In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire\na complete view of metabolite status. Here, we describe a non-quantitative direct-infusion\nhigh-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method\nfor both dried blood spots (DBS) and plasma. 110 DBS of 42 patients harboring 23 different inborn\nerrors of metabolism (IEM) and 86 plasma samples of 38 patients harboring 21 different IEM were\nanalyzed using DI-HRMS. A peak calling pipeline developed in R programming language provided\nZ-scores for -1875 mass peaks corresponding to-3835 metabolite annotations (including isomers)\nper sample. Based on metabolite Z-scores, patients were assigned a â??most probable diagnosisâ?? by\nan investigator blinded for the known diagnoses of the patients. Based on DBS sample analysis,\n37/42 of the patients, corresponding to 22/23 IEM, could be correctly assigned a â??most probable\ndiagnosisâ??. Plasma sample analysis, resulted in a correct â??most probable diagnosisâ?? in 32/38 of the\npatients, corresponding to 19/21 IEM. The added clinical value of the method was illustrated by\na case wherein DI-HRMS metabolomics aided interpretation of a variant of unknown significance\n(VUS) identified by whole-exome sequencing. In summary, non-quantitative DI-HRMS metabolomics\nin DBS and plasma is a very consistent, high-throughput and nonselective method for investigating\nthe metabolome in genetic disease.
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