Alarm anti-protease trappin-2 negatively correlates with proinflammatory cytokines in patients with periodontitis

Investigating the diagnostic potential of IL-1β, IL-10, and IL-36γ in gingival crevicular fluid in patients with different periodontal conditions

BACKGROUND

The study aimed to analyze cytokine levels, including interleukin (IL)-1β, IL-10, and IL-36γ, to investigate the link between pro- and anti-inflammatory responses in periodontal conditions and assess their potential as diagnostic biomarkers for distinguishing between different types of periodontal conditions.

METHODS

80 systemically healthy non-smokers (25 periodontally healthy, 25 with gingivitis, 30 with periodontitis) were included. Clinical periodontal parameters were recorded, and gingival crevicular fluid (GCF) samples were obtained. Receiver operating characteristic (ROC) curve analysis was applied to determine the diagnostic value of cytokines.

RESULTS

IL-36γ had the highest sensitivity for diagnosing periodontitis, although its specificity for identifying those without periodontitis was relatively low. The combination of IL-1β and IL-36γ was the most effective in differentiating periodontitis from periodontal health. IL-10 was found to be an acceptable discriminator for distinguishing gingivitis from healthy conditions. However, its sensitivity and specificity for identifying gingivitis were lower. The combination of the three cytokines showed the highest ability to distinguish between periodontitis and gingivitis.

CONCLUSION

The levels of IL-1β, IL-10, and IL-36γ in GCF may provide insights into periodontal health and disease status. Further studies are needed to validate these results and explore the potential of these cytokines in periodontal disease management.

Probing the salivary proteome for prognostic biomarkers in response to non-surgical periodontal therapy

AIM

This prospective study investigated the salivary proteome before and after periodontal therapy.

MATERIALS AND METHODS

Ten systemically healthy, non-smoking, stage III, grade C periodontitis patients underwent non-surgical periodontal treatment. Full-mouth periodontal parameters were measured, and saliva (n = 30) collected pre- (T0), and one (T1) and six (T6) months post-treatment. The proteome was investigated by label-free quantitative proteomics. Protein expression changes were modelled over time, with significant protein regulation considered at false discovery rate <0.05.

RESULTS

Treatment significantly reduced bleeding scores, percentages of sites with pocket depth ≥5 mm, plaque and gingival indexes. One thousand seven hundred and thirteen proteins were identified and 838 proteins (human = 757, bacterial = 81) quantified (≥2 peptides). At T1, 80 (T1 vs. T0: 60↑:20↓), and at T6, 118 human proteins (T6 vs. T0: 67↑:51↓) were regulated. The salivary proteome at T6 versus T1 remained stable. Highest protein activity post- versus pre-treatment was observed for cellular movement and inflammatory response. The small proline-rich protein 3 (T1 vs. T0: 5.4-fold↑) and lymphocyte-specific protein 1 (T6 vs. T0: 4.6-fold↓) were the top regulated human proteins. Proteins from Neisseria mucosa and Treponema socranskii (T1 vs. T0: 8.0-fold↓, 4.9-fold↓) were down-regulated.

CONCLUSIONS

Periodontal treatment reduced clinical disease parameters and these changes were reflected in the salivary proteome. This underscores the potential of utilizing saliva biomarkers as prognostic tools for monitoring treatment outcomes.

Salivary secretory leukocyte protease inhibitor levels in patients with stage 3 grade C periodontitis: a comparative cross-sectional study

Secretory leukocyte protease inhibitor (SLPI) is an anti-protease that protects mucosal tissue integrity owing to its anti-microbial and immunomodulatory properties. This study aimed to investigate SLPI levels in periodontal diseases, and analyze the potential correlation with clinical periodontal parameters. Whole saliva samples were obtained from healthy (n = 24), gingivitis (n = 24) and patients with stage 3 grade C periodontitis (n = 24). SLPI was measured by ELISA and normalized by total protein. Receiver operating characteristics (ROC) curve was used for estimating the area under the curve (AUC). The normalized SLPI levels were significantly reduced in periodontitis compared with gingivitis (4.84-fold) or health (1.83-fold) and negatively correlated with periodontal parameters. The ROC curves showed a good predictor value of the SLPI for differentiation of periodontitis versus health or gingivitis (AUC ≥ 0.80). This study demonstrates that the levels of SLPI are high in periodontal health, further elevated in gingivitis, but eventually decreased in severe periodontitis beyond the former two states. This observation may have broader implications in the context of inflammatory diseases affecting the oral mucosa, as it shows that the bacterial burden is disturbing the homeostatic balances of anti-microbial and anti-protease factors in the oral cavity.

Evaluation of salivary biomarkers for the diagnosis of periodontitis

Background

Salivary interleukin (IL)-1β, matrix metalloproteinase (MMP)-8, pyridinoline cross-linked carboxyterminal telopeptide of type I collagen (ICTP) and Porphyromonas gingivalis (Pg) are related to periodontitis. This study aimed to investigate the diagnostic potential of these biomarkers and to build a prediction panel for diagnosing periodontal disease.

