The term autism-spectrum disorders (ASD) exemplifies the tremendous heterogeneity in this developmental disorder at both the phenotypic and underlying genetic levels. It has repeatedly been observed that ASD disproportionately affects males (B) relative to females (@). Although many hypotheses attempt to explain this bias, no clear answers have emerged because of inconsistent and incomplete phenotyping and small sample sizes. We propose to leverage the interdisciplinary strengths and recruiting power of our network to study sex- specific differences by deep phenotyping and genotyping of ASD participants. We will recruit a sex-balanced cohort of ASD (N=125 B N=125 @) and matched typically developing (TD) comparison participants (N=125 B, N=125 @), as well as a set of unaffected siblings (US;N=63 @, N=62 B). We will quantitatively phenotype multiple behavioral domains and measure several key ASD-related neural systems at the level of brain structure (sMRI), connectivity (DTI and fMRI), function (task based and resting state fMRI), and temporal dynamics (EEG). Additionally, we will measure copy number variation (CNV) and single nucleotide variation (SNV) for these participants and their parents, allowing us to test sex- and circuit-specific genotype-phenotype hypotheses for five candidate ASD genes and ultimately extend our methods to a search for novel sex-specific and high-risk genes.
Our Specific Aims are to: 1) Identify sex differences in brain structure, function, connectivity, and temporal dynamics in ASD. 2) Characterize associations between DNA sequence and copy number variants and brain structure and function in @ASD and @TD versus BASD and BTD. 3) Relate brain differences in structure, function, and temporal dynamics to heterogeneity in ASD behavior and genetics. We hypothesize that advanced network methods can aid in understanding the tremendous heterogeneity in ASD by connecting different levels of phenotype with genetic variation. We will therefore combine multiple levels of biology and endophenotypes - SNVs, CNVs, behavioral metrics, and resting state imaging and electrophysiology measures - into one framework across affected and unaffected siblings and controls using an integrated network analysis, iWGCNA.

Public Health Relevance

In this project, we will pool together our interdisciplinary expertise and recruitment efforts across four leading Centers for the study of autism spectrum disorder (Yale, UCLA, Harvard, and University of Washington) in an effort to: 1) Identify difference between boys and girls in brain mechanisms underlying autism spectrum disorder;2) Search for relationships between brain mechanisms and underlying genetic differences;3) Discover the brain and genetic mechanisms underlying heterogeneity in the presentation and severity of autism spectrum disorder in boys and girls.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01MH100028-03
Application #
8723889
Study Section
Special Emphasis Panel (ZHD1)
Program Officer
Gilotty, Lisa
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Yale University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
City
New Haven
State
CT
Country
United States
Zip Code
06510
Ventola, Pamela E; Yang, Daniel; Abdullahi, Sebiha M et al. (2016) Brief Report: Reduced Restricted and Repetitive Behaviors after Pivotal Response Treatment. J Autism Dev Disord 46:2813-20
Venkataraman, Archana; Yang, Daniel Y-J; Dvornek, Nicha et al. (2016) Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder. Neuroreport 27:1081-5
Garman, Heather D; Spaulding, Christine J; Webb, Sara Jane et al. (2016) Wanting it Too Much: An Inverse Relation Between Social Motivation and Facial Emotion Recognition in Autism Spectrum Disorder. Child Psychiatry Hum Dev 47:890-902
Chen, Christina; Van Horn, John Darrell; GENDAAR Research Consortium (2016) Developmental neurogenetics and multimodal neuroimaging of sex differences in autism. Brain Imaging Behav :
Brown, Jesse A; Van Horn, John D (2016) Connected brains and minds--The UMCD repository for brain connectivity matrices. Neuroimage 124:1238-41
Geschwind, Daniel H; State, Matthew W (2015) Gene hunting in autism spectrum disorder: on the path to precision medicine. Lancet Neurol 14:1109-20
Cotney, Justin; Muhle, Rebecca A; Sanders, Stephan J et al. (2015) The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment. Nat Commun 6:6404
Venkataraman, Archana; Duncan, James S; Yang, Daniel Y-J et al. (2015) An unbiased Bayesian approach to functional connectomics implicates social-communication networks in autism. Neuroimage Clin 8:356-66
Coffman, M C; Anderson, L C; Naples, A J et al. (2015) Sex differences in social perception in children with ASD. J Autism Dev Disord 45:589-99
Jack, Allison; Pelphrey, Kevin A (2015) Neural Correlates of Animacy Attribution Include Neocerebellum in Healthy Adults. Cereb Cortex 25:4240-7

Showing the most recent 10 out of 20 publications