Glyphosate is the most widely used herbicide in the world. It has been recently classified as a possible carcinogenic agent to humans by the International Agency for Research on Cancer and there is increasing concern about chronic low dose exposure to glyphosate. To better understand its exposure risk, it is important to develop fast and sensitive methods to monitor the concentrations of glyphosate and its major metabolite, aminomethylphosphonic acid (AMPA), in water, food, and biological samples (i.e., blood and urine). A GC-MS/MS method has been developed for analysis of glyphosate and AMPA in human urine. Due to high polarity and solubility in water, low volatility, and absence of chromophoric groups in their molecular structures, detection of glyphosate and AMPA by GC/MS/MS must be achieved by derivatization. Urine samples were deproteinized with acetonitrile and dried with nitrogen flow, and then derivatized with 0.3 mL of 2,2,2-trifluoroethanol and 0.7 mL of trifluoroacetic anhydride at 110<sup>o</sup>C for 1 hour. After derivatization, the mixture was cooled down and evaporated to dryness with nitrogen flow, and the residue was then dissolved in 100 mL of ethyl acetate. The extract was analyzed by GC-MS/MS with negative chemical ionization. The method was validated for its specificity, linearity, working range, accuracy, limits of detection (LOD), and limits of quantitation (LOQ). Calibration curves showed good linearity in the range of 0.1 to 50 μg/L with correlation coefficient (R) &gt; 0.999 for both glyphosate and AMPA. The LOD values were 0.02 μg/L and 0.03 μg/L and LOQ values were 0.08 μg/L and 0.1 μg/L, respectively for glyphosate and AMPA. The spike recoveries ranged from 97.5 to 121% for glyphosate and AMPA with relative standard deviation (RSD) values lower than 11%. The method has been fully validated for measurement of low-level concentrations of glyphosate and AMPA in human urine samples.

Method development for analysis of herbicide glyphosate and its metabolite aminomethylphosphonic acid in human urine samples using GC-MS/MS

2019 Fall National Meeting

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