Genetic factors have long been known to play a role in the development of autism, but the contribution of common genetic variations — those that crop up in at least one percent of the general population — to the disorder is not known. Randy Buckner and his colleagues at Harvard University are developing a new, highly efficient approach to explore the effects of these variations on brain functions associated with autism.
Many of the hundreds of genes involved in brain development have common variations that presumably contribute to the typical diversity found in the general population. Buckner and colleagues hypothesize that genetic predisposition to autism occurs when brain development is steered down an abnormal path through the combined influence of dozens — or even hundreds — of common variations, each with a small role.
To determine the role of such variations in autism, Buckner and colleagues will first attempt to understand their role in typical development. To that end, the researchers will collect saliva samples from 1,000 typically developing people, as well as data from a recently developed imaging tool called functional connectivity magnetic resonance imaging, or fcMRI. This tool allows researchers to examine basic properties of brain organization — such as which hemisphere is dominant for language, and whether typical connectivity patterns are present in brain systems used for thinking — and link differences in these properties to specific genetic variants. The researchers will pay particular attention to variations in genes known to be associated with autism.
Buckner and colleagues have dubbed their effort the Brain Genomics Superstruct Project, as it builds on, or 'superstructs', the collective foundation laid by previous work on autism. Because the complex studies linking genetics and brain function will require the effort of many research groups, the researchers plan to share their data collection, which will eventually include 5,000 people. The team will also share their rapid fcMRI protocol, which eases the burden of data acquisition by capturing imaging data in less than 15 minutes per subject.