Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning.
Romain MagnyNicolas AuzeilBertrand LefrèreBruno MégarbanePascal HouzéLaurence LabatPublished in: Metabolites (2022)
Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient.
Keyphrases
- liquid chromatography
- tandem mass spectrometry
- ms ms
- high resolution mass spectrometry
- mass spectrometry
- ultra high performance liquid chromatography
- newly diagnosed
- high resolution
- ejection fraction
- phase ii
- clinical trial
- simultaneous determination
- prognostic factors
- high performance liquid chromatography
- randomized controlled trial
- single molecule
- artificial intelligence
- network analysis
- postoperative pain