Our overall purpose is not solely to detect interactions, but rather to understand the genotype-phenotype association in relation to onset age of smoking. As such, it is the joint-significance of the main effect and the interaction terms that is of interest. Hence, for each SNP, we allow for the possibility of statistical interaction between age-at-onset of smoking (and other covariates) and allele count. This involves evaluation of the non-genetic base model, the main-effect model and the interaction model: (Eq. 1)ln(P1−P)=α+β1(age)+β2(sex)+β3(rAOS) (Eq. 2)ln(P1−P)=α+β1(age)+β2(sex)+β3(rAOS)+β4G (Eq. 3)ln(P1−P)=α+β1(age)+β2(sex)+β3(rAOS)+β4∗G+β5(G×rAOS) where α is the intercept, age is age at interview, sex is coded as 0 or 1, rAOS is age-at-onset of regular smoking (reversed and recoded as described), G is genotype for a given SNP, presumed to be log-additive. The final term in Equation 3 represents the product or interaction term. Note that in Equation 3, the term β4* designates the genetic main effect when rAOS=0, which corresponds to AOS=16, the sample median.
