title: Invited commentary: GE-Whiz! Ratcheting gene-environment studies up to the whole genome and the whole exposome.
abstract: One goal in the post-genome-wide association study era is characterizing gene-environment interactions, including scanning for interactions with all available polymorphisms, not just those showing significant main effects. In recent years, several approaches to such "gene-environment-wide interaction studies" have been proposed. Two contributions in this issue of the American Journal of Epidemiology provide systematic comparisons of the performance of these various approaches, one based on simulation and one based on application to 2 real genome-wide association study scans for type 2 diabetes. The authors discuss some of the broader issues raised by these contributions, including the plausibility of the gene-environment independence assumption that some of these approaches rely upon, the need for replication, and various generalizations of these approaches.
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA. dthomas@usc.edu
authors.forename: Duncan C
authors.initials: DC
authors.lastname: Thomas
authors.forename: Juan Pablo
authors.initials: JP
authors.lastname: Lewinger
authors.forename: Cassandra E
authors.initials: CE
authors.lastname: Murcray
authors.forename: W James
authors.initials: WJ
authors.lastname: Gauderman
mesh_terms: D015992:Body Mass Index; D016022:Case-Control Studies; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D005260:Female; D059647:Gene-Environment Interaction; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male