Cortical morphological markers in children with autism: a structural magnetic resonance imaging study of thickness, area, volume, and gyrification

Abstract

Background: Individuals with autism spectrum disorder (ASD) have been characterized by altered cerebral cortical structures; however, the field has yet to identify consistent markers and prior studies have included mostly adolescents and adults. While there are multiple cortical morphological measures, including cortical thickness, surface area, cortical volume, and cortical gyrification, few single studies have examined all these measures. The current study analyzed all of the four measures and focused on pre-adolescent children with ASD.

Methods: We employed the FreeSurfer pipeline to examine surface-based morphometry in 60 high-functioning boys with ASD (mean age = 8.35 years, range = 4-12 years) and 41 gender-, age-, and IQ-matched typically developing (TD) peers (mean age = 8.83 years), while testing for age-by-diagnosis interaction and between-group differences.

Results: During childhood and in specific regions, ASD participants exhibited a lack of normative age-related cortical thinning and volumetric reduction and an abnormal age-related increase in gyrification. Regarding surface area, ASD and TD exhibited statistically comparable age-related development during childhood. Across childhood, ASD relative to TD participants tended to have higher mean levels of gyrification in specific regions. Within ASD, those with higher Social Responsiveness Scale total raw scores tended to have greater age-related increase in gyrification in specific regions during childhood.

Conclusions: ASD is characterized by cortical neuroanatomical abnormalities that are age-, measure-, statistical model-, and region-dependent. The current study is the first to examine the development of all four cortical measures in one of the largest pre-adolescent samples. Strikingly, Neurosynth-based quantitative reverse inference of the surviving clusters suggests that many of the regions identified above are related to social perception, language, self-referential, and action observation networks-those frequently found to be functionally altered in individuals with ASD. The comprehensive, multilevel analyses across a wide range of cortical measures help fill a knowledge gap and present a complex but rich picture of neuroanatomical developmental differences in children with ASD.

Keywords: Autism spectrum disorder; Brain development; Brain structure; Neuroanatomy; Surface-based morphometry.

Fig. 1

Clusters exhibiting significant age-by-diagnosis interaction effects on a cortical thickness, b cortical volume, and c cortical gyrification. The effects are illustrated by representative scatterplots. Results were corrected for multiple comparisons using cluster analysis, p < 0.05, two-sided. There were no surviving clusters for surface area. The numeric labels indicate distinct clusters, and the corresponding information associated with each cluster can be found in the tables. Dark gray = sulci; light gray = gyri

Fig. 2

Clusters exhibiting significant between-group differences independent of age on cortical gyrification. The effects are illustrated by a representative boxplot. Results were corrected for multiple comparisons using cluster analysis, p < 0.05, two-sided. There were no surviving clusters for cortical thickness, surface area, and cortical volume. The numeric labels indicate distinct clusters, and the corresponding information associated with each cluster can be found in the tables. Dark gray = sulci; light gray = gyri

Fig. 3

Clusters exhibiting significant age-by-SRS total raw scores interaction effects within the ASD group on cortical gyrification. The effects are illustrated by a representative interaction plot using predicted gyrification values conditional upon high and low levels of SRS total raw scores (M ± 1 SD) and high and low levels of age (M ± 1 SD). The error bars indicate standard errors of the mean. There were no surviving clusters for cortical thickness, surface area, and cortical volume. The numeric labels indicate distinct clusters, and the corresponding information associated with each cluster can be found in the tables. Dark gray = sulci; light gray = gyri