Abstract
Understanding heterogeneity in neural phenotypes is an important goal on the path to precision medicine for autism spectrum disorders (ASD). Age is a critically important variable in normal structural brain development and examining structural features with respect to age-related norms could help to explain ASD heterogeneity in neural phenotypes. Here we examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of deviance relative to typically-developing (TD) age-related norms. Across a large sample (n=942 per group) and wide age range (5-40 years), we applied a normative modelling approach that provides individualized whole-brain maps of age-related CT deviance in ASD. This approach isolates a highly age-deviant CT subtype with a median prevalence of 7.6% across all brain regions and prevalence within specific regions that can be greater than 10%. Individuals in this ASD subtype are statistical outliers in case-control models and this small subset of individuals drives a large majority of small effect results from case-control comparisons. Testing age-normed CT scores also highlights on-average differentiation and associations with behavioural symptomatology that is separate from insights gleaned from traditional case-control approaches. This work showcases a novel individualized approach for understanding ASD heterogeneity that could further prioritize work on a subset of individuals with significant cortical pathophysiology represented in age-related CT deviance.