Polymorphisms of the <scp>ADAM</scp>33 gene and chronic obstructive pulmonary disease risk: a meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The T1 (rs2280091), S1 (rs3918396) and S2 (rs528557) polymorphisms in a disintegrin and metalloprotease (ADAM33) gene has been implicated in susceptibility of chronic obstructive pulmonary disease (COPD). But, a number of studies have reported inconclusive results. The aim of this study is to investigate the relationship between T1 (rs2280091), S1 (rs3918396) and S2 (rs528557) polymorphisms in ADAM33 gene and COPD risk by meta-analysis. METHODS: We searched PubMed database, Embase database, Chinese National Knowledge Infrastructure database and Wanfang database, covering all studies till September 5, 2012. Statistical analysis was performed using software METAGEN (STATA 12.0) and Revman5.0. RESULTS: A total of 2139 COPD cases and 3765 controls in 10 case-control studies were included in this study. The results showed that S2 (rs528557) and T1 (rs2280091) polymorphisms did not result in an increased or a decreased risk of COPD. The analysis described in this report demonstrated that S1 (rs3918396) polymorphism (GG + AG vs AA) was significantly associated with the total and Asian. Odds ratio (OR)total = 1.27 [95% confidence interval (CI) 1.03-1.56, P = 0.03], ORAsian = 1.44 (95% CI 1.13-1.83, P = 0.003) but not with Caucasians. CONCLUSIONS: This meta-analysis suggested that S1 (rs3918396) polymorphism of ADAM33 is associated with increased risk of COPD in Asian (China) but not in Caucasians. Future studies are needed to validate our conclusions.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.043 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".