DOI
https://doi.org/10.25772/P1CF-B866
Defense Date
2023
Document Type
Thesis
Degree Name
Master of Science
Department
Human Genetics
First Advisor
Brien Riley
Abstract
Objective: Using a mixture of statistical techniques like structural equation modeling, confirmatory, and exploratory factor analyses, we aimed to determine the genetic factor structure among Externalizing, Internalizing, and Psychotic spectrum disorders through methods that evaluate GWAS-based correlations. Additionally, a subsequent factor analysis based on the most suitable psychiatric model was conducted to understand how non-clinical behavioral traits align with this factor structure.
Methods: Publicly available GWAS summary statistics for twelve major psychiatric disorders, six substance use measures and two personality domains were incorporated into structural equation models. Using the GenomicSEM software package, GWAS-based correlations were estimated between all twelve disorders and eight non-clinical traits before applying exploratory (EFA) and confirmatory factor analyses (CFA) to identify the genetic factor structure.
Results: EFA of the twelve psychiatric disorders indicated that a three-factor model (Internalizing, Externalizing, Psychotic) best fit the data. Internalizing, Externalizing, and Psychotic dimensions were moderately correlated. A secondary CFA of non-clinical traits indicated that substance use and risk-taking were genetically related to the Externalizing factor, high levels of neuroticism were associated with the Internalizing factor.
Conclusions: The present results corroborate prior research from twin, family, and other molecular studies on the factor structure of DSM-based psychiatric disorders. Significant associations were detected between the latent factors and non-clinical psychosocial measures of behavior. These additional measures highlight the importance of including sub-clinical, behavioral phenotypes in studying the comorbidity of psychiatric illness.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
8-11-2023