Elsevier

Neuropharmacology

Volume 62, Issue 3, March 2012, Pages 1164-1167
Neuropharmacology

Commentary
Genetic mouse models relevant to schizophrenia: Taking stock and looking forward

https://doi.org/10.1016/j.neuropharm.2011.08.009Get rights and content

Abstract

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene–gene and gene–environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue.

This article is part of a Special Issue entitled ‘Schizophrenia’.

Section snippets

Which gene(s)?

There is no shortage of putative schizophrenia genes to study in a mouse model. Naturally, most work has focused on the genes which are considered to have the greatest depth and breadth of evidence for their involvement. Amongst these, Disrupted in schizophrenia 1 (DISC1) has been the most extensively studied, in a range of different mutants (Johnstone et al., 2011). Reflecting this focus, three papers in this issue pertain to DISC1 and are discussed later.

Other genetic mutants are studied not

What genetic manipulation?

The simplest and most widely used genetic manipulation is to knock the gene out. However, although this approach can be invaluable for identifying the role of a putative schizophrenia gene in brain function, the relevance to schizophrenia is limited in that there is no evidence for null mutations in the disorder. Heterozygous knockouts (e.g. Meck et al., 2012) in which ∼50% of expression is retained are better, particularly for genes where there is evidence for hemizygosity or a similar degree

Modeling gene–environment interactions

It is widely considered that genetic and environmental risk factors for schizophrenia do not act independently, but interactively (van Os et al., 2008). Hence, many investigators are studying the impact of an environmental intervention in genetic mouse models (Ayhan et al., 2009). The choice of intervention is, like the choice of gene, a decision affected by prior belief about the importance of the factor(s) in schizophrenia, as well as by practicalities, expertise, and interest. Environmental

Which phenotypes, which readouts?

Whichever genetic models and manipulations are used, a critical question remains as to which phenotype(s) to measure. These range increasingly broadly, from behavior to electrophysiology and morphology (with many specific readouts within each domain), and include modeling of symptoms and endophenotypes (e.g. Powell et al., 2009, Jaaro-Peled et al., 2010). Within electrophysiology, for example, Gandal et al. (2012) describe a recent addition to the phenotypic repertoire, the study of gamma

Conclusions

As the articles in this special issue illustrate, genetic mouse models relevant to schizophrenia are a thriving and productive research area. Equally, they demonstrate the complexities and decisions involved at each step, from choice of model, through experimental design and execution, to data interpretation. As the evidence for specific genes and genetic variants associated with schizophrenia becomes more compelling, and as the epidemiological and statistical evidence for gene–gene and

Acknowledgments

DP holds the University of Oxford Christopher Welch Scholarship. KS is funded by a studentship from the Wellcome Trust. JB is funded by a studentship from the Medical Research Council (MRC). WN holds a Department of Pharmacology studentship. KPL is a Wellcome Trust Career Development Fellow. DMB is a Wellcome Trust Senior Research Fellow. EMT is a Royal Society University Research Fellow. Our work is also supported by grants from MRC, BBSRC, and the BMA Margaret Temple Fellowship.

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