Sex and Diagnosis Effects on Microstructural White Matter Properties in Individuals with Autism Spectrum Conditions

Saturday, May 19, 2012: 11:00 AM
Grand Ballroom East (Sheraton Centre Toronto)
10:15 AM
A. N. Ruigrok1, M. V. Lombardo2, M. C. Lai2, F. dell'Acqua3, M. Catani3, J. Suckling4, B. Chakrabarti1,5, M. Craig6, D. G. Murphy7, U. K. MRC AIMS Consortium8 and S. Baron-Cohen2, (1)Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, (2)Autism Research Centre, University of Cambridge, Cambridge, United Kingdom, (3)Section of Brain Maturation, Department of Psychological Medicine and Psychiatry, Institute of Psychiatry, King's College London, London, United Kingdom, (4)Brain Mapping Unit, University of Cambridge, Cambridge, United Kingdom, (5)Centre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, United Kingdom, (6)Institute of Psychiatry, King's College London, London, United Kingdom, (7)Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King's College London, London, United Kingdom, (8)Institute of Psychiatry, King's College London; University of Cambridge; University of Oxford, London, United Kingdom
Background: Autism spectrum conditions (ASC) affect more males than females. Many studies are either exclusively male or reflect the skewed population sex ratio. Such studies neglect females and overlook the possibility that different etiological or compensatory mechanisms may be at work in males and females with ASC. While some studies have explicitly looked at this question at the behavioral level, sex differences in ASC have not been extensively investigated at the neural level.  

Objectives: To examine the microstructure of four major white matter tracts: the cingulum, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and the uncinate fasciculus (UF), to test for similarities and differences between males and females with and without ASC. 

Methods: 30 adult males and 31 adult females with an ADI-R confirmed diagnosis of ASC (aged 18-45) and age- and IQ-matched typically developing controls (31 males and 31 females) were scanned on a cardiac-gated 32-direction diffusion tensor imaging sequence at 3T. Data preprocessing was implemented in ExploreDTI (Leemans, et al., 2009). Deterministic tractography was performed on the cingulum, IFOF, ILF and UF according to guidelines given by Catani & Thiebaut de Schotten (2008) using TrackVis software (http://trackvis.org). Repeated-measures analysis of covariance (ANCOVA) was performed on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and tract volume respectively, with ‘hemisphere’ and ‘tract’ as within-subjects factors, ‘diagnosis’ and ‘sex’ as between-subject factors, and ‘age’ as a covariate. Any significant interaction effects were followed up by post-hoc repeated-measures ANCOVAs and multivariate ANCOVAs.  

Results: Within the UF there were significant three-way sex*diagnosis*hemisphere interactions for MD and RD. This reflected a trend towards significance for a sex*diagnosis interaction for RD. A significant diagnosis*hemisphere interaction was found for IFOF volume. This interaction was driven by a significant effect main of diagnosis in the right IFOF (F(1,118)=4, p=0.048) with a larger observed volume in typically developing individuals (21.08ml) than in individuals with ASC (19.52ml). Trends towards significant three-way sex*diagnosis*hemisphere interactions were observed for FA, RD and tract volume in the cingulum, UF and IFOF. 

Conclusions: Adults with ASC have smaller right IFOF volumes than typical controls. As the IFOF is a tract that connects the orbito-frontal cortices (OFC) to the occipital cortices, this likely affects connectivity between these areas. OFC has a role in reward-based decision-making and has been implicated in impaired theory of mind in autism. The finding of trends towards significance in other tracts may reflect the method used, which tests an average along each entire tract. Further analysis using voxel-based whole-brain approach may uncover localized differences in microstructural properties of these tracts.

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