QBI Neuroscience Seminar: Human Saliva: Linking Oral Fluids With Systemic Diseases
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- Full Description:
- A/Professor Chamindie Punyadeera
Institute of Health and Biomedical Innovation, Translational Research Institute,
Queensland University of Technology, Brisbane
Title: Human Saliva: Linking Oral Fluids With Systemic Diseases
Abstract: Salivary diagnostics is gaining attention within the medical community, as studies demonstrate that saliva contains virtually all of the same medical diagnostic information as blood. Researchers have also shown changes in salivary hormone and protein levels when a person suffers from a concussion. This happens shortly after head trauma.
It is now becoming evident that there is a strong association between oral and systemic diseases. Inflammation is a key connector between oral disease and systemic diseases. Human saliva functions as a plasma ultra-filtrate and contains 2,340 proteins that are either transported across blood into salivary glands or produced by the salivary glands. The collection of saliva is less invasive compared with taking a blood sample making it very accessible to both patients and clinicians. Saliva is also a medium that is ideal for large population-based screening, potentially providing healthcare systems a more economical approach to detecting heart failure (HF) within the community.
Within our team, we are using saliva as a biological matrix to detect ischemic heart disease and HF. We used AlphaLISAŽ technology to quantify C-Reactive Protein (CRP) levels in saliva samples collected from controls and cardiac patients. The mean CRP levels in saliva collected from controls was 285 pg/mL and in cardiac patients was 1680 pg/mL (p<0.01). Analysis of CRP concentrations in paired serum and saliva samples from cardiac patients gave a positive correlation (r2 = 0.84, p < 0.001). Similarly, salivary NT-proBNP levels in the healthy controls and HF participants were <16 pg/mL and 76.8 pg/mL, respectively. The salivary NT-proBNP immunoassay showed a clinical sensitivity of 82.2% and specificity of 100%, positive predictive value of 100% and negative predictive value of 83.3%, with an overall diagnostic accuracy of 90.6%.
Saliva is in close proximity to head and neck cancers (HNCs), especially oral cavity cancers and by analysing DNA methylation, miRNA and glycosylation changes in saliva samples, we were able to diagnose HNCs. Aberrant changes in DNA methylation and glycosylation are hallmarks of tumour development. Using the promoter DNA methylation of RASSF1α, DAPK1, and p16 we could discriminate a HNC patient group (n = 143) from a control group (n = 31) with 87% specificity and 80% sensitivity (with a Fisher exact test P < .0001). Using a multi-marker logistic regression analysis, a panel of nine miRNA demonstrated a sensitivity of 95% and a specificity of 93% (AUC = 0.98) when discriminating saliva collected from patients (n=100) from saliva from precancer patients (n=29). These data support the scientific notion that saliva is an ideal biological medium to detect both oral and systemic events. Further research is warranted before salivary diagnostics enter routine clinical practice.
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