Brain anatomy of autism spectrum disorders I. Focus on corpus callosum

Abstract

This Section of Epidemiology and Psychiatric Sciences regularly appears in each issue of the Journal to describe relevant studies investigating the relationship between neurobiology and psychosocial psychiatry in major psychoses. The aim of these Editorials is to provide a better understanding of the neural basis of psychopathology and clinical features of these disorders, in order to raise new perspectives in every-day clinical practice. This brief review aims to examine the structural magnetic resonance imaging (sMRI) studies on corpus callosum in autism spectrum disorders (ASD) and discuss the clinical and demographic factors involved in the interpretation of results.

Targeted disruption of the mouse protein phosphatase ppm1l gene leads to structural abnormalities in the brain

“…Notably, some patients with mutations in PPP2R1A, encoding the scaffolding Aa subunit of PP2A, exhibit enlarged ventricles with agenesis or hypoplasia of the corpus callosum; this is consistent with the phenotype observed in ppm1l D/D mice [26]. Consistent with the functional role of callosal fibers in higher order cognition by connecting two cerebral hemispheres, accumulating evidence indicates that impaired formation of callosal fiber tracts such as corpus callosum is a common feature of neurodevelopmental disorders, including attention-deficit hyperactivity disorder (ADHD) and autistic spectrum disorder (ASD) [28,29]. In the present behavioral analysis, ppm1l D/D mice exhibited abnormalities in motor coordination and balance.…”

The effect of age, sex and clinical features on the volume of Corpus Callosum in pre‐schoolers with Autism Spectrum Disorder: a case–control study

“…Crucially, when our data were separated according to median age (≤49 months and >49 months), it became evident that the absence of CC volume differences between patients and controls was driven by the older ASD subjects, as younger male individuals with ASD displayed a statistically significant increase of CC volume compared with sex and age‐matched controls. This result suggests an atypical CC growth trajectory in subjects with ASD, characterised by a greater development in early ages, followed by a slower rate of growth in subsequent ages, resulting in smaller CC in adolescent and adult patients (Bellani et al., ). An increase in CC volume at 6 and 12 months of age in infants who later develop ASD, relative to TD infants, corroborates this hypothesis (Wolff et al., ).…”

“…Among long‐distance WM structures, the corpus callosum (CC) is the largest commissural tract in the human brain connecting the left and right hemispheres and it is thought to be involved in the integration of neural information across distant brain regions. For this crucial role, the CC has been frequently implicated in the pathogenesis of ASD (for recent reviews, see Frazier and Hardan, ; Bellani et al., ), because problems with processing of multiple source of sensory information are common in ASD patients (Iarocci & McDonald, ), and are possibly sustained by the specific combination of a local overconnectivity and a long‐distance under‐connectivity (Kana et al., ). In keeping with this theory, the increased length of CC fibres was directly related to reductions in interhemispheric connectivity and CC size in adults with ASD (Lewis et al., ).…”

A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective

“…However the exact etiopathogenesis of ASD remains unclear, with predominant theories proposing genetic factors affecting cortical migration (Nickl‐Jockschat and Michel, 2011) and synaptic regulation (Takahashi et al, 2012), and altered developmental processes leading to both hypo‐ and hyper‐connectivity in different brain regions (Conti et al, 2017; Kana et al, 2014; Muller et al, 2011), specifically local over‐connectivity, long distance under connectivity (Wass, 2011), and excessive growth in several brain regions (Polšek et al, 2011). Consequently, there have been a wide range of structural brain regions implicated with ASD, most commonly that of early brain overgrowth and head circumference (Mosconi et al, 2009; Sacco et al, 2015), as well as more localised brain regions that may be associated with the social and motor impairments characteristic of ASD, including the frontal lobes, amygdala, cerebellum (Amaral et al, 2008; Li et al, 2017; Sivapalan and Aitchison, 2014), corpus callosum (Bellani et al, 2013; Hrdlicka, 2008; Stigler et al, 2011) and basal ganglia (Calderoni et al, 2014; Dougherty et al, 2016a). However, there has not yet been an agreement on structural changes in the brain that reflect these underlying mechanisms of ASD, limiting the utility of machine learning to provide accurate diagnoses of ASD and patient prognoses (Kassraian‐Fard et al, 2016).…”