Over the past few years, genome-wide association studies (GWASs) have identified numerous genes associated with common human diseases. In these studies, genetic variation in thousands of individuals is collected and correlated with the disease status in these individuals. Environmental factors often interact with genetic variation to increase risk of disease. Identifying these interactions, referred to as gene-by-environment (GxE) interactions, is now a major focus of research in both human studies and model organism studies. Discovering GxE interactions can provide insight into disease pathways, an understanding of the effect of environmental factors in disease, better risk prediction and personalized therapies. Model organisms such as mouse are ideal environments for studying GxE interactions because environmental exposures can be carefully controlled. In this proposal we propose to develop methodology that determine whether or not gene-by-environment interactions are present and can quantify the total amount of these interactions. The results of our project will be a set of methods that can then be widely used by many researchers involved in studies to discovery gene-by-environment interactions. We will apply our developed methods to the Minnesota Center for Twin and Family Research (MCTFR) data to investigate how gene-environment interplay influences the development of substance abuse (SA) and to mouse genetic studies investigating the genetic factors which influence response to high fat diet and susceptibility to heart failure. We will make our methods available to the research community through publicly available software packages and webserver resources.
An individual's predisposition to disease depends on both genetic factors and environmental factors as well as the interaction of these genetic and environmental factors. Relatively little is known about these interactions and few of them have been discovered. This proposal is relevant to human health because it develops novel methods for discovering these types of interactions which can provide insight into the factors which contribute to disease leading to directions for new treatments and therapies.
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