Identification and characterization of amiodarone metabolites in rats using UPLC–ESI-QTOFMS-based untargeted metabolomics approach
| Autor: | Kyung-Sik Moon, Su-Jun Lee, Dong-Hyun Kim, Gabin Kim, Daeun Yim, Jae-Gook Shin, Eun Sook Jeong |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Spectrometry Mass Electrospray Ionization Health Toxicology and Mutagenesis Electrospray ionization Glucuronidation Amiodarone 010501 environmental sciences Toxicology Mass spectrometry Tandem mass spectrometry 030226 pharmacology & pharmacy 01 natural sciences Rats Sprague-Dawley Hydroxylation 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Metabolomics Tandem Mass Spectrometry medicine Animals Chromatography High Pressure Liquid 0105 earth and related environmental sciences Chromatography Rats chemistry Anti-Arrhythmia Agents Drug metabolism medicine.drug |
| Zdroj: | Journal of Toxicology and Environmental Health, Part A. 81:481-492 |
| ISSN: | 1087-2620 1528-7394 |
| Popis: | Amiodarone is a class III anti-arrhythmic benzofuran derivative extensively utilized in treatment of life-threatening ventricular and supraventricular arrhythmias. However, amiodarone also produces adverse side effects including liver injury due to its metabolites rather than parent drug. The purpose of the present study was to identify metabolites of amiodarone in the plasma and urine of rats administered the drug by using an untargeted metabolomics approach. Drug metabolites were profiled by ultra-performance liquid chromatography-linked electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS) and results subjected to multivariate data analysis. A total of 49 amiodarone metabolites were identified and their structures were characterized by tandem mass spectrometry. Amiodarone metabolites are presumed to be generated via five major types of metabolic reactions including N-desethylation, hydroxylation, carboxylation (oxo/hydroxylation), de-iodination, and glucuronidation. Data demonstrated that an untargeted metabolomics approach appeared to be a reliable tool for identifying unknown metabolites in a complex biological matrix. |
| Databáze: | OpenAIRE |
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