Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1,985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision making.

Atypical cortical organization and reduced integrity of the gray–white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray–white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray–white matter interface, which indicates a less distinct gray–white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well-defined gray–white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition, which is accompanied by differences in gray matter neuroanatomy and white matter connectivity. However, it is unknown whether these differences are linked or reflect independent aetiologies. Using a multimodal neuroimaging approach, we therefore examined 51 male adults with ASD and 48 neurotypical controls to investigate the relationship between gray matter local gyrification (lGI) and white matter diffusivity in associated fiber tracts. First, ASD individuals had a significant increase in gyrification around the left pre- and post-central gyrus. Second, white matter fiber tracts originating and/or terminating in the cluster of increased lGI had a significant increase in axial diffusivity. This increase in diffusivity was predominantly observed in tracts in close proximity to the cortical sheet. Last, we demonstrate that the increase in lGI was significantly correlated with increased diffusivity of short tracts. This relationship was not significantly modulated by a main effect of group (i.e., ASD), which was more closely associated with gray matter gyrification than white matter diffusivity. Our findings suggest that differences in gray matter neuroanatomy and white matter connectivity are closely linked, and may reflect common rather than distinct aetiological pathways.

These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.