Genetic variants of microsomal epoxide hydrolase and glutamate-cysteine ligase in COPD
Bibliographic record
Abstract
The genetic factors that contribute to the development of chronic obstructive pulmonary disease (COPD) are poorly understood. Many candidate genes have been proposed, including enzymes that protect the lung against oxidative stress, such as microsomal epoxide hydrolase (EPHX1) and glutamate-cysteine ligase (GCL). To date, most reported findings have been for EPHX1, particularly in relation to functional variants associated with fast and slow metabolism of epoxide intermediates. The present study aimed to identify any association of variation in these genes with COPD susceptibility or severity. In total, 1,017 white COPD patients and 912 nondiseased age and sex matched smoking controls were genotyped for six single nucleotide polymorphisms (SNPs) in EPHX1 (including the fast and slow variants and associated haplotypes), and eight SNPs in the two genes encoding GCL. GCL is a rate-limiting enzyme in the synthesis of glutathione, a major contributor to anti-oxidant protection in the lung. No association of variation was found in EPHX1 or GCL with susceptibility to COPD or disease severity. This is the largest reported study to date and is well powered to detect associations that have been previously suggested. The current data indicate that these genetic variants are unlikely to be related to susceptibility or disease severity in white chronic obstructive pulmonary disease patients.
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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 | 0.000 | 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) | 0.002 | 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".