Reliability of oral biomarkers in the prediction and diagnosis of periodontal disease.
Majeed. Zeyad Nazar ZN; Alabsi. A M AM; Philip. Koshy K; Swaminathan. Dasan D
Key Findings
- MMP‑8, IL‑1β, PGE2 and IL‑6 in gum fluid correlate best with gum disease severity
- A combined Cumulative Risk Score using three biomarkers predicts disease 2‑3 times better than any single marker
- LL‑37 was measured but did not emerge as a top predictor
Practical Outcomes
- For biohackers interested in oral health, focus on monitoring inflammation‑related markers rather than LL‑37. Using a multi‑marker test or risk score could give a clearer picture of periodontal risk, but the study doesn’t provide a direct treatment protocol.
Summary
The study looked at several substances in gum fluid to see which best predict gum disease. It found that enzymes and inflammation signals (MMP‑8, IL‑1β, PGE2, IL‑6) were the strongest clues, while the peptide LL‑37 was less useful on its own. Combining three markers into a risk score improved accuracy.
Abstract
Research has been intensive on the possibility of using the ideal oral fluids in the prediction and diagnosis of periodontal disease. This study aimed to detect the most accurate biomarkers that can be used to predict and diagnose periodontal disease. Gingival crevicular fluid (GCF) and subgingival plaque samples were collected. The levels of biomarkers ( Human Cathelicidine LL-37 (LL-37), Matrix Metalloproteinase -8 (MMP-8), Matrix Metalloproteinase -9 (MMP-9), interleukin (IL)-6, interleukin (IL)-1β, tumour necrosis factor-α (TNF-α), osteoprotegerin (OPG), OC and PGE2) were quantified by Enzyme-Linked Immunosorbent Assay (ELISA), while the subgingival periodontal pathogens (<i>T. forsythia, T. denticola, P. gingivalis</i> and <i>A.a</i>) were identified using Real-time Polymerase Chain Reaction (RT-PCR). Cumulative Risk Score (CRS), a new statistical approach, was used to evaluate the accuracy of applying oral biomarkers in the diagnosis of periodontal disease based on three selected biomarkers. The results of this study showed that MMP-8, IL-1β, PGE2 and IL-6 in GCF are associated with increased count of periodontal pathogens and different clinical periodontal parameters when compared to the other biomarkers. This association increased significantly by using CRS, which had 2 to 3 times higher odds ratios than the use of any selected biomarkers alone. In conclusion, this study showed that the levels of biomarkers in the GCF, mainly MMP-8, IL-1β, PGE2 and IL-6, if used separately, could be useful in the prediction and diagnosis of periodontal disease to a certain degree of accuracy. The study also showed that the combination of three GCF biomarkers in a single biomarker package to establish the CRS index is more precise in the prediction and diagnosis of periodontal disease than the use of other biomarkers.
Study Information
pubmed
2025
2025-09-26T00:00:00.000Z
10.4103/jomfp.jomfp_5_25
35