AUTHOR=Picolo Bianca Uliana , Silva Nathália Rabello , Martins Mário Machado , Almeida-Souza Hebréia Oliveira , de Sousa Letícia Cristina Machado , Polveiro Richard Costa , Goulart Filho Luiz Ricardo , Sabino-Silva Robinson , Alonso-Goulart Vivian , Saraiva da Silva Luciana 

TITLE=Salivary proteomics profiling reveals potential biomarkers for chronic kidney disease: a pilot study

JOURNAL=Frontiers in Medicine

VOLUME=Volume 11 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1302637

DOI=10.3389/fmed.2024.1302637

ISSN=2296-858X

ABSTRACT=IntroductionChronic kidney disease (CKD) is a global public health problem, and the absence of reliable and accurate diagnostic and monitoring tools contributes to delayed treatment, impacting patients’ quality of life and increasing treatment costs in public health. Proteomics using saliva is a key strategy for identifying potential disease biomarkers.MethodsWe analyzed the untargeted proteomic profiles of saliva samples from 20 individuals with end-stage kidney disease (ESKD) (n = 10) and healthy individuals (n = 10) using liquid chromatography–tandem mass spectrometry (LC–MS/MS) to identify potential biomarkers for CKD. A volcano plot was generated using a p-value of ≤0.05 and a fold change (FC) ≥ 2.0. Multivariate analysis was performed to generate the orthogonal partial least squares discriminant analysis (OPLS-DA) model and the variable importance in projection (VIP) scores. The accuracy of candidate biomarker proteins was evaluated using receiver operating characteristic (ROC) curves.ResultsIn total, 431 proteins were identified in the salivary proteomic profile, and 3 proteins were significantly different between the groups: apoptosis inhibitor 5 (API5), phosphoinositide phospholipase C (PI-PLC), and small G protein signaling modulator 2 (Sgsm2). These proteins showed good accuracy based on the ROC curve and a VIP score of >2.0. During pathway enrichment, PI-PLC participates in the synthesis of IP3 and IP4 in the cytosol. Gene ontology (GO) analysis revealed data on molecular functions, biological processes, cellular components, and protein classes.ConclusionWe can conclude that the salivary API5, PI-PLC, and Sgsm2 can be potential biomarker candidates for CKD detection. These proteins may participate in pathways related to renal fibrosis and other associated diseases, such as mineral and bone disorders.