The role of matrix metalloproteinase polymorphisms in the rate of decline in lung function
Bibliographic record
Abstract
The matrix metalloproteinases (MMPs) comprise a family of at least 20 proteolytic enzymes that play an essential role in tissue remodeling. MMP1 (interstitial collagenase), MMP9 (gelatinase B) and MMP12 (macrophage elastase) are thought to be important in the development of emphysema. A number of naturally occurring polymorphisms of human MMP gene promoters have been identified and found to alter transcriptional activity. Additionally, we detected a novel polymorphism in the MMP12 coding region (Asn357Ser). The aim of this study was to investigate the role of MMP polymorphisms in the development of chronic obstructive lung disease. We determined the prevalence of these polymorphisms in 590 continuing smokers chosen from the National Heart Lung and Blood Institute, Lung Health Study for having the fastest (n = 284) and slowest (n = 306) 5 year rate of decline of lung function. Of the five polymorphisms, only G-1607GG was associated with a rate of decline in lung function. The -1607GG allele was associated with a fast rate of decline (P = 0.02) [corrected]. However, haplotypes consisting of alleles from the MMP1 G-1607GG and MMP12 Asn357Ser polymorphisms were associated with rate of decline of lung function (P = 0.0007). These data suggest that polymorphisms in the MMP1 and MMP12 genes, but not MMP9, are either causative factors in smoking-related lung injury or are in linkage disequilibrium with causative polymorphisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".