Association between matrix metalloproteinase-3 gene polymorphism and susceptibility to chronic periodontitis: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: This study aimed to explore the correlation between the Matrix Metalloproteinase-3 (MMP-3) 1171 5A/6A gene polymorphism and susceptibility to Chronic Periodontitis (CP). Methods: Following the PRISMA guidelines, a systematic search was conducted across four electronic databases (PubMed, Embase, Web of Science, and Cochrane Library) without any time or language limitations. The selection criteria included case-control studies examining the association between the MMP-3 gene polymorphism and CP. The data were independently extracted and cross-checked by two reviewers. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies. Statistical heterogeneity and publication bias were assessed. Results: Five studies, published between 2004 and 2019, met the inclusion criteria for the meta-analysis. No significant association was observed between MMP-3 gene polymorphism and CP susceptibility across all subjects in the four gene models. However, subgroup analysis revealed significant differences based on genotyping methods and smoking habits. Using PCR-RFLP genotyping method, the allele and additive models showed a positive correlation with the risk of CP (5A vs 6A, OR=1.12, 95%CI (1.02č 1.23); 5A5A vs 6A6A, OR=2.85, 95%CI (1.61č4.86)). In contrast, using Sanger sequencing method, the 5A mutation appeared to reduce CP susceptibility (5A vs 6A, OR=0.77, 95%CI (0.67č0.87); 5A5A vs 6A6A, OR= 0.20, 95%CI (0.09č0.42)). Moreover, smoking habits appeared to modulate the risk. Among smokers, the 5A mutation increased susceptibility to CP, while among nonsmokers it decreased. Conclusions: While no significant correlation was found in the overall population, the stratified analysis revealed nuanced relationships contingent on genotyping methods and smoking habits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".