Methods

A total of 80 participants were enrolled in a cross-sectional study and divided into healthy (n = 25), gingivitis (n = 24), and periodontitis (n = 31) groups based on their periodontal exam results. A full mouth periodontal examination was performed and unstimulated saliva was collected. Salivary IL-1β, MMP-8, ICTP, and Pg were assessed using enzyme-linked immunosorbent assay (ELISA) and quantitative real time PCR (qPCR). Their potentials for diagnosing periodontal disease were analyzed and combined prediction panels of periodontal disease were evaluated.

Results

As a single marker, IL-1β showed the best diagnostic value of the four markers evaluated and exhibited an area under the curve (AUC) value of 0.88 with 90% sensitivity and 76% specificity for discriminating periodontitis subjects from healthy subjects, an AUC value of 0.80 with 83% sensitivity and 76% specificity for discriminating gingivitis subjects from healthy subjects and an AUC value of 0.66 with 68% sensitivity and 64% specificity for differentiating periodontitis subjects from gingivitis subjects. The combination of IL-1β, ICTP, and Pg exhibited the highest efficacy for discriminating periodontitis subjects from healthy subjects (AUC = 0.94) and gingivitis subjects (AUC = 0.77). The combination of IL-1β and MMP-8 exhibited the best ability to discriminate gingivitis from healthy subjects (AUC = 0.84).

Conclusions

Salivary IL-1β, MMP-8, ICTP, and Pg showed significant effectiveness for diagnosing periodontal disease. The combination of IL-1β, ICTP, and Pg can be used to discriminate periodontitis subjects from healthy subjects and gingivitis subjects, and the combination of IL-1β and MMP-8 can be used to discriminate gingivitis subjects from healthy subjects.

Validation and verification of predictive salivary biomarkers for oral health

Oral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for gingivitis and periodontitis, which are major oral health threats, affecting the gums. These need to be verified and validated for their potential use as differentiators of health, gingivitis and periodontitis status, before they are translated to chair-side for diagnostics and personalized monitoring. We aimed to measure 10 candidates using high sensitivity ELISAs in a well-controlled cohort of 127 individuals from three groups: periodontitis (60), gingivitis (31) and healthy (36). The statistical approaches included univariate statistical tests, receiver operating characteristic curves (ROC) with the corresponding Area Under the Curve (AUC) and Classification and Regression Tree (CART) analysis. The main outcomes were that the combination of multiple biomarker assays, rather than the use of single ones, can offer a predictive accuracy of > 90% for gingivitis versus health groups; and 100% for periodontitis versus health and periodontitis versus gingivitis groups. Furthermore, ratios of biomarkers MMP-8, MMP-9 and TIMP-1 were also proven to be powerful differentiating values compared to the single biomarkers.

Salivary Total Protease Activity Based on a Broad-Spectrum Fluorescence Resonance Energy Transfer Approach to Monitor Induction and Resolution of Gingival Inflammation

OBJECTIVE

Salivary total protease and chitinase activities were measured by a broad-spectrum fluorescence resonance energy transfer approach as predictors of induction and resolution of gingival inflammation in healthy individuals by applying an experimental human gingivitis model.

METHODS

Dental biofilm accumulated (21 days, Induction Phase) by omitting oral hygiene practices followed by a 2-week Resolution Phase to restore gingival health in an experimental gingivitis study. Plaque accumulation, as assessed by the Turesky Modification of the Quigley-Hein Plaque Index (TQHPI), and gingival inflammation, assessed using the Modified Gingival Index (MGI), scores were recorded and unstimulated saliva was collected weekly. Saliva was analysed for total protein, albumin, total protease activity and chitinase activity (n = 18).

RESULTS

The TQHPI and MGI scores, as well as total protease activity, increased until day 21. After re-establishment of oral hygiene, gingival inflammation levels returned to values similar to baseline (day 0). Levels of protease activity decreased significantly, but not to baseline values. Furthermore, 'fast' responders, who responded immediately to plaque, exhibited significantly higher proteolytic activity throughout the experimental course than 'slow' responders, who showed a lagged inflammatory response.

CONCLUSION

The results indicate that differential inflammatory responses encompass inherent variations in total salivary proteolytic activities, which could be further utilised in contemporary diagnostic, prognostic and treatment modalities for periodontal diseases.

Saliva proteomics updates in biomedicine

In the years of personalized (or precision) medicine the 'omics' methodologies in biomedical sciences-genomics, transcriptomics, proteomics and metabolomics-are helping researchers to detect quantifiable biological characteristics, or biomarkers, that will best define the human physiology and pathologies. Proteomics use high throughput and high efficiency approaches with the support of bioinformatic tools in order to identify and quantify the total protein content of cells, tissues or biological fluids. Saliva receives a lot of attention as a rich biological specimen that offers a number of practical and physiological advantages over blood and other biological fluids in monitoring human health. The aim of this review is to present the latest advances in saliva proteomics for biomedicine.