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Record W2322175913 · doi:10.1158/1538-7445.am10-937

Abstract 937: Nicotinic acetylcholine receptor polymorphisms, secondhand smoke and lung cancer risk

2010· article· en· W2322175913 on OpenAlexaff
Kofi Asomaning, Rihong Zhai, Chau‐Chyun Sheu, Rebecca S. Heist, Feng Chen, Geoffrey Liu, Li Su, Xihong Lin, David C. Christiani

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsLung cancerSingle-nucleotide polymorphismMedicinePopulationMinor allele frequencyOncologyInternal medicineGeneticsEnvironmental healthBiologyGenotype

Abstract

fetched live from OpenAlex

Abstract Introduction: Passive or secondhand smoke (SHS) exposure is an independent risk factor for adult non-small cell lung cancer (NSCLC). In 2008, three genome wide association studies (GWAS) identified a locus on chromosome region 15q24-25.1 that was strongly associated with lung cancer. In this study, we assessed the interaction of the two most significant single nucleotide polymorphisms (SNPs) reported (rs8034191, rs1051730) with SHS on lung cancer risk. We hypothesize that after adjusting for active cigarette smoking, individuals with the risk alleles and the highest cumulative exposure to SHS are at the greatest risk of lung cancer. Methods: This study population is derived from a large ongoing case control study evaluating the molecular epidemiology of lung cancer, which began in 1992 at the Massachusetts General Hospital. The polymorphisms were genotyped by the 5V nuclease assay (Taqman) using the ABI Prism 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA). Interviewer-administered questionnaires collected information on demographics, and detailed smoking histories from each subject. Second hand smoke exposure duration and frequency was self-reported for three different activities (leisure, work and at home). The cumulative SHS exposure was the sum of all durations multiplied by their frequency weight. We used the co-dominant genetic model for individual SNPs, controlling for age, gender, pack years, years since smoking cessation and smoking status. We tested for interaction using the Likelihood Ratio Test by incorporating cross product interaction terms of indicator variables for each SNP and quartiles of cumulative exposure. Results: A total of 2071 cases and 1506 controls were analyzed. Among cases, exposure to SHS at home 1924(93%), work 1727 (83%), leisure 1791 (86%); among controls 1328 (88%), 1044 (69%) and 1233 (82%) respectively. In stratified analysis, for study participants in the highest quartile of cumulative SHS exposure and comparing the homozygous variant to the wildtype, the adjusted odds ratio (AOR) for lung cancer was 1.55 (0.99-2.44) (rs8034191) and 1.66 (1.05-2.62) (rs1051730). In the lowest quartile of SHS exposure the corresponding results were 0.94 (0.47-1.89) (rs8034191) and 0.91(0.45-1.84) (rs1051730). There was no evidence for gene-SHS interaction. Conclusion: Our results indicate that secondhand smoke does not modify the association of rs1051730 and rs8034191 with non-small cell lung cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 937.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.082
GPT teacher head0.440
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes1
Has abstractyes

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