Asphalt PAH Biomarkers Inhibition Is Very Effective Against Carcinogenic Materials
Hot asphalt produces aerosolized emissions of polycyclic aromatic hydrocarbons (PAHs), some of which are carcinogenic.
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In this article, we are going to investigate how asphalt biomarkers inhibition can be very effective against hazardous materials.
We looked at the naphthalene (Nap), phenanthrene (Phe), and pyrene (Pyr) urinary biomarkers in 20 road paving workers exposed to hot asphalt and in 6 road milling workers not exposed to hot asphalt (reference group).
Urine samples taken at baseline, post-shift, at bedtime, and in the morning on three consecutive days were all included in our analysis.
In each urine sample, we measured the monohydroxylated metabolites of Nap (OH-Nap), Phe (OH-Phe), and Pyr (OH-Pyr), as well as unmetabolized Nap (U-Nap) and Phe (U-Phe).
No discernible differences in biomarker levels were found between pavers and millers in baseline samples, indicating similar background exposures.
The high pairwise correlations observed between levels of all biomarkers in post-shift, bedtime, and morning urine samples point to shared exposure sources.
All biomarker concentrations among pavers were significantly higher in post-shift samples, indicating quick uptake and elimination of PAHs after contact with hot asphalt (biomarker levels were not elevated among millers).
The levels of U-Nap, U-Phe, OH-Phe, and OH-Pyr across pavers were analyzed using linear mixed-effects models, and the results revealed significant effects of work assignments, with roller operators having lower biomarker levels than the other workers. However, no correlation between OH-Nap levels and work was found, presumably as a result of cigarette smoking.
According to regression coefficients for a time among pavers, the biological half-lives of U-Phe, U-Nap, OH-Phe, and OH-Pyr were each estimated to be 8 hours, 10 hours, 13 hours, and 26 hours, respectively.
These findings support the use of U-Nap, U-Phe, OH-Phe, and OH-Pyr as short-term biomarkers of exposure to PAHs coming from hot asphalt, but probably not OH-Nap.
Questions remain regarding the rates of uptake and elimination for individual PAHs as well as the impact that jobs, hydration levels, and smoking status may have on biomarker levels.
This is true even though some relationships between airborne exposures to PAHs and urinary PAH biomarkers have been examined in workers exposed to hot asphalt (Väänänen et al., 2003; McClean et al., 2004b; Campo et al., 2006a,b; Vä We used repeated measures sampling to measure the levels of five PAH biomarkers in the urine of 26 road construction workers in order to answer these questions (McClean et al., 2004a,b).
U-Nap, U-Phe, OH-Nap, OH-Phe, and OH-Pyr urinary concentrations were comparable to those found in other occupational studies of asphalt exposure.
The most prevalent urinary analyte overall was OH-Nap, which was then followed by OH-Phe, OH-Pyr, U-Nap, and finally U-Phe.
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Based on the overall median values of these analytes, our results show that the concentration of U-Nap was 0.35 percent of OH-Nap and that the concentration of U-Phe was 0.85 percent of OH-Phe.
The mean levels of U-Nap and U-Phe in a prior study of coke oven workers were 4 and 13%, respectively, of the corresponding phenolic metabolite levels. These values are by about an order of magnitude lower (Waidyanatha et al., 2003).
These findings suggest that higher concentrations of unmetabolized Nap and Phe are excreted in urine at elevated exposure levels as these coke oven workers are thought to have had higher exposures to Nap and Phe than the asphalt workers in the current study (Sobus et al., 2009).
These findings might point to metabolic saturation for Nap and Phe in settings with elevated PAH levels. However, more investigation is required to validate this hypothesis.
Nap, Phe, and Pyr exposure sources for paving and milling workers are generally suggested by significant pairwise correlations between analyte levels.
There were no differences in analyte levels between millers and pavers in baseline samples taken on the morning of the first day of the workweek.
This suggests that PAHs were produced over the weekend in both groups of workers from similar background sources, such as the ambient environment and diet.
Due to the fact that millers did not work with hot asphalt, no analyte showed a significant increase above baseline levels in their urine. (McClean et al., 2004a,b). The post-shift samples for pavers showed the biggest departures from baseline levels.
Comparing GM levels revealed that U-Phe was the most sensitive biomarker, with post-shift levels being about seven times higher than baseline levels. Other biomarkers that showed increases over baseline included OH-Phe and OH-Pyr, U-Nap, and OH-Nap.
We examined the effects of time, hydration level (based on measurements of urinary creatinine), work assignments, workday, and smoking status on levels of PAH biomarkers measured in post-shift and bedtime urine samples from the 20 paving workers using linear mixed-effects models.
According to the findings, urinary creatinine was positively correlated with each urinary analyte (P-value 0.0001), indicating lower urine volume and higher analyte concentrations.
Given that unmetabolized organic compounds frequently enter urine through diffusion and that concentration should be independent of urine output, these results for U-Nap and U-Phe were unexpected (Boeniger et al., 1993).
It is necessary to conduct more research to ascertain how creatinine affects the levels of U-Nap and U-Phe in comparison to OH-Nap, OH-Phe, and OH-Pyr.
We observe that whether or not creatinine was included, the final statistical models for each analyte were essentially identical.
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We calculated elimination rate constants for each analyte by including a fixed effect for time in our models.
By including a "time assignment" interaction term in each model, we first looked at elimination rates specific to particular work assignments.
Using a single elimination rate constant, the results demonstrated that each model successfully described the data, indicating that analytes were eliminated at the same rate regardless of the work assignment.
