16337
White-Matter Network Inefficiencies in ASD at 24 Months

Saturday, May 17, 2014: 2:20 PM
Marquis BC (Marriott Marquis Atlanta)
J. D. Lewis1, A. C. Evans2, J. R. Pruett3, K. N. Botteron4, L. Zwaigenbaum5, A. M. Estes6, G. Gerig7, D. L. Collins2, P. Kostopoulos8, R. C. McKinstry3, S. Dager9, S. J. Paterson10, R. T. Schultz10, M. A. Styner11, H. C. Hazlett11, J. Piven11 and .. The IBIS Network12, (1)McGill University, Montreal, QC, Canada, (2)Montreal Neurological Institute, McGill University, Montreal, QC, Canada, (3)Washington University School of Medicine, Saint Louis, MO, (4)Psychiatry and Radiology, Washington University School of Medicine, Saint Louis, MO, (5)University of Alberta, Edmonton, AB, Canada, (6)Speech and Hearing Sciences, University of Washington, Seattle, WA, (7)School of Computing & Scientific Computing and Imaging Institute SCI, University of Utah, Salt Lake City, UT, (8)McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada, (9)University of Washington, Seattle, WA, (10)Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA, (11)University of North Carolina at Chapel Hill, Chapel Hill, NC, (12)Autism Center of Excellence, Chapel Hill, NC
Background: Autism Spectrum Disorder (ASD) is a developmental disorder defined by behavioural symptoms that emerge during the first years of life, and begin to stabilize by 24 months. Recent research has indicated that abnormalities in connectivity may contribute to behavioural symptoms. However, this research is equivocal with respect to both the nature of connectivity abnormalities and the regions in which they occur, and currently provides little insight into their early developmental origins. Studies have reported different mixtures of over- and under-connectivity. Critically, most samples have included participants far past the age of onset of the defining behaviours, so many of the reported abnormalities may have resulted from cascade effects of developmentally earlier deviations.

Objectives: To ascertain whether there are abnormalities in connectivity in ASD when behaviours defining ASD first become clear, and if so, which parts of the network are involved.

Methods: An analysis of network efficiency, i.e. the capacity to exchange information across a network, was used to assess white-matter connectivity in a sample of 24-month-olds participating in a multi-site study of brain and behavioural development in ASD. The participants were 113 infants at high risk for ASD by virtue of having an older sibling with ASD, and 23 typically developing infants at low-risk. Of the high-risk infants, 31 were classified as ASD based on Autism Diagnostic Observation Schedule (ADOS) scores assessed at 24 months. Structural MRI data were processed with a fully automated pipeline to derive a cortical surface for each subject and overlay a fine-grain cortical parcellation. Diffusion tractography was used to establish the strength of connectivity between regions of this parcellation, and the lengths of those connections. The efficiency of information transfer between each node and all others (global efficiency) was then assessed for each subject, as well as the efficiency of information transfer between the neighbours of each node (local efficiency). Group differences in these two measures were assessed via statistical linear models, controlling for age, sex, and site.

Results: Significantly decreased local and global efficiency was seen over bilateral posterior regions in high-risk ASD infants relative to both low- and high-risk non-ASD infants. Reductions were present in broad regions of the occipital, parietal, and temporal lobes, including primary visual, somatosensory, and auditory areas, as well as associated secondary processing areas. For global efficiency, reductions were also present in Broca’s area; otherwise frontal cortex showed no group differences. Reductions in both local and global efficiency were lesser in comparison to high-risk non-ASD infants than low-risk infants, and more left-lateralized. There were no regions showing increased local or global efficiency.

Conclusions: These results suggest delayed myelination and pruning of connectivity, and so delay or deficit in the optimization of network structure. These immature networks show both reduced segregation and reduced capacity to integrate information between regions. The regions implicated are those involved in early processing of auditory, visual, and somatosensory inputs, areas which typically mature early. Findings of frontal lobe abnormalities in older individuals may result from these early inefficiencies in processing sensory inputs.