Estudo translacional prospectivo de uso da saliva como uma ferramenta de diagnóstico e monitoramento para condições sistêmicas pediátricas

Abstract

Advances have demonstrated that saliva reflects both physiological and pathological conditions, showing promising potential in genetic and molecular aspects for the non-invasive diagnosis and monitoring of systemic conditions. Moreover, saliva presents notable advantages, such as easy, painless, low-cost, and non-invasive collection—especially suitable for pediatric populations. The aim of this study was to assess the stability and variation in salivary inositol levels in children with and without Type 1 Diabetes Mellitus (T1DM), as well as to correlate salivary and urinary fluid profiles with plasma glycemic control parameters in T1DM. Additionally, the study aimed to characterize the salivary proteomic profile of children with Congenital Zika Syndrome (CZS), identifying predictive biomarkers of risk for syndrome progression, in association with phenotypic characteristics. Two clinical, observational, prospective cohort, multicenter, quantitative, descriptive, and analytical studies were conducted. In Study A, 42 children (23 with T1DM and 19 controls), matched for age and sex, were followed semiannually over one year, at three distinct time points: T0, T6, and T12 months. After informed consent, anamnesis, and collection of saliva and urine samples, salivary flow rate and total salivary protein concentration were measured, along with 24-hour urinary volume and urinary creatinine levels. Quantification of compounds was performed using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS): myo-inositol (MI), D-chiro-inositol (DCI), and glucose in both fluids. In Study B, 18 children were enrolled—10 diagnosed with CZS and 8 controls—and followed annually over a three-year period. Annually, participants underwent a collection protocol at timepoints T1, T2, and T3: informed consent, anamnesis, saliva collection, salivary flow measurement, and dental care. Samples underwent extraction, total protein quantification, and mass spectrometry-based proteomic analysis. ProGenesis software was used to identify differentially expressed proteins (DEPs). Data from both studies were tabulated using Microsoft Excel (2019) and analyzed in SPSS, with statistical significance set at p < 0.05. In Study A, significant differences were observed between groups, with reduced salivary flow in the T1DM group (p = 0.004 at T6), higher salivary MI levels in T1DM (T6 p = 0.007; mean across timepoints p = 0.009), and increased MI/DCI salivary ratio in T1DM (T0, p < 0.001; T6, p = 0.001; T12, p = 0.004; mean across timepoints p < 0.001). The MI/DCI ratio was markedly elevated in the T1DM group—up to 2,065 times higher than in controls at T0. All urinary parameters showed significant group differences (p < 0.001). After normalization (saliva by flow rate and total proteins; urine by 24-hour volume and creatinine), all significant findings were maintained at least at one timepoint or across the average of T0–T12. Furthermore, correlations were found between parameters in saliva and urine. In T1DM, a significant correlation between DCI levels in both fluids (mean of T0–T12; p = 0.020; rho = –0.613), and between salivary and urinary MI/DCI ratios at T6 (p = 0.037; rho = 0.900) was observed. After normalization, further significant correlations in the T1DM group were found involving DCI (p = 0.006, rho = –0.692; p = 0.008, rho = –0.720), MI/DCI ratio (p = 0.037, rho = –0.900), and glucose (p = 0.002, rho = 0.725; p = 0.001, rho = 0.688). Additionally, a significant inverse correlation was observed between HbA1c and the MI/DCI ratio (p = 0.002; rho = –0.752), also maintained after normalization by salivary flow (p = 0.013; rho = –0.642) and total proteins (p = 0.008; rho = –0.722), highlighting the MI/DCI ratio’s potential as a glycemic control marker. In Study B, a total of 491 proteins were identified, with 32 DEPs in T1, 34 in T2, and 47 in T3 from salivary proteomic analysis. Nine DEPs stood out in the CZS group for being present in at least two of the three timepoints analyzed. STRING network and cluster/reactome analyses identified 5 functional clusters in T1, 3 in T2, and 6 in T3. These clusters included proteins involved in immune response, production of reactive oxygen species (ROS), muscle contraction, regulation of glycolysis/gluconeogenesis, and epigenetic modifications. Longitudinal analysis confirmed, through two clusters from T1–T2 and three from T2–T3, the progression toward an adaptive immune response. In conclusion, the MI/DCI ratio emerged as a converging parameter across salivary and urinary fluids, with potential utility as a monitoring tool for T1DM. Additionally, the salivary proteomic profile revealed a scenario of persistent hyperinflammation in CZS, likely modulated by long-term inflammatory and epigenetic alterations, which may contribute to the onset or worsening of neurological damage—ranging from neuronal apoptosis to autoimmune-mediated hyperinflammation.