Date of Award

2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Graduate Group

Neuroscience

First Advisor

Edward S. Brodkin

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is complex both in its behavioral presentation and in its genetic basis. The use of quantitative behavioral phenotypes instead of the binary, categorical phenotype of diagnosis (Yes ASD, No ASD) has yet to be broadly applied in some areas of ASD research, including ASD genetics. Prior to investigating quantitative ASD-related phenotypes in humans, we reviewed the literature connecting synaptic cell adhesion molecules to social affiliation (a behavior disrupted in autism) in rodent models, and we proposed a mechanistic model. Then, by recruiting autistic adults and their extended family members through the Autism Spectrum Program of Excellence and having them complete a detailed quantitative phenotypic battery, we were able to address the reliability of quantitative phenotyping measures and to start investigating them. We found nearly all of the tested quantitative phenotypes to be heritable across several ASD-relevant behavioral domains – including social communication, repetitive behaviors, and executive functioning. Additionally, we found poor agreement between self-report and informant-report of two such measures (the Social Responsiveness Scale (social communication) and the Behavior Rating Inventory for Executive Function (executive functioning)) among autistic adults. Finally, we looked at the relationships between several relevant quantitative phenotypes, namely measures of overall ASD-related traits, psychological resilience, anxiety, and depression. We found these constructs to be related in such a way that suggests that enhancing resilience may mitigate depression among those high in ASD-related traits. All together, this work points to the promise of a quantitative trait approach in ASD research and highlights the need for several, overlapping measures across multiple behavioral domains for the most thorough understanding of ASD-related behavioral phenotypes.

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