Epistasis and its possible effects on transmission disequilibrium tests.
Most approaches to analysing complex genetic disorders are based on an underlying model that assumes that the probability of being affected is mainly due to the effect of a major, single disease locus. Where the penetrance (the conditional probability of being affected) is hypothesised to be influenced by known covariates, methods have been developed to accommodate these covariates appropriately in the analysis. Unexplained variation in the incomplete penetrance is then attributed to either unspecified environmental effects or to other genes of small effect that might act epistatically with the 'disease gene'. Recently, there have been some proposals to incorporate two (or more) possibly epistatic identified loci as major effects in the analysis. However, the effect of two (or more) major epistatic disease genes on the analysis of data that assumes a single 'disease gene', and so ignores any other major gene, does not seem to have been explored. This investigation is undertaken here for triad data consisting of affected singletons and their parents. Following development of a quite general underlying genetic model, a global approach to analysing two marker loci for triad data is developed. This approach is the appropriate one for such data where two, possibly epistatic, loci have been identified a priori. The motivation for the development of this methodology is to evaluate the possible effect a second epistatic disease locus might be having on the results for triad data collected and analysed in different population studies, where the underlying analysis is based on an underlying major, single disease locus model. It is shown that, dependent on the population parameters associated with the other unidentified major disease gene, results concerning the single 'disease gene' can vary markedly. So, finding that conclusions differ from study to study may be indicative of the 'disease gene' under investigation acting epistatically with other major disease genes.
Wilson
S R
SR
Centre for Mathematics and its Applications and Centre for Bioinformation Science, Australian National University, Canberra, ACT, Australia. Sue.Wilson@anu.edu.au
D004843:Epistasis, Genetic; D005260:Female; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006801:Humans; D016014:Linear Models; D015810:Linkage Disequilibrium; D008297:Male; D008957:Models, Genetic
D005819:Genetic Markers