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


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 <0.2. RESULTS:Among 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10-5 ), PSMC5 (P = 4.51 × 10-4 ) and CD33 (P = 2.71 × 10-4 ) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10-5 ) and SCN1B (P = 2.76 × 10-4 ) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10-5 ). CONCLUSIONS:Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

SUBMITTER: Xia Z 

PROVIDER: S-EPMC7221445 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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

Xia Zhiyu Z   Su Yu-Ru YR   Petersen Paneen P   Qi Lihong L   Kim Andre E AE   Figueiredo Jane C JC   Lin Yi Y   Nan Hongmei H   Sakoda Lori C LC   Albanes Demetrius D   Berndt Sonja I SI   Bézieau Stéphane S   Bien Stephanie S   Buchanan Daniel D DD   Casey Graham G   Chan Andrew T AT   Conti David V DV   Drew David A DA   Gallinger Steven J SJ   Gauderman W James WJ   Giles Graham G GG   Gruber Stephen B SB   Gunter Marc J MJ   Hoffmeister Michael M   Jenkins Mark A MA   Joshi Amit D AD   Le Marchand Loic L   Lewinger Juan P JP   Li Li L   Lindor Noralane M NM   Moreno Victor V   Murphy Neil N   Nassir Rami R   Newcomb Polly A PA   Ogino Shuji S   Rennert Gad G   Song Mingyang M   Wang Xiaoliang X   Wolk Alicja A   Woods Michael O MO   Brenner Hermann H   White Emily E   Slattery Martha L ML   Giovannucci Edward L EL   Chang-Claude Jenny J   Pharoah Paul D P PDP   Hsu Li L   Campbell Peter T PT   Peters Ulrike U  

Cancer medicine 20200324 10


<h4>Background</h4>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.<h4>Methods</h4>To improve statistical power and interpretation for gene-environment interaction (G × E) testing, we tested genetic variants t  ...[more]

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