Structural elucidation of novel biomarkers of known metabolic disorders based on multistage fragmentation mass spectra

Abstract

Specific diagnostic markers are the key to effective diagnosis and treatment of inborn errors of metabolism (IEM). Untargeted metabolomics allows for the identification of potential novel diagnostic biomarkers. Current separation techniques coupled to high-resolution mass spectrometry provide a powerful tool for structural elucidation of unknown compounds in complex biological matrices. This is a proof-of-concept study testing this methodology to determine the molecular structure of as yet uncharacterized m/z signals that were significantly increased in plasma samples from patients with phenylketonuria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. A hybrid linear ion trap-orbitrap high resolution mass spectrometer, capable of multistage fragmentation, was used to acquire accurate masses and product ion spectra of the uncharacterized m/z signals. In order to determine the molecular structures, spectral databases were searched and fragmentation prediction software was used. This approach enabled structural elucidation of novel compounds potentially useful as biomarkers in diagnostics and follow-up of IEM patients. Two new conjugates, glutamyl-glutamyl-phenylalanine and phenylalanine-hexose, were identified in plasma of phenylketonuria patients. These novel markers showed high inter-patient variation and did not correlate to phenylalanine levels, illustrating their potential added value for follow-up. As novel biomarkers for 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, three positional isomers of 3-methylglutaconyl carnitine could be detected in patient plasma. Our results highlight the applicability of current accurate mass multistage fragmentation techniques for structural elucidation of unknown metabolites in human biofluids, offering an unprecedented opportunity to gain further biochemical insights in known inborn errors of metabolism by enabling high confidence identification of novel biomarkers.

Inborn Errors of Metabolism in the Era of Untargeted Metabolomics and Lipidomics

“…Untargeted metabolomics widens the range of metabolites associated with IEMs and discovers new compounds that could be potential biomarkers. Using untargeted metabolomics in phenylketonuria of patient plasma led to the identification of two new biomarkers, glutamyl-glutamyl-phenylalanine, and phenylalanine-hexose [177]. These new markers showed a high degree of variation between PKU patients and did not correlate with phenylalanine levels, illustrating their potential to highlight new mechanisms of the disease that would require further validation.…”

Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform

“…Noticeably, we, as well as others [8,9,11], show the potential of metabolomics in IEM diagnostics, but in none of these reports full analytical and clinical validation has been performed, while this is a requirement before application in the clinic. In addition to the potential of screening for known IEMs, untargeted metabolomics platforms allow the identification of new biomarkers, useful to establish diagnoses or to use as a surrogate marker for disease outcome [9,25,26]. Finally, metabolomics provides a comprehensive biochemical phenotype that facilitates interpretation of possible biochemical consequences of variants of unknown significance identified in whole exome sequencing or whole genome sequencing [9,11,27].…”

From mass to metabolite in human untargeted metabolomics: Recent advances in annotation of metabolites applying liquid chromatography-mass spectrometry data

“…Here gas-phase fragmentation of product ions can be performed in multiple stages. For low complexity chemical structures, MS/MS data can suffice but for more complex structures and where two structurally similar isomers can differ only in the position of a single functional group then MS n data provides increased confidence and accuracy (see [45,46] for examples of this application applying offline and online approaches). The collection of MS n data…”