Association of Metalloproteinase Gene Polymorphisms with Systemic Sclerosis in the European Caucasian Population
Bibliographic record
Abstract
OBJECTIVE: Systemic sclerosis (SSc) is classified among the complex genetic disorders and is characterized by massive extracellular matrix deposits. These may be due to overactivation of transforming growth factor ss that may be in part a result of abnormal remodeling of extracellular matrix and microfibrils. Metalloproteinases (MMP) are a family of proteolytic enzymes, and MMP 2, 9, and 14 contribute to the degradation of microfibrils. Our aim was to determine whether polymorphisms of the MMP2, MMP9, and MMP14 genes confer susceptibility to SSc in a large population. METHODS: A case-control study was performed in 659 SSc patients and 511 healthy matched controls from a European Caucasian population. Six Tag single-nucleotide polymorphisms (SNP) of the MMP2 gene and 2 SNP of MMP9 and MMP14 genes were genotyped. RESULTS: All SNP were in Hardy-Weinberg equilibrium in the control population. There was no association between the MMP2, MMP9, and MMP14 variants we investigated and SSc for allelic and genotype frequencies. No association was observed for the different subphenotypes of SSc patients. CONCLUSION: Our results in a large cohort of European Caucasian SSc patients do not support that MMP2, MMP9, and MMP14 genes are involved in the genetic background of SSc.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".