Disturbance of OH-PAH metabolites in urine induced by single PAH lab exposure

Due to the high exposure toxicity and individual variability of polycyclic aromatic hydrocarbons (PAHs), it is difficult to accurately characterize the actual exposure of exposed individuals through external exposure detection. In this study, the monohydroxyl metabolites of naphthalene, phenanthrene, pyrene, and 9-fluorenone were identified in the urine of low-dose PAH-exposed individuals based on ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS), and their concentrations were monitored for 15 consecutive days after exposure. The results showed that the metabolite concentrations of naphthalene, phenanthrene, and pyrene were basically the same, and all of them reached the maximum value at day 8. In contrast, the metabolite of 9-fluorenone reached its maximum value on day 2. This study showed that the four metabolites were strongly correlated with their parent PAH exposure, with a wide detection window, and their assays were specific, sensitive, and reliable, while the sampling difficulty was low, so the four hydroxylated PAHs may be potential low-dose biomarkers of PAH internal exposure. This study will provide methodological and data support for further health risk studies involving internal exposure to organic pollutants such as PAHs.

Variability in urinary biomarkers of human exposure to polycyclic aromatic hydrocarbons and its association with oxidative stress

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants. Urinary concentrations of mono-hydroxylated metabolites of PAHs (OH-PAHs) have been used as biomarkers of these chemicals' exposure in humans. Little is known, however, with regard to intra- and inter-individual variability in OH-PAH concentrations and their association with oxidative stress. We conducted a longitudinal study of measurement of urinary concentrations of 15 OH-PAHs and 7 oxidative stress biomarkers (OSBs) of DNA damage [8-hydroxy-2'-deoxyguanosine (8-OHdG)], lipid [malondialdehyde (MDA) and F₂-isoprostanes (PGF_2α)] and protein [o,o'-dityrosine (diY)] peroxidation in 19 individuals for 44 consecutive days. Metabolites of naphthalene (OHNap), fluorene (OHFlu), phenanthrene (OHPhe), and pyrene (OHPyr) were found in >70% of 515 urine samples analyzed, at sum concentrations (∑OH-PAH) measured in the range of 0.46-60 ng/mL. After adjusting for creatinine, OHNap and ∑OH-PAH concentrations exhibited moderate predictability, with intra-class correlation coefficients (ICCs) ranging from 0.359 to 0.760. However, ICC values were low (0.001-0.494) for OHFlu, OHPhe, and OHPyr, which suggested poor predictability for these PAH metabolites. Linear mixed-effects analysis revealed that an unit increase in ∑OH-PAH concentration corresponded to 4.5%, 5.3%, 20%, and 21% increase in respective urinary 8-OHdG, MDA, PGF_2α, and diY concentrations, suggesting an association with oxidative damage to DNA, lipids, and proteins. The daily intakes of PAHs, calculated from urinary concentrations of OH-PAHs, were 10- to 100-fold below the current reference doses. This study provides valuable information to design sampling strategies in biomonitoring studies and in assigning exposure classifications of PAHs in epidemiologic studies.

Assessment of kitchen emissions using a backpropagation neural network model based on urinary hydroxy polycyclic aromatic hydrocarbons

Kitchen emissions are mixed indoor air pollutants with adverse health effects, but the large-scale assessment is limited by costly equipment and survey methods. This study aimed to discuss the application of backpropagation (BP) neural network models in the assessment of kitchen emissions based on the exposure marker. A total of 3686 participants were recruited for the kitchen survey, and their sleep quality was measured by the Pittsburgh sleep quality index (PSQI). After excluding the confounders, 365 participants were selected to assess their urinary hydroxy polycyclic aromatic hydrocarbons (OH-PAHs) concentrations by ultra-high-performance liquid chromatography/tandem mass spectrometry. Two BP neural network models were then set up using the survey and detection data from the 365 participants and used to predict the total urinary OH-PAHs concentrations of all participants. The total urinary OH-PAHs and 1-hydroxy-naphthalene (1-OHNap) concentrations were significantly higher among the 365 participants with poor sleep quality (global PSQI score > 5; P < 0.05). Results from internal and external validation showed that our model has high credibility (model 2). Further, the participants with higher predicted total urinary OH-PAHs concentrations were associated with the global PSQI score of >5 (odds ratio (OR) = 1.284, 95% confidence interval (CI) = 1.082-1.525 for participants with predicted total urinary OH-PAHs concentrations of over 1.897 μg/mmol creatinine in model 1, and OR = 1.467, 95% CI = 1.240-1.735 for participants with predicted total urinary OH-PAHs concentrations of over 2.253 μg/mmol creatinine in model 2) after adjusting for the confounders. Findings suggest that the BP neural network model is suitable for assessing kitchen emissions, and the urinary OH-PAHs concentrations can be taken as the model outlay.

A novel analytical methodology for the determination of hydroxy polycyclic aromatic hydrocarbons in breast and cow milk samples

Hydroxy polycyclic aromatic hydrocarbons (OHPAHs) in biological fluids, such as milk, are considered as biomarkers of exposure to polycyclic aromatic hydrocarbons (PAHs) in organism. The presence of OHPAHs in milk samples indicates a potential contamination on human organisms and milk producing animals. In this way, infants can be contaminated by lactation through the consumption of milk of both, human and animal origins. In this paper, eight OHPAHs have been analyzed in commercial cow milks and in human breast milk using HPLC and fast scanning fluorimetric detection (FSFD). Extraction and cleaning procedures of OHPAHs from milk samples have been investigated, and the experimental results using two bibliographic protocols and a new proposed protocol have been compared. The new protocol using enzymatic hydrolysis, proteins precipitation and, solvent extraction using acetonitrile, was proposed as the most adequate for the determination of 2-hydroxyfluorene, 1-/9-, 2-/3- and 4-hydroxyphenanthrenes, 1-hydroxypyrene and 3-hydroxybenzo[a]pyrene. The method recoveries ranged from 80-102% and 75-91% for fresh cow milk and for human breast milk, respectively, for all components except for 3-OHBz[a] Py. Low recovery values were calculated for 3-hydroxybenzo[a]pyrene in all cases. No statistical difference in the method performance was observed between fresh cow milk and human breast milk.