Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

Journal of Personalized Medicine

Christopher Herz¹  JohannesR. Peham¹  Michal Karpíšek²  PatrickR. Schmidlin³  PuneN. Paqué³  Thomas Thurnheer³  JoëlS. Jenzer³  FlorianJ. Wegehaupt³  Thomas Attin³  Philipp Körner³  Nagihan Bostanci⁴  Kai Bao⁴  GeorgiosN. Belibasakis⁴  JohnP. Hays⁵  WendyE. Kaman⁵  Konstantinos Mitsakakis⁶  DanielB. Wiedemeier⁷ 

[1] Austrian Institute of Technology, Molecular Diagnostics, Giefinggasse 4, 1210 Wien, Austria;BioVendor-Laboratorní Medicína, a.s., Research and Diagnostic Products Division, Immunoassays, Clinical Validation & BioVendor Analytical Testing Service, Karasek 1767/1, 62100 Brno, Czech Republic;Clinic of Conservative and Preventive Dentistry, Center of Dental Medicine, University of Zurich, Plattenstrasse 11, 8032 Zurich, Switzerland;Department of Dental Medicine, Division of Oral Diseases, Karolinska Institutet, 141 04 Huddinge, Sweden;Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre Rotterdam (Erasmus MC), 3015 GD Rotterdam, The Netherlands;Hahn-Schickard, Georges-Koehler-Allee 103, 79110 Freiburg, Germany;Statistical Services, Center of Dental Medicine, University of Zurich, Plattenstrasse 11, 8032 Zurich, Switzerland;

关键词: diagnostics;    interleukins;    screening;    personalized monitoring;    saliva;    biomarkers;   

DOI  :  10.3390/jpm11030235

来源: DOAJ

【 摘 要 】

This study investigated the potential of salivary bacterial and protein markers for evaluating the disease status in healthy individuals or patients with gingivitis or caries. Saliva samples from caries- and gingivitis-free individuals (n = 18), patients with gingivitis (n = 17), or patients with deep caries lesions (n = 38) were collected and analyzed for 44 candidate biomarkers (cytokines, chemokines, growth factors, matrix metalloproteinases, a metallopeptidase inhibitor, proteolytic enzymes, and selected oral bacteria). The resulting data were subjected to principal component analysis and used as a training set for random forest (RF) modeling. This computational analysis revealed four biomarkers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) to be of high importance for the correct depiction of caries in 37 of 38 patients. The RF model was then used to classify 10 subjects (five caries-/gingivitis-free and five with caries), who were followed over a period of six months. The results were compared to the clinical assessments of dental specialists, revealing a high correlation between the RF prediction and the clinical classification. Due to the superior sensitivity of the RF model, there was a divergence in the prediction of two caries and four caries-/gingivitis-free subjects. These findings suggest IL-4, IL-13, IL-2-RA, and eotaxin/CCL11 as potential salivary biomarkers for identifying noninvasive caries. Furthermore, we suggest a potential association between JAK/STAT signaling and dental caries onset and progression.

【 授权许可】

Unknown