Glyphosate is the most heavily used herbicide worldwide and recent reports indicate that it may have deleterious neurological and neurodegenerative effects on human health. Here I demonstrate that glyphosate can infiltrate the brain in a dose-dependent manner in mice sub-acutely exposed to 125, 250, or 500 mg/kg/day. I also establish that glyphosate elicits a neuroinflammatory response in both the cortex and hippocampus, marked by elevation of tumor necrosis factor α (TNFα), and causes transcriptomic dysregulation of key genes involved in oligodendrocyte proliferation, maturation, and myelination. Given that both the hippocampus and the cortex are critical for learning and memory, and are affected in Alzheimer’s disease (AD), I investigate how 50 or 500 mg/kg chronic glyphosate exposure influences locomotion, anxiety-like behavior, and cognition in the APP/PS1 mouse model of AD. Results show that while glyphosate did not influence weight, appearance, locomotion, or anxiety-like behavior, learning acquisition is impaired in the place preference and reaction time tasks following 500mg/kg chronic exposure. Additionally, I report a strong increase in water consumption in glyphosate-exposed mice, demonstrating that chronic glyphosate exposure induces polydipsia. To ascertain whether glyphosate influences AD pathogenesis, I examine neuropathological changes following chronic daily oral exposure to 50 or 500 mg/kg glyphosate. Post-mortem analysis of amyloid-beta (Aβ) in APP/PS1 hippocampal and cortical tissue show that 50 or 500 mg/kg of glyphosate elevates soluble and insoluble Aβ1-40 and Aβ1-42 in both sexes, with females showing higher levels. Further analysis of cortical TNFα levels in chronically exposed APP/PS1 mice and littermate controls confirms a neuroinflammatory response. I report no differences in amyloid precursor protein (APP) processing pathway components, CA1 NeuN+ neuronal number, relative density of Iba1+ microglia in the hippocampus, or relative density of MBP+ oligodendrocytes in the fimbria. I also show that 50mg/kg chronic glyphosate exposure elevates hemoglobin A1c levels, indicating disruptions in glucose metabolism that may be tied to polydipsia. Collectively, these results indicate that glyphosate crosses the blood-brain barrier, induces a neuroinflammatory response, and exacerbates amyloid pathology. Ultimately, these findings provide important insight into the concerns surrounding the neurological implications of glyphosate exposure.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, diagnosed late in

the disease by a series of motor deficits that manifest over years or decades. It is characterized by degeneration of mid-brain dopaminergic neurons with a high prevalence of dementia associated with the spread of pathology to cortical regions. Patients exhibiting symptoms have already undergone significant neuronal loss without chance for recovery. Analysis of disease specific changes in gene expression directly from human patients can uncover invaluable clues about a still unknown etiology, the potential of which grows exponentially as additional gene regulatory measures are questioned. Epigenetic mechanisms are emerging as important components of neurodegeneration, including PD; the extent to which methylation changes correlate with disease progression has not yet been reported. This collection of work aims to define multiple layers of PD that will work toward developing biomarkers that not only could improve diagnostic accuracy, but also push the boundaries of the disease detection timeline. I examined changes in gene expression, alternative splicing of those gene products, and the regulatory mechanism of DNA methylation in the Parkinson’s disease system, as well as the pathologically related Alzheimer’s disease (AD). I first used RNA sequencing (RNAseq) to evaluate differential gene expression and alternative splicing in the posterior cingulate cortex of patients with PD and PD with dementia (PDD). Next, I performed a longitudinal genome-wide methylation study surveying ~850K CpG methylation sites in whole blood from 189 PD patients and 191 control individuals obtained at both a baseline and at a follow-up visit after 2 years. I also considered how symptom management medications could affect the regulatory mechanism of DNA methylation. In the last chapter of this work, I intersected RNAseq and DNA methylation array datasets from whole blood patient samples for integrated differential analyses of both PD and AD. Changes in gene expression and DNA methylation reveal clear patterns of pathway dysregulation that can be seen across brain and blood, from one study to the next. I present a thorough survey of molecular changes occurring within the idiopathic Parkinson’s disease patient and propose candidate targets for potential molecular biomarkers.

