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Influences of methamphetamine-induced acute intoxication on urinary and plasma metabolic profiles in the rat

Shima, Noriaki, Miyawaki, Izuru, Bando, Kiyoko, Horie, Hiroshi, Zaitsu, Kei, Katagi, Munehiro, Bamba, Takeshi, Tsuchihashi, Hitoshi, Fukusaki, Eiichiro·2011·Toxicology
DOI 10.1016/j.tox.2011.05.012
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Abstract

Methamphetamine (MA) is an illicit psychostimulant, and its abuse has become an international public health problem. MA intoxication can cause life-threatening hyperthermia, renal and liver failure, cardiac arrhythmias, and neurological damage. To investigate the relationship between the underlying mechanism of such intoxication and metabolic networks, mass spectrometry-based metabolomics experiments were performed on Sprague-Dawley rats treated with MA at 10mgkg(-1)h(-1) for 4h. Using a combination of gas chromatography-time-of-flight mass spectrometry and capillary electrophoresis-tandem mass spectrometry, global and targeted analyses were performed on biological samples collected during 0-24 and 72-96h (for urine), and at 24 and 96h (for plasma) after the last drug administration. Body temperature and plasma biochemical parameters were also measured to detect abnormal reactions in neuronal and other several tissues. 5-Oxoproline, saccharic acid, uracil, 3-hydroxybutyrate (3-HB), adipic acid, glucose, glucose 6-phosphate, fructose 1,6-bisphosphate, and tricarboxylic acid (TCA) cycle intermediates, such as fumarate, were proposed as potential biomarkers related to MA-induced intoxications. In particular, the observation of decreased TCA cycle intermediates and 3-HB and increased glucose suggested that high doses of MA inhibit biogenic energy production by glycolysis, oxidative phosphorylation via the TCA cycle, and the beta-oxidation of fatty acids. These results may provide…

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  • Adult humans are characterized by individual metabolic phenotypes; metabolic profiles can predict susceptibility to DILI.

    “Adult humans are characterized by individual metabolic phenotypes [37,38,39,40,41]; there are areas of the metabolome unique to each individual that remain stable over time. “Metabolic profiles” can be detected that allow us to predict which individuals may present ways of metabolizing drugs that make them more susceptible to presenting DILI [17].”

    From Metabolomic Analysis of Pediatric Patients with Idiosyncratic Drug-Induced Liver Injury According to the Updated RUCAM (2023) · cites this paper as [41]

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Research works printed but not linked: 43

