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488 From discovery to the clinical laboratory: a methodological appraisal of untargeted metabolomics platforms to characterize inborn errors of metabolism.

Published online by Cambridge University Press:  03 April 2024

Rachel Wurth
Affiliation:
Mayo Clinic
Coleman Turgeon
Affiliation:
Mayo Clinic
Zinandré Stander
Affiliation:
Mayo Clinic
Devin Oglesbee
Affiliation:
Mayo Clinic
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Abstract

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OBJECTIVES/GOALS: Untargeted metabolomics platforms are powerful biomarker discovery tools. However, the absence of uniform study design, data analysis, and reporting standards limits translation of this research into the clinical lab. The goal was to critically appraise existing untargeted metabolomics platforms that analyzed inborn errors of metabolism. METHODS/STUDY POPULATION: A search strategy was conducted in MEDLINE via PubMed from January 16, 2013, to January 16, 2023. The search strategy was limited to primary literature articles written in English that evaluated human subjects with inborn errors of metabolism (IEMs). Articles that performed targeted metabolomic analysis or analyzed non-human samples were excluded. Information on patient cohorts analyzed, sample types, and method design were extracted using a template. Categorical data are summarized as frequencies and percentages. RESULTS/ANTICIPATED RESULTS: A total of 96 distinct IEMs were evaluated by the different untargeted metabolomics methods included in this review. However, most IEMs (55/96, 57%) were evaluated by a single platform, in a single study, with a limited cohort size. Only one study validated their results using a separate, validation cohort. There was considerable diversity in the separation techniques and mass spectrometry instrumentation used by the studies to create their untargeted metabolomics methods. Slightly over half (59%) of the studies identified at least some of the metabolites detected in their samples with the highest level of confidence. Importantly, most of the included studies reported adherence to quality metrics, including use of quality control material (65%) and internal standards in their analysis (61%). DISCUSSION/SIGNIFICANCE: Future studies analyzing IEM patient samples with untargeted metabolomics platforms should progress beyond single-subject studies and evaluate the reproducibility of the research using a prospective, or validation cohort as well as confirm metabolite annotations with reference metabolites standards to generate clinically useful data.

Type
Precision Medicine/Health
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2024. The Association for Clinical and Translational Science