<p> Obesity is a growing concern as 42.3% of people in the U.S were considered obese in the years 2017- 2018. Little is known about the genetic components that contribute to weight gain. In humans, the hormone glucagon is a major contributor to the body’s energy demand as it helps break down lipids. Therefore, learning more about this pathway could enable a range of therapeutics. In fact, studies have shown that glucagon treatments have helped patients with both weight loss and appetite suppression. In this project, we analyzed candidate genes that modify the glucagon pathway in <em>Drosophila melanogaster.</em> We reduced the expression of the fly version of the glucagon receptor (AKHR) in our model. This induces fat retention in the L3 larvae, which mimics obesity in humans. We then crossed our model to the DGRP and looked for natural variation in fat content using a density assay. The density assay examines the relative fat levels of the larvae by slowly increasing the amount of sucrose in water. This enables us to observe whether we have lean larvae which float later or fat larvae which float early on. We used the variation in floating concentration to identify candidate modifier genes through GWA or genome-wide association study. We crossed our <em>AKHR</em> RNAi model to RNAi for various candidate modifier genes that may enhance or suppress fat retention. We screened these candidates initially with the same density assay used in the original study. This resulted in four candidate genes that significantly impacted the density of the larvae: <em>THADA</em>, <em>AmyD</em>, <em>GluRIIC</em>, and <em>CG9826</em>. We further characterized these candidates using biochemical assays to analyze stored metabolites such as triglycerides, glucose, glycogen, and protein. These have been further analyzed under control, high sugar, and high fat conditions to see if the larvae are resistant to environmental changes. <em>CG9826</em> showed significant increase in stored fats across all environments. <em>THADA</em> RNAi showed an increase in fat in the high fat environment. Overexpression of <em>THADA</em> showed a decrease in fat storage in the high fat environment. Our goal is to advance our understanding of the glucagon signaling pathway, obesity, and lipid metabolism. We are also hopeful to provide candidate genes that can be regarded as future therapeutic targets. </p>

Background: We aimed to increase the knowledge regarding the familial arrhythmogenic disorder Long QT Syndrome (LQTS) and its recessive variant Jervell and Lange-Nielsen Syndrome (JLNS) in Sweden, including prevalences and clinical phenotypes. A specific focus was directed towards two KCNQ1 mutations –p.Y111C and p.R518X- commonly identified in Swedish LQTS index cases. Methods: Cases and families with LQTS (p.Y111C or p.R518X) and JLNS were recruited via regional clinical practices, national referrals to the Clinical Genetics laboratory, Umeå University Hospital, and a national inventory. Molecular genetics methods were used for case ascertainment. Clinical data was obtained via medical records, a questionnaire, and/or an interview. Electrocardiograms were manually assessed. In p.R518X heterozygotes intra-familial phenotypic variability (QTc and cardiac events) was assessed by analysis of sequence variants (modifier genes). The origins of the mutations p.Y111C and p.R518X were investigated using genealogical and haplotype analysis (microsatellite markers). In families sharing a common haplotype mutation age and associated prevalence was analyzed using ESTIAGE and DMLE computer software. Results: We identified p.Y111C (170 mutation-carriers) and p.R518X (101 mutation-carriers) as two major causes of LQTS/JLNS in Sweden. LQTS phenotype was revealed to be relatively benign in p.Y111C and p.R518X (annual incidence of life-threatening cardiac events, before therapy 0.05% and 0.04%, respectively). Gender-specific effects of genetic modifiers on phenotypic expression were seen. A founder origin, approximately 600-700 years ago in two northern river valleys was established for p.Y111C and p.R518X, and a high prevalence of LQTS founder descendants suggested. A minimum JLNS prevalence of 1:200 000 in preadolescent Swedish children was revealed. JLNS phenotype was mainly severe, with a cumulative incidence of life-threatening cardiac events of 53% (annual incidence rate before therapy 5%) and four sudden deaths. Possible founder effects regarding four KCNQ1 mutations; p.Y111C (8%), p.R518X (50%), c.572_576del (17%) and p.Q530X (8%) together explained 83% of the JLNS mutation-spectrum in Sweden, consisting of 8 KCNQ1 mutations. Conclusion: The high prevalence of p.Y111C- and p.R518X-related LQTS as well as JLNS revealed in Sweden could be explained by the combination of mild clinical phenotypes in heterozygotes and strong founder effects present during the population development of northern Sweden. Increased knowledge regarding the occurrence of LQTS and JLNS as well as mutation- and/or genotype-specific data constitute prerequisites for possible improvement of patient management.

<p>The goal of this thesis is to algorithmically identify candidate modifiers for <i>retinitis pigmentosa</i> (RP) to help improve therapy and predictions for this genetic disorder that may lead to a complete loss of vision. A current research by (Chow et al., 2016) focused on the genetic contributors to RP by trying to recognize a correlation between genetic modifiers and phenotypic variation in female <i>Drosophila melanogaster</i>, or fruit flies. In comparison to the genome-wide association analysis carried out in Chow et al.’s research, this study proposes using a K-Means clustering algorithm on RNA expression data to better understand which genes best exhibit characteristics of the RP degenerative model. Validating this algorithm’s effectiveness in identifying suspected genes takes priority over their classification.</p><p>This study investigates the linear relationship between <i>Drosophila </i>eye size and genetic expression to gather statistically significant, strongly correlated genes from the clusters with abnormally high or low eye sizes. The clustering algorithm is implemented in the R scripting language, and supplemental information details the steps of this computational process. Running the mean eye size and genetic expression data of 18,140 female <i>Drosophila</i> genes and 171 strains through the proposed algorithm in its four variations helped identify 140 suspected candidate modifiers for retinal degeneration. Although none of the top candidate genes found in this study matched Chow’s candidates, they were all statistically significant and strongly correlated, with several showing links to RP. These results may continue to improve as more of the 140 suspected genes are annotated using identical or comparative approaches.</p>

<p>  </p> <p>Inhalation is a primary route of environmental and occupational exposures. Inhalation toxicology studies have thoroughly demonstrated the efficacy and adverse effects of a large number of chemicals, metals, pharmaceuticals, and agrochemicals. With the rapid development of new technologies and emergence of prominent subpopulations, some emerging exposure issues have arisen. To better protect public health, it is necessary to address these numerous emerging issues related to inhalation toxicology including 1) exposures to complex and unknown chemical emissions generated as we resolve infrastructure needs, 2) real-world exposure scenarios such as nanoparticle (NP) mixtures that may induce unique toxicity, and 3) variations in toxicity responses that occur in vulnerable and prevalent subpopulations following exposures. We designed three aims 1) to characterize differential representative composite manufacturing emissions (CMEs) and toxicity assessment of inhalation exposure to CMEs, 2) to examine the contribution of variable iron and manganese NP components in welding fumes to pulmonary toxicity, and 3) to evaluate metabolic syndrome (MetS)-induced variations in NP-Biocorona (NP-BC) composition following inhalation and modulation of pulmonary toxicity. Overall, this proposal aimed to characterize the emerging and complex exposures occurring in the real world and elucidate the mechanisms of differential pulmonary toxicity and susceptibility associated with CMEs, different metal NP components in welding fumes, and underlying diseases such as MetS. The conclusions from this project can help to improve the application of water infrastructure repairing technology and the utilization of welding and understand the mechanism of susceptibility to NP exposure among individuals with underlying diseases. Furthermore, the findings from these evaluations have supported and improved worldwide regulation, which promotes a safer utilization of novel materials, newly developed medicines, and complex chemicals.</p>