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Identifying high-impact therapeutic targets for autism spectrum disorders using rat models

City: 
New York
State/Province: 
NY
State/Province Full: 
New York
Country: 
United States

One recurrent finding in autism spectrum disorders (ASD) is that there are many gene and chromosome mutations that can lead to these conditions. Current estimates are that there are over 500 genes that can contribute to ASD, each one found altered in a small fraction of individuals with ASD. At the same time, there is a great need, as stated in the Autism Speaks mission, to “improve quality of life through more effective medicines,” and new medicines are frequently developed with a gene or gene products as the target. With hundreds of potential genes for ASD, it is not feasible to develop novel medicines against all of them, it is important to understand how genes work together and which genes are the ones that control the other ASD genes. This will support the selection of a small subset of ASD genes for developing new medicines. These key genes (called driver genes) and pathways would represent the optimal targets for developing new medicines. One tool that is invaluable in understanding brain function and how genes work together in the brain is the use of laboratory animals. Rats are the model system of choice for use in studies that seek validation of novel medicines. In addition, they provide unique opportunities to study complex social behaviors and detailed analyses of the brain. For example, the brain region called the prefrontal cortex has emerged as an area of great interest in ASD, and rats provide a simple means to study this region. This study explores genes in the prefrontal cortex in 6 rat models and makes use of integrated biological approaches to identify driver genes and pathways disrupted in the brain in ASD. The use of multiple independent rat models not only provides baseline data on these important models, but also can begin to identify pathways and modules that are changed in multiple types of ASD. Furthermore, such modules can identify driver genes and these driver genes can represent optimal therapeutic targets. This can help advance the mission to “improve quality of life through more effective medicines.”