Associations of IL6 polymorphisms with lung function decline and COPD
Bibliographic record
Abstract
BACKGROUND: Interleukin-6 (IL6) is a pleiotropic pro-inflammatory and immunomodulatory cytokine which probably plays an important role in the pathogenesis of chronic obstructive pulmonary disease (COPD). There is a functional single nucleotide polymorphism (SNP), -174G/C, in the promoter region of IL6. It was hypothesised that IL6 SNPs influence susceptibility for impaired lung function and COPD in smokers. METHODS: Seven and five SNPs in IL6 were genotyped in two nested case-control samples derived from the Lung Health Study (LHS) based on phenotypes of rate of decline of forced expiratory volume in 1 s (FEV(1)) over 5 years and baseline FEV(1) at the beginning of the LHS. Serum IL6 concentrations were measured for all subjects. A partially overlapping panel of nine IL6 SNPs was genotyped in 389 cases of COPD from the National Emphysema Treatment Trial (NETT) and 420 controls from the Normative Aging Study (NAS). RESULTS: In the LHS, three IL6 SNPs were associated with decline in FEV(1) (0.023< or =p< or =0.041 in additive models). Among them, the IL6_-174C allele was associated with a rapid decline in lung function. The association was more significant in a genotype-based analysis (p = 0.006). In the NETT-NAS study, IL6_-174G/C and four other IL6 SNPs, all of which are in linkage disequilibrium with IL6_-174G/C, were associated with susceptibility to COPD (0.01< or =p< or =0.04 in additive genetic models). CONCLUSION: The results suggest that the IL6_-174G/C SNP is associated with a rapid decline in FEV(1) and susceptibility to COPD in smokers.
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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 | 0.000 | 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 | 0.001 |
| 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".