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dc.contributor.advisorVamsi K. Mootha.en_US
dc.contributor.authorShaham, Odeden_US
dc.contributor.otherHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.date.accessioned2010-04-28T17:17:50Z
dc.date.available2010-04-28T17:17:50Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/54670
dc.descriptionThesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2009.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractThe integrated network of biochemical reactions known collectively as metabolism is essential for life, and dysfunction in parts of this network causes human disease - both rare, inherited disorders and common diseases such as diabetes mellitus. The study of metabolic disease depends upon quantitative methods which are traditionally custom-tailored to a given compound. Recent advances in technologies such as mass spectrometry now enable the simultaneous measurement of a diverse metabolite collection spanning multiple biological pathways, an approach known as metabolic profiling or metabolomics. This dissertation describes the development of one such metabolic profiling system and its application to the study of two major topics in human energy metabolism: the fasting:feeding transition and mitochondrial disease. In the first study, we profile human plasma in response to glucose ingestion, detecting dozens of metabolite changes and identifying several distinct effects of insulin. Based on these observations, we propose a multivariate view of insulin sensitivity, and show that individuals at risk for developing diabetes mellitus can differ in their insulin response profile, a concept of potential value for estimating disease risk and progression. In the second study, we elucidate a metabolic signature of human mitochondrial disease that reflects substrate oxidation, biosynthesis and energy charge.en_US
dc.description.abstract(cont.) We demonstrate that the culture media profile of a cellular disease model of mitochondrial dysfunction reflects the plasma profile of human patients, an approach that could be applicable to other diseases as well. In addition, we show that a combination of metabolites distinguishes individuals with mitochondrial disease from healthy individuals better than the currently used diagnostic markers. Our findings provide insight into human disorders of energy metabolism, and demonstrate the utility of a profiling approach for the understanding of metabolic disease.en_US
dc.description.statementofresponsibilityby Oded Shaham.en_US
dc.format.extent114 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.titleA metabolic profiling approach to human disorders of energy metabolismen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.identifier.oclc607333303en_US


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