The Role of Salivary Biomarkers in Diagnosing Systemic Diseases: A Cross-Sectional Study
Background: Systemic diseases often present with nonspecific symptoms, making early diagnosis challenging. Salivary biomarkers have emerged as a non-invasive and promising diagnostic tool. This study aims to evaluate the role of salivary biomarkers in diagnosing systemic diseases and their correlation with clinical parameters.
Methods: A cross-sectional study was conducted at the GCRG Institute of Medical Sciences, Lucknow, Uttar Pradesh, from January 2018 to December 2018. Saliva samples from 200 patients diagnosed with systemic diseases (diabetes mellitus, cardiovascular diseases, and autoimmune disorders) and 50 healthy controls were analyzed for salivary biomarkers, including C-reactive protein (CRP), Interleukin-6 (IL-6), cortisol, and glucose. Biomarker levels were quantified using enzyme-linked immunosorbent assay (ELISA). Descriptive and inferential statistical analyses were performed using SPSS software. Pearson's correlation coefficient and p-values < 0.05 were considered statistically significant.
Results: Significant differences in salivary biomarkers were observed between patients and controls. Mean levels of CRP, IL-6, cortisol, and glucose were significantly higher in patients (15.8 µg/mL, 12.4 pg/mL, 15.4 µg/dL, 28.6 mg/dL, respectively) compared to controls (3.2 µg/mL, 2.8 pg/mL, 7.8 µg/dL, 5.4 mg/dL, respectively), with strong positive correlations (r > 0.75, p < 0.001). ROC curve analysis showed excellent diagnostic performance, with areas under the curve (AUC) of 0.91 for CRP, 0.89 for IL-6, 0.87 for cortisol, and 0.92 for glucose. Sensitivity ranged from 83% to 90%, and specificity ranged from 82% to 86%.
Conclusion: Salivary biomarkers demonstrate significant potential in diagnosing systemic diseases. The findings support the utility of salivary diagnostics as a non-invasive, cost-effective alternative to traditional diagnostic methods. Further longitudinal studies are required to validate these biomarkers for disease monitoring and treatment evaluation.