Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.695491
Title: Metabolic profiling for biomarker discovery in biochemical genetics
Author: Robinette, Steven Lawrence
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2013
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Abstract:
Functional characterization of the phenotypic consequences of genetic variants increasingly constitutes the rate-limiting step in the study of biochemical genetics. This thesis presents the application of metabolic profiling technologies, including Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS), to identify metabolic perturbations resulting from inborn errors of metabolism, congenital diseases affecting the kidney, and animal models of both genetic mutations and renal pathology. In the case of newborn screening for enzyme deficiencies, two mass spectrometric assays, traditional tandem mass spectrometry (MS/MS) with multiple reaction monitoring and direct injection nanospray high resolution mass spectrometry (ns-HR-MS), were applied to profile dried blood spot (DBS) samples of over 6,000 newborns and identify the metabolic perturbations resulting from 24 congenital disorders of metabolism. To study genetic mutations with more complex phenotypic consequences affecting the kidney, urinary metabolic profiles were evaluated for four congenital kidney diseases. The natural history of cystinosis, showing changes in the urinary profile of cystinosis patients over time and with age, glomerular filtration rate, drug therapy, and transplantation, and a comparison of urinary perturbations seen in these human Mendelian disorders to the perturbations induced by region specific nephrotoxins characterize the urinary metabolic associations with these renal phenotypes. Finally, new computational approaches for analyzing metabolic profiling data are presented and evaluated, including for improving biomarker identification with two-dimensional NMR and increasing metabolomic coverage with high resolution mass spectrometry. Integrating metabolic and genetic diagnostics should enhance understanding of the relationship between genes and health and mechanisms by which genetic variations manifest as inherited disease.
Supervisor: Nicholson, Jeremy ; Gahl, William Sponsor: Marshall Aid Commemoration Commission ; National Science Foundation (U.S.) ; National Institutes of Health
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.695491  DOI: Not available
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