Tobacco smoke induces changes in IL-1 family in bronchial epithelial cells obtained from asthmatic individuals
Bibliographic record
Abstract
Exposure to tobacco smoke (ETS) induces epigenetic modifications including DNA methylation [ 1 ]. In asthma, it has been shown that those modifications affect immune cell differentiation by downregulating expression of specific pro-inflammatory cytokines [ 2 – 4 ]. Interleukin 1 (IL-1) is recognized to be increased in asthma [ 5 ] and by cigarette smoke [ 5 , 6 ]. Based on previous genetic association [ 7 , 8 ] and DNA methylation signature of receptors in asthma and/or atopy the aim of this study is to evaluate the changes in expression and methylation pattern induced by ETS for IL-1 subunit alpha ( IL-1A ) and beta ( IL-1B ), receptors type I ( IL-1R1 ), type II ( IL-1R2 ) and antagonist ( IL-1RA ) and for interleukin 33 ( IL-33 ) in lung tissue. Primary epithelium cells isolated from bronchial biopsies of mild asthmatics and non-asthmatics individuals were exposed to whole tobacco smoke according to method described [ 9 ]. Level of mRNA was measured by qRT-PCR and methylation was assessed by bis-pyrosequencing for IL-1A , IL-1B , IL-1R1 , IL-1R2 , IL-1RA and IL-33 . ETS increased mRNA level of IL-1A and IL-1B in both asthmatic and non-asthmatic individuals. IL-33 showed a significant decrease in gene expression following ETS in asthmatic individuals but not in non-asthmatics . IL-1R1 was decreased in non-asthmatic individuals but no change was observed in asthmatics. IL-1R2 and IL-1RA increased in both asthmatic and non-asthmatic individuals. We observed DNA methylation differences in IL-1R1 promoter between ETS and non-ETS cells. Modifications of genes expression induced by tobacco smoke could modify IL-1 family resulting in an increase of inflammation in lung tissues of asthmatic and non-asthmatic individuals. These changes may be induced by DNA methylation. Efforts to better interpret and integrate data from genetics and epigenetics are needed to better understand the biology of asthma as well as a better comprehension of the impact of tobacco smoke in the inflammatory component of asthma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".