The Neuroanatomy of Autism Spectrum Disorder in 22q11.2 Deletion Syndrome

Poster Presentation
Friday, May 11, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
M. Gudbrandsen1, E. Daly1, R. H. Wichers1,2, C. M. Murphy1,2, V. Stoencheva1,2, E. Perry1,2, D. S. Andrews3, D. G. Murphy4, C. Ecker5, L. Kushan6, C. Bearden6 and M. Craig1,2, (1)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, (2)Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, United Kingdom, (3)Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California Davis, Sacramento, CA, (4)Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (5)Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-University Frankfurt am Main, Frankfurt, Germany, (6)University of California, Los Angeles, CA
Background: Individuals with syndromic forms of autism spectrum disorder (ASD) provide a unique opportunity to understand specific genetic risk mechanisms. For example, individuals with 22q11.2 Deletion Syndrome (22q11DS) have a 30-50% risk of developing ASD (Schneider et al., 2014). The neurobiological mechanisms contributing to this increased risk are unknown, but likely include genetically-determined differences in specific developmental pathways. We, and others, previously reported that individuals with ASD and 22q11DS both have significant differences in cortical volume(CV), surface area(SA) and cortical thickness(CT) (Ecker et al., 2013; Jalbrzikowski et al., 2013). In the present study, we examined the relationship between brain anatomy and ASD symptomatology in individuals with 22q11DS based on different diagnostic criteria, as it remains currently unknown to what extent the clinical ASD phenotype in the context of the 22q11.2 microdeletion resembles the clinical ASD phenotype in non-22q11DS individuals. For instance, clinical studies reliably report significant social/communication impairments in 22q11DS, while repetitive/stereotyped behaviours are less common (Wenger et al., 2016). We thus subdivided individuals based on ASD-symptoms in the social/communication and repetitive domains separately, in order to elucidate their respective neuroanatomical correlates.

Objectives: To establish whether 22q11DS individuals with ASD symptomatology are neuroanatomically distinct from those without.

Methods: We included 55 individuals with 22q11DS (27 male/28 female), age range 6-31 years (mean age=14+6 years). Of these, 10 (i.e. 18%) met strict diagnostic criteria based on the ADI-R cut-offs in all three domains (abbreviated as 22q11.ASD), and 30 (i.e. 55%) met the diagnostic cut-offs in the social/communication domain only (22q11.SC). Both ASD groups were matched on age and full-scale IQ to their respective controls. Participants underwent structural T1-weighted magnetic resonance imaging (MRI) at the Institute of Psychiatry, Psychology and Neuroscience, London and the Semel Institute for Neuroscience, UCLA. Vertex-wise measures of CV, CT and SA were derived using FreeSurfer v6.0.0 software (http://surfer.nmr.mgh.harvard.edu), and analysed by regression of a GLM including group, gender and IQ as categorical fixed effect factors. Corrections for multiple comparisons across the whole brain were performed using a random-field-based cluster-threshold(p<0.05) (Worsley et al., 1999).

Results: There were no difference in brain anatomy when applying gold-standard diagnostic criteria for ASD in all three domains. However, when applying a more lenient cut-off in the restricted/repetitive behaviour domain, we found significantly increased CV in the left dorsolateral prefrontal & posterior cingulate cortex, in 22q11.SC compared to their respective controls, which was driven by a commensurate increase in SA. Furthermore, increased SA was found in the right temporo-parietal-junction, middle & superior temporal sulcus, and inferior temporal gyrus. Last, we found that individuals with 22q11.SC had significantly decreased CV and SA in the left entorhinal cortex. We did not observe any significant differences in CT.

Conclusions: Individuals with 22q11DS and ASD symptomatology, predominantly in the social/communication domains, are neuroanatomically distinct from those without. The spatially distributed network of volumetric differences associated with the autistic symptoms in 22q11DS has previously been linked to wider ASD symptoms and traits, and might provide useful information for patient stratification and predictions of clinical outcomes in the future.