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Comparison of immunoassay and HPLC-MS/MS used to measure urinary metabolites of atrazine, metolachlor, and chlorpyrifos from farmers and non-farmers in Iowa

Abstract

Urine samples were collected from 51 participants in a study investigating pesticide exposure among farm families in Iowa. Aliquots from the samples were sent to two different labs and analyzed for metabolites of atrazine (atrazine mercapturate), metolachlor (metolachlor mercapturate) and chlorpyrifos (TCP) by two different analytical methods: immunoassay and high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). HPLC-MS/MS methods tend to be highly specific, but are costly and time consuming. Immunoassay methods are cheaper and faster, but can be less sensitive due to cross reactivity and matrix effects. Three statistical methods were employed to compare the two analytical methods. Each statistical method differed in how the samples that had results below the limit of detection (LOD) were treated. The first two methods involved an imputation procedure and the third method used maximum likelihood estimation (MLE). A fourth statistical method that modeled each lab separately using MLE was used for comparison. The immunoassay and HPLC-MS/MS methods were moderately correlated (correlation 0.40–0.49), but the immunoassay methods consistently had significantly higher geometric mean (GM) estimates for each pesticide metabolite. The GM estimates for atrazine mercapturate, metolachlor mercapturate, and TCP by immunoassay ranged from 0.16–0.98 μg l−1, 0.24–0.45 μg l−1 and 14–14 μg l−1, respectively and by HPLC-MS/MS ranged from 0.0015–0.0039 μg l−1, 0.12–0.16 μg l−1, and 2.9–3.0 μg l−1, respectively. Immunoassays tend to be cheaper and faster than HPLC-MS/MS, however, they may result in an upward bias of urinary pesticide metabolite levels.

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Correspondence to Brian D Curwin.

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Curwin, B., Hein, M., Barr, D. et al. Comparison of immunoassay and HPLC-MS/MS used to measure urinary metabolites of atrazine, metolachlor, and chlorpyrifos from farmers and non-farmers in Iowa. J Expo Sci Environ Epidemiol 20, 205–212 (2010). https://doi.org/10.1038/jes.2009.15

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