Dataset Information

Systematic review: diet-gene interactions and the risk of colorectal cancer.

ABSTRACT:

Background

Diet contributes significantly to colorectal cancer (CRC) aetiology and may be potentially modifiable.

Aim

To review diet-gene interactions, aiming to further the understanding of the underlying biological pathways in CRC development.

Methods

The PubMed and Medline were systematically searched for prospective studies in relation to diet, colorectal cancer and genetics.

Results

In a meta-analysis, no interaction between NAT1 phenotypes and meat intake in relation to risk of CRC was found (P-value for interaction 0.95). We found a trend towards interaction between NAT2 phenotypes and meat intake in relation to risk of CRC. High meat intake was not associated with risk of CRC among carriers of the slow NAT2 phenotype, whereas NAT2 fast acetylators with high meat intake were at increased risk of CRC (OR = 1.25; 95% confidence interval (CI): 0.92-2.01) compared with slow acetylators with low meat intake (reference), P-value for interaction = 0.07. Low meat intake in the studied populations may influence the result. Interactions between meat, cruciferous vegetables, fibres, calcium, vitamins, and alcohol and ABCB1, NFKB1, GSTM1, GSTT1, CCND1, VDR, MGTM, IL10 and PPARG are suggested.

Conclusions

A number of interactions between genetic variation and diet are suggested, but the findings need replication in independent, prospective, and well-characterised cohorts before conclusions regarding the underlying biological mechanisms can be reached. When the above criteria are met, studies on diet-gene interactions may contribute valuable insight into the biological mechanisms underlying the role of various dietary items in colorectal carcinogenesis.

SUBMITTER: Andersen V

PROVIDER: S-EPMC3565452 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Publications

Systematic review: diet-gene interactions and the risk of colorectal cancer.

Andersen V V Holst R R Vogel U U

Alimentary pharmacology & therapeutics 20121210 4

<h4>Background</h4>Diet contributes significantly to colorectal cancer (CRC) aetiology and may be potentially modifiable.<h4>Aim</h4>To review diet-gene interactions, aiming to further the understanding of the underlying biological pathways in CRC development.<h4>Methods</h4>The PubMed and Medline were systematically searched for prospective studies in relation to diet, colorectal cancer and genetics.<h4>Results</h4>In a meta-analysis, no interaction between NAT1 phenotypes and meat intake in re ...[more]

PMID: 23216531

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Project description:BackgroundRisk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors.MethodsWe conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement.ResultsWe included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry.ConclusionsThough not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed.

Project description:BackgroundBoth genetic background and diet are important determinants of cardiovascular diseases (CVD). Understanding gene-diet interactions could help improve CVD prevention and prognosis. We aimed to summarise the evidence on gene-diet interactions and CVD outcomes systematically.MethodsWe searched MEDLINE® via Ovid, Embase, PubMed®, and The Cochrane Library for relevant studies published until June 6th 2022. We considered for inclusion cross-sectional, case-control, prospective cohort, nested case-control, and case-cohort studies as well as randomised controlled trials that evaluated the interaction between genetic variants and/or genetic risk scores and food or diet intake on the risk of related outcomes, including myocardial infarction, coronary heart disease (CHD), stroke and CVD as a composite outcome. The PROSPERO protocol registration code is CRD42019147031.Results and discussionWe included 59 articles based on data from 29 studies; six articles involved multiple studies, and seven did not report details of their source population. The median sample size of the articles was 2562 participants. Of the 59 articles, 21 (35.6%) were qualified as high quality, while the rest were intermediate or poor. Eleven (18.6%) articles adjusted for multiple comparisons, four (7.0%) attempted to replicate the findings, 18 (30.5%) were based on Han-Chinese ethnicity, and 29 (49.2%) did not present Minor Allele Frequency. Fifty different dietary exposures and 52 different genetic factors were investigated, with alcohol intake and ADH1C variants being the most examined. Of 266 investigated diet-gene interaction tests, 50 (18.8%) were statistically significant, including CETP-TaqIB and ADH1C variants, which interacted with alcohol intake on CHD risk. However, interactions effects were significant only in some articles and did not agree on the direction of effects. Moreover, most of the studies that reported significant interactions lacked replication. Overall, the evidence on gene-diet interactions on CVD is limited, and lack correction for multiple testing, replication and sample size consideration.

Dataset Information

Systematic review: diet-gene interactions and the risk of colorectal cancer.

Background

Aim

Methods

Results

Conclusions

Publications

Systematic review: diet-gene interactions and the risk of colorectal cancer.

Similar Datasets

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