Proteomic and metabolomic profile of saliva related to periodontitis and Gestational Diabetes Mellitus during the 3rd trimester of pregnancy

• Grant number: 22/10292-8
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): September 01, 2023
• Effective date (End): August 31, 2025
• Field of knowledge: Health Sciences - Dentistry - Pediatric Dentistry
• Principal Investigator: Marília Afonso Rabelo Buzalaf
• Grantee: Gerson Aparecido Foratori Junior
• Host Institution: Faculdade de Odontologia de Bauru (FOB). Universidade de São Paulo (USP). Bauru , SP, Brazil

Abstract

Gestational Diabetes Mellitus (GDM) and gestational hormones may have synergistic effects on periodontal tissues. Although there are epidemiological findings linking these outcomes, this association is uncertain and can be misinterpreted due to a variety of confounding factors. In addition, the pathophysiological mechanisms related to the association between GDM and periodontitis must be further investigated. The aim of this study will be to determine the proteomic and metabolomic profile of saliva related to GDM and periodontitis in women during the 3rd trimester of pregnancy. Pregnant women will be divided into: with GDM and periodontitis (GDM-P); with GDM but without periodontitis (GDM-NP); without GDM but with periodontitis (N-P); and without GDM and periodontitis (N-NP). Participants will be matched by age and socioeconomic status. For the grouping, fasting glycemic levels and after 1 and 2 hours of the Oral Glucose Tolerance Test (OGTT) will be evaluated and the full-mouth periodontal examination will be performed. Samples of unstimulated saliva will be collected. For proteomic analysis, saliva samples will be individually evaluated and processed by Mass Spectrometry (Nano Liquid Chromatography Electron Spray Ionization Tandem Mass Spectrometry - nLC-ESI-MS/MS). Difference in the proteins expression between groups will be expressed as p < 0.05 for the down-regulated proteins, and 1-p > 0.95 for the up-regulated proteins. For the metabolomic analysis, saliva samples will be analyzed individually by Nuclear Magnetic Resonance Spectroscopy operating at a proton frequency of 600 MHz. Multivariate analysis will be performed using Partial Least Squares Discriminant Analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA). 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's correlation will be applied between metabolite levels and clinical parameters. Considering the variation in sensitivity and specificity for different cutoff values of the outcomes, the ROC curve will be used to identify the potential of certain metabolites to act as biomarkers. The significance level of 5% will be adopted. The relevance of this work is based on the innovative aspect, considering both the methods of analysis adopted and the potential of the results, which may result in actions aimed at maintaining health in this population. (AU)