Longitudinal Cortical Development During Adolescence and Young Adulthood in Autism Spectrum Disorder: Increased Cortical Thinning but Comparable Surface Area Changes

Abstract

Objective Prior reports suggest that autism spectrum disorder (ASD) is associated with atypically excessive early brain growth. Recent cross-sectional studies suggest that later cortical development during adolescence/adulthood might also be aberrant, though longitudinal designs are required to evaluate atypical growth trajectories. The present study sought to examine longitudinal changes in cortical thickness and surface area among adolescents and young adults with ASD. Method Two (70 total) high-resolution anatomic magnetic resonance imaging scans approximately two years apart were acquired from 17 adolescents with ASD and 18 typically developing (TD) adolescents, matched on age (range=14–24 years old), IQ, sex ratio, and handedness. The FreeSurfer image analysis suite was utilized to quantify longitudinal changes in cortical thickness and surface area. Results Accelerated cortical thinning for the ASD group as compared to the TD group was found in two areas in the left hemisphere, the posterior portion of ventral temporal cortex and superior parietal cortex (cluster corrected p<.01). For ventral temporal cortex, cortical thinning was associated with everyday executive function impairments, and thinner cortex at time 2 was correlated with ASD social symptoms. Differences in surface area changes were not detected. Conclusion The present longitudinal study extends prior cross-sectional research by demonstrating increased cortical thinning (in portions of temporal and parietal cortex) but comparable surface area growth rates in ASD compared to TD controls during adolescence and into young adulthood. These findings provide further evidence for atypical cortical development beyond the early years in ASD marked by increased cortical thinning in late adolescence/young adulthood.

Mapping 22q11.2 Gene Dosage Effects on Brain Morphometry

“…As conventional subcortical volume analysis may obscure fine-grained differences in anatomical changes, a novel surface-based high-resolution parametric mapping technique was used to investigate shape differences across subjects for all subcortical regions of interest (ROIs) (Mamah et al, 2016). This technique is sensitive to subtle volumetric variations (Gutman et al, 2012(Gutman et al, , 2015 that may represent underlying subfield organization (Wang et al, 2008). It has recently shown high vertexwise heritability, suggesting that shape indexes a biologically valid phenotype (Roshchupkin et al, 2016).…”

“…We found opposing effects of CT and SA in in 22q-del versus 22q-dup in medial temporal and frontal brain regions strongly implicated in idiopathic schizophrenia (Palaniyappan et al, 2011;Shepherd et al, 2012), suggesting relevant underlying brain mechanisms that may be selective for schizophrenia. Alternatively, because both 22q-del and 22q-dup confer increased risk for ASD, opposing effects in common brain regions implicated in autism (Ecker et al, 2013;Wallace et al, 2015;Ohta et al, 2016) (e.g., decreased vs increased SA in medial frontal regions in 22q-del and 22q-dup, respectively) may result in similar downstream phenotypic effects on traits, such as language delay and reciprocal social behavior deficits. Future, prospective longitudinal brain-behavior investigations in these two groups are necessary to test these hypotheses.…”

Neuroimaging-Based Phenotyping of the Autism Spectrum

“…Studying a cross-sectional sample of adolescents and young adults with ASD and controls, for example, Wallace and colleagues observed more rapid age-related cortical thinning in temporal and parietal regions compared to controls (Wallace et al 2010). In two separate longitudinal studies, one including individuals aged 3-39 years (Zielinski et al 2014) and the other including individuals aged 14-24 years (Wallace et al 2015), researchers have also demonstrated accelerated thinning in ASD in adolescence. Overall, these data indicate that a comprehensive understanding of ASD may likely require accounting for its impact on dynamic brain changes from childhood into adulthood, in which complex morphological anomalies may vary over time throughout the life span.…”

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

“…Magnetic resonance imaging (MRI) studies have suggested that the pathogenesis of autism involves alterations to brain volume (Courchesne et al, 2001, Hazlett et al, 2005, McAlonan et al, 2005, Piven et al, 1995), as well as widespread region-specific differences across the brain, involving the cerebellum, amygdala, and thalamus (Hardan et al, 2006, Hazlett et al, 2005, Nacewicz et al, 2006, Schumann et al, 2004), among others (for review, see (Amaral et al, 2008, Anagnostou and Taylor, 2011, Ecker and Murphy, 2014, Lainhart, 2006, Verhoeven et al, 2010)). Similarly, diffusion tensor imaging (DTI) studies have further revealed differences across white matter microstructure (for review, see (Travers et al, 2012)), while other imaging strategies have associated ASD with alterations of cortical thickness (Hazlett et al, 2011, Wallace et al, 2015, Zielinski et al, 2014) and brain connectivity (Anderson et al, 2011, Belmonte et al, 2004, Just et al, 2012, Kleinhans et al, 2008, Vissers et al, 2012). Furthermore, group differences have been observed to be dynamic, as recent studies have highlighted disparities of developmental trajectories between individuals with and without autism (Hazlett et al, 2011, Lange et al, 2015, Travers et al, 2015b, Wolff et al, 2015, Wolff et al, 2012, Zielinski et al, 2014).…”