  1. Albertson, 1999, Methamphetamine and the expanding complications of amphetamines, West J. Med., 170, 214
  2. Bando, K., Kunimatsu, T., Sakai, J., Kimura, J., Funabashi, H., Seki, T., Bamba, T., Fukusaki, E. GC–MS-based metabolomics reveals mechanism of action for hydrazine induced hepatotoxicity in rats. J. Appl. Toxicol., doi:10.1002/jat.1591, 2010 Dec 10. · DOI
  3. Bando, 2010, Influences of biofluid sample collection and handling procedures on GC–MS based metabolomic studies, J. Biosci. Bioeng., 110, 491, 10.1016/j.jbiosc.2010.04.010 · DOI
  4. Berman, 2008, Changes in cerebral glucose metabolism during early abstinence from chronic methamphetamine abuse, Mol. Psychiatry, 13, 897, 10.1038/sj.mp.4002107 · DOI
  5. Boudonck, 2009, Discovery of metabolomics biomarkers for early detection of nephrotoxicity, Toxicol. Pathol., 37, 280, 10.1177/0192623309332992 · DOI
  6. Cahill, 2006, Fuel metabolism in starvation, Annu. Rev. Nutr., 26, 1, 10.1146/annurev.nutr.26.061505.111258 · DOI
  7. Darke, 2008, Major physical and psychological harms of methamphetamine use, Drug Alcohol Rev., 27, 253, 10.1080/09595230801923702 · DOI · Paper page
  8. De Vos, 2007, Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry, Nat. Protoc., 2, 778, 10.1038/nprot.2007.95 · DOI
  9. Dettmer, 2007, Mass spectrometry-based metabolomics, Mass Spectrom. Rev., 26, 51, 10.1002/mas.20108 · DOI
  10. Dickinson, 1994, The ovine fetal sympathoadrenal response to the maternal administration of methamphetamine, Am. J. Obstet. Gynecol., 170, 1452, 10.1016/S0002-9378(13)90487-7 · DOI
  11. Gramsbergen, 2007, Serotonin mediates rapid changes of striatal glucose and lactate metabolism after systemic 3,4-methylenedioxymethamphetamine (MDMA, “Ecstasy”) administration in awake rats, Neurochem. Int., 51, 8, 10.1016/j.neuint.2007.03.004 · DOI
  12. Gudelsky, 2008, Actions of 3,4-methylenedioxymethamphetamine (MDMA) on cerebral dopaminergic, serotonergic and cholinergic neurons, Pharmacol. Biochem. Behav., 90, 198, 10.1016/j.pbb.2007.10.003 · DOI
  13. Harada, 2008, Quantitative analysis of anionic metabolites for Catharanthus roseus by capillary electrophoresis using sulfonated capillary coupled with electrospray ionization-tandem mass spectrometry, J. Biosci. Bioeng., 105, 249, 10.1263/jbb.105.249 · DOI
  14. Herring, 2008, Comparison of time-dependent effects of (+)-methamphetamine or forced swim on monoamines, corticosterone, glucose, creatine, and creatinine in rats, BMC Neurosci., 9, 49, 10.1186/1471-2202-9-49 · DOI
  15. Hirayama, 2009, Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry, Cancer Res., 69, 4918, 10.1158/0008-5472.CAN-08-4806 · DOI
  16. Homer, 2008, Methamphetamine abuse and impairment of social functioning: a review of the underlying neurophysiological causes and behavioral implications, Psychol. Bull., 134, 301, 10.1037/0033-2909.134.2.301 · DOI
  17. Kim, 2005, Frontal glucose hypometabolism in abstinent methamphetamine users, Neuropsychopharmacology, 30, 383, 10.1038/sj.npp.1300699 · DOI
  18. Kim, 2006, Prefrontal grey-matter changes in short-term and long-term abstinent methamphetamine abusers, Int. J. Neuropsychopharmacol., 9, 221, 10.1017/S1461145705005699 · DOI
  19. Kim, 2009, Dose-dependent frontal hypometabolism on FDG-PET in methamphetamine abusers, J. Psychiatr. Res., 43, 1166, 10.1016/j.jpsychires.2009.03.011 · DOI
  20. Kuhara, 2001, Diagnosis of inborn errors of metabolism using filter paper urine, urease treatment, isotope dilution and gas chromatography–mass spectrometry, J. Chromatogr. B: Biomed. Sci. Appl., 758, 3, 10.1016/S0378-4347(01)00138-4 · DOI
  21. Kuhara, 2005, Gas chromatographic-mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism, Mass Spectrom. Rev., 24, 814, 10.1002/mas.20038 · DOI
