While environmental factors are thought to play some role in causing autism spectrum disorder, there is no question that genetics are heavily involved. Risk of autism increases significantly for children with family histories of the disorder. In identical twins, for example, if one has autism, the other can have up to a 90 percent chance of developing it as well.
Two landmark studies published last month in Nature changed the landscape of how scientists understand the genetics of autism. International teams of researchers identified dozens of genes directly linked to the disorder. To do so, they sequenced and analyzed the exomes – segments of the genome which contains functional genes – from thousands of children with autism, their families and unrelated individuals.
In the larger of the two studies, scientists looked at more than 10,000 exomes, representing billions of basepairs of DNA and terabytes of data. The Herculean task of sorting through this volume of information, akin to digging through 10,000 haystacks to find a few needles, was shouldered by Xin He, PhD, assistant professor in the Department of Human Genetics at the University of Chicago.
“How do you efficiently analyze and extract meaningful information from this huge amount of data?” He told ScienceLife. “That was my role in the study.”
He, then a post-doctoral fellow at Carnegie Mellon, was instrumental in the development of sophisticated analytical methods that allowed the team to find specific autism-related genes amidst the cacophony of information. Remarkably, they were able to pinpoint 33 genes with an extremely strong association with risk of for autism, and 107 that are likely involved as well. Until this point, only 11 genes had ever been conclusively linked to autism.
To identify risk genes, He and his colleagues built a powerful method called TADA (transmission and de novo association) to analyze both inherited and de novo mutations (spontaneously acquired, non-inherited mutations) simultaneously. Previous analyses have focused on de novo mutations, based on the idea that any gene that is recurrently mutated in multiple children with autism represents a candidate risk gene. Such recurrent events are rare, however. The new method combines the information in de novo events with more subtle, but still significant, effects from inherited mutations. By analyzing thousands of genomes, He and his colleagues were able to greatly increase their ability to find autism-linked mutations, as well as decrease the chances of false discoveries.
“You can think of TADA as taking two pictures of the sky and overlaying them on top of each other. The stars that occur in both pictures are intensified,” He said. “In our case, each type of data, de novo or inherited mutations, represents a snapshot of the functions of all genes in relation to autism. By combining these two snapshots, we were able to identify much larger set of genes than what could be done before. This is a significant increase in our knowledge of autism.”
The risk genes they discovered represent a veritable treasure trove for autism researchers. Many of these are related to how neurons communicate with each other and neuronal development, and some are linked to how other genes are turned on or off. With these now identified, scientists around the world have new research directions to better understand autism and targets for the development of new therapies.
While these findings are exciting, He cautions that they are only associated with risk for autism, which is a complex disease involving many factors including environment. Having a mutation to a gene might increase the chances of developing autism by a few percentage points or might have no effect at all, and many more studies need to be made to identify their precise role in the disorder.
Interestingly, many of the identified genes are associated with other developmental disorders such as schizophrenia, intellectual disability, congenital heart disease and metabolic disorders. He is now working with collaborators to apply TADA to other disorders.
“By knowing the specific genes involved in disease, then you know how to manipulate cells through drugs or other therapeutic means to reverse the effects of mutations, which can someday lead to better treatments,” He said. “That is the ultimate goal for this kind of study.”