faculty of Pharmacy
UT WoS
000632046500002
Keywords in English
Validation; verification; predictive salivary; biomarker; oral health
Tags
International impact, Reviewed
Změněno: 16/4/2021 18:32, Mgr. Hana Hurtová
Abstract
V originále
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.