Validation of a LC-MS/MS Method for Quantifying Urinary Nicotine, Six Nicotine Metabolites and the Minor Tobacco Alkaloids—Anatabine and Anabasine—in Smokers' Urine
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Validation of a LC-MS/MS Method for Quantifying Urinary Nicotine, Six Nicotine Metabolites and the Minor Tobacco Alkaloids—Anatabine and Anabasine—in Smokers' Urine

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    PLoS One
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    Tobacco use is a major contributor to premature morbidity and mortality. The measurement of nicotine and its metabolites in urine is a valuable tool for evaluating nicotine exposure and for nicotine metabolic profiling--i.e., metabolite ratios. In addition, the minor tobacco alkaloids--anabasine and anatabine--can be useful for monitoring compliance in smoking cessation programs that use nicotine replacement therapy. Because of an increasing demand for the measurement of urinary nicotine metabolites, we developed a rapid, low-cost method that uses isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) for simultaneously quantifying nicotine, six nicotine metabolites, and two minor tobacco alkaloids in smokers' urine. This method enzymatically hydrolyzes conjugated nicotine (primarily glucuronides) and its metabolites. We then use acetone pretreatment to precipitate matrix components (endogenous proteins, salts, phospholipids, and exogenous enzyme) that may interfere with LC-MS/MS analysis. Subsequently, analytes (nicotine, cotinine, hydroxycotinine, norcotinine, nornicotine, cotinine N-oxide, nicotine 1'-N-oxide, anatabine, and anabasine) are chromatographically resolved within a cycle time of 13.5 minutes. The optimized assay produces linear responses across the analyte concentrations typically found in urine collected from daily smokers. Because matrix ion suppression may influence accuracy, we include a discussion of conventions employed in this procedure to minimize matrix interferences. Simplicity, low cost, low maintenance combined with high mean metabolite recovery (76-99%), specificity, accuracy (0-10% bias) and reproducibility (2-9% C.V.) make this method ideal for large high through-put studies.
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  • Volume:
    9
  • Issue:
    7
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