The impact of incomplete linkage disequilibrium and genetic model choice on the analysis and interpretation of genome-wide association studies.
When conducting a genetic association study, it has previously been observed that a multiplicative risk model tends to fit better at a disease-associated marker locus than at the ungenotyped causative locus. This suggests that, while overall risk decreases as linkage disequilibrium breaks down, non-multiplicative components are more affected. This effect is investigated here, in particular the practical consequences it has on testing for trait/marker associations and the estimation of mode of inheritance and risk once an associated locus has been found. The extreme significance levels required for genome-wide association studies define a restricted range of detectable allele frequencies and effect sizes. For such parameters there is little to be gained by using a test that models the correct mode of inheritance rather than the multiplicative; thus the Cochran-Armitage trend test, which assumes a multiplicative model, is preferable to a more general model as it uses fewer degrees of freedom. Equally when estimating risk, it is likely that a multiplicative risk model will provide a good fit to the data, regardless of the underlying mode of inheritance at the true susceptibility locus. This may lead to problems in interpreting risk estimates.
Iles
Mark M
MM
Section of Epidemiology and Biostatistics, Cancer Research UK Clinical Centre, Leeds Institute of Molecular Medicine, University of Leeds, St James's University Hospital, Beckett Street, Leeds, LS9 7TF, UK. m.m.iles@leeds.ac.uk
D005787:Gene Frequency; D005819:Genetic Markers; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D012306:Risk
D005819:Genetic Markers