Longitudinal Development of White Matter in Autism Spectrum Disorder

Friday, May 13, 2016: 2:09 PM
Room 307 (Baltimore Convention Center)
D. C. Dean1, B. G. Travers2, N. Adluru1, D. Tromp1, D. Destiche1, A. Freeman1, B. A. Zielinski3, M. D. Prigge4, J. S. Anderson5, E. D. Bigler6, N. Lange7, A. L. Alexander1 and J. E. Lainhart1, (1)Waisman Center, University of Wisconsin-Madison, Madison, WI, (2)Occupational Therapy Program in Kinesiology, University of Wisconsin Madison, Madison, WI, (3)Pediatrics and Neurology, University of Utah, Salt Lake City, UT, (4)Pediatrics, University of Utah, Salt Lake City, UT, (5)University of Utah, Salt Lake City, UT, (6)Psychology/Neuroscience Center, Brigham Young University, Provo, UT, (7)McLean Hospital, Cambridge, MA
Background: Increasing evidence has suggested autism spectrum disorder (ASD) to be a disorder of impaired brain connectivity, and in particular, microstructural alterations of underlying white matter (see Travers et al. 2012 for review). In particular, diffusion tensor imaging (DTI) has been influential to the study of white matter alterations in ASD, while recent evidence has implicated aberrant development of specific white matter regions in association with ASD. These region of interest studies impart great insight into the neurobiological changes of white matter in ASD, however, it is unclear the magnitude and extent of such alterations across the whole brain. To assess this, we can examine and longitudinally model developmental change at the voxel-level. Understanding these specific white matter network “signatures” at the group and individual levels may help us better determine meaningful subgroups within the autism spectrum.

Objectives: We examined and characterized the developmental changes of DTI parameters across the brain in a large, longitudinal sample of ASD and and typically developing (TD) individuals. We specifically compared the developmental trajectories of FA, MD, RD, and AD between TD and ASD individuals.  

Methods: MRI Acquisition: Participants for this study consisted of 100 males with ASD and 57 age-matched males with typical development (TD) between 3 and 39 years of age. A total of 434 (287 ASD, 147 TD) longitudinal DTI datasets were acquired. Images were corrected for distortion and head motion and maps of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) were calculated. Images were subsequently aligned to a population-specific template using DTI-TK. Analysis: Developmental changes of diffusion parameters (i.e. FA, MD, RD) of the brain were modeled using a semi-parametric approach with penalized smoothing splines. This modeling was performed at the voxel-scale, creating statistical maps of developmental changes across the brain. Results were subsequently corrected for multiple comparisons using the false discovery rate.

Results: Across white matter, the group with ASD had significantly different developmental trajectories (p<0.05, FDR corrected) than the group with typical development (Fig 1). In particular, trajectory differences of FA were observed in genu of the corpus callosum, bilateral posterior limb of the internal capsule, cortical spinal tract, superior longitudinal fasciculus and inferior fronto-occipital fasciculus (Fig. 1A). While overlapping MD trajectory differences were found in the internal capsules, widespread and distinct MD trajectory differences were also observed (Fig 1B).

Conclusions: Longitudinal studies have traditionally focused on examining developmental differences within predefined brain regions. However, this has the potential of masking subtle changes within a particular brain region. By utilizing a voxel-wise mixed-effect modeling approach, our findings reveal the developmental trajectory of white matter to differ between ASD and TD across much of the brain. While these findings agree with the literature of white matter microstructure alterations in ASD, they also raise questions about the behavioral processes involved with these alterations as well as the specific neurobiological mechanisms underlying these changes.