Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning

Abstract

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.

Life-Threatening Cardiogenic Shock Related to Venlafaxine Poisoning—A Case Report with Metabolomic Approach

“…Eleven additional metabolites were annotated. Based on data acquired in the positive ion mode, an MN including venlafaxine and all phase-I/phase-II metabolites were generated as previously described [ 37 ]. Clusterization was based on the common product ions displayed by all MS/MS spectra of venlafaxine metabolites, including the methoxyphenyl and hydroxycyclohexyl radical.…”

“…Data processing: Raw data files acquired in positive and negative ion modes were converted into open-source mzXML files using MSConvert 3.0™ [ 34 , 35 ]. Data processing was performed using MZmine 2.53 as previously described [ 36 , 37 ]. Briefly, MS and MS/MS spectral data were extracted using a mass detection noise level set at 1E5 and 5E3, respectively.…”

Development and Validation of Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Determination of Tramadol and Its Phase I and II Metabolites in Human Urine

“…TD and M1 (ODT) have half-lives of 5-6 and 7-9 h, respectively. Thus, regular dosage may cause bioaccumulation due to M1's extended elimination halflife [8]. The six metabolic pathways that inculcate N-demethylation, O-demethylation, oxidative N-dealkylation, dehydration, cyclohexyl oxidation, and conjugation yield TD metabolites [9].…”

A Transversal Approach Combining In Silico, In Vitro and In Vivo Models to Describe the Metabolism of the Receptor Interacting Protein 1 Kinase Inhibitor Sibiriline

“…Consequently, a semi-quantitative visualization of molecule repartition in different matrix samples can be provided by a multi-matrix approach. MN has already proven its interest in drug metabolism analysis for in vitro, in vivo clinical, or forensic purposes [9,[19][20][21][22][23][24].…”