Most examples of GxE research in the social sciences have been candidate gene or twin/sibling studies (Boardman et al. 2011; Guo and Tong 2006; Miller et al. 2010; Rodgers et al. 2001; van den Oord and Rowe 2000). Recent declines in the costs of genome-wide genotyping in conjunction with an increasing number of population-based studies with genome-wide data make a genome-wide gene-by-environment interaction (GWGEI) approach possible (Cornelis et al. 2012; Mukherjee et al. 2012; Thomas et al. 2012). For example, the Health and Retirement Study (HRS), the National Longitudinal Study of Adolescent Health (Add Health), the Framingham Heart Study (FHS), and the Wisconsin Longitudinal Study (WLS) either have collected or are collecting genetic information from their respondents. Demographers will soon be “drinking from the firehose” (Hunter and Kraft 2007). This article aims to provide a roadmap for the integration of genome-wide data into social science research through the application of GWAS and GWGEI methods to a phenotype with both genetic and environmental influences. One of the primary goals of this article is to evaluate the relevance of the current GxE
