Gene-environment interaction in genome-wide association studies.
It is a commonly held belief that most complex diseases (e.g., diabetes, asthma, cancer) are affected in part by interactions between genes and environmental factors. However, investigators conducting genome-wide association studies typically test for only the marginal effects of each genetic marker on disease. In this paper, the authors propose an efficient and easily implemented 2-step analysis of genome-wide association study data aimed at identifying genes involved in a gene-environment interaction. The procedure complements screening for marginal genetic effects and thus has the potential to uncover new genetic signals that have not been identified previously.
Murcray
Cassandra E
CE
Department of Preventive Medicine, University of Southern California, Los Angeles, California 90089-9010, USA. murcray@usc.edu
Lewinger
Juan Pablo
JP
Gauderman
W James
WJ
D016022:Case-Control Studies; D004777:Environment; D004812:Epidemiologic Methods; D005786:Gene Expression Regulation; D005787:Gene Frequency; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D016017:Odds Ratio; D020641:Polymorphism, Single Nucleotide
D005819:Genetic Markers