Hair analysis for the biomonitoring of polycyclic aromatic hydrocarbon exposure: comparison with urinary metabolites and DNA adducts in a rat model.

  • Human Biomonitoring Research Unit
October 01, 2018 By:
  • Grova N
  • Hardy EM
  • Fays F
  • Duca RC
  • Appenzeller BMR.

Alongside the analysis of urinary metabolites which are traditional biomarkers of polycyclic aromatic hydrocarbons (PAH) exposure, the possibility of detecting PAH as well as their metabolites in hair has also recently been demonstrated. As the concentration of pollutants detected in hair is not impacted by short-term variations in exposure as can be observed with urine, it accurately represents an individual's average level of exposure, which is the most relevant information when investigating possible linkages with biological effects. In the current study, based on a rat model exposed to a mixture of PAHs for a 90-day period, the linkage between the PAH exposure level and the resulting concentration of their metabolites in hair was then investigated. The linkage between exposure levels and the concentrations of OH-PAH in hair collected at the end of the experiment were compared to those obtained using urinary concentration of OH-PAH collected from the same animals. Linear relationship between levels of exposure and the concentration of OH-PAH in the rats' hair (R(2) 0.722-0.965, p < 0.001) was observed for 28 OH-PAH out of the 54 investigated. The difference in PAH concentration between the different groups of exposure and the possibility to back determine the animals' level of exposure on the basis of PAH-metabolite concentrations in both hair and urine was also demonstrated. In addition to the strong linear relation observed between the doses of exposure and the levels of concentration of hydroxylated metabolites in hair (p < 0.001), the analysis of a subset of animals demonstrated a linkage between 3-OH-benzo[a]pyrene concentration levels in hair and the levels of B[a]P-DNA adduct formed (p < 0.05), thereby suggesting the potential of their analysis to predict genetic alteration.

2018 Oct. Arch Toxicol.92(10):3061-3075. Epub 2018 Aug 29.
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