Using Saliva Analysis for Periodontal Disease Detection

Saliva is a combination of oral fluids, including secretions from salivary glands, bronchial and nasal secretions, serum and blood derivatives from oral wounds, bacteria and bacterial byproducts, viruses, fungi, desquamated epithelial cells, food, cellular components, and gingival crevicular fluid (GCF). The analysis of GCF components in saliva may aid the development of a simple diagnostic test for periodontal diseases.  Analysis of saliva offers some advantages when used for diagnostic purposes. One advantage is that saliva can be easily collected in a noninvasive manner and without the need for special equipment.¹ In addition, salivary analysis may provide a feasible, cost-effective approach for large-scale screening of patients.¹

The inflammatory marker β-glucuronidase (βG) in GCF has been known to identify patients at risk for periodontal diseases. Studies show a strong positive correlation between salivary levels of βG and an increase in attachment loss or probing depth at multiple sites (eg, ≥ four sites with ≥ 5 mm probing depth). The available data provide evidence that increased salivary levels of βG, a GCF marker that has been linked to an increased risk of periodontitis, could be used for diagnostic screening for periodontal conditions.²

Chairside Testing

The typical clinical methods for assessing a patient’s periodontal condition tend to uncover the damage the periodontium has already endured. They reveal disease history, as opposed to disease activity. It is important to find a diagnostic tool that can predict and assess active periodontal diseases. Such methods have already been developed, such as MMP-8 chairside testing that is beneficial during the maintenance phase of periodontal therapy. The analysis of GCF could be used in collaboration with clinical assessments to better examine periodontal disease activity. Select GCF components are proven to act as biomarkers for periodontal diseases, which include host-derived enzymes, host-response modifiers, and tissue breakdown products.³ Collecting GCF and analyzing its composition can help determine periodontal disease activity and predict future disease progression.

Discussing the importance of oral health and educating patients about effective self-care are important tools in preventing periodontal diseases. Additionally, equipping patients with the knowledge to recognize the initial visible changes in the gingiva when periodontal diseases first progress can motivate patients to seek treatment early. Implementing diagnostic techniques—such as chairside GCF testing—during routine checkups can help promote early detection, treatment, and the arrest of periodontitis. Increased flow of GCF can be used as a biomarker in conjunction with traditional diagnostic methods to detect periodontal disease.⁴ In addition, clinicians can utilize biomarker analysis to help customize periodontal treatment and provide individualized recommendations.

References

1. Lamster IB, Ahlo JK. Analysis of gingival crevicular fluid as applied to the diagnosis of oral and systemic diseases. Ann NY Acad Sci.2007;1098: 216­–229.
2. Lamster IB, Oshrain RL, Harper DS, Celenti RS, Hovliaras CA, Gordon JM. Enzyme activity in crevicular fluid for detection and prediction of clinical attachment loss in patients with chronic adult periodontitis: six month results. J Periodontol. 1988;59:516–523.
3. Majeed ZN, Philip K, Alabsi AM, Pushparajan S, Swaminathan D. Identification of gingival crevicular fluid sampling, analytical methods, and oral biomarkers for the diagnosis and monitoring of periodontal diseases: a systematic review. Dis Markers. 2016;2016:1804727.
4. Tsuchida S, Satoh M, Takiwaki M, Nomura F. Current status of proteomic technologies for discovering and identifying gingival crevicular fluid biomarkers for periodontal disease. Int J Mol Sci. 2018;20:86.

This information originally appeared in Rivera M, Apolinar S, Smith M. Gingival crevicular fluid as a biomarker for periodontal disease. Decisions in Dentistry. 2021;7(4):40–43.