News Release

Genetic analysis begins to unravel the impact of rare mutations on the severity of autism

Peer-Reviewed Publication

American Association for the Advancement of Science (AAAS)

Analyzing genetic data from more than 2,300 individuals with autism, a team has explored how a class of genetic mutations may influence the severity of symptoms in some people with autism spectrum disorder. Although more work is needed, their results begin to unravel the complex genetic origins of autism and the murky relationship between mutations and the condition's phenotype, or observable effects. Autism spectrum disorder is a complex and diverse condition, both in terms of its causes and its impact on affected individuals. People with autism can have a variety of symptoms and phenotypes, ranging from mild social deficits to severe cognitive impairment and disabilities. Researchers suspect that autism also has many contributing factors, including both environmental variables and multiple types of genetic mutations. Studies suggest that at least hundreds, if not thousands, of genes are involved in the development of autism; this genetic complexity has frustrated efforts to understand how specific mutations impact the phenotypes of autistic individuals. Koire et al. decided to investigate the relationship between autism symptoms and de novo missense variants - a type of mutation - in genes that are rarely mutated. Using an advanced computational prediction method, the researchers analyzed genetic data and missense variants in 2,384 individuals with autism, as well as 1,792 unaffected siblings. The experiments identified missense variants in 398 genes that they predict can affect molecular pathways involved in the development of neurons, the activity of connections between neurons, and other key aspects of the nervous system. Furthermore, patients who harbored missense variants that were most predicted to impact phenotype tended to have lower IQ scores. Koire et al. say that their genetic techniques could also help researchers study and identify disease-related genes in other conditions with complex genetic origins.


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