Utility and validity of DISC1 mouse models in biological psychiatry. (3rd May 2016)

• Record Type: Journal Article
• Authors: Tomoda, T.; Sumitomo, A.; Jaaro-Peled, H.; Sawa, A.
• Is Part Of: Neuroscience. Volume 321(2016)
• Page Start: 99
• Page End: 107
• Publication Date: 2016-05-03
• Subjects: DISC1 Disrupted-in-schizophrenia 1 -- AD Alzheimer's disease -- DN dominant-negative -- PPI prepulse inhibition -- DSM Diagnostic and Statistical Manual of Mental Disorders -- PAK p21-activated kinase; DISC1 -- mouse models -- psychiatry; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2015.12.061
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Multiple DISC1 models have been generated, but can be organized into three categories. DISC1 models are useful in their biological and face validities. DISC1 models are utilized at molecular, cellular, circuitry, and behavioral levels. Several enigmas in DISC1 biology at present can be addressed with the mouse models. Abstract: We have seen an era of explosive progress in translating neurobiology into etiological understanding of mental disorders for the past 10–15 years. The discovery of Disrupted-in-schizophrenia 1 ( DISC1 ) gene was one of the major driving forces that have contributed to the progress. The finding that DISC1 plays crucial roles in neurodevelopment and synapse regulation clearly underscored the utility and validity of DISC1-related biology in advancing our understanding of pathophysiological processes underlying psychiatric conditions. Despite recent genetic studies that failed to identify DISC1 as a risk gene for sporadic cases of schizophrenia, DISC1 mutant mice, coupled with various environmental stressors, have proven successful in satisfying face validity as models of a wide range of human psychiatric conditions. Investigating mental disorders using these models is expected to further contribute to the circuit-level understanding of the pathological mechanisms, as well as to the development of novel therapeutic strategies in the future.