Rodent models are a key factor in the process of translating psychiatric genetics and genomics findings, allowing us to shed light on how risk-genes confer changes in neurobiology by merging different types of data across fields, from behavioural neuroscience to the burgeoning omics (e.g. genomics, epigenomics, proteomics, etc.). Moreover, they also provide an indispensable first step for drug discovery. However, recent evidence from both clinical and genetic studies highlights possible limitations in the current methods for classifying psychiatric illness, as both symptomology and underlying genetic risk are found to increasingly overlap across disorder diagnoses. Meanwhile, integration of data from animal models across disorders is currently limited. Here, we argue that behavioural neuroscience is in danger of missing informative data because of the practice of trying to ‘diagnose’ an animal model with a psychiatric illness. What is needed is a shift in emphasis, from seeking to ally an animal model to a specific disorder, to one focused on a more systematic assessment of the neurobiological and behavioural outcomes of any given genetic or environmental manipulation.
The integration of data across animal models of psychiatric genetic risk is currently limited by the tendency to focus on a disorder-specific diagnosis. We argue a more multidimensional approach should be adopted, one which places emphasis on: developing a system of classification that identifies broad behaviour/cognition, neurochemistry and neurophysiology phenotypes (blue and red circles), looking for association across categories of phenotypes (overlapping blue and red circles), and finally on identifying disorder-relevant endophenotypes which may be shared across diagnostic categories (yellow circle). For example, here we focus on overlaps in Autism and Schizophrenia endophenotypes that can be integrated into phenotypic analysis.