• GAW;
  • case-control;
  • family-based;
  • cross-sectional;
  • longitudinal;
  • rheumatoid arthritis;
  • Framingham Heart Study;
  • GWAS


Despite the importance of gene-environment (G×E) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genome-wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 contributions, which introduced a variety of new methods for the detection of G×E interactions in both case-control and family-based data using both cross-sectional and longitudinal study designs. Many of these contributions detected significant G×E interactions. Although these interactions have not yet been confirmed, the results suggest the importance of testing for interactions. Issues of sample size, quantifying the environmental exposure, longitudinal data analysis, family-based analysis, selection of the most powerful analysis method, population stratification, and computational expense with respect to testing G×E interactions are discussed. Genet. Epidemiol. 33 (Suppl. 1):S68–S73, 2009. © 2009 Wiley-Liss, Inc.