Abstract 2195: Genome-wide interaction analyses between genetic variants and alcohol consumption and risk of colorectal cancer
Notice bibliographique
Résumé
Abstract Genome-wide association studies (GWAS) have successfully identified numerous genetic loci for colorectal cancer. However, GWAS loci explain only a subset of the estimated heritability and interactions with environmental risk factors have been discussed as a potential source of the missing heritability. To explore this further we conducted a genome-wide interaction analyses between genetic variants and alcohol consumption, a frequently observed risk factor for colorectal cancer. We included 8,058 cases and 8,765 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium. Individual-level alcohol consumption data were harmonized across studies and participants were grouped as nondrinkers (drinking < 1 g of alcohol per day); light-moderate drinkers (drinking 1-28 g of alcohol per day); and heavy drinkers (drinking >28 g of alcohol per day). We used standard logistic regression (including an interaction term) and our newly developed Cocktail method, which includes a screening step based on: a) marginal associations between genetic variants and colorectal cancer and b) correlation between genetic variants and an environmental factor, followed by a testing step for interactions while correcting for multiple testing using weighted hypothesis testing. As the association between alcohol intake and colorectal cancer was inverse in light/moderate drinkers (OR=0.91, P=0.005) but positive in heavy drinkers (OR=1.22, P=0.0005) compared with non-drinkers, we conducted the interaction analyses separately. Using standard logistic regression to test for interaction, we identified two potential novel loci associated with colorectal cancer, 9q22.32/FBP1 (the most significant SNP rs9409565 with PG×E =1.76×10-8) and 11q22.1/CNTN5 (the most significant SNP rs6590690 with PG×E=4.95×10-8). At 9q22.32/FBP1, the common allele of rs9409565 was associated with decreased risk of colorectal cancer in all nondrinkers (OR=0.87, 95% Confidence interval [CI] 0.82-0.99, P=6.4×10-6) but was associated with increased risk in all light-moderate drinkers (OR=1.16, 95% CI 1.10-1.22, P=8.2×10-8). Similarly, at 11q22.1/CNTN5 the common allele of rs6590690 was associated with reduced risk of colorectal cancer in all nondrinkers (OR=0.76, 95% CI 0.69-0.85, P=1.2×10-6) but with increased risk in light-moderate drinkers (OR=1.32, 95% CI 1.20-1.45, P=2.5×10-8). We did not find any interaction for heavy drinkers; however, only 12 % of the participants were heavy drinkers thus limiting power. We also did not find genome-wide significant interactions using the Cocktail method. FBP1 functions as a tumor suppressor and has been shown to be involved in gastric, liver and colon carcinogenesis. Our findings demonstrate the utility of genome-wide gene-environmental interaction analyses to identify novel interactions in colorectal cancer, contributing to our understanding of colorectal cancer etiology. Citation Format: Jian Gong, Carolyn Hutter, Jenny Chang-Claude, Polly Newcomb, Sonja Berndt, Hermann Brenner, Andrew T. Chan, Loic Le Marchand, Tabitha Harrison, Yi Lin, Martha L. Slattery, Emily White, John Potter, Shuo Jiao, Mathieu Lemire, Li Hsu, Ulrike Peters. Genome-wide interaction analyses between genetic variants and alcohol consumption and risk of colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2195. doi:10.1158/1538-7445.AM2014-2195
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,007 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».