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Validation of a dual LC–HRMS platform for clinical metabolic diagnosis in serum, bridging quantitative analysis and untargeted metabolomics

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Mass spectrometry-based metabolomics is a rapidly growing field in both research and diagnosis. Generally, the methodologies and types of instruments used for clinical and other absolute quantification experiments are different from those used for biomarkers discovery and untargeted analysis, as the former requires optimal sensitivity and dynamic range, while the latter requires high resolution and high mass accuracy. We used a Q-TOF mass spectrometer with two different types of pentafluorophenyl (PFP) stationary phases, employing both positive and negative ionization, to develop and validate a hybrid quantification and discovery platform using LC–HRMS. This dual-PFP LC–MS platform quantifies over 50 clinically relevant metabolites in serum (using both MS and MS/MS acquisitions) while simultaneously collecting high resolution and high mass accuracy full scans to monitor all other co-eluting non-targeted analytes. We demonstrate that the linearity, accuracy, and precision results for the quantification of a number of metabolites, including amino acids, organic acids, acylcarnitines and purines/pyrimidines, meets or exceeds normal bioanalytical standards over their respective physiological ranges. The chromatography resolved highly polar as well as hydrophobic analytes under reverse-phase conditions, enabling analysis of a wide range of chemicals, necessary for untargeted metabolomics experiments. Though previous LC–HRMS methods have demonstrated quantification capabilities for various drug and small molecule compounds, the present study provides an HRMS quant/qual platform tailored to metabolic disease; and covers a multitude of different metabolites including compounds normally quantified by a combination of separate instrumentation.

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We thank Julio A. Gutierrez and Robert T. Schooley for providing patient sera. We would like to thank William L. Nyhan for valuable suggestions. We thank Bonnie Holmes, Kasie Auler and Priscilla Burks for running GC–MS, amino acid analyzer, and triple-quadrupole methods.

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Correspondence to Ilya Gertsman.

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Gertsman, I., Gangoiti, J.A. & Barshop, B.A. Validation of a dual LC–HRMS platform for clinical metabolic diagnosis in serum, bridging quantitative analysis and untargeted metabolomics. Metabolomics 10, 312–323 (2014).

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