Brain structure anomalies in autism spectrum disorder—a meta‐analysis of VBM studies using anatomic likelihood estimation

Abstract

Autism spectrum disorders (ASD) are pervasive developmental disorders with characteristic core symptoms such as impairments in social interaction, deviance in communication, repetitive and stereotyped behavior, and impaired motor skills. Anomalies of brain structure have repeatedly been hypothesized to play a major role in the etiopathogenesis of the disorder. Our objective was to perform unbiased meta-analysis on brain structure changes as reported in the current ASD literature. We thus conducted a comprehensive search for morphometric studies by Pubmed query and literature review. We used a revised version of the activation likelihood estimation (ALE) approach for coordinate-based meta-analysis of neuroimaging results. Probabilistic cytoarchitectonic maps were applied to compare the localization of the obtained significant effects to histological areas. Each of the significant ALE clusters was analyzed separately for age effects on gray and white matter density changes. We found six significant clusters of convergence indicating disturbances in the brain structure of ASD patients, including the lateral occipital lobe, the pericentral region, the medial temporal lobe, the basal ganglia, and proximate to the right parietal operculum. Our study provides the first quantitative summary of brain structure changes reported in literature on autism spectrum disorders. In contrast to the rather small sample sizes of the original studies, our meta-analysis encompasses data of 277 ASD patients and 303 healthy controls. This unbiased summary provided evidence for consistent structural abnormalities in spite of heterogeneous diagnostic criteria and voxel-based morphometry (VBM) methodology, but also hinted at a dependency of VBM findings on the age of the patients.

Early Screening of Autism Spectrum Disorder: Recommendations for Practice and Research

“…Given that neuroanatomical abnormalities in ASD have been shown to occur consistently across development, 96,97 and biological mechanisms (including genetic) may provide a measurable "signature" even before symptom expression, there is hope that specific biomarkers may eventually be identified that could contribute to early diagnosis. Indeed, recent studies from developmental neuroscience and molecular biology have shown promise in identifying specific markers that can distinguish children with ASD from other high-risk and low-risk peers, even during infancy.…”

Right Temporoparietal Gray Matter Predicts Accuracy of Social Perception in the Autism Spectrum

“…However, other studies have found gray matter increases in some of these and other regions in ASD, making the current picture on structural brain differences in ASD somewhat inconsistent (Amaral et al 2008). These inconsistencies may be related to the recently often discussed heterogeneity in the spectrum, as well as between-study differences with respect to functionality and age of the ASD group (Brambilla et al 2003;Nordahl et al 2007;Amaral et al 2008;Nickl-Jockschat et al 2011). …”

Correlation between Morphologic Changes and Autism Spectrum Tendency in Obsessive-Compulsive Disorder

“…In ASD, NicklJockschat and associates reported disturbances in several regions, including the lateral occipital lobe, pericentral region, medial temporal lobe, and basal ganglia and proximate to the right parietal operculum, 10 and Via and associates found robust decreases in GM volume in the bilateral amygdala-hippocampus complex and the bilateral precuneus as well as a small increase in the middle-inferior frontal gyrus. 11 Though the sample sizes of both metaanalyses were sufficient (277 patients with ASD and 303 controls 10 ; 496 patients with ASD and 471 controls 11 ), their results were totally different, which may be attributable to their different statistical approaches (activation likelihood estimation [ALE] 12 and signed differential mapping [SDM] 13 ). Though we see some overlapped regions between ASD and OCD, little is known about the association between these 2 disease entities.…”