Date of Thesis
Masters Thesis (Bucknell Access Only)
Master of Science
David S. Rovnyak
NMR, Metabolomics, Diabetes
Metabolomics offers the potential of associating a macroscopic view of an organism to measured levels of small molecule reporters of metabolic pathways. Despite large growth in metabolomics studies, critical questions on reproducibility and stability warrant investigation. Initially, detection limits and efficient extraction methods were performed to assess accuracy and precision in measurements using standards. This work then examined aqueous extractions of fetal bovine serum (FBS) by 600 MHz 1H NMR spectroscopy for stability and reproducibility of metabolite levels over time at storage temperatures of 20, 4, -35, and -80 °C. Using four replicates for each storage temperature, 48 metabolites in FBS were profiled. As expected, metabolite levels degraded at a faster rate at room temperature. Unexpectedly, most metabolites were stable at room temperature for nearly two weeks such as phenylalanine and valine. However, metabolites such as allantoin, creatinine, and glutamine detectably degraded over just 2 hours of room temperature exposure. Storage of samples at 4 °C dramatically improves the lifetime of all metabolites, further emphasizing all sample handling steps should be moved to cold rooms. Degradation occurring in samples stored at -30 and -80 °C appear to be caused by freeze/thaw cycles of periodic NMR measurements, rather than degradation from storage time. As expected, metabolites were much more stable for longer periods of time at colder storage temperatures.
We next pursued a model study to test the ability of NMR spectroscopy to act as the sole metabolic profiler in correlating patient states to systematic changes in metabolite levels in an effort to utilize metabolomics for personalized medicine. Type II Diabetes (T2D) has previously been studied by metabolomics methods, so a study was designed around T2D patients to compare and validate against recent literature results. Further, questions remain about the risk factors and onset of T2D. This work reports the NMR analysis of human serum contrasting three female, mostly Caucasian cohorts: lean (low BMI), obese (high BMI), and obese (high BMI) with T2D. Spectra were profiled and subjected to PCA and PLS-DA multivariate analysis, where substantial clustering of the three cohorts based on altered metabolite levels was achieved solely from NMR data. Notably, elevated levels of valine, leucine, phenylalanine, isoleucine, and tyrosine were observed in high BMI T2D patients, consistent with recent reports using other techniques such as LC-MS 1. Nine of the ten variables causing the most separation and clustering in this study have previously been reported as possible biomarkers in T2D 1-5, with glutamate contributing the most to separating the three cohorts. However, this work reports a new finding that hypoxanthine varied significantly between these cohorts, which had not previously been observed. Further, these cohorts were selected from a commercial serum provider and are considered highly variable with respect to confounding factors, and this work demonstrates the ability to cluster a diverse population versus a specific disease state.
Miele, Matthew, "Validating NMR-Based Metabolomics Methods With Applications to Type II Diabetes in Human Serum" (2015). Master’s Theses. 153.