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Anal Bioanal Chem. 2019 Apr 2. doi: 10.1007/s00216-019-01719-z. [Epub ahead of print]

Application of differential mobility-mass spectrometry for untargeted human plasma metabolomic analysis.

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Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, 48105, USA.
Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, 48105, USA.
Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, 48105, USA.


Differential mobility spectrometry (DMS) has been gaining popularity in small molecule analysis over the last few years due to its selectivity towards a variety of isomeric compounds. While DMS has been utilized in targeted liquid chromatography-mass spectrometry (LC-MS), its use in untargeted discovery workflows has not been systematically explored. In this contribution, we propose a novel workflow for untargeted metabolomics based solely on DMS separation in a clinically relevant chronic kidney disease (CKD) patient population. We analyzed ten plasma samples from early- and late-stage CKD patients. Peak finding, alignment, and filtering steps performed on the DMS-MS data yielded a list of 881 metabolic features (unique mass-to-charge and migration time combinations). Differential analysis by CKD patient group revealed three main features of interest. One of them was putatively identified as bilirubin based on high-accuracy MS data and comparison of its optimum compensation voltage (COV) with that of an authentic standard. The DMS-MS analysis was four times faster than a typical HPLC-MS run, which suggests a potential for the utilization of this technique in screening studies. However, its lower separation efficiency and reduced signal intensity make it less suitable for low-abundant features. Fewer features were detected by the DMS-based platform compared with an HPLC-MS-based approach, but importantly, the two approaches resulted in different features. This indicates a high degree of orthogonality between HPLC- and DMS-based approaches and demonstrates the need for larger studies comparing the two techniques. The workflow described here can be adapted for other areas of metabolomics and has a value as a prescreening method to develop semi-targeted workflows and as a faster alternative to HPLC in large biomedical studies.


Biomarker discovery; Chronic kidney disease; Differential mobility spectrometry; Mass spectrometry; Untargeted metabolomics


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