Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Tasevska, Natasha
Description
Metabolomics focuses on the study of metabolic changes occurring in varioussystems and utilizes quantitative and semi-quantitative measurements of multiple metabolites in parallel. Mass spectrometry (MS) is the most ubiquitous platform in this field, as it provides superior sensitivity regarding measurements of complex metabolic profiles in biological systems. When combined with MS, multivariate statistics and advanced machine learning algorithms provide myriad opportunities for bioinformatics insights beyond simple univariate data comparisons. In this dissertation, the application of MS-based metabolomics is introduced with an emphasis on biomarker discovery for human disease detection. To advance disease diagnosis using MS-based metabolomics, numerous statistical techniques have been implemented in this research including principal component analysis, factor analysis, partial least squares-discriminant analysis (PLS-DA), orthogonal PLS-DA, random forest, receiver operating characteristic analysis, as well as functional pathway/enzyme enrichment analyses. These approaches are highly useful for improving classification sensitivity and specificity related to disease-induced biological variation and can help identify useful biomarkers and potential therapeutic targets. It is also shown that MS-based metabolomics can distinguish between clinical and prodromal disease as well as similar diseases with related symptoms, which may assist in clinical staging and differential diagnosis, respectively. Additionally, MS-based metabolomics is shown to be promising for the early and accurate detection of diseases, thereby improving patient outcomes, and advancing clinical care. Herein, the application of MS methods and chemometric statistics to the diagnosis of breast cancer, coccidioidomycosis (Valley fever), and senile dementia (Alzheimer's disease) are presented and discussed. In addition to presenting original research, previous efforts in biomarker discovery will be synthesized and appraised. A Comment will be offered regarding the state of the science, specifically addressing the inefficient model of repetitive biomarker discovery and the need for increased translational efforts necessary to consolidate metabolomics findings and formalize purported metabolic markers as laboratory developed tests. Various factors impeding the translational throughput of metabolomics findings will be carefully considered with respect to study design, statistical analysis, and regulation of biomedical diagnostics. Importantly, this dissertation will offer critical insights to advance metabolomics from a scientific field to a practical one including targeted detection, enhanced quantitation, and direct-to-consumer considerations.
ContributorsJasbi, Paniz (Author) / Johnston, Carol S (Thesis advisor) / Gu, Haiwei (Thesis advisor) / Lake, Douglas F (Committee member) / Sweazea, Karen (Committee member) / Tasevska, Natasha (Committee member) / Arizona State University (Publisher)
Created2022
Description
Background: Sugars form advanced glycation end products (AGEs) throughnatural metabolism and interactions with proteins, lipids, and nucleic acids, which accumulate in tissues and have been implicated in the etiology of chronic diseases. Due to the increased consumption of fructose and its high ability to form AGEs, a further understanding of this association is important to clarify the role of sugars in disease. The objective was to explore the association between usual fructose intake and serum levels of AGEs, as measured by carboxymethyl-lysine (CML) and methylglyoxal derivative (MG-H1), in healthy adults. Methods: This is a secondary analysis of a 15-d controlled feeding study (n=100) with participants consuming their usual diet conducted in the Phoenix metropolitan area. To assess participants’ usual diet, they were asked to complete two 7-d food diaries, which were then used to create custom 15-d menu plans administered during the feeding period. Forty participants were selected based on their 15-d mean total fructose intake for this analysis [top and bottom 20% of the sample distribution (median, IQR); high fructose (HF) n= 20, 72.6 (66.1-90.4) g/day, low fructose (LF) n= 20, 28.8 (22.7-32.2) g/day. Fasting serum collected five weeks after the feeding period were analyzed for CML and MG-H1, two well-established AGEs, using ELISA kits. A database of 549 common foods with known CML amounts was used to calculate exogenous CML intake based on daily food intake data. A general linear model was fitted to investigate the difference in serum CML and MG-H1 between LF and HF groups while adjusting for age, gender, BMI, and exogenous CML intake. Results: Participants in the HF group had significantly higher serum CML and lower MG-H1 levels compared to participants in the LF group (p=0.013 and p=0.002, respectively). This difference remained statistically significant after adjusting for covariates. Conclusions: The findings suggest that endogenous CML formation may be an explanation for the significantly higher serum CML levels in the HF compared to the LF group. This is significant in further understanding mechanisms of fructose intake and disease etiology and could have implications for at-risk populations consuming a high fructose diet.
ContributorsWeigand, Bethany (Author) / Tasevska, Natasha (Thesis advisor) / Sweazea, Karen (Committee member) / Lee, Chong (Committee member) / Arizona State University (Publisher)
Created2021