Literature DB >> 28978190

Lessons Learned From Past Gene-Environment Interaction Successes.

Beate R Ritz, Nilanjan Chatterjee, Montserrat Garcia-Closas, W James Gauderman, Brandon L Pierce, Peter Kraft, Caroline M Tanner, Leah E Mechanic, Kimberly McAllister.   

Abstract

Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned.
© The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  exposure; gene-environment; genome-wide association studies; interactions; metabolism genes; pathway genes; pharmacogenomics

Mesh:

Year:  2017        PMID: 28978190      PMCID: PMC5860326          DOI: 10.1093/aje/kwx230

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   5.363


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9.  A linear mixed-model approach to study multivariate gene-environment interactions.

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