Gene-environment interaction tests for dichotomous traits in trios and sibships.
When testing for genetic effects, failure to account for a gene-environment interaction can mask the true association effects of a genetic marker with disease. Family-based association tests are popular because they are completely robust to population substructure and model misspecification. However, when testing for an interaction, failure to model the main genetic effect correctly can lead to spurious results. Here we propose a family-based test for interaction that is robust to model misspecification, but still sensitive to an interaction effect, and can handle continuous covariates and missing parents. We extend the FBAT-I gene-environment interaction test for dichotomous traits to using both trios and sibships. We then compare this extension to joint tests of gene and gene-environment interaction, and compare the joint test additionally to the main effects test of the gene. Lastly, we apply these three tests to a group of nuclear families ascertained according to affection with Bipolar Disorder.
Hoffmann
Thomas J
TJ
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. tjhoffm@fas.harvard.edu
Lange
Christoph
C
Vansteelandt
Stijn
S
Laird
Nan M
NM
D000465:Algorithms; D001714:Bipolar Disorder / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D004777:Environment; D005190:Family; D005260:Female; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D035781:Siblings