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The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.

ABSTRACT: With limited funding and biological specimen availability, choosing an optimal sampling design to maximize power for detecting gene-by-environment (G-E) interactions is critical. Exposure-enriched sampling is often used to select subjects with rare exposures for genotyping to enhance power for tests of G-E effects. However, exposure misclassification (MC) combined with biased sampling can affect characteristics of tests for G-E interaction and joint tests for marginal association and G-E interaction. Here, we characterize the impact of exposure-biased sampling under conditions of perfect exposure information and exposure MC on properties of several methods for conducting inference. We assess the Type I error, power, bias, and mean squared error properties of case-only, case-control, and empirical Bayes methods for testing/estimating G-E interaction and a joint test for marginal G (or E) effect and G-E interaction across three biased sampling schemes. Properties are evaluated via empirical simulation studies. With perfect exposure information, exposure-enriched sampling schemes enhance power as compared to random selection of subjects irrespective of exposure prevalence but yield bias in estimation of the G-E interaction and marginal E parameters. Exposure MC modifies the relative performance of sampling designs when compared to the case of perfect exposure information. Those conducting G-E interaction studies should be aware of exposure MC properties and the prevalence of exposure when choosing an ideal sampling scheme and method for characterizing G-E interactions and joint effects.

SUBMITTER: Stenzel SL

PROVIDER: S-EPMC4256150 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.

Stenzel Stephanie L SL Ahn Jaeil J Boonstra Philip S PS Gruber Stephen B SB Mukherjee Bhramar B

European journal of epidemiology 20140604 5

With limited funding and biological specimen availability, choosing an optimal sampling design to maximize power for detecting gene-by-environment (G-E) interactions is critical. Exposure-enriched sampling is often used to select subjects with rare exposures for genotyping to enhance power for tests of G-E effects. However, exposure misclassification (MC) combined with biased sampling can affect characteristics of tests for G-E interaction and joint tests for marginal association and G-E interac ...[more]

PMID: 24894824

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Project description:BackgroundGenome-wide association studies (GWAS) have identified more than 40 colorectal cancer susceptibility loci, but only a small fraction of heritability was explained. To account for missing heritability, we investigated gene-environment interactions (G × Es) between GWAS-identified single-nucleotide polymorphisms (SNPs) and established risk or protective factors for colorectal cancer using both case-only and case-control study designs.MethodsData on 703 colorectal cancer cases and 1406 healthy controls from the National Cancer Center in Korea were used. We tested interactions between 31 GWAS-identified SNPs and 13 established risk or protective factors for colorectal cancer (family history, body mass index, history of colorectal polyps, inflammatory bowel disease, and diabetes mellitus, alcohol drinking, smoking, regular exercise, regular aspirin use, postmenopausal hormone replace therapy, red meat and processed meat intake, and dairy consumption). Logistic regression models were used to assess G × Es for colorectal cancer risk.ResultsThe SNP rs4444235 at 14q22.2 interacted with regular exercise in colorectal cancer (pcase-only = 2.4 × 10- 3, pcase-control = 1.5 × 10- 3). The risk allele (C) of rs4444235 increased the risk of colorectal cancer in regularly exercising individuals (OR = 1.47, 95% CI = 1.02-2.10) but decreased the risk in non-exercising individuals (OR = 0.76, 95% CI = 0.62-0.94). Furthermore, the G × E between the SNP rs2423279 at 20p12.3 and regular aspirin use was statistically significant (pcase-only = 7.7 × 10- 3, pcase-control = 1.6 × 10- 3). The additive effect of the risk allele (T) of rs2423279 on colorectal cancer risk was increased among regular aspirin users (OR = 4.62, 95% CI = 1.97-10.80).ConclusionOur results suggest that SNP rs4444235 at 14q22.2 and SNP rs2423279 at 20p12.3 may interact with regular exercise and aspirin use in colorectal carcinogenesis.

Dataset Information

The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.

Publications

The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.

Similar Datasets

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