Atypical sulcal anatomy in young children with autism spectrum disorder

Abstract

Autism spectrum disorder is associated with an altered early brain development. However, the specific cortical structure abnormalities underlying this disorder remain largely unknown. Nonetheless, atypical cortical folding provides lingering evidence of early disruptions in neurodevelopmental processes and identifying changes in the geometry of cortical sulci is of primary interest for characterizing these structural abnormalities in autism and their evolution over the first stages of brain development. Here, we applied state-of-the-art sulcus-based morphometry methods to a large highly-selective cohort of 73 young male children of age spanning from 18 to 108 months. Moreover, such large cohort was selected through extensive behavioral assessments and stringent inclusion criteria for the group of 59 children with autism. After manual labeling of 59 different sulci in each hemisphere, we computed multiple shape descriptors for each single sulcus element, hereby separating the folding measurement into distinct factors such as the length and depth of the sulcus. We demonstrated that the central, intraparietal and frontal medial sulci showed a significant and consistent pattern of abnormalities across our different geometrical indices. We also found that autistic and control children exhibited strikingly different relationships between age and structural changes in brain morphology. Lastly, the different measures of sulcus shapes were correlated with the CARS and ADOS scores that are specific to the autistic pathology and indices of symptom severity. Inherently, these structural abnormalities are confined to regions that are functionally relevant with respect to cognitive disorders in ASD. In contrast to those previously reported in adults, it is very unlikely that these abnormalities originate from general compensatory mechanisms unrelated to the primary pathology. Rather, they most probably reflect an early disruption on developmental trajectory that could be part of the primary pathology.

Keywords: Autism; MRI; morphometry; sulci.

Fig. 1

A dedicated segmentation pipeline was developed by combining VBM8, SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/), Freesurfer (http://surfer.nmr.mgh.harvard.edu/) and BrainVISA (http://brainvisa.info/index.html) in order to cumulate their strength. It results in a set of sulcal pieces, each sulcal part being associated with a set of shape descriptors. The 4 steps are detailed in the text and supplementary materials and the sulcal attributes are illustrated in panel 4: sulcal pieces that are colored following a) anatomical denomination, b) mean depth, c) maximum depth and d) area of the folds.

Fig. 2

Illustration of the sulcal nomenclature and shape descriptors used in the current work. A) The nomenclature of sulci used in this study. It can be compared with the finest-scale nomenclature of 59 sulcal pieces available in BrainVISA (http://www.lnao.fr/IMG/png/brainvisa_sulci_atlas_with_table_150dpi-r90.png). B) Illustration of the sulcus shape descriptors used in this work for the left central sulcus of an individual. The depth of the central sulcus is known to vary, due to the presence of a buried gyrus (Cykowski et al., 2008). The depth is computed for each point at the bottom of the fold as the distance to the hull, following the sulcus (in orange). The mean depth is the average of the depth across all bottom points and the maximum depth corresponds to the maximal value (in blue). The length is illustrated in green and the area of the sulcus corresponds to the area of the sulcus tessellation shown here as a red ribbon.

Fig. 3

Main effect of diagnostic group on sulcal shape descriptors: sulcal index, length, maximum depth and mean depth. The sulci in red have a p < 0.05/21 i.e., p < 0.05 after Bonferroni correction, the sulci in blue have a p < 0.01 uncorrected and the sulci in black have a p < 0.05 uncorrected, see text for details.

Fig. 4

Sulcal shape descriptors showing a significant age by group interaction. We show a scatter plot of each of these descriptors as a function of age (CTR as blue circles and AUT as red crosses), with the within group linear regression with age (blue line for CTR and red line for AUT).