Can Saliva be the New Bio-fluid to Monitor Children's Oral Health?

Overview

Background: Salivary diagnosis is an emerging field; the potentially valuable biofluid contains many molecules of the systemic circulation. Still, its profile in health has been scarcely investigated. Aim: This study aimed to characterize the inflammatory profile of healthy children's saliva, and to associate the parameters with clinical diagnoses of caries and gingival inflammation. Study design: Unstimulated saliva was collected from 100 children who underwent clinical dental examinations. The saliva samples were analysed for total protein, specific cytokines (IL-10, IL-8, IL-6 and TNF- α) and bacteria using Bradford assay, ELISA and quantitative real-time polymerase chain reaction, respectively. Salivary values were analysed according to age, plaque index (PI) and gingival index (GI).

Salivary diagnosis is an emerging field that has progressed through several important developments, including salivary proteome and the development of compact point-of-care devices for rapid analysis. Indeed, an increasing number of salivary markers have been identified; and some have been associated with cancer, cardiovascular diseases, autoimmune diseases, viral and bacterial diseases, and human immunodeficiency. Saliva is frequently studied due to the easy, non-invasive, and rapidly obtained collection, without the need for specialized equipment. Moreover, the prodigious fluid source of saliva provides many, if not most, of the molecules found in the systemic circulation, rendering it a potentially valuable bio-fluid for diagnoses. Several types of inflammatory biomarkers associated with oral diseases, as well as systemic diseases, have been detected in saliva. Cytokines are among the most investigated biomarkers in this context. Due to their involvement in inflammatory, infectious and immunological diseases, cytokines may serve as markers of local oral pathologies such as periodontal disease and carries. Indeed, in adults, evidence shows that such disease can be detected through saliva biomarkers such as interleukins (IL)-1b, -6, -8 and -10), tumor necrosis factor- α (TNF- α) and matrix metalloproteinases (MMP)-8 and -9 in adults. Additionally, as some etiologies of oral pathology as gingivitis include bacterial infection such as Streptococcus, Fusobacterium, Actinomyces, Veillonella, Treponema, Capnocytophaga and Eikenella, saliva may also be used to measure bacterial load. Dental caries is one of the most common childhood diseases worldwide, and is associated with polymicrobial colonization on tooth surfaces. Both acidogenic and aciduric bacteria, such as the Mutans group of Streptococci and Lactobacilli, are primary etiological agents of dental caries. Lactobacilli and S. Mutans are mostly found together in saliva . The diversity of microbes in saliva has been shown to increase in the caries active status. In children with cavitated carious lesions, altered concentrations of the cytokines IL-6 and IL-8 were reported. The objective of this study was to characterize the inflammatory and microbiological profile of the saliva of healthy children, and to associate those levels with clinical diagnosis of caries and gingival disease. Materials and methods Study population The study population comprised 100 participants, born during 2008-2016 (aged 4-12 years at the time of the study). Clinical oral examination Dental examinations were conducted by two dental students using a dental mirror, dental explorer and dental probe, and included the following parameters: * Oral hygiene - measured by the plaque index (PI), as described previously,18 only on buccal surfaces. * Periodontal status - measured by the gingival index (GI), as described previously * Caries status measured by the DMFT/ dmft index (D=decay, M=missing, F=filling; T per tooth) in permanent/ primary dentition . All the values were collected and recorded in a data table. Saliva collection Saliva was collected in a quiet room between 0800 and 1230 hr. The children were asked to collect saliva in their mouths and to spit it into a wide test tube for 3 min. The saliva was immediately stored at 4°C and further kept at -80°C until analysis. Data were collected onto paper charts, which were transferred to a computer program. Bacteria testing Bacterial DNA was extracted from saliva using DNA extraction kit (Qiagen). The DNA was then tested using specific primers for total bacteria: Strep. Mutans, Lactobacillus and Fusobacterium nucleatum using quantitative real-time polymerase chain reaction. Salivary cytokine quantification Salivary levels of human TNF- α, IL-10, IL-8, and IL-6 were measured using ELISA kits according to manufacturer instructions (R\&D systems, Minneapolis, MN, US). The saliva samples were transferred to the periodontal laboratory in Hadassah Ein Kerem Hospital for analysis. The ELISA method works by a cytokine carbonate-specific monoclonal antibody placed in a 96-well plate. After dilution of µL 83 saliva to 10 ml PBS of antibody capture, the active solution is placed with the antibody in the well, and covered overnight at room temperature. Subsequently, we wash with µL 400 (buffer wash) and repeat this step three times. We then block the wells by adding µL 300 diluent reagent for one hour at room temperature, and wash again as described above. We dilute at 100 µL, cover and incubate for 2 hours at room temp. We then rinse again, and add detection antibody at a concentration of 166 µL to 10 ml, cover and incubate for 2 hours. Next, we add biotin-related antibody, followed by HRP-streptavidin conjugate, and TMB as a substrate. The reaction is stopped by acid sulfuric and quantified using 650nm-OD490. Statistical analysis All the experiments were performed in triplicate. The data were stratified according to age, DMF, PI and GI. Three age groups were set according to dental age: primary dentition - ages 0-6 years; mixed dentition - ages 6-11 years; and permanent dentition - above age 11 years. DMFT was stratified by ≤2 and \>2. The PI was stratified by ≤1 and \>1. GI was stratified by equal to zero versus above zero. The data were analysed using a statistical software package (SigmaStat, Jandel Scientific, San Rafael, CA, USA). One-way repeated measure analysis of variance (RM ANOVA) was applied to test the significance of the differences between the treated groups. When significant results were found, inter-group differences were tested for significance using the Student's t-test and the Bonferroni correction for multiple testing. Statistical significance was set at p\<0.05.