ArticleGenetic epidemiology2013
Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.
Article in Genetic epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
73 citing papers in PubMed, 6 syntheses or guidelines pooled it, 108 citations in OpenAlex.
- Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies.International journal of cancer · 2019Pooled it
- Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct.The American journal of clinical nutrition · 2017Pooled it
- Pooled it
- An updated meta-analysis of 37 case-control studies on the association between NFKB1 -94ins/del ATTG promoter polymorphism and cancer susceptibility.Oncotarget · 2016Pooled it
- Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?Genetic epidemiology · 2016Pooled it
- Post-GWAS gene-environment interplay in breast cancer: results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79,000 women.Human molecular genetics · 2014Pooled it
- Profile of biological aging in first primary cancers: a pan-cancer analysis of two large-scale cohorts from the UK and Hong Kong.BMC medicine · 2025Article
- Ethical, Legal, and Social Implications of Gene-Environment Interaction Research.Genetic epidemiology · 2025Review
- Influence of structural racism on cancer health disparities: Tailoring measures relevant to multiple myeloma.Cancer · 2024Article
- SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations.bioRxiv : the preprint server for biology · 2024Article
- Decoding Cancer Risk: Understanding Gene-Environment Interactions in Cancer Development.Cureus · 2024Review
- Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking.JCO precision oncology · 2024Article
- Alzheimer's Disease Prevention and Treatment Based on Population-Based Approaches.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Article
- A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.Breast cancer research : BCR · 2023Article
- Early-life farm exposures and eczema among adults in the Agricultural Lung Health Study.The journal of allergy and clinical immunology. Global · 2022Article
- Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.Biology · 2022Article
- Three-way interaction effects of early life stress, positive parenting and FKBP5 in the development of depressive symptoms in a general population.Journal of neural transmission (Vienna, Austria : 1996) · 2021Article
- Article
- Using Genetic Marginal Effects to Study Gene-Environment Interactions with GWAS Data.Behavior genetics · 2021Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.