This study from Weill Cornell Medicine investigators leveraged machine learning to analyze neuroimaging data from 299 people with autism and 907 neurotypical people. They found patterns of brain connections linked with behavioral traits in people with autism, such as verbal ability, social affect, and repetitive or stereotypic behaviors. The study confirmed that the four autism subgroups could also be replicated in a separate dataset and showed that differences in regional gene expression and protein-protein interactions explain the brain and behavioral differences. This work highlights a new approach to discovering subtypes of autism that might one day lead to new approaches for diagnosis and treatment.
