Comprehensive follow-up of novel autism genetic discoveries
Mark Daly, Ph.D.
Massachusetts General Hospital
Based on a genome-wide association study, Mark Daly of Massachusetts General Hospital and his colleagues reported in 2008 that genetic variation in the 16p11.2 chromosomal region is a major risk factor for autism. Daly and colleagues also uncovered more than 100 other rare genetic variations that appear to contribute to risk of autism, but these polymorphisms need further confirmation to prove an association with the disorder. Taking advantage of the SFARI Simplex Collection, the researchers plan to intensively sequence the implicated regions to find rare point mutations that would not be detectable using past or current genome scanning techniques.
Studying the genetics of autism is technically difficult for several reasons. The genetic variants that raise autism risk could be inherited within a family or develop for the first time in the affected generation. The variants may include point mutations in the genetic sequence and genomic rearrangements, such as deletions, insertions and duplications, called copy-number variants. So far, more than ten genes have been implicated in autism, but even taken together, they only account for a small percentage of autism cases. Daly proposes that comparison of the autism-associated variants from two sources would be a powerful way to identify autism-related genes. The group’s original study analyzed samples from the Autism Genetic Resource Exchange, a collection of samples from families that have multiple children with autism, suggesting the presence of inherited variants. The SFARI Simplex Collection, in contrast, gathers samples from families with one child with autism, but unaffected siblings and parents, in order to identify spontaneous or de novo variants.
Daly and colleagues plan to perform a meta-analysis of the two collections to look for and characterize common variants. Genes uncovered in both collections would probably be influential in the development of autism. Combining the data sets may also help pinpoint causative variants. For example, the researchers plan to determine the precise boundaries of copy-number variants in order to learn which genes are affected. They also plan to sequence the variants using quick and inexpensive new methods, so that many samples can be analyzed to reveal genetic variations in the region.
Their results may suggest how a particular variant leads to autism, for example by disrupting gene expression. The findings could also serve as a starting point for diagnostic tests or future mechanistic studies, perhaps identifying pathways that could be targeted for therapies.