CART ACE II - Project 5: Genetic and genomic analyses to connect genes to brain to cognition in ASD

Project summary

Overview: Autism Spectrum Disorder (ASD) varies widely in both symptoms and causes and perhaps is best thought of as "the autisms".  ASD has a strong genetic component, but the mutations causing the disorder are largely unknown.  Research from several groups including our own suggests that studying cognitive or behavioral components of autism, or endophenotypes, may aid in identification of more homogeneous subgroups and hasten the identification of genetic loci underlying this condition.  We will use genetic measures to define more homogeneous subtypes of autism so as to increase power in clinical trajectory and treatment studies, identify biomarkers and integrate genetic data with measures of behavior and brain function to identify biological processes that are disrupted in ASD and thereby find early diagnostic signs and treatment targets.

Project 5 Summary: Genetic factors contribute significantly to autism susceptibility, but the heterogeneity of ASD poses a challenge for genetic studies. In our previous ACE Center project we showed how a common ASD susceptibility variant in CNTNAP2 modulates brain function, connecting gene to brain to endophenotype for the first time in ASD.  We also identified several cases of rare, large copy number variation (CNV) and smaller variants of less certain pathogenecity.  In this current ACEII Center project, we will continue to genetically characterize all ACEII probands, hypothesizing that identifying certain etiological subclasses may provide more homogeneous populations that will be more predictive of trajectory and outcome. We will integrate identification of CNV with gene expression data to identify dysregulated genes within and nearCNVs, thus improving classification of pathogenecity, and identify those with mutations currently undetectable by structural variant analysis alone.

We will take a systems approach to functionally group these genes into biological pathways, and thus to group patients by shared molecular defects. We then will relate shared molecular pathyway defects in the patient subsets to the phenotypic biomarker measurements collected in the ACEII projects 1-4. We will test the relationship between known and newly discovered genetic variants and measures of behavior, eye tracking/pupillometry, EEG, and brain imaging at both single time points and examing longitudinal trajectories, as well as their influence on response to treatment. In this way, we seek to connect genetic variation to measures of brain function as a means of unraveling the genetics and phenotypic heterogeneity observed in ASD, and to develop improved predictors of diagnosis and treatment response.

Primary Investigator: 
Daniel Geschwind, M.D., Ph.D.