Network over‐connectivity differentiates autism spectrum disorder from other developmental disorders in toddlers: A diffusion MRI study

Abstract

Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other-DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other-DD including intellectual disability and language disorder) according to DSM-IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (D ) and the tract-averaged fractional anisotropy (D ) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other-DD groups. The network differences resulted in an over-connectivity pattern (i.e., higher D and D values) in the ASD group with a significance of P < 0.05. No contra-comparison results were found. The over-connectivity pattern in ASD occurred in networks primarily involving the fronto-temporal nodes, known to be crucial for social-skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network-based diffusion study comparing toddlers with ASD and those with other-DD. Results indicate the detection of different connectivity patterns in ASD and other-DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333-2344, 2017. © 2017 Wiley Periodicals, Inc.

The journey to autism: Insights from neuroimaging studies of infants and toddlers

“…Seed-based, resting-state functional connectivity between the amygdala and canonical targets is reduced in preschool-aged children with ASD (Shen et al, 2016), consistent with what might be expected given increased amygdala volumes and atypical FA in limbic regions such as the uncinate and the inferior longitudinal fasciculi (Conti et al, 2017; Solso et al, 2016; Wolff et al, 2012; Xiao et al, 2014). A series of studies from Courchesne et al also indicates atypical connectivity in language areas, patterns of which have been associated with measures of receptive and expressive language function (Dinstein et al, 2011; Eyler et al, 2012; Lombardo et al, 2015; Redcay & Courchesne, 2008).…”

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

“…In addition, it is not clear from the reviewed studies if changes in WM volume occur with autism. Although structural MRI is ideal for capturing longitudinal changes in brain structure, investigations into WM may benefit from diffusion MR imaging (Conti et al, 2017), in order to probe the microstructure of the brain and elucidate any changes in connectivity associated with ASD (Jou et al, 2011). Although the amygdala has known biological roles with social and communicative function which are directly associated with symptoms indicative of ASD, findings on changes in amygdala volume were mixed across the reviewed studies.…”

“…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).…”

Development of White Matter Circuitry in Infants With Fragile X Syndrome

“…33 The white matter development observed in infants with FXS in our study appear to be distinct from those reported in similar studies of nonsyndromic ASD. 26,34,35 Infants and toddlers with ASD are reported to show higher initial FA followed by a period of relatively slower white matter development thereafter. 26,34 This finding is in contrast with the low and stable FA we observed in infants with FXS, and is consistent with previous work indicating that the neural signature of FXS may be distinct from that of idiopathic ASD.…”