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Brain Morphometry Abnormalities in Patients with Autism Spectrum Disorders and Schizophrenia: Same or Different?

Thursday, 2 May 2013: 14:00-18:00
Banquet Hall (Kursaal Centre)
14:00
M. Assaf1, A. Ahmadi2, C. Hyatt2, C. A. Berwise2 and G. Pearlson3, (1)200 Retreat Ave., Institute of Living, Hartford Hospital / Yale University, Hartford, CT, (2)Institute of living/Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, (3)Institute of Living, Hartford Hospital / Yale University, Hartford, CT
Background: Although autism spectrum disorders (ASD) and schizophrenia (SZ) have distinct clinical symptomatology, recent studies suggest that they may share common deficits in social skills and underlying etiopathology. Recent neuroimaging techniques have demonstrated brain morphometric abnormalities in both SZ and ASD patients, with potential overlaps. More specifically, structural brain studies in ASD patients suggest that as for SZ, abnormal volume and cortical thickness (most likely thinning) might underlie the neuropathology of the disease. Direct comparisons between these two patient groups, however, have not yet been performed to determine which brain regions have common versus distinctive structural abnormalities.

Objectives: The major goal of this pilot study was to study the brain structure in both SZ and ASD patients in comparison to matched healthy controls (HC) to explore structural abnormalities, commonalities and differences in brain structure in SZ and ASD. We hypothesized that while SZ and ASD will demonstrate unique deficits they will also share some abnormalities. 

Methods: In this study we analyzed the morphometric parameters of structural MRI (sMRI) data (MPRAGE sequence) collected at the Olin Center from 14 high-functioning ASDs (Autistic disorder, Asperger’s syndrome and PDD-NOS), 19 chronic SZ patients (schizoaffective patients were excluded) and 19 HC, ages 15 to 30, with normal range IQ (>80). Groups were matched on sex, race, full-scale IQ and handedness. Structural data were analyzed using FreeSurfer tools (version 5.1, http://surfer.nmr.harvard.edu) to measure local gyrification index (LGI).

Results: For LGI, one-way ANOVA demonstrated a main effect of group in left inferior frontal gyrus (IFG), superior temporal gyrus (STG) and sulcus (STS) and inferior parietal lobule (IPL), as well as lingual and fusiform gyri; and in right inferior temporal sulcus (ITS) (significant following Monte Carlo simulation at a cluster-wise probability of p<0.05 FWE). Follow-up t-tests demonstrated that for left IFG both SZ and ASD groups showed reduced LGI compared to HC. Group-specific LGI abnormalities were seen in right ITS and left STS/IPL and fusiform gyrus, where only SZ showed lower LGI, compared to HC and ASD.  

Conclusions: In this pilot study we directly compared brain morphometry of ASD and SZ patients to HC and found reduced cortical gyrification in IFG in both patient groups. Conversely, parietal and temporal regions showed diagnosis-specific abnormalities in cortical gyrification. Importantly, all implicated regions are known to be involved in cognitive processes related to social functioning and language, domains that are deficient in both SZ and ASD. Implications for patients’ diagnosis and symptoms will be discussed.

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