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Analysis Uncovers Hundreds of Autism-Linked Genes Using Evolution-Informed Approach

NEW YORK — Researchers have identified hundreds of genes associated with autism spectrum disorder using a new "evolutionary action" prediction method.

While a number of genes have already been tied to autism spectrum disorder, they tend to only explain a small portion of cases. To identify additional genes that contribute to the condition, researchers led by Baylor College of Medicine's Olivier Lichtarge turned to an evolution-informed approach to prioritize de novo missense variants found among individuals with autism but not their unaffected siblings that are likely to be harmful. As they reported Wednesday in Science Translational Medicine, the researchers homed in on nearly 400 genes and traced them to almost two dozen biological pathways, including several involved in neurogenesis. These missense variants could further predict more severe disease.

"This opens doors on many fronts," co-author Young Won Kim, a graduate student in Lichtarge's lab at Baylor, said in a statement. "It suggests new genes we can study in ASD, and that there is a path forward to advise parents of children with these mutations of the potential outcomes in their child and how to best involve external support in early development intervention, which has shown to make a huge difference in outcome as well."

For their analysis, the researchers compared the number of de novo missense variants in 2,384 individuals with autism spectrum disorder to the those in 1,792 unaffected siblings. Overall, affected individuals harbored more de novo variants than their siblings. In particular, the researchers identified 1,418 missense variants affecting 1,269 genes among the individuals with autism spectrum disorder.

Teasing out the effect of missense variants can be difficult, and Lichtarge and his colleagues used the evolutionary action equation, a tool they developed to gauge the effect of de novo missense variants on protein function. The EA equation incorporates both information on where the variant falls and how conserved or variable that region is in evolutionary history, along with information on the substitution itself. This leads to a score on a 100-point scale in which higher scores are associated with lower fitness of the protein.

Within their cohort, the researchers identified 398 genes affecting 23 pathways with higher-than-expected EA scores among individuals with autism spectrum disorder.

These genes included several with known links to autism spectrum disorder, such as genes found on the Simons Foundation Autism Research Initiative list, as well as novel ones. The implicated pathways likewise contained some, like axonogenesis, that are relevant to autism spectrum disorder and nervous system function.

This number of affected genes and pathways likely reflects the complex nature of autism spectrum disorder. "For something as intricate as brain function involving cognition, reasoning, and social interaction, among others, the answer seems to be that there is a lot of interplay between overlapping and complementary processes," Lichtarge said in an email.

He and his colleagues further investigated whether increasing EA scores were associated with more severe autism spectrum disorder phenotypes, which they gauged using intelligence quotient scores. After splitting their cohort into high-, intermediate-, and low-IQ groups, the researchers found that individuals in the low-IQ group had more variants with high EA scores than expected by chance, while the converse was true for the individuals in the high-IQ group.

The findings suggest that de novo missense variants have the possibility of affecting genes in key neurological pathways that can influence the severity of autism spectrum disorder.

Lichtarge noted that autism spectrum disorder is marked by a range of phenotypes and levels of penetrance and that, going forward, investigating the associations between disease severity and affected pathways could help pick out which pathways are the most relevant to disease. Eventually, he added, knowing which pathways are affected could help in screening patients as well as in choosing therapeutic approaches.

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