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Record W2019671306 · doi:10.1289/ehp.1307459

<i>GSTP1</i> and <i>TNF</i> Gene Variants and Associations between Air Pollution and Incident Childhood Asthma: The Traffic, Asthma and Genetics (TAG) Study

2014· article· en· W2019671306 on OpenAlexaff
Elaina MacIntyre, Michael Bräuer, Erik Melén, Carl Peter Bauer, Mario Bauer, Dietrich Berdel, Anna Bergström, Bert Brunekreef, Moira Chan‐Yeung, Claudia Klümper, Elaine Fuertes, Ulrike Gehring, Anna Gref, Joachim Heinrich, Olf Herbarth, Marjan Kerkhof, Gerard H. Koppelman, Anita L. Kozyrskyj, Göran Pershagen, Dirkje S. Postma, Elisabeth Thiering, Carla M. T. Tiesler, Christopher Carlsten

Bibliographic record

VenueEnvironmental Health Perspectives · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsAsthmaWheezeGSTP1MedicineOdds ratioConfoundingBronchial hyperresponsivenessSingle-nucleotide polymorphismTobacco smokeEnvironmental healthImmunologyInternal medicineGeneticsRespiratory diseaseBiologyGenotypeGene

Abstract

fetched live from OpenAlex

Background: Genetics may partially explain observed heterogeneity in associations between traffic-related air pollution and incident asthma.Objective: Our aim was to investigate the impact of gene variants associated with oxidative stress and inflammation on associations between air pollution and incident childhood asthma.Methods: Traffic-related air pollution, asthma, wheeze, gene variant, and potential confounder data were pooled across six birth cohorts. Parents reported physician-diagnosed asthma and wheeze from birth to 7–8 years of age (confirmed by pediatric allergist in two cohorts). Individual estimates of annual average air pollution [nitrogen dioxide (NO2), particulate matter ≤ 2.5 μm (PM2.5), PM2.5 absorbance, ozone] were assigned to each child’s birth address using land use regression, atmospheric modeling, and ambient monitoring data. Effect modification by variants in GSTP1 (rs1138272/Ala114Val and rs1695/IIe105Val) and TNF (rs1800629/G-308A) was investigated.Results: Data on asthma, wheeze, potential confounders, at least one SNP of interest, and NO2 were available for 5,115 children. GSTP1 rs1138272 and TNF rs1800629 SNPs were associated with asthma and wheeze, respectively. In relation to air pollution exposure, children with one or more GSTP1 rs1138272 minor allele were at increased risk of current asthma [odds ratio (OR) = 2.59; 95% CI: 1.43, 4.68 per 10 μg/m3 NO2] and ever asthma (OR = 1.64; 95% CI: 1.06, 2.53) compared with homozygous major allele carriers (OR = 0.95; 95% CI: 0.68, 1.32 for current and OR = 1.20; 95% CI: 0.98, 1.48 for ever asthma; Bonferroni-corrected interaction p = 0.04 and 0.01, respectively). Similarly, for GSTP1 rs1695, associations between NO2 and current and ever asthma had ORs of 1.43 (95% CI: 1.03, 1.98) and 1.36 (95% CI: 1.08, 1.70), respectively, for minor allele carriers compared with ORs of 0.82 (95% CI: 0.52, 1.32) and 1.12 (95% CI: 0.84, 1.49) for homozygous major allele carriers (Bonferroni-corrected interaction p-values 0.48 and 0.09). There were no clear differences by TNF genotype.Conclusions: Children carrying GSTP1 rs1138272 or rs1695 minor alleles may constitute a susceptible population at increased risk of asthma associated with air pollution.Citation: MacIntyre EA, Brauer M, Melén E, Bauer CP, Bauer M, Berdel D, Bergström A, Brunekreef B, Chan-Yeung M, Klümper C, Fuertes E, Gehring U, Gref A, Heinrich J, Herbarth O, Kerkhof M, Koppelman GH, Kozyrskyj AL, Pershagen G, Postma DS, Thiering E, Tiesler CM, Carlsten C, TAG Study Group. 2014. GSTP1 and TNF gene variants and associations between air pollution and incident childhood asthma: the traffic, asthma and genetics (TAG) Study. Environ Health Perspect 122:418–424; http://dx.doi.org/10.1289/ehp.1307459

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.275
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations83
Published2014
Admission routes1
Has abstractyes

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