Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Abstract

Background: Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods: Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results: We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions: These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Figure 1.. Study demographics and methods overview.

A. Box and violin plots representing age distribution of each study by diagnostic group and sex. B. Methods overview. Global cortical and subcortical grey matter volume (GMV, sGMV), white matter volume (WMV), and ventricular cerebrospinal fluid (CSF) volume, and regional cortical thickness, volume and surface area based on the Desikan-Killiany (DK) parcellations were estimated for each participant. Sex-specific lifespan developmental trajectories for each neuroanatomical measure were estimated using generalised additive models of location scale and shape (GAMLSS) for a sample of 75,241 typically developing individuals, accounting for site and scanner specific variables . Out-of-sample estimates for the study sample used here were generated based on these reference models, resulting in a (per)centile score for each measure of each participant, indicating where they fall within the sample range (0–1).

Figure 2.. Case-control differences in global and regional centile scores of structural MRI metrics.

A. Box and raincloud plots showing group differences in global neuroanatomical measures. Raincloud plots show the density distribution of centiles per group. Autistic individuals had significantly larger ventricles than TD individuals, but no differences were observed in any other measures. Individuals with ADHD had significantly lower cortical grey, white, and subcortical grey matter volume and total surface area centiles relative to controls, but greater mean cortical thickness centiles. B. Regional group differences. Brain maps show Cohen’s d effect sizes, with significant regions (passing 5% FDR) outlined in black. Red represents positive effect sizes (autism or ADHD > controls), and blue represents negative effect sizes (autism or ADHD < controls). Overall, autistic individuals had significantly greater cortical volume and thickness in the superior temporal gyrus; whereas individuals with ADHD had significant and widespread decreases in cortical volume and surface area, and increases in cortical thickness.

Figure 3.. Interactions between sex and diagnostic group on centile scores of regional MRI metrics.

A. Brain maps showing effect sizes and significance of interaction per brain region, and box and violin plots showing comparison of values broken down by group for two significant regions. B. Sex-stratified regional association with diagnosis. All maps show Cohen’s d effect sizes, with significant regions (passing 5% FDR) outlined in black. Red represents positive effect sizes (autism or ADHD > controls), and blue represents negative effect sizes (autism or ADHD < controls).

Figure 4.. Regional interactions between diagnosis and age.

Brain maps show interaction effect sizes and regional significance, and scatter plots show the relationship between CT and age in the autism/ADHD and TD groups in regions where a significant interaction was observed.

Figure 5.. Cortical alterations (relative to controls) in individuals with co-occurring autism and ADHD and overlap of effect size significance and direction.

A. Main effects of diagnosis relative to controls; interaction with sex; main effects in males, and main effects in females. All maps show Cohen’s d effect sizes, with significant regions (passing 5% FDR) outlined in black. Red represents positive effect sizes (autism+ADHD > controls), and blue represents negative effect sizes (autism+ADHD < controls). B. Brain maps showing the pairwise overlap of effect size direction and significance for the autism, ADHD and autism+ADHD groups. Regions which had a positive effect size in both groups’ analysis (in comparison to controls) are shown in red; regions which had a negative effect size in both groups are shown in blue. Regions in white were in discordant directions between groups. Regions which were significantly different from controls in both groups are outlined in black. Note that the superior temporal gyrus showed a significant effect in both autism and ADHD for cortical volume, but in opposite directions.