Organic acidurias are a large group of inherited metabolic disorders (IMDs), commonly diagnosed by GC-MS analysis of organic acids in urine after acidic extraction and trimethylsilylation. In this study, a GC×GC-ToF-MS method has been optimized for the analysis of pathological metabolites in urine. An automated data processing strategy based on the use of mass spectra and GC retention times for the target search and quantification of pathological metabolites has been developed. Using this procedure, each unknown sample is automatically examined for the presence of markers of several diseases at the same time. The method has been applied for the analysis of 6 challenging proficiency testing samples from patients with IMDs (thymidine phosphorylase deficiency, mevalonic aciduria, hawkinsinuria, aromatic l-amino acid decarboxylase deficiency, propionic acidemia and medium-chain acyl-CoA dehydrogenase deficiency). Using the GC×GC-ToF-MS method, we were able to determine complete sets of markers for all the IMDs. The quality of the mass spectral matches for the pathological markers was higher than 800 (out of 1000).
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