The purpose of this dissertation was 1) to develop noninvasive strategies to assess skeletal muscle size, architecture, and composition in young and old adults (study #1) and 2) evaluate the impact of chemotherapeutic treatment on skeletal muscle satellite cells and capillaries (study #2). For study #1 ultrasound images were obtained from the quadriceps muscles of young (8 m, 8 f) and older (7 m, 5 f) participants on two occasions, separated by 5-15 days. Images were collected while the participants were both standing and supine, and were analyzed for muscle thickness, pennation angle, and echogenicity. In addition, test-retest reliability and ICCs were evaluated for each posture and when imaging sites remained marked or were re-measured from visit #1 to visit #2. Generally, in both younger and older adults muscle thickness was greater and echogenicity was lower in the anterior quadriceps when images were collected standing versus supine. Maintaining the imaging site between visits did not influence test re-test reliability for either age group. Older adults exhibited smaller muscle thickness, lower pennation angle and increased echogenicity. Further, variability for the use of ultrasound to determine muscle thickness and pennation angle was greater in older versus younger adults. Findings from study #1 highlight several methodological considerations for US-based assessment of skeletal muscle characteristics that should be considered for improving reproducibility and generalizability of US to assess skeletal muscle characteristics and function across the aging spectrum. This is particularly relevant given the emerging use of ultrasound to assess skeletal muscle characteristics in healthy and clinical populations. In the second study, ovariectomized female Sprague-Dawley rats were randomized to receive three bi-weekly intraperitoneal injections of the chemotherapeutic drug, Doxorubicin (DOX) (4mg/kg; cumulative dose 12mg/kg) or vehicle (VEH; saline). Animals were euthanized 5d following the last injection, and the soleus (SOL) and extensor digitorum longus (EDL) muscles were dissected and prepared for immunohistochemical and RT-qPCR analyses. Relative to VEH, cross-sectional area (CSA) of the SOL and EDL muscle fibers were 26% and 33% smaller, respectively, in DOX animals (P<0.05). In the SOL satellite cell and capillary densities were 39% and 35% lower, respectively, in DOX animals (P<0.05), whereas in the EDL satellite cell and capillary densities were unaffected by DOX administration (P>0.05). In the SOL MYF5 mRNA expression was increased in DOX animals (P<0.05), while in the EDL MGF mRNA expression was reduced in DOX animals (P<0.05). Chronic DOX administration is associated with reduced fiber size in multiple skeletal muscles, however DOX appears to impact the satellite cell and capillary densities in a muscle-specific manner. These findings from study #2 highlight that therapeutic targets to protect skeletal muscle from DOX may vary across muscles. Collectively, these findings 1) improve the ability to examine muscle size and function in younger and older adults, and 2) identify promising therapeutic targets to protect skeletal muscle from the harmful effects of chemotherapy treatment.

Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view into biological mechanisms that impact disease trait and risk. In spite of available data types and ability to collect them simultaneously from patients, researchers still rely on their independent analysis. Combining information from multiple biological data can reduce missing information, increase confidence in single data findings, and provide a more complete view of genotype-phenotype correlations. Although rare disease genetics has been greatly improved by exome sequencing, a substantial portion of clinical patients remain undiagnosed. Multiple frameworks for integrative analysis of genomic and transcriptomic data are presented with focus on identifying functional genetic variations in patients with undiagnosed, rare childhood conditions. Direct quantitation of X inactivation ratio was developed from genomic and transcriptomic data using allele specific expression and segregation analysis to determine magnitude and inheritance mode of X inactivation. This approach was applied in two families revealing non-random X inactivation in female patients. Expression based analysis of X inactivation showed high correlation with standard clinical assay. These findings improved understanding of molecular mechanisms underlying X-linked disorders. In addition multivariate outlier analysis of gene and exon level data from RNA-seq using Mahalanobis distance, and its integration of distance scores with genomic data found genotype-phenotype correlations in variant prioritization process in 25 families. Mahalanobis distance scores revealed variants with large transcriptional impact in patients. In this dataset, frameshift variants were more likely result in outlier expression signatures than other types of functional variants. Integration of outlier estimates with genetic variants corroborated previously identified, presumed causal variants and highlighted new candidate in previously un-diagnosed case. Integrative genomic approaches in easily attainable tissue will facilitate the search for biomarkers that impact disease trait, uncover pharmacogenomics targets, provide novel insight into molecular underpinnings of un-characterized conditions, and help improve analytical approaches that use large datasets.