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Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Authors :
Zhiyu Xia
Yu‐Ru Su
Paneen Petersen
Lihong Qi
Andre E. Kim
Jane C. Figueiredo
Yi Lin
Hongmei Nan
Lori C. Sakoda
Demetrius Albanes
Sonja I. Berndt
Stéphane Bézieau
Stephanie Bien
Daniel D. Buchanan
Graham Casey
Andrew T. Chan
David V. Conti
David A. Drew
Steven J. Gallinger
W. James Gauderman
Graham G. Giles
Stephen B. Gruber
Marc J. Gunter
Michael Hoffmeister
Mark A. Jenkins
Amit D. Joshi
Loic Le Marchand
Juan P. Lewinger
Li Li
Noralane M. Lindor
Victor Moreno
Neil Murphy
Rami Nassir
Polly A. Newcomb
Shuji Ogino
Gad Rennert
Mingyang Song
Xiaoliang Wang
Alicja Wolk
Michael O. Woods
Hermann Brenner
Emily White
Martha L. Slattery
Edward L. Giovannucci
Jenny Chang‐Claude
Paul D. P. Pharoah
Li Hsu
Peter T. Campbell
Ulrike Peters
Source :
Cancer Medicine, Vol 9, Iss 10, Pp 3563-3573 (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Abstract Background Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods To improve statistical power and interpretation for gene‐environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype‐Tissue Expression Project for all genes with heritability ≥1%. We used a mixed‐effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI‐CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR

Details

Language :
English
ISSN :
20457634 and 46648933
Volume :
9
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.873e6d162b46648933e4b0b52bd613
Document Type :
article
Full Text :
https://doi.org/10.1002/cam4.2971