31079
Atypical Scaling between the Inner and Outer Curvature of the Brain in Autism Spectrum Disorder
Oral Presentation
Thursday, May 2, 2019: 2:54 PM
Room: 517B (Palais des congres de Montreal)
T. Schäfer1, C. Mann1, A. Bletsch1, E. Loth2, D. G. Murphy3, J. K. Buitelaar4, T. Charman5, T. Banaschewski6, S. Baron-Cohen7, S. Bolte8, S. Durston9, L. G. EU-AIMS10 and C. Ecker1,11, (1)Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-University Frankfurt am Main, Frankfurt, Germany, (2)Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (3)Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (4)Radboud University Medical Center Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, Netherlands, (5)Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (6)Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany, (7)Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, (8)Center for Neurodevelopmental Disorders (KIND), Center for Psychiatry Research, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden, (9)Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands, (10)EU-AIMS Organization, London, United Kingdom, (11)Department of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is accompanied by an atypical brain development. Neuroanatomical abnormalities in ASD include differences in surface area and cortical thickness, as well as atypical patterns of cortical gyrification or folding (Ecker et al., 2015). Some evidence suggests that cortical gyrification is driven by a differential expansion of the upper and lower cortical layers (Richman et al., 1975), which is expected to affect the curvature of the inner and outer surface of the brain in an idiosyncratic fashion (Ronan et al., 2013). This hypothesis is also supported by (i)
post mortem reports of an atypical cortical lamination in ASD (Avino et al., 2010), and (ii) genetic studies indicating that ASD-related genes are not equally expressed across all cortical layers but affect some cortical layers more than others (Parikshak et al., 2013; Willsey et al., 2013). However, this hypothesis has not yet been addressed
in vivo.
Objectives: The present study aimed to establish whether the difference between the inner and outer curvature (Dcurv) of the brain differs between individuals with ASD and neurotypical controls.
Methods: 166 males with ASD (inclusion based on ADI-R score and FSIQ³80) and 164 neurotypical controls, aged 7-31 years were assessed at six European sites as part of the EU-AIMS Longitudinal European Autism Project (LEAP) (Loth et al., 2017). For all 330 participants, high-resolution structural T1-weighted volumetric images were obtained. Cortical surface models were derived using the FreeSurfer v6.0 image analysis suite (http://surfer.nmr.mgh.harvard.edu/). The Dcurv was calculated as the difference between the mean curvature on the inner and outer cortical surface and mapped to a common space template for group comparison. Parameter estimates for Dcurv were derived using a general linear model (GLM) at each vertex with (1) group and site as categorical fixed-effects factors, (2) linear age, as well as an age-by-group interaction, as well as (3) cortical thickness and FSIQ as continuous covariates. Corrections for multiple comparisons were performed using random-field theory (RFT)-based cluster-corrected analysis for non-isotropic images using a p=0.05 (two-tailed) cluster significance threshold.
Results: There was no significant difference in age between groups [t(328)=0.322, p=0.747]. However the groups differed in FSIQ [t(328)=2.692, p=0.007]. In ASD, we established that the Dcurv was significantly reduced relative to neurotypical controls predominantly in brain regions of the frontal and parietal lobes (RFT-based cluster corrected, p<0.05). A significant increase in Dcurv in ASD was observed in the anterior and posterior cingulate cortex (see Figure 1). In the right prefrontal cortex, measures of Dcurv were also negatively correlated with symptom severity in the ADI-R domain of social interaction (r=-0.18, p<.05), as well as in the domain of restricted and repetitive behaviours (r=-0.2, p<.05).
Conclusions: Our findings suggest that the scaling between outer and inner curvature of the brain may be atypical in ASD, possibly mediated by altered differential expansion of the inner and outer cortical layers. Measures of Dcurv may thus be used to guide future studies into layer-specific cortical development, and to stratify ASD individuals into biologically more homogeneous subgroups.
