Date of Award
Doctor of Philosophy (PhD)
Understanding causal factors in the development of early childhood neuropsychiatric conditions is essential for an understanding of disease mechanisms and therapeutic approaches. Yet the lack of objective classification of psychiatric diagnoses, phenotypic and genetic heterogeneity, pleiotropy, and extensive comorbidity have posed immense challenges to the acquisition of knowledge regarding neuropsychiatric disease etiology. While it is unequivocally established that nearly all psychiatric conditions are substantially heritable, non-genetic factors do play a role in the development of psychopathology. This thesis explores both genetic and environmental contributors to neuropsychiatric conditions in an attempt to refine the characterization of some of these risk factors. In Part 1 (comprising Chapter 2), we examined putative environmental contributors to early childhood psychopathology broadly. We found that none of the factors were significantly correlated with one another, nor did they predict child behavioral and functional outcomes. These findings suggest that current measures of risk and outcome require further development and that genetically-informative study design should be employed in future interrogations of environmental contributors to psychopathology. In Part 2 (comprising Chapters 3 – 4) we focused on autism spectrum disorder (ASD) with the ultimate goal of refining current risk prediction efforts. To do so, we employed a quantitative measure of autistic traits, the Social Responsiveness Scale (SRS), since a strong body of evidence demonstrates that ASD is the pathological tail of a continuous distribution of autism-related variation in reciprocal social behavior (AVR). As a first step, we established the longitudinal stability of the SRS to ensure its reliability as a measure over the life course. The SRS demonstrated very high measurement stability from early childhood through adulthood, as well as an ability to clearly delineate the long-term trajectory of cases and controls. Having determined the longitudinal stability of AVR, we then were able to employ the SRS in a genetic study of risk prediction. Using polygenic risk scores (PRS) derived from a genome-wide association study (GWAS) of ASD, we examined if ASD-PRS could explain AVR in a familial sample of individuals with and without a diagnosis of ASD. Despite the small sample size of our discovery GWAS dataset, ASD-PRS explained a significant, albeit modest, proportion of the variance in AVR—critically, in both affected and unaffected individuals. This work lays the foundation for future studies characterizing polygenic risk of early childhood neuropsychiatric disorders.
Chair and Committee
John N. Constantino
Ryan Bogdan, Lisa Connor, Nico Dosenbach, Chris Gunter,
Wagner, Rachael Elizabeth, "Refining the Characterization of Causation in Early Childhood Neuropsychiatric Conditions: Nature, Nurture, and Time" (2021). Arts & Sciences Electronic Theses and Dissertations. 2382.