Association of a Functional Polymorphism in the Matrix Metalloproteinase-12 Promoter Region with Systemic Sclerosis in an Italian Population
Bibliographic record
Abstract
OBJECTIVE: To investigate the possible implication of the matrix metalloproteinase-12 (MMP-12) gene in the genetic predisposition to systemic sclerosis (SSc) susceptibility and clinical phenotype. METHODS: The MMP-12 rs2276109 A/G functional polymorphism was selected as a genetic marker and genotyped by polymerase chain reaction-restriction fragment length polymorphism assay in 513 unrelated subjects of Italian white ancestry: 250 patients with SSc [146 limited cutaneous SSc (lcSSc), 104 diffuse cutaneous SSc (dcSSc)] and 263 healthy individuals. RESULTS: A significant difference was observed in MMP-12 rs2276109 genotype distribution between patients with SSc and controls (p = 0.0003), and between lcSSc and dcSSc (p = 0.003). The A allele frequency was significantly higher in patients with SSc than in controls (p = 0.0002), and higher in dcSSc than in lcSSc (p = 0.003). After adjustment for age and sex, the homozygosity for the A allele significantly influenced the predisposition to SSc and to dcSSc (OR 2.44, 95% CI 1.61-3.71, p < 0.0001; OR 4.69, 95% CI 2.36-9.33, p < 0.0001, respectively). A trend toward an association between the AA genotype and lcSSc was observed (p = 0.06). The homozygosity for the A allele was also significantly and independently associated with antitopoisomerase I antibody positivity (OR 6.39, 95% CI 2.18-18.76, p = 0.001) and interstitial lung disease (OR 2.94, 95% CI 1.25-6.95, p = 0.01). CONCLUSION: The MMP-12 rs2276109 gene polymorphism may contribute to susceptibility to SSc, and in particular to dcSSc and pulmonary fibrosis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".