Scientific Abstract
Background: There is increasing evidence that alterations in brain morphology associated with Autism Spectrum Disorder (ASD) are present on a continuum with autistic traits in the general population. Investigating relationships between autistic traits and brain structure may provide insight into the biological processes underlying autistic traits. However, only a few studies have examined brain measures of cortical thickness and surface area in population-based samples thus far, and findings have been mixed.
Methods: We included 8,830 children aged 9–10 from the population-based Adolescent Brain Cognitive Development (ABCD) Study collected across 21 sites in the United States. The presence and severity of autistic traits (e.g., difficulties with social communication, narrow range of interests) were measured using the 11-item parent-report Social Responsiveness Scale (SRS) collected at 1 year follow-up. Mean cortical thickness and total surface area were determined using T1w magnetic resonance imaging (MRI) data collected at baseline and processed using Freesurfer. Linear mixed-effect models were used to investigate the relationship between the total SRS score and imaging measures, while controlling for sex, age at MRI, and race as fixed effects, and site as a random effect.
Results: At least one autistic trait was endorsed by 80% of children. Total SRS score was significantly higher in males compared to females (W= 8,508,951, p=< 2.2e-16). Total SRS also significantly varied by race (H = 46.4, p=7.4e-09). Mean cortical thickness was significantly decreased (b=-5.70e-04, p=0.02) with increased total SRS scores. Total surface area was also significantly decreased (b=-174.79, p=6.8e-06) with increased total SRS scores. There were no significant interactions between SRS score and sex on imaging measures.
Conclusion: We find evidence that increased autistic traits are associated with both decreased mean cortical thickness and total surface area in children aged 9-10. Further work is needed that examines specific brain regions and the role of other contributing factors to understand better how alterations may underlie autistic traits.