Dataset Information

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

ABSTRACT: Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

SUBMITTER: Figueiredo JC

PROVIDER: S-EPMC3990510 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Figueiredo Jane C JC Hsu Li L Hutter Carolyn M CM Lin Yi Y Campbell Peter T PT Baron John A JA Berndt Sonja I SI Jiao Shuo S Casey Graham G Fortini Barbara B Chan Andrew T AT Cotterchio Michelle M Lemire Mathieu M Gallinger Steven S Harrison Tabitha A TA Le Marchand Loic L Newcomb Polly A PA Slattery Martha L ML Caan Bette J BJ Carlson Christopher S CS Zanke Brent W BW Rosse Stephanie A SA Brenner Hermann H Giovannucci Edward L EL Wu Kana K Chang-Claude Jenny J Chanock Stephen J SJ Curtis Keith R KR Duggan David D Gong Jian J Haile Robert W RW Hayes Richard B RB Hoffmeister Michael M Hopper John L JL Jenkins Mark A MA Kolonel Laurence N LN Qu Conghui C Rudolph Anja A Schoen Robert E RE Schumacher Fredrick R FR Seminara Daniela D Stelling Deanna L DL Thibodeau Stephen N SN Thornquist Mark M Warnick Greg S GS Henderson Brian E BE Ulrich Cornelia M CM Gauderman W James WJ Potter John D JD White Emily E Peters Ulrike U

PLoS genetics 20140417 4

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet intera ...[more]

PMID: 24743840

Similar Datasets

Project description:ImportanceCandidate gene analysis approaches have shown that colorectal cancer (CRC) risk attributable to diet may differ according to genotype. A genome-wide approach further allows for the exploration of underlying pathways for associations between diet and CRC risk across the genome.ObjectivesTo identify genetic variants that modify diet-CRC associations and to further explore the underlying pathways in the cause of CRC.Design, setting, and participantsThis nested case-control study used data on White British participants from the prospective cohort UK Biobank. Participants were recruited between March 13, 2006, and October 1, 2010, and data were censored June 25, 2021.ExposuresThe average frequency intake of 11 dietary factors in the year preceding baseline was obtained via a touchscreen questionnaire. After quality control for more than 93 million variants of imputed genetic data, 4 122 345 variants remained.Main outcomes and measuresColorectal cancer cases were identified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Genome-wide interaction analysis was performed to test interactions between dietary factors and variants using a conditional logistic regression model. Summary statistics of interactions at the variant level were used to calculate empirical P values for interactions at gene and gene-set levels in gene-based and gene-set enrichment analyses.ResultsA total of 4686 participants with CRC (mean [SD] age, 60.7 [6.6] years; 2707 men [57.8%]) received a new diagnosis during a median of 12.4 years (IQR, 11.6-13.1 years) of follow-up. Once a case was detected, 3 matched controls were identified, for a total of 14 058 controls (mean [SD] age, 60.4 [6.6] years; 8121 men [57.8%]). A total of 324 variants were identified that interacted with diet consumption at the suggestive threshold (P < 1 × 10-5). In gene-based analysis, aggregation of multiple EPDR1 gene variants was found to interact with fish intake regarding CRC risk. Furthermore, gene-set enrichment analysis found that several sets of protein-coding genes, which were overrepresented with particular functions and pathways, interacted with the consumption of milk (ART), cheese (OR), tea (KRT), and alcohol (PRM and TNP).Conclusions and relevanceIn this nested case-control study, the risk of CRC associated with fish intake was modified by multiple single-nucleotide polymorphisms of the EPDR1 gene. The findings further suggested possible functions and pathways that might link the consumption of milk, cheese, tea, and alcohol with CRC development.

Dataset Information

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Publications

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets