Microbiome Biomarkers for Periodontitis: A Systematic Review and Meta-Analysis of Diagnostic Performance

Periodontitis, a chronic inflammatory disease, poses a significant global health challenge. With projections indicating that severe cases could surge by 44% by 2050, affecting over 1 billion individuals worldwide, the urgency of accurate and early diagnosis cannot be overstated. Traditional diagnostic methods, primarily relying on clinical parameters such as probing pocket depth and radiographic assessment, have inherent limitations. These methods predominantly focus on evaluating the structural damage caused by the disease rather than detecting the active presence of pathogenic bacteria. For instance, pocket probing measures the depth of the space between the gum and tooth, but it fails to provide real-time information about the ongoing infection process, often resulting in delayed diagnosis when substantial tissue destruction has already occurred.

Fig.1 (a) Risk of bias and applicability concerns evaluation for the reviewed studies (PRISMA Framework). (b) Summary of risk of bias and applicability issues (PRISMA). (Dong A., et al., 2025)

The Role of the Oral Microbiome in Periodontitis

The oral cavity harbors a complex and diverse microbiome, consisting of hundreds of bacterial species. In a healthy state, this microbiome maintains a delicate balance. However, in periodontitis, there is a dysbiosis, a shift in the microbial community composition, where pathogenic bacteria gain dominance. Key periodontal pathogens, such as Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola, play crucial roles in the disease process. Porphyromonas gingivalis, for example, produces a variety of virulence factors, including proteases that degrade host tissues and evade the immune response, facilitating the progression of periodontitis. Understanding the composition and dynamics of the oral microbiome is thus essential for developing more effective diagnostic strategies.

Saliva-Based Biomarkers: A Non-Invasive Approach

Saliva offers a convenient and non-invasive source for biomarker discovery in periodontitis diagnosis. Several bacterial species have emerged as promising biomarkers in saliva samples. Porphyromonas gingivalis has demonstrated remarkable diagnostic potential, with a sensitivity of 89.2% and a specificity of 94.6%, translating to an area under the curve (AUC) value above 0.80, which is indicative of excellent diagnostic accuracy. Similarly, Tannerella forsythia shows comparable sensitivity (89.2%) and a high specificity of 86.5%, also achieving a high AUC. Prevotella intermedia has an 86.5% sensitivity and 83.8% specificity, contributing to the pool of salivary biomarkers.

Combining multiple bacterial biomarkers in saliva can further enhance diagnostic performance. For example, a study that investigated 11 subgingival plaque-specific bacteria in saliva achieved a sensitivity of 90.5%, highlighting the synergistic effect of multiple biomarkers. However, not all salivary biomarkers perform equally well; salivary endotoxin, for instance, has shown relatively lower sensitivity at 69%, indicating the need for careful biomarker selection.

Subgingival Plaque Biomarkers: Targeting the Infection Nidus

Subgingival plaque, located in the periodontal pocket, is the epicenter of periodontal infection. Biomarkers derived from this site tend to exhibit higher diagnostic accuracy compared to those in saliva. Endotoxin activity, which measures the presence of bacterial toxins in subgingival plaque, has shown outstanding performance with a sensitivity of 90.6% and a specificity of 87.9%, resulting in an AUC of 0.93. Combinations of bacterial biomarkers also excel in subgingival plaque analysis. Testing for a panel of 5 bacterial species achieved a sensitivity of 85.1% and a perfect specificity of 100%, with an AUC of 0.88.

Treponema denticola, often associated with advanced periodontitis, shows 82% sensitivity and 83% specificity in subgingival samples. Chairside tests (CSTs) that detect multiple periodontal pathogens simultaneously have proven to be highly effective, with a sensitivity of 85% and a specificity of 100%, making them a practical tool for immediate in-office diagnosis.

Comparative Analysis of Biomarkers

Biomarker Type	Sample Source	Sensitivity	Specificity	AUC
Porphyromonas gingivalis	Saliva	89.2%	94.6%	0.92
Endotoxin activity	Subgingival plaque	90.6%	87.9%	0.93
5-bacteria panel	Subgingival plaque	85.1%	100%	0.88
Tannerella forsythia	Saliva	89.2%	86.5%	0.88

This table illustrates the varying performance of different biomarkers. While subgingival plaque biomarkers generally exhibit higher accuracy, saliva-based biomarkers offer the advantage of non-invasiveness, making them suitable for initial screening. Porphyromonas gingivalis stands out as a versatile biomarker with good performance in both sample types.

Clinical Implications and Future Prospects

The integration of oral microbiome biomarkers into clinical practice has the potential to revolutionize periodontitis diagnosis. Dentists could perform quick and accurate tests during routine check-ups, enabling early detection of the disease, even in patients with minimal clinical symptoms. For high-risk patients, such as smokers or those with diabetes, biomarker-based diagnostics can identify subclinical infections, allowing for timely intervention and prevention of disease progression.

However, several challenges need to be addressed for widespread implementation. Standardization of sample collection, processing, and biomarker analysis across different laboratories is crucial. Future research should focus on validating biomarkers in larger, diverse populations, exploring novel biomarker combinations, and developing user-friendly point-of-care testing platforms. Additionally, investigating the role of other components of the oral microbiome, such as bacteriophages and metabolites, could further enhance our understanding of periodontitis pathogenesis and diagnosis.

In conclusion, oral microbiome biomarkers hold great promise in transforming periodontitis diagnosis from a reactive approach based on tissue damage assessment to a proactive, infection-focused strategy. With continued research and development, these biomarkers could become an integral part of routine periodontal care, improving patient outcomes and reducing the global burden of periodontitis.

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Reference

Dong, Anbo, Gordon Proctor, and Svetislav Zaric. "Diagnostic Accuracy of Microbiome‐Derived Biomarkers in Periodontitis: Systematic Review and Meta‐Analysis." Journal of Periodontal Research (2025).