Variants in transient receptor potential channels and toll-like receptors modify airway responses to allergen and air pollution: a randomized controlled response human exposure study
Bibliographic record
Abstract
BACKGROUND: Environmental co-exposure to allergen and traffic-related air pollution is common globally and contributes to the exacerbation of respiratory diseases. Individual responses to environmental insults remain variable due to gene-environment interactions. OBJECTIVE: This study examined whether single nucleotide polymorphisms (SNPs) in lung cell surface receptor genes modifies lung function change and immune cell recruitment in allergen-sensitized individuals exposed to diesel exhaust (DE) and allergen. METHODS: In this randomized, double-blinded, four-arm, crossover study, 13 allergen-sensitized participants underwent allergen inhalation challenge following a 2-hour exposure to DE, particle-depleted diesel exhaust (PDDE) or filtered air (FA). Lung function tests and bronchoscopic sample collection were performed up to 48 h after exposures. Transient receptor potential channel (TRPA1 and TRPV1) and toll-like receptor (TLR2 and TLR4) risk alleles were used to construct an unweighted genetic risk score (GRS). Exposure-by-GRS interactions were tested using mixed-effects models. RESULTS: In participants with high GRS, allergen exposure was associated with an increase in airway hyperresponsiveness (AHR) when co-exposed to PDDE (p = 0.03) but not FA or DE. FA and PDDE also were associated with a relative increase in macrophages and decrease in lymphocytes in bronchoalveolar lavage. CONCLUSIONS: TRPs and TLRs variants are associated with increased AHR and altered immune cellularity in allergen-exposed individuals. This effect is blunted by DE exposure, suggesting greater influence of unmeasured gene variants as primary meditators of a particulate-rich co-exposure. TRIAL REGISTRATION: The study was registered with ClinicalTrials.gov on December 20, 2013 (NCT02017431).
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".