This project is designed to evaluate the efficacy of a novel imaging, biochemical, and behavioral approach for detecting autism spectrum disorder (ASD) and discovering mechanisms associated with ASD symptomology. Although considerable knowledge has been gained, the lack of reliable predictors during the first year of life remains a major impediment to implementing effective early interventions in children at-risk for ASD. The heterogeneity in ASD renders it unlikely that one specific biomarker will provide a pathognomonic sign of ASD. However, the combination of biomarkers and behavioral indicators being tested in this application has the potential to reveal a biosignature of ASD that can be identified in infancy. We are focusing on the amygdala and limbic system dysfunction in our application. Amygdala dysfunction has been proposed as a critical component of social impairment in ASD, the core symptom that differentiates ASD from other neurodevelopmental disorders. However, functional imaging biomarkers of amygdala dysfunction are yet to be discovered and validated. The current project combines two sensitive functional magnetic resonance imaging (fMRI) measures of amygdala dysfunction in ASD: rapid face detection and reduced amygdala habituation to faces into a new, robust, fMRI habituation paradigm. In addition, we developed a novel amygdala habituation measure using olfactory stimuli. First, we will confirm the sensitivity of our amygdala habituation measures (assayed using emotional faces and odors) for distinguishing children with ASD from typically developing controls. Second we address the mechanisms for atypical habituation, by testing whether reduced fMRI habituation in ASD is driven by alterations in levels of glutamate (excitatory) and/or gamma-amino butyric acid (GABA, inhibitory). Lastly, we are testing whether our battery of olfactory measures including odor detection, cyclic adenosine monophosphate (cAMP) levels (the primary signaling pathway used by olfactory sensory neurons), and fMRI alterations are sensitive and specific biomarkers of ASD. We propose that olfactory measures may be an effective proxy for socioemotional processing given the primacy of emotion in olfactory perception and its shared neuroanatomical substrates with limbic structures affected in ASD. To further investigate the specificity of olfactory measures, we will test the ability of our measures to discriminate between individuals with ASD, typically developing (TD) children and children with clinically significant sensory processing symptoms (SPD). The proposed research addresses Objective 1 of the NIMH Strategic Plan by integrating behavioral and biological markers and examining how neurobiological mechanisms - specifically GABA and glutamate levels - contribute to atypical brain habituation in ASD. Fifty children (8-12 years of age) with high functioning ASD (Full-scale IQ >70), 50 children with clinically significant sensory processing symptoms (SPD) and 50 typically developing controls (TD) will participate in the study. The TD and SPD groups will be matched to the ASD group according to age, gender, and Full-scale IQ.

Public Health Relevance

Autism is a severe developmental disorder affecting approximately 1.1% of US children aged 3 to 17 years. In order to accurately predict which infants will develop the disorder and provide timely intervention, sensitive and specific biomarkers need to be discovered. In this study, we will investigate amygdala dysfunction and olfactory processing measures for their potential as early biomarkers of autism.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH104313-01
Application #
8755424
Study Section
Special Emphasis Panel (ZMH1-ERB-L (05))
Program Officer
Gilotty, Lisa
Project Start
2014-08-15
Project End
2019-05-31
Budget Start
2014-08-15
Budget End
2015-05-31
Support Year
1
Fiscal Year
2014
Total Cost
$474,949
Indirect Cost
$166,198
Name
University of Washington
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Askren, Mary K; McAllister-Day, Trevor K; Koh, Natalie et al. (2016) Using Make for Reproducible and Parallel Neuroimaging Workflow and Quality-Assurance. Front Neuroinform 10:2