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Objectives: The aim of the study was to characterize the PAH exposure level based on 1-hydroxypyrene (1-HP) in urine of Polish pregnant women and to assess the relationship between PAH and factors such as smoking, environmental tobacco smoke exposure, place of residence, heating and cooking method. Materials and Methods: The study population included in this analysis consisted of 449 pregnant women who had been the subjects of the prospective Polish Mother and Child Cohort study performed in 8 regions of Poland. The women were interviewed three times during pregnancy (once in each trimester). 1–HP concentration in urine was chosen as the biomarker of exposure to PAH. The urine sample was analysed using high performance liquid chromatography (HPLC). The active and passive smoking exposure was verified by saliva cotinine, analysed by high performance liquid chromatography coupled with tandem mass spectrometry (LC-MSMS) and isotope dilution method. Results: 1-HP concentration in urine ranged from 0.02 to 10.2 μg/g creatinine with the geometric mean (GM) 0.4 μg/g creatinine. The significantly higher concentration of urinary 1-HP in pregnant women was observed for summer collection (GM ratio: 1.1; p = 0.01), among smokers (GM ratio: 1.7; p < 0.001) and for the women living in big cities (GM ratio: 1.3; p = 0.001). Conclusions: The significantly higher concentration of urinary 1-HP in pregnant women was observed for summer collection, among smokers and those living in big cities.
EN
Objectives 1-hydroxypyrene is an important biomarker of exposure to polycyclic aromatic hydrocarbons (PAHs), which appears in the urine of exposed human subjects. In developing countries, where advanced instruments are not available, the importance of this biomarker demands convenient and sensitive methods for determination purposes. This study aimed at developing a methodology to quantify 1-hydroxypyrene (a biomarker of PAHs exposure) based on the UV-visible detector in the reverse phase high pressure liquid chromatography (HPLC). Material and Methods A 20 μl injection of sample was used for manual injection into the HPLC Shimadzu, equipped with the SPD-20 A UV-visible detector, the LC-20AT pump and the DGU-20A5 degasser. The C-18 column was used for the purpose of the analysis. Results The method showed a good linearity (the range: R² = 0.979–0.989), and high detectability up to the nmol level. The average retention was 6.37, with the accuracy of 2%, and the percentage of recovery remained 108%. The overall performance of this method was comparable (in terms of detection sensitivity) and relatively better than previously reported studies using the HPLC system equipped with the UV-detector. Conclusions This method is suitable and reliable for the detection/quantification of the 1-OHP in human urine samples, using the UV-detector, however, it is less sensitive as compared to the results of a florescence detector.
EN
The role of glutathione S-transferase Mu 1 (GSTM1) in the biomonitoring of polycyclic aromatic hydrocarbons (PAHs) is not clear. Our purpose has been to evaluate the influence of GSTM1 genotypes on 1-hydroxypyrene (1-OHP), deoxyribonucleic acid (DNA) adducts, and micronucleus frequency in both occupational and non-occupational populations of null and active GSTM1 carriers. We conducted a meta-analysis on 25 articles that met our strict inclusion criteria (11 studies on 1-OHP, 9 on DNA adducts, and 5 on the micronucleus frequency). In the case of occupationally exposed workers, micronucleus frequency was only significantly higher in the null GSTM1 carriers than in the active GSTM1 carriers. In the non-occupationally exposed general population, 1-OHP and micronucleus frequency were significantly higher in the null GSTM1 carriers. The results of Egger’s test and funnel plot analysis indicated no significant publication bias. In conclusion, GSTM1 genotypes may affect the urinary 1-OHP in the non-occupationally exposed general population, and micronucleus frequency in both occupational workers and non-occupational population. Int J Occup Med Environ Health 2017;30(2):177–201
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