Development of Biochemical Assays for the Screening, Diagnosis, and Prognosis of Treatable Inborn Errors of Metabolism

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Hong, Xinying

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Inborn errors of metabolism (IEM) are a phenotypically and genetically heterogenous group of disorders caused by defective enzymes, cofactors or transporters in metabolic pathways, which lead to dysfunctional metabolism and/or the accumulation of toxic intermediate metabolites. Although individually rare, they are common as a group with a combined incidence rate of 1 in 800. A subset of these disorders have viable treatments and novel therapies are being developed at rapid pace for an increasing number of IEM. However, to achieve the optimal therapeutic outcome, it is essential to initiate treatments prior to the onset of irreversible symptoms. Therefore, treatable inborn errors of metabolism are excellent candidates for newborn screening program, which is a broad public health prevention program that aims at identifying a number of conditions for which early intervention can reduce premature mortality and morbidity. Tandem mass spectrometry (MS/MS) is the most comprehensive platform for quantifying enzymatic function and biomarkers in dried blood spots (DBS), which are the sample specimens used in newborn screening programs. An enormous effort has been made to develop high-throughput and robust MS/MS-based biochemical assays for newborn screening. Herein, we report (1) a liquid chromatography MS/MS (LC-MS/MS) assay to improve the current screening test for classic galactosemia; (2) a multiplexed ultra-performance liquid chromatography MS/MS (UPLC-MS/MS) assay for the screening of 18 IEM; (3) a large-scale study to investigate the feasibility of newborn screening of metachromatic leukodystrophy (MLD). Apart from these biochemical assays for screening purposes, a high-performance diagnostic test for MLD was developed. To better understand the clinical outcomes of the MLD-related variants, a transient gene expression system was designed to study these variants systematically.

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Thesis (Ph.D.)--University of Washington, 2020

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