Development and validation of a simple and robust method for arsenic speciation in human urine using HPLC/ICP-MS.

J AOAC Int

California Department of Public Health, Biochemistry Section, Environmental Health Laboratory Branch, Richmond, CA 94804, USA.

Published: June 2015

In order to better distinguish the different toxic inorganic and organic forms of arsenic (As) exposure in individuals, we have developed and validated a simple and robust analytical method for determining the following six As species in human urine: arsenous (III) acid (As-III), As (V) acid, monomethylarsonic acid, dimethylarsinic acid, arsenobetaine (AsB), and arsenocholine. In this method, human urine is diluted using a pH 5.8 buffer, separation is performed using an anion exchange column with isocratic HPLC, and detection is achieved using inductively coupled plasma-MS. The method uses a single mobile phase consisting of low concentrations of both phosphate buffer (5 mM) and ammonium nitrate salt (5 mM) at pH 9.0; this minimizes the column equilibration time and overcomes challenges with separation between AsB and As-III. In addition, As-III oxidation is prevented by degassing the sample preparation buffer at pH 5.8, degassing the mobile phase online at pH 9.0, and by the use of low temperature (-70 °C) and flip-cap airtight tubes for long term storage of samples. The method was validated using externally provided reference samples. Results were in agreement with target values at varying concentrations and successfully passed external performance test criteria. Internal QC samples were prepared and repeatedly analyzed to assess the method's long-term precision, and further analyses were completed on anonymous donor urine to assess the quality of the method's baseline separation. Results from analyses of external reference samples agreed with target values at varying concentrations, and results from precision studies yielded absolute CV values of 3-14% and recovery from 82 to 115% for the six As species. Analysis of anonymous donor urine confirmed the well-resolved baseline separation capabilities of the method for real participant samples.

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Source
http://dx.doi.org/10.5740/jaoacint.14-103DOI Listing

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