Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.
paper
Cited
Public
- Authors
- Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M; NCI Gene-Environment Think Tank
- Year
- 2013
- Journal
- Genetic epidemiology
- PMID
- 24123198
- DOI
- 10.1002/gepi.21756
- PMCID
- PMC4143122
Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors.
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| Name | Type |
|---|---|
| 8q22.3 local | variant |
| alcohol | phenotype |
| ALDH2 | gene |
| benzidine local | drug |
| benzidine-exposed workers local | cohort |
| bladder cancer | phenotype |
| bladder cancer GWAS (10,519 cases, 13,218 controls) local | cohort |
| body mass index | phenotype |
| breast cancer | phenotype |
| cancer | phenotype |
| cancer phenotypes | phenotype |
| cancer risk | phenotype |
| CASP8 | gene |
| colorectal cancer | phenotype |
| common complex trait local | phenotype |
| common variants | cohort |
| complex diseases | phenotype |
| Complex diseases and outcomes local | phenotype |
| diabetes | phenotype |
| disease | phenotype |
| Early childhood exposure local | drug |
| environmental exposures | drug |
| environmental factors | drug |
| epigenetic components local | drug |
| esophageal cancer | phenotype |
| Esophageal squamous cell carcinoma | phenotype |
| ever/never smoking local | drug |
| GAME-ON Initiative local | cohort |
| genetic factors | cohort |
| genetic variants | cohort |
| GEWIS studies local | cohort |
| GxE local | phenotype |
| imputed genotypes local | variant |
| In utero exposure local | drug |
| large consortium local | cohort |
| Longitudinal study | cohort |
| LSP1 local | gene |
| NAT2 | gene |
| nested case-control study local | cohort |
| non-coding RNA local | gene |
| non-smokers | phenotype |
| obesity | phenotype |
| PAHs local | drug |
| parity local | drug |
| PhenX initiative local | cohort |
| polygenic risk-scores local | phenotype |
| rare disease | phenotype |
| rare variant | cohort |
| rs1495741 local | variant |
| smoking | phenotype |
| SNP | cohort |
| SNP×E case-control study local | cohort |
| tamoxifen | drug |
| vegetable consumption local | drug |
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