title: Efficient designs of gene-environment interaction studies: implications of Hardy-Weinberg equilibrium and gene-environment independence.
abstract: It is important to investigate whether genetic susceptibility variants exercise the same effects in populations that are differentially exposed to environmental risk factors. Here, we assess the power of four two-stage case-control design strategies for assessing multiplicative gene-environment (G-E) interactions or for assessing genetic or environmental effects in the presence of G-E interactions. We considered a di-allelic single nucleotide polymorphism G and a binary environmental variable E under the constraints of G-E independence and Hardy-Weinberg equilibrium and used the Wald statistic for all tests. We concluded that (i) for testing G-E interactions or genetic effects in the presence of G-E interactions when data for E are fully available, it is preferable to ascertain data for G in a subsample of cases with similar numbers of exposed and unexposed and a random subsample of controls; and (ii) for testing G-E interactions or environmental effects in the presence of G-E interactions when data for G are fully available, it is preferable to ascertain data for E in a subsample of cases that has similar numbers for each genotype and a random subsample of controls. In addition, supplementing external control data to an existing case-control sample leads to improved power for assessing effects of G or E in the presence of G-E interactions.
authors.affiliation: Department of Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA 19104, USA. jinboche@mail.med.upenn.edu
authors.forename: Jinbo
authors.initials: J
authors.lastname: Chen
authors.forename: Guolian
authors.initials: G
authors.lastname: Kang
authors.forename: Tyler
authors.initials: T
authors.lastname: Vanderweele
authors.forename: Cuilin
authors.initials: C
authors.lastname: Zhang
authors.forename: Bhramar
authors.initials: B
authors.lastname: Mukherjee
mesh_terms: D016022:Case-Control Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D059647:Gene-Environment Interaction; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012107:Research Design