23707
Age-Related Changes in Cortical Morphometry; A Longitudinal MRI Study of Males with Autism and Controls.

Friday, May 12, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
E. Daly1, A. Marshall2, D. S. Andrews3, A. Shahidiani3, C. Ecker4 and D. G. Murphy1, (1)Sackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom, (2)King's College London, London, United Kingdom, (3)Sackler Institute for Translational Neurodevelopmental Sciences, IoPPN, King's College London, London, United Kingdom, London, United Kingdom, (4)Department of Child and Adolescent Psychiatry, Psychosomatics and Psychiatry, Goethe-University Frankfurt am Main, Frankfurt, Germany
Background:

Cortical volume (CV) is the product of 2 underlying components: cortical thickness (CT) and surface area (SA). This is of importance because both CT and SA have distinct genetic and developmental origins. Hence measurement of CT and SA allows us to ‘fractionate’ the underpinning mechanisms behind differences in brain volume in people with autism spectrum disorders (ASD), and to investigate how these differ over time.

Objectives:

We acquired structural MRI over multiple time periods to investigate brain morphometry and growth trajectory differences between individuals with ASD and typically developing controls.

Methods:

We included 64 males – 32 with ASD and 32 controls. ASD was diagnosed using ADI and ADOS. We obtained 62 scans from individuals with ASD (mean age = 15 years; range 6-19 years; mean inter-scan interval 1.1 years) and 54 scans from 32 typically developing controls (TDC) males (mean age = 14 years; range 8-19 years; mean inter-scan interval 1.0 years). FreeSurfer, image analysis software, was used to measure CV, CT and SA. Automatic longitudinal processing was used to obtain reliable measurements at each time point. Cross-sectional between group (i.e. TDC, ASD) comparisons at baseline were carried out using a general linear model and the SurfStat toolbox. Differences in developmental trajectories over multiple time points were investigated using linear mixed effects models.

Results: At baseline, there are main effects of group for CV and SA. The ASD group had significantly greater CV and SA in insula/postcentral gyrus. There was no difference in CT. Longitudinal analysis revealed significant age related changes in CV, CT and SA globally in both groups. However, the ASD group showed more CV, CT and SA reductions with age than the TD group globally in frontal, temporal, parietal, and occipital lobes.

Conclusions:

Individuals with ASD have significantly greater age-related loss of brain tissue than controls. Larger studies, and including older (and aged) populations, are required to determine if these age-related differences are associated with change in symptomatic and/or cognitive profile.