Each person with autism has a unique set of abilities and disabilities, and this heterogeneity has made the finding the genetic causes of the disorder difficult. Daniel Geschwind and his colleagues at the University of California, Los Angeles, plan to look for commonalities in gene expression that might define subgroups of people with autism — information that will aid the search for both the cause of and treatment for autism.

Autism is characterized by defects in social interactions, communication and behavior, and is sometimes accompanied by mental retardation. The severity of these impairments, however, varies significantly from case to case. This diversity probably arises from mutations that affect different genetic pathways in brain development, but it also obscures these pathways. To make studying autism easier and more effective, these heterogeneous cases have been divided into more homogeneous subgroups based on different criteria. For example, grouping people with autism by language ability has uncovered the CNTNAP2 gene as a risk factor for autism. Sorting cases by physical features, such as head size, or biomarkers may also prove powerful in defining autism subgroups, revealing a link between individual genetic risk factors and specific components of the disorder.

Geschwind and colleagues plan to forge this link by analyzing gene expression in people with autism, looking to form subgroups based on which genetic pathways are active. For this study, they will analyze unclassified cases of autism represented in the Autism Genetic Resource Exchange, which has collected blood from more than 1,000 families with two or more children with autism. The researchers plan to analyze gene expression in these cells using microarrays and try to define subgroups from the patterns they observe. In their previous work, they found that two different and traceable causes of autism have both common and distinct gene expression patterns in blood cells, demonstrating the approach’s feasibility and usefulness. They also identified shared common features in these seemingly distinct monogenic causes of autism.

Once Geschwind and colleagues have assigned unclassified cases of autism to gene expression-based subgroups, they plan to look for behavior and cognitive traits that frequently accompany the gene expression patterns, and compare their data with known genetic variations associated with autism. Such links may point to the genetic pathways that control the trait, and would be a clue to further pursue the genetic causes of autism.