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Record W2315021292 · doi:10.1158/1538-7445.am10-4739

Abstract 4739: Interactions between variants of angiogenesis pathway genes and reflux symptom, BMI, and smoking in esophageal adenocarcinoma susceptibility

2010· article· en· W2315021292 on OpenAlexaff
Rihong Zhai, Feng Chen, Geoffrey Liu, Monica Ter‐Minassian, Li Su, Kofi Asomaning, Zhao‐Xi Wang, Matthew H. Kulke, Xihong Lin, Rebecca S. Heist, Chau‐Chyun Sheu, John C. Wain, Susanne H. Hooshmand, Norman S. Nishioka, David C. Christiani

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineBody mass indexGastroenterologyOdds ratioOncologyPDGFRASingle-nucleotide polymorphismGenotypeGeneBiologyGenetics

Abstract

fetched live from OpenAlex

Abstract Esophageal adenocarcinoma (EA) is a complex malignancy that involves multiple genetic and environmental risk factors. Genetic polymorphisms in angiogenesis pathway, gastroesophageal reflux symptoms (reflux), higher body mass index (BMI), and tobacco smoking have been individually associated with EA development. However, interactions among multiple factors in EA risk have not been well characterized. We conducted a case-only study to investigate gene-environment interactions among 145 functional/tagging SNPs of angiogenesis pathway genes, reflux, smoking, and BMI in 335 patients with EA. We used a two-stage approach to detect interactions: first, we applied random forest (RF) approach to select important interacting markers based on mean decrease in accuracy and mean decrease in GINI index; then we estimated the interaction odds ratios (ORinter) of RF selected interaction markers by case-only logistic regression, adjusting for covariates and false discovery rate (FDR). We identified twelve interaction markers that were significantly associated with EA risk (all FDR_Ps<0.05). Among them, six interaction markers, including reflux*rs2295778 (HIF1AN) (ORinter=2.27; 95% CI, 1.44-3.57), reflux*rs996999 (MMP1) (ORinter=1.80; 95%CI, 1.12-2.89), reflux*rs13337626 (TSC2) (ORinter=2.18; 95%CI, 1.15-4.12), BMI*rs2114039 (PDGFRA) (ORinter=2.06; 95%CI, 1.29-3.30), BMI*rs6554164 (PDGFRA) (ORinter=1.92; 95% CI, 1.20-3.08), and BMI*rs17708574 (PDGFRB) (ORinter=1.89; 95%CI, 1.12-3.18) were significantly associated with increased risk of EA. On the other hand, six interaction markers, including reflux*rs2519757 (TSC1) (ORinter=0.43; 95% CI, 0.21-0.83), smoking*rs2295778 (HIF1AN) (ORinter=0.45; 95%CI, 0.26-0.79), smoking*rs2296188 (FLT1) (ORinter=0.50; 95%CI, 0.28-0.87), BMI*rs2296188 (FLT1) (ORinter=0.41; 95%CI, 0.24-0.73), BMI*rs11941492 (KDR) (ORinter=0.52; 95%CI, 0.32-0.85), and BMI*rs17619601 (FLT1) (ORinter=0.26; 95%CI, 0.09-0.75) were significantly associated with decreased risk of EA. These findings suggest that variants in angiogenesis pathway genes, reflux, smoking, and BMI jointly contribute to EA development through gene-environment interactions. 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 4739.

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)0.002
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.079
GPT teacher head0.414
Teacher spread0.335 · 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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