Salivary Proteomics & Gene Expression Analysis: Applications in Orthodontics and Oral Health Care Research-A Pilot
Vaibhav Gandhi1, Po-Jung Chen1, Sumit Yadav1
1Department of Growth and Development, College of Dentistry, University of Nebraska Medical Center, Lincoln, NE, USA.
Background:
Advances in analytical techniques, including salivary proteomics and gene expression analysis, have enabled the identification of thousands of proteins and specific genetic markers, providing a comprehensive understanding of salivary composition and its dynamic changes in response to therapeutic interventions.
Objectives:
To conduct the salivary proteomic analyses using the LC-MS/MS method and identify the number of proteins in the whole saliva. This study also assessed the effect of an intraoral vibration device on the expression of specific genes associated with the bone remodeling process.
Design:
This pilot project is a prospective study where salivary samples were assessed at baseline (0 day), Midpoint (15 days), and Endpoint (30 days) following the intervention.
Methods:
This study utilized an intraoral vibration device as a therapeutic intervention to observe the changes in the salivary proteomic analyses using the LC-MS/MS method. Salivary gene expression analysis was conducted for ALPL, OPN, IL1B, IL1RN, IL1R1, TNF alpha, RANKL, and RUNX2 genes.
Results:
A total of 1119 proteins in 1059 clusters at 1 minimum peptide and a 444 proteins in 384 clusters at 2 minimum peptides were identified in saliva. Out of all of the genes included in this experiment, OPN showed significant upward change at mid point (9 fold) (15 days) followed by moving toward the baseline level (2.3-fold) toward the end point (30 days).
Conclusion:
This study highlights the potential of salivary proteomics and gene expression analysis as a promising tool for biomarker discovery, emphasizing the complexity and their variability. Despite of some challenges, the advantages of whole saliva collection and the sensitivity of shotgun proteomics and gene expression analysis support its potential as a high-throughput, practical approach for future applications in the field of oral health care.
