SciTech

Autism-related genes identified

Researchers have had recent success in understanding the genetic basis for neuropsychiatric diseases.

Kathryn Roeder, an assistant professor in the department of statistics and the Lane Center for Computational Biology at Carnegie Mellon, and Bernie Devlin, professor of psychiatry at the University of Pittsburgh, recently led an international research team that successfully identified 33 genes that contribute to autism risk. Their study, published last week in Nature, utilized new approaches that take advantage of all the information that can be learned when comparing genetic data.

According to the Autism Society of America, almost one percent of the world’s population is autistic, and autism affects more than 3.5 million Americans. Scientists are trying to understand what causes the disease so that therapies can be developed.

The human genome contains over 20,000 genes, and it remains a challenge to identify the genes that form the basis of complex diseases. Roeder has devoted her time to using statistical and computational approaches to identify the changes in proteins at the molecular level that could lead to the symptoms of autism.

She explained that previous approaches compared the genomes of children who have autism and their parents to identify changes in the DNA that would cause loss of function mutations in a gene. It is important to determine whether these changes are statistically significant and found in enough of the patient population. In other words, the changes must not be due to random chance, but must instead be directly related to the disease.

Roeder explained that, using this established method, they had identified nine genes, but the progress was slow. She knew that they “had a long way to go to making significant progress and would never make it there in a reasonable time.”

Roeder and Devlin noticed that many of the children and parents that were analyzed were simply ignored because there were many significant changes that directly caused mutations. Also, there may have been unique cases where the mothers might have contained the mutation and passed it on to their child, but were not autistic themselves because women are more robust to autism than men.
In essence, Roeder and her collaborators built a model that utilized both the important changes and the less significant changes to rank genes in relation to the disease. Using this method, she explained that they were able to identify relevant genes “twice as fast.” However, Roeder expressed that simply identifying a list of genes does not directly mean that we are immediately closer to a cure. Roeder focused largely on determining the relationships between the genes and the roles they play in biological processes.

Now that this research has identified interesting genes to explore, other scientists can perform direct biological experiments by knocking out the gene of interest and identifying the phenotypic changes that lead to autism.

Roeder was amazed at the cooperation between the numerous collaborators that contributed patient data for this study and believes that the sharing of data to benefit the bigger whole is necessary for significant progress moving forward.

She will continue to work on the project to identify when and where these genes are active. For example, if a gene is found to be relevant in the frontal cortex during development, biologists will be able to develop treatments that directly target the causes of autism.