Analysis of the salivary proteomic and metabolomic profile during pregnancy

• Grant number: 24/07973-9
• Support Opportunities: Regular Research Grants
• Start date: March 01, 2025
• End date: February 28, 2027
• Field of knowledge: Health Sciences - Dentistry - Pediatric Dentistry
• Principal Investigator: Marília Afonso Rabelo Buzalaf
• Grantee: Marília Afonso Rabelo Buzalaf
• Host Institution: Faculdade de Odontologia de Bauru (FOB). Universidade de São Paulo (USP). Bauru , SP, Brazil
• Associated researchers: Gerson Aparecido Foratori Junior ; Tatiana Kelly da Silva Fidalgo

Abstract

Obesity, Gestational Diabetes Mellitus (GDM) and pregnancy hormones may have synergistic effects on periodontal tissues. Although there are epidemiological findings that associate these outcomes, this association is uncertain and may be misinterpreted due to a variety of confounding factors. Furthermore, the pathophysiological mechanisms related to the association between obesity or GDM with gingivitis or periodontitis, respectively, should be further investigated. The objectives of this proposal are divided into two axes: 1) Evaluate salivary proteins and metabolites associated with periodontitis and Gestational Diabetes Mellitus in women during the 3rd trimester of pregnancy; 2) Evaluate salivary proteins associated with gingivitis and obesity in women during the 3rd trimester of pregnancy. In axis 1, pregnant women will be divided into: with GDM and periodontitis (GDM-P); with GDM but without periodontitis (GDM-WP); no GDM but with periodontitis (N-P); and no GDM and no periodontitis (N-WP). Samples of whole-mouth unstimulated saliva will be collected and submitted to proteomic analysis by Mass Spectrometry (nLC-ESI-MS/MS) and metabolomics by Nuclear Magnetic Resonance Spectroscopy operating at a proton frequency of 500 MHz. In axis 2, pregnant women will be divided into: with obesity and excessive Gingival Bleeding (GB) (G1 = BMI e 30 kg/m2; GB > 50%); with obesity, but without gingivitis (G2 = BMI e 30 kg/m2; GB < 10%); with normal BMI, but with excessive GB (G3 = BMI 18.5-24.99 kg/m2; GB > 50%); with normal BMI and no gingivitis (G4 = BMI 18.5-24.99 kg/m2; GB < 10%). Samples of unstimulated saliva will be collected and submitted to proteomic analysis by Mass Spectrometry (nLC-ESI-MS/MS). The difference in protein expression between groups will be expressed as p < 0.05 for downregulated proteins, and 1-p > 0.95 for upregulated proteins. In the metabolomic analysis, multivariate analysis will be performed using Partial Least Squares Discriminant Analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA). The Variable Importance in Projection (VIP) scores will be used for multivariate analysis of the metabolites. After data normalization, univariate analysis will be performed using ANOVA and Pearson correlation will be applied between metabolite levels and clinical parameters. Considering the variation in sensitivity and specificity for different cutoff values of the outcomes studied, the ROC curve will be used to identify the potential of certain metabolites to act as biomarkers. A significance level of 5% will be adopted. The relevance of this work is based on the innovative aspect, considering both the analysis methods adopted and the potential results, which could result in actions aimed at maintaining health in this population. (AU)