Molecular genetic models related to schizophrenia and psychotic illness: heuristics and challenges

Schizophrenia is a heritable disorder that may involve several common genes of small effect and/or rare copy number variation, with phenotypic heterogeneity across patients. Furthermore, any boundaries vis-à-vis other psychotic disorders are far from clear. Consequently, identification of informative animal models for this disorder, which typically relate to pharmacological and putative pathophysiological processes of uncertain validity, faces considerable challenges. In juxtaposition, the majority of mutant models for schizophrenia relate to the functional roles of a diverse set of genes associated with risk for the disorder or with such putative pathophysiological processes. This chapter seeks to outline the evidence from phenotypic studies in mutant models related to schizophrenia. These have commonly assessed the degree to which mutation of a schizophrenia-related gene is associated with the expression of several aspects of the schizophrenia phenotype or more circumscribed, schizophrenia-related endophenotypes; typically, they place specific emphasis on positive and negative symptoms and cognitive deficits, and extend to structural and other pathological features. We first consider the primary technological approaches to the generation of such mutants, to include their relative merits and demerits, and then highlight the diverse phenotypic approaches that have been developed for their assessment. The chapter then considers the application of mutant phenotypes to study pathobiological and pharmacological mechanisms thought to be relevant for schizophrenia, particularly in terms of dopaminergic and glutamatergic dysfunction, and to an increasing range of candidate susceptibility genes and copy number variants. Finally, we discuss several pertinent issues and challenges within the field which relate to both phenotypic evaluation and a growing appreciation of the functional genomics of schizophrenia and the involvement of gene × environment interactions.