Autism spectrum disorders are now among the most prevalent medical conditions of childhood. Only a small fraction of the 486,000 individuals under 20 years of age with an autism-spectrum disorder (ASD) in the U.S are young enough to benefit from intensive early intervention. Overall prognosis for the older children with autism is not good. Despite improvements in treatment and education over the past 30 years, adult outcome even for non-mentally retarded individuals with autism has not significantly improved. The majority continue to need high levels of parental and community support throughout their lives. One reason for this huge public health problem is that the brain-basis of fundamental deficits in older children and adults with autism is not well understood. We propose collaboration between a longitudinal neuroimaging, clinical, and neuropsychological study of late neurodevelopment in autism and the National Alliance for Medical Imaging Computing (NA- MIC), one of the NIH Roadmap National Centers for Biomedical Computing. The collaboration will bring state-of-the-art brain imaging analysis tools developed by NA-MIC into autism clinical research and form a new highly interactive multidisciplinary research team. Working together, the computer scientists and clinical researchers will use critical biological questions in autism to """"""""drive"""""""" the development of NA-MIC """"""""tools"""""""". The critical biological questions are 1) what is the microstructural basis of abnormal brain connectivity during late neurodevelopment in autism, and 2) how is brain microstructure related to deficits, developmental trajectory, and outcome. We will use Time 1 and Time 2 high-resolution MRI and diffusion tensor imaging data that have already been collected on a single 3Tesla scanner on a cohort of 100 males with high-functioning autism and 72 typically developing males. Time 3 and 4 data are being collected over the next 5 years (MH080826). We will use novel, non-tractography-based, diffusion tensor image analysis methods developed by NA-MIC to compare, at the level of both individuals and groups, microstructural features along entire white matter tracts in language, social, and repetitive behavior neural networks. We will integrate the white matter analysis with structural image analysis of cortical and subcortical gray matter. We will determine how microstructural white matter features, gray matter morphometric features, and clinical deficits are related to each other and change over time in autism.

Public Health Relevance

Autism is now one of the most prevalent medical disorders of childhood. Adult outcome for even high-functioning older children and adolescents with autism is still usually poor, with a high need for lifelong clinical and community support. Understanding the brain- basis of deficits, disease course, and outcome in these individuals is critical for development of autism-specific treatments as well as secondary and tertiary preventive interventions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH084795-04
Application #
8210961
Study Section
Special Emphasis Panel (ZRG1-BST-E (50))
Program Officer
Gilotty, Lisa
Project Start
2009-04-01
Project End
2012-11-30
Budget Start
2012-02-01
Budget End
2012-11-30
Support Year
4
Fiscal Year
2012
Total Cost
$332,991
Indirect Cost
$85,491
Name
University of Utah
Department
Psychiatry
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
McLaughlin, Kristine; Travers, Brittany G; Dadalko, Olga I et al. (2018) Longitudinal development of thalamic and internal capsule microstructure in autism spectrum disorder. Autism Res 11:450-462
Prigge, Molly B D; Bigler, Erin D; Travers, Brittany G et al. (2018) Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder. J Autism Dev Disord 48:3319-3329
Lalani, Sanam J; Duffield, Tyler C; Trontel, Haley G et al. (2018) Auditory attention in autism spectrum disorder: An exploration of volumetric magnetic resonance imaging findings. J Clin Exp Neuropsychol 40:502-517
Travers, Brittany G; Bigler, Erin D; Duffield, Tyler C et al. (2017) Longitudinal development of manual motor ability in autism spectrum disorder from childhood to mid-adulthood relates to adaptive daily living skills. Dev Sci 20:
Dean 3rd, D C; Lange, N; Travers, B G et al. (2017) Multivariate characterization of white matter heterogeneity in autism spectrum disorder. Neuroimage Clin 14:54-66
Dean 3rd, Douglas C; Travers, Brittany G; Adluru, Nagesh et al. (2016) Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder. Brain Connect 6:415-33
Green, Ryan R; Bigler, Erin D; Froehlich, Alyson et al. (2016) Beery VMI performance in autism spectrum disorder. Child Neuropsychol 22:795-817
Travers, Brittany G; Bigler, Erin D; Tromp, Do P M et al. (2015) Brainstem White Matter Predicts Individual Differences in Manual Motor Difficulties and Symptom Severity in Autism. J Autism Dev Disord 45:3030-40
Jantz, Paul B; Bigler, Erin D; Froehlich, Alyson L et al. (2015) WIDE RANGE ACHIEVEMENT TEST IN AUTISM SPECTRUM DISORDER: TEST-RETEST STABILITY. Psychol Rep 116:674-84
Lange, Nicholas; Travers, Brittany G; Bigler, Erin D et al. (2015) Longitudinal volumetric brain changes in autism spectrum disorder ages 6-35 years. Autism Res 8:82-93

Showing the most recent 10 out of 32 publications