  22. Kumar, 2010, Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach, Anal. Chim. Acta, 19, 47, 10.1016/j.aca.2009.11.063 · DOI
  23. Lommen, 2009, MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing, Anal. Chem., 81, 3079, 10.1021/ac900036d · DOI
  24. Meredith, 2005, Implications of chronic methamphetamine use: a literature review, Harv. Rev. Psychiatry, 13, 141, 10.1080/10673220591003605 · DOI
  25. Park, 2010, Characterization of blood glucose level regulation in mouse opioid withdrawal models, Neurosci. Lett., 476, 119, 10.1016/j.neulet.2010.03.014 · DOI
  26. Perez, 1999, Methamphetamine-related stroke: four cases, J. Emerg. Med., 17, 469, 10.1016/S0736-4679(99)00009-8 · DOI
  27. Perrine, 2009, Cardiac effects of MDMA on the metabolic profile determined with 1H-magnetic resonance spectroscopy in the rat, NMR Biomed., 22, 419, 10.1002/nbm.1352 · DOI
  28. Robertson, 2005, Metabonomics in toxicology: a review, Toxicol. Sci., 85, 809, 10.1093/toxsci/kfi102 · DOI
  29. Sailasuta, 2010, Glial dysfunction in abstinent methamphetamine abusers, J. Cereb. Blood Flow Metab., 30, 950, 10.1038/jcbfm.2009.261 · DOI
  30. Shiomi, Y., Nishiumi, S., Ooi, M., Hatano, N., Shinohara, M., Yoshie, T., Kondo, Y., Furumatsu, K., Shiomi, H., Kutsumi, H., Azuma, T., Yoshida, M. GC–MS-based metabolomic study in mice with colitis induced by dextran sulfate sodium. Inflamm. Bowel. Dis., doi:10.1002/ibd.21616, 2011 Feb 1. · DOI
  31. Soga, 2003, Quantitative metabolome analysis using capillary electrophoresis mass spectrometry, J. Proteome Res., 2, 488, 10.1021/pr034020m · DOI
  32. Sugimoto, 2010, Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles, Metabolomics, 6, 78, 10.1007/s11306-009-0178-y · DOI
  33. Tata, 2007, Augmentation of methamphetamine-induced toxicity in the rat striatum by unpredictable stress: contribution of enhanced hyperthermia, Eur. J. Neurosci., 26, 739, 10.1111/j.1460-9568.2007.05688.x · DOI
  34. Trygg, 2007, Chemometrics in metabonomics, J. Proteome Res., 6, 469, 10.1021/pr060594q · DOI
  35. Trygg, 2002, Orthogonal projections to latent structures (O-PLS), J. Chemom., 16, 119, 10.1002/cem.695 · DOI
  36. United Nations Office on Drugs and Crime, 2010, 10.18356/079beef9-en · DOI
  37. Volkow, 2001, Higher cortical and lower subcortical metabolism in detoxified methamphetamine abusers, Am. J. Psychiatry, 158, 383, 10.1176/appi.ajp.158.3.383 · DOI
  38. Wang, 2004, Partial recovery of brain metabolism in methamphetamine abusers after protracted abstinence, Am. J. Psychiatry, 161, 242, 10.1176/appi.ajp.161.2.242 · DOI
  39. Wiklund, 2007, Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models, Anal. Chem., 80, 116
  40. Wohlfarth, 2010, Bioanalysis of new designer drugs, Bioanalysis, 2, 965, 10.4155/bio.10.32 · DOI
  41. Yu, 2002, Plasma l-5-oxoproline kinetics and whole blood glutathione synthesis rates in severely burned adult humans, Am. J. Physiol. Endocrinol. Metab., 282, E247, 10.1152/ajpendo.00206.2001 · DOI
  42. Yuan, 2006, Relationship between temperature, dopaminergic neurotoxicity, and plasma drug concentrations in methamphetamine-treated squirrel monkeys, J. Pharmacol. Exp. Ther., 316, 1210, 10.1124/jpet.105.096503 · DOI
  43. Zhao, 2007, General versus specific actions of mild-moderate hypothermia in attenuating cerebral ischemic damage, J. Cereb. Blood Flow Metab., 27, 1879, 10.1038/sj.jcbfm.9600540 · DOI

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Metadata

Authors
Shima, N., Miyawaki, I., Bando, K., Horie, H., Zaitsu, K., Katagi, M., Bamba, T., Tsuchihashi, H., & Fukusaki, E.
Venue
Toxicology
Publisher
Elsevier BV
Published
2011-09
Volume
287
Issue
1-3
Pages
29-37
ISSN
0300-483X
DOI
10.1016/j.tox.2011.05.012
Cited by
75
References
0
Language
en
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