treating the effect of each haplotype on the phenotype sequentially, assuming that the phenotype is a rough estimate of the percent of substrate metabolized. The first haplotype catalyzes conversion of a percentage of substrate to metabolite and the second haplotype acts upon the remaining substrate. For the multiplicative model we use %n1 = β0 • βH1 • βH2, where β0 corresponds to a global parameter, the intercept, and a βH parameter is identified for each defined haplotype H. The modeled phenotype, “%n1” refers to D2-nicotine/(D2-nicotine + D2-cotinine) at time point 1. This is the same as 1 –(D2-cotinine/(D2-nicotine + D2-cotinine)). The regression was performed on the log of the model: log (%n1) = log(β0) + log(βH1) + log(βH2). Use of the log-transformed parameters here is a mathematical convenience that allows the regression for the multiplicative model to be performed as additive. Under this model, log (βH) values close to zero correspond to βH parameters close to one, which corresponds to slower metabolism. The null hypothesis for these tests is that the genotype in question does not influence nicotine metabolism.
