J 2021

Validation and verification of predictive salivary biomarkers for oral health

BOSTANCI, N., K. MITSAKAKIS, B. AFACAN, K. BAO, B. JOHANNSEN et. al.

Základní údaje

Originální název

Validation and verification of predictive salivary biomarkers for oral health

Autoři

BOSTANCI, N. (garant), K. MITSAKAKIS, B. AFACAN, K. BAO, B. JOHANNSEN, D. BAUMGARTNER, L. MULLER, Hana KOTOLOVÁ (203 Česká republika, domácí), G. EMINGIL a Michal KARPÍŠEK (203 Česká republika, domácí)

Vydání

Nature Scientific Reports, London, NATURE RESEARCH, 2021, 2045-2322

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30104 Pharmacology and pharmacy

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 4.996

Kód RIV

RIV/00216224:14160/21:00121412

Organizační jednotka

Farmaceutická fakulta

UT WoS

000632046500002

Klíčová slova anglicky

Validation; verification; predictive salivary; biomarker; oral health

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 16. 4. 2021 18:32, Mgr. Hana Hurtová

Anotace

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.