Genetic association studies commonly involve fitting a simple statistical model that relates genetic markers to a phenotype. This approach is especially useful when investigating a large number of markers. If the focus is narrowed to a small region of the genome with only a few markers more complex models of the phenotype can be specified that permit the simultaneous analysis of multiple markers. This paper presents two complementary sets of mixture analyses. First, survival mixture models are used to investigate potential heterogeneity in self-reported first use of tobacco, alcohol, cannabis, inhalants, and other substances for each phenotype separately. Second, all phenotypes are analyzed simultaneously in a latent class analysis in order to discriminate between potentially different patterns of initiation across substances. In both sets of analyses, ten single nucleotide polymorphisms (SNPs) in the CHRNA5/A3/B4 gene cluster are used to predict different aspects of heterogeneity in substance use initiation. The CHRNA5/A3/B4 gene cluster is a well-replicated region that has been associated with drug behaviors in over thirty different studies.
