A study led by Baylor College of Medicine researchers identified a novel computational approach for identifying genes most likely associated with autism spectrum disorders (ASD), and to predicting the severity of intellectual disability in ASD patients as a result.
The team fed a massive volume of evolutionary data to their analyses on mutations' contribution to protein evolution, and on the impact of human variants on protein function.
Researchers concentrated on de novo missense variants in particular, to identify mutations that differentiate ASD patients and unaffected siblings.
The Baylor researchers used the Evolutionary Action equation to assess the impact of each missense mutation on a corresponding protein.
Baylor’s Young Won Kim said the results suggest new genes to study, and “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.”
From Baylor College of Medicine
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