Detecting gene-environment interactions in genome-wide association data
Article first published online: 18 NOV 2009
© 2009 Wiley-Liss, Inc.
Supplement: Genetic Analysis Workshop 16: Approaches to Analysis of Genome-Wide Data
Volume 33, Issue Supplement 1, pages S68–S73, 2009
How to Cite
Engelman, C. D., Baurley, J. W., Chiu, Y.-F., Joubert, B. R., Lewinger, J. P., Maenner, M. J., Murcray, C. E., Shi, G. and Gauderman, W. J. (2009), Detecting gene-environment interactions in genome-wide association data. Genet. Epidemiol., 33: S68–S73. doi: 10.1002/gepi.20475
- Issue published online: 18 NOV 2009
- Article first published online: 18 NOV 2009
- NIH National Institute of General Medical Sciences. Grant Number: R01 GM031575
- rheumatoid arthritis;
- Framingham Heart Study;
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.