All t-tests performed were two-sided. Normality of nicotine metabolism metrics was tested using the Shapiro-Wilk test. Among subjects in the most common diplotype classes normality was further tested controlling for diplotype by using the difference from diplotype mean for each subject and applying the Shapiro-Wilk test. Stepwise regression analyses were initially performed without assumptions to determine the contributions of less-frequent CYP2A6 alleles, gender, and current smoking status to measured metabolism phenotype according to additive and multiplicative models in 189 subjects. The additive model simply treats the parameter estimate for each defined CYP2A6 haplotype in a diplotype as an equal part in the phenotype, i.e. Phenotype = haplotype1 + haplotype2. The multiplicative model determines the parameter estimate for each haplotype in the context of the full diplotype: 1 Phenotype = haplotype1 • haplotype2. Conceptually, this method may also be seen as 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
