Profiling and comparison of toxicant metabolites in hair and urine using a mass spectrometry-based metabolomic data processing method.

Anal Chim Acta

Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan. Electronic address:

Published: April 2019

Urine and hair are used for assessing human exposure to toxicants. Urine tests can show acute toxicant exposure. Hair analysis can be used to determine chronic toxicant exposure after months to years; however, compared to urine, hair analysis in exposure assessments is much less frequently investigated. Urine and hair are different matrices, and their mechanisms of toxicant metabolite incorporation are different. The toxicant metabolites present in urine and hair may also be different. To clarify this issue, a procedure was developed to identify toxicant metabolites in rat samples using a mass spectrometry-based metabolomic data processing method. Di-(2-propylheptyl) phthalate (DPHP), an industrial plasticizer, was used as the model toxicant. The developed procedure identified not only known DPHP metabolites (mono-(propyl-6-oxo-heptyl) phthalate, mono-(propyl-6-hydroxyheptyl) phthalate, and mono-(propyl-6-carboxyhexyl) phthalate) but also novel metabolites that were structurally related to DPHP in the rat samples, indicating that the developed procedure successfully identified toxicant metabolites in in vivo samples. Among the 62 tentative metabolites identified from the 7-day urine and the 28-day hair samples, 33 were detected in only the urine samples, 19 were detected in only the hair samples, and 10 were identified in both the urine and hair samples. A total of 15 out of the 62 metabolites were confirmed as DPHP structure-related metabolites based on MS/MS analysis. Among the 15 DPHP structure-related metabolites, only 2 metabolites were present in both the urine and hair samples. These results suggested that the metabolites identified in urine could not be applied to exposure assessments based on hair analysis.

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http://dx.doi.org/10.1016/j.aca.2018.11.009DOI Listing

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