Normative age modelling of cortical thickness in autistic males

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 agerelated CT deviance.

Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder

“…While many other neuroimaging studies of ASD have reported greater cortical thickness values 5,15,31 , others have reported lower thickness 65 , or no differences 9 . Our findings of greater CT in ASD are largely in agreement with other large-scale neuroimaging studies, including studies using the ABIDE dataset 5,15,16,66 and recent findings by the ENIGMA consortium 6 . However, the recent ENIGMA study, in addition to greater CT in ASD in the frontal and posterior cingulate cortices, also reports significantly less CT in ASD in the temporal and parahippocampal cortices.…”

“…Results of studies examining different age ranges of ASD, in particular in those with small sample sizes, are often conflicting or inconsistent. Recent large scale studies examining wide age ranges that have attempted to reconcile these inconsistencies have reported cortical thickness differences in childhood and early adolescence, followed by normalisation of group differences later in life 5,6,66 . While we cannot strictly make inferences about cortical development from our cross-sectional dataset, here, we seem to recapitulate these results to an extent, though the results observed in our age-centred analysis are subtle.…”

Big data approaches to decomposing heterogeneity across the autism spectrum

“…Regression, a developmental feature seen in autistic individuals, is another key stratifier that is surprisingly under-studied but with plausible unique biological bases [95,96]. Within the developmental dimension, heterogeneity can be assessed as both inter-and intra-individual variability, but can also cover individualized deviance from group trajectories over time- [38] or age-specific norms [97,98]. Chronogeneity thus offers a unique vantage point on multi-level heterogeneity not covered by understanding heterogeneity at static time points.…”

From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder

“…The deviating participants were in many cases quite extreme, which suggests a possible reason for inconsistencies in case-control studies (Bethlehem et al, 2018). Therefore, the description of patients on the group level is certainly not sufficient, a cluster level description may not be refined enough to capture the complexity of ASD, which may, in fact, be relatively patient specific.…”