Comparison of affected sibling-pair linkage methods to identify gene x gene interaction in GAW15 simulated data.
Non-parametric linkage methods have had limited success in detecting gene by gene interactions. Using affected sibling-pair (ASP) data from all replicates of the simulated data from Problem 3, we assessed the statistical power of three approaches to identify the gene x gene interaction between two loci on different chromosomes. The first method conditioned on linkage at the primary disease susceptibility locus (DR), to find linkage to a simulated effect modifier at Locus A with a mean allele sharing test. The second approach used a regression-based mean test to identify either the presence of interaction between the two loci or linkage to the A locus in the presence of linkage to DR. The third method applied a conditional logistic model designed to test for the presence of interacting loci. The first approach had decreased power over an unconditional linkage analysis, supporting the idea that gene x gene interaction cannot be detected with ASP data. The regression-based mean test and the conditional logistic model had the lowest power to detect gene x gene interaction, possibly because of the complex recoding of the tri-allelic DR locus for use as a covariate. We conclude that the ASP approaches tested have low power to successfully identify the interaction between the DR and A loci despite the large sample size, which may be due to the low prevalence of the high-risk DR genotypes. Additionally, the lack of data on discordant sibships may have decreased the power to identify gene x gene interactions.
Larkin
Emma K
EK
Department of Epidemiology and Biostatistics, Case Western Reserve University, Triangle Building, Suite 260, 11400 Euclid Avenue, Cleveland, Ohio 44106, USA. emma.larkin@case.edu
Morris
Nathan J
NJ
Li
Yali
Y
Nock
Nora L
NL
Stein
Catherine M
CM