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A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits

Several association studies support the hypothesis that genetic variants can modify the influence of environmental factors on behavioral outcomes, i.e., G × E interaction. The case-control design used in these studies is powerful, but population stratification with respect to allele frequencies can...

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Autores principales: van der Sluis, Sophie, Dolan, Conor V., Neale, Michael C., Posthuma, Danielle
Formato: Texto
Lenguaje:English
Publicado: Springer US 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2480607/
https://www.ncbi.nlm.nih.gov/pubmed/18389355
http://dx.doi.org/10.1007/s10519-008-9201-8
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author van der Sluis, Sophie
Dolan, Conor V.
Neale, Michael C.
Posthuma, Danielle
author_facet van der Sluis, Sophie
Dolan, Conor V.
Neale, Michael C.
Posthuma, Danielle
author_sort van der Sluis, Sophie
collection PubMed
description Several association studies support the hypothesis that genetic variants can modify the influence of environmental factors on behavioral outcomes, i.e., G × E interaction. The case-control design used in these studies is powerful, but population stratification with respect to allele frequencies can give rise to false positive or false negative associations. Stratification with respect to the environmental factors can lead to false positives or false negatives with respect to environmental main effects and G × E interaction effects as well. Here we present a model based on Fulker et al. (1999) and Purcell (2002) for the study of G × E interaction in family-based association designs, in which the effects of stratification can be controlled. Simulations illustrate the power to detect genetic and environmental main effects, and G × E interaction effects for the sib pair design. The power to detect interaction was studied in eight different situations, both with and without the presence of population stratification, and for categorical and continuous environmental factors. Results show that the power to detect genetic and environmental main effects, and G × E interaction effects, depends on the allele frequencies and the distribution of the environmental moderator. Admixture effects of realistic effect size lead only to very small stratification effects in the G × E component, so impractically large numbers of sib pairs are required to detect such stratification.
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spelling pubmed-24806072008-07-22 A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits van der Sluis, Sophie Dolan, Conor V. Neale, Michael C. Posthuma, Danielle Behav Genet Original Research Several association studies support the hypothesis that genetic variants can modify the influence of environmental factors on behavioral outcomes, i.e., G × E interaction. The case-control design used in these studies is powerful, but population stratification with respect to allele frequencies can give rise to false positive or false negative associations. Stratification with respect to the environmental factors can lead to false positives or false negatives with respect to environmental main effects and G × E interaction effects as well. Here we present a model based on Fulker et al. (1999) and Purcell (2002) for the study of G × E interaction in family-based association designs, in which the effects of stratification can be controlled. Simulations illustrate the power to detect genetic and environmental main effects, and G × E interaction effects for the sib pair design. The power to detect interaction was studied in eight different situations, both with and without the presence of population stratification, and for categorical and continuous environmental factors. Results show that the power to detect genetic and environmental main effects, and G × E interaction effects, depends on the allele frequencies and the distribution of the environmental moderator. Admixture effects of realistic effect size lead only to very small stratification effects in the G × E component, so impractically large numbers of sib pairs are required to detect such stratification. Springer US 2008-04-04 2008 /pmc/articles/PMC2480607/ /pubmed/18389355 http://dx.doi.org/10.1007/s10519-008-9201-8 Text en © The Author(s) 2008 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Original Research
van der Sluis, Sophie
Dolan, Conor V.
Neale, Michael C.
Posthuma, Danielle
A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title_full A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title_fullStr A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title_full_unstemmed A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title_short A General Test for Gene–Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits
title_sort general test for gene–environment interaction in sib pair-based association analysis of quantitative traits
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2480607/
https://www.ncbi.nlm.nih.gov/pubmed/18389355
http://dx.doi.org/10.1007/s10519-008-9201-8
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