Salivary Biomarkers for Dental Caries Detection and Personalized Monitoring

Abstract

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.

Keywords: JAK; STAT; biomarkers; caries; diagnostics; interleukins; personalized monitoring; saliva; screening.

Figure 1

Flow-chart showing the study design, study population, and applied saliva analyses. Biomarkers of the Cytokine 30-Plex Human Panel are color-coded for cytokines (green), chemokines (yellow), and growth factors (blue). * Eotaxin/CCL11.

Figure 2

Detection matrix of all biomarkers (x-axis) in the analyzed 73 subjects (y-axis). Color codes show data measured above (blue) or below (red) the detection limit. Numbers on the left correspond to the numbers of patients with the same pattern of biomarkers above/below the detection limit. Numbers on the right represent the numbers of biomarkers below the detection limit per line.

Figure 3

Results obtained from a principal component analysis (PCA) with the first dimension on the x-axis (36%) and the second dimension on the y-axis (8.4%). The groups are separated by color and shape (caries = red square; gingivitis = green triangle; caries = red circle). Three bigger shapes are located at the center of gravity for each group.

Figure 4

Random forest results plotted according to mean decrease in accuracy, show the strongest discriminators, namely, IL-4, IL-13, IL-2-RA, and eotaxin/CCL11.

Figure 5

Boxplots of the four strongest group classifiers (IL-4, IL-13, IL-2-RA, and eotaxin/CCL11) based on random forest classification, with median values and interquartile ranges for each group shown (healthy individuals, patients with gingivitis, and those with caries). p-values were derived from Kruskal–Wallis tests followed by post hoc pairwise comparisons according to Conover. ns = p > 0.05; *** p ≤ 0.001 (see Table 1 for specific p-values).

Figure 6

PCA loading plot visualizing the correlation between the biomarkers tested and clusters of samples, grouped based on their similarity. The red-colored arrows show the four biomarkers (ordered from top to bottom): IL-4, IL-13, IL-2-RA, and eotaxin/CCL11. The S. mutans arrow is colored in green, in close proximity to IL-4.

Figure 7

The clinical statuses of five healthy and five caries patients were assessed and classified by dental specialists as well as by biomarker-based RF predictions (Healthy Patient_1 to _5, and Cariogenic Patient_1 to _5). The graphs visualize and compare the classification results based on the RF modeling (white) and the clinical assessment by dental specialists (black) for each timepoint (T0 = baseline, T1 = after 4 months, T2 = after 5 months, and T3 = after 6 months). The tables below the graph show the respective biomarker concentrations in pg/mL, with N/D = values below the detection limit.

Figure 7

The clinical statuses of five healthy and five caries patients were assessed and classified by dental specialists as well as by biomarker-based RF predictions (Healthy Patient_1 to _5, and Cariogenic Patient_1 to _5). The graphs visualize and compare the classification results based on the RF modeling (white) and the clinical assessment by dental specialists (black) for each timepoint (T0 = baseline, T1 = after 4 months, T2 = after 5 months, and T3 = after 6 months). The tables below the graph show the respective biomarker concentrations in pg/mL, with N/D = values below the detection limit.