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Research indicates that without healthy and close relationships, well-being and functioning suffer. Despite this knowledge, quality of relationships has not been emphasized in the mental health literature, especially as related to social anxiety disorder (SAD) where social support needs may be higher. The aim of this study was to examine how those with SAD compared to those with another anxiety disorder (generalized anxiety disorder; GAD), a mood disorder (major depressive disorder; MDD) and those with no recent history of disorder, on measures of quality of relationships with family, friends and partners, as well as on intimacy and role functioning. Data were drawn from the National Comorbidity Survey Replication (NCS-R; Kessler et al., 2004), a large, U.S. nationally-representative epidemiological data set. Logistic regressions were used to examine the quality of relationships for those with SAD as compared to GAD, MDD and no disorder. The associations among relationship quality and high versus low severity of SAD were also examined. It was found that those with SAD were less likely to report high family and friend support than were those with no disorder, but more likely to report high marital support than those with GAD or MDD. Those with SAD were more likely to report high family stress than those with no disorder, but no more likely to report relationship stress than were the other clinical groups. With respect to severity of SAD, those with high SAD severity were more likely to report high friendship stress than those with low SAD severity. In examining role impairment, those with SAD were less likely to report social impairment than those with GAD or MDD, and less likely to report close relationship impairment than those with MDD. Those with high SAD severity reported higher impairment across social and close relationship functioning compared to those with low severity. This study redresses many of the limitations in the current literature, and the results inform future research efforts on treatment practices and prevention.

Thesis (Ph. D.) in Psychology--University of Maine, 2002. / Includes vita. Includes bibliographical references (leaves 118-137).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph.D.)--University of Melbourne, Dept. of Psychology, 2004. / Typescript (photocopy). Includes bibliographical references (leaves 275-322).

Thesis Plan B (M.S.)--University of Wisconsin--Stout, 2008. / Includes bibliographical references.

Polycystic Ovarian Syndrome is the one of the leading causes of infertility among women who are of child-bearing age. The syndrome’s vast range of phenotypes has made it challenging for researchers to not only consistently diagnose but also discover a cure. Currently, there are several proposed treatments being looked into, however, much of the research focuses on employing promising biomarkers, micro ribonucleic acids (miRNAs), that can potentially aid in diagnosis. The four prominent locations of research for these biomarkers include: ovarian tissues specifically looking into granulosa cells (GC), adipose tissue, follicular fluid, and the serum. My goal is to determine which of these areas holds the most promise to diagnose this syndrome in the years to come. This study reviewed a large collection of the current polycystic ovarian syndrome literature evaluating both reported miRNAs and how viable those would be as potential biomarkers to use for the future. The data showed that a majority of these promising biomarkers were found in granulosa cells, adipose tissue, and follicular fluid. Although there were miRNAs that were deemed promising in the serum, research is still far from conclusive in using these miRNAs as biomarkers for diagnosis of polycystic ovarian syndrome. By comparing the miRNAs selected from each type of location, I was able to conclude that miR-21, miR-93, miR-223, and miR-let-7b hold the most promise for the potential to become biomarkers for polycystic ovarian syndrome in the near future. Currently, there is a lot of research particularly surrounding these miRNAs and how they were shown to have been expressed in statistically significant levels among women with the syndrome. However, because of their complexity, miRNAs do not regulate one single pathway, it is hard to describe a mechanism that explains the pathophysiology of the syndrome. I believe we are still far away from successfully zooming in on one biomarker. By determining the most potential biomarker(s), we can focus resources and efforts towards finding a better diagnostic tool for this syndrome.

Obesity is a common medical illness that is known to confer risk for a large number of medical illnesses, such as Type II Diabetes, hypertension, cancer, and late-life dementia. More recently, the relation between obesity and decline in cognitive performance, independent of other comorbid medical conditions, has begun to be examined. Individuals with mood disorders (Bipolar Disorder [BD] or Major Depressive Disorder [MDD]) display an increased prevalence of both obesity and risk factors for cardiovascular disease. Moreover, BD and MDD are associated with impairment in cognitive functioning across multiple domains. The contribution of obesity to cognitive decline in this population has not been explored. This thesis begins with a systematic review of the literature examining the impact of obesity on cognition, providing a thorough background of this relation. The following chapter introduces a prospective cohort study designed to comprehensively explore the relation between obesity and cognition in individuals both with, or without, a mood disorder. The first of set of results from this study are presented in the remaining chapters. The neuropsychological study findings indicate that MDD and obesity may have an additive effect on cognition, resulting in significant cognitive decline in obese adults with MDD. Moreover, we show that different neural activation patterns are seen during a cognitive magnetic resonance imaging (MRI) task in obese versus obese MDD patients. Collectively, this provides strong evidence that populations already at risk for cognitive impairment, such as mood disorder populations, are susceptible to further cognitive changes due to increased weight. / Thesis / Doctor of Philosophy (PhD)

Autism spectrum disorder (ASD) encompasses a broad range of neurodevelopmental disorders, with two core symptoms: deficits in social communication, and restrictive interests and repetitive behaviors. Genetics is thought to play a large role in ASD and currently there are hundreds of associated genes. We first studied the thousand and one amino acid kinase gene (TAOK2), which plays an important role in neurodevelopment. We found that loss of TAOK2 causes deficits in neuron development and activity, leading to morphological changes in various mouse brain regions and ASD-related behaviors. We studied the impact of de novo mutations identified in TAOK2, which caused aberrant neuron dendritic arborization and formation of synapses. To elucidate how TAOK2 regulates neuron development we used a proximity-labeling proteomics technique (BioID) to identify its protein-protein interaction (PPI) network. We applied this same methodology to a total of 41 ASD-risk genes and observed multiple convergent biological processes, including the less-studied mitochondrial and metabolic pathways. ASD-risk genes, including TAOK2, associated with mitochondrial proteins were found to have altered cellular respiration. The shared ASD-risk gene PPI network enriched for other ASD-risk genes and was used to group genes based on their shared PPI networks. These gene groups showed correlation between the clinical behavior scores of individuals that had mutations within the distinct gene groups. Lastly, we identified changes in the PPI networks of multiple ASD-risk genes through BioID, which we validated with various functional assays. In summary, we developed a proximity-labeling proteomics method that identified multiple convergent biological pathways associated with ASD. Studying the function of TAOK2 revealed multiple disease-relevant pathologies associated with the disorder, however proximity labeling has the potential to categorize multiple ASD-risk genes and elucidate their shared signaling pathways, which together, can advance the development of robust treatments for ASD. / Thesis / Doctor of Philosophy (PhD) / Autism spectrum disorder (ASD) is a group of brain disorders that affect more than 1% of children. Genetic variants are thought to cause ASD pathology, however there are currently hundreds of genes that have not been studied. We studied how disruption of one of those genes, TAOK2, alters brain development in mice and identified TAOK2 variants in multiple children with ASD. We then used BioID to find the shared disease-related mechanisms between multiple ASD-risk genes, and found that mitochondrial function and activity were connected to many of these genes. We showed that BioID can be used to study the effect of mutations in multiple ASD-risk genes simultaneously. Last, we could group children with ASD with similar behavior test scores based on the shared mechanisms of ASD-risk genes. Together our findings could be used to advance the development of robust treatments or new diagnostic tools for ASD.

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