The estimated T1/2 values and 95% confidence intervals for U-Phe, U-Nap, OH-Pyr, and OH-Nap were 7.70 h (5.17 h, 15.1 h), 10.2 h (7.07 h, 17.8 h), 13.3 h (7.79 h, 46.2 h), and 13.6 h (9.00 h, 27.7 h), respectively.
The unmetabolized substances (U-Nap and U-Phe) appeared to be eliminated from the body more quickly than the hydroxylated analytes, despite the fact that there was uncertainty surrounding these estimates (as shown by the 95% confidence intervals) (Campo et al., 2007). For OH-Phe and OH-Pyr, slightly longer elimination half-lives were noted.
The estimates for these analytes (13 h) were quite comparable and fell within the range of estimates for OH-Pyr (4-48 h) found in the literature (Jacob and Seidel, 2002; Brandt and Watson, 2003; Hansen et al., 2008).
Some analyses of the urinary excretion rate of OH-Pyr suggest a biphasic excretion process, with a rapid phase of elimination (hours), followed by a slower phase (days) (Heikkilä et al., 1995; Buratti et al., 2007), though this has not been evaluated here.
Additional data support the idea that OH-Nap is excreted in two phases, with the first phase being very fast (1.2–1.9 h) and the second phase being slower (14–46 h) and more like OH–Pyr.
Due to the highly significant effect of smoking, the estimate of 26 h for the half-life of OH-Nap in this investigation is likely to be positively skewed.
Asphalt PAH Biomarkers
We included a fixed effect for "workday" in our models to examine the effects of bioaccumulation over successive workdays in light of the estimated elimination rates of the PAH biomarkers in our study.
Both OH-Nap, which was significantly influenced by smoking status, and U-Phe, which had the shortest estimated elimination half-life, showed no workday effects. For U-Nap, OH-Phe, and OH-Pyr, a significant workday effect was noticed.
The first day of the workweek saw the lowest levels of each analyte, and levels rose on workdays two and three.
Even though these significant workday effects indicate that analyte levels from previous workdays have accumulated, the contributions were rather negligible in comparison to those linked to exposures on the current day.
After accounting for time and workday effects, paving workers' urinary analyte levels for U-Nap, U-Phe, OH-Phe, and OH-Pyr were significantly influenced by their work assignments, with roller operators having the lowest levels.
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No discernible differences between paver operators, screedmen, and rakers were found for any analyte when roller operators were excluded from the models.
Prior analyses of this study population revealed that, depending on the type of exposure (air measurement or dermal patch measurement) and the specific exposure surrogate (total dermal PACs versus dermal Pyr) used for dermal patch measurements, the rank order of PAC exposures varied across work assignments (McClean et al., 2004a,b).
However, when compared to paver operators, screedmen, and rakers, roller operators were found to have experienced the lowest air levels (as measured by both total airborne PACs and airborne Pyr) and the lowest dermal patch levels (as measured by both total dermal PACs and dermal Pyr).
We have evidence that U-Nap, U-Phe, OH-Phe, and OH-Pyr are likely good surrogates for occupational exposure to PACs (including PAHs) in jobs involving hot asphalt because results of our urinary biomarkers follow the same patterns.
According to the results of the OH-Nap final model, smoking status had a very significant impact on analyte levels. In other studies of workers exposed to asphalt, similar effects of smoking on OH-Nap have been noted (Väänänen et al., 2006; Buratti et al., 2007).
The lower correlation coefficients for OH-Nap compared to the other analytes are likely explained by this smoking effect.
In contrast to U-Nap, U-Phe, OH-Phe, and OH-Pyr, OH-Nap showed no significant effects of work assignment after accounting for the smoking effect.
Compared to the other urinary biomarkers assessed in our study, the effect of smoking lessens the usefulness of OH-Nap as a measure of PAH exposure among asphalt-exposed workers.
Since Nap can be found in cigarette smoke (Rustemeier et al., 2002), it was expected that smoking status would have an impact on both OH-Nap and U-Nap. While there was a noticeable smoking effect for OH-Nap, there was none for U-Nap.
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Studies of workers exposed to jet fuel (JP-8) and coke oven emissions have found similar results regarding the effects of smoking on OH-Nap and U-Nap (Serdar et al., 2003a,b; Waidyanatha et al., 2003). According to Serdar et al.
(2004), smoking cigarettes may induce detoxification enzymes at low Nap exposure levels, leading smokers to produce more OH-Nap than nonsmokers do at low exposure levels and less OH-Nap than nonsmokers do at high exposure levels (Serdar et al., 2004). The discrepancies between OH-Nap and U-Nap in this study could be explained by a similar mechanism.
In studies of PAH exposure, levels of OH-Pyr in the urine have frequently been linked to smoking status (Van Rooij et al., 1994; Hansen et al., 2008).
Additionally, studies of occupational exposure to PAHs coming from asphalt have shown how smoking affects OH-Pyr (Campo et al., 2006b; Marczynski et al., 2006; Väänänen et al., 2006; Buratti et al., 2007).
No smoking effect (P-value > 0.10) was found for OH-Pyr in our analysis of 20 workers applying hot-mix asphalt after adjusting for creatinine concentration, time of sample collection, work assignment, and workday.
This result was not entirely unexpected given that, after adjusting for age, body mass index, and inhalation, and dermal Pyr exposure, only a marginal effect (P-value 0.10) of smoking on OH-Pyr was seen in a prior analysis of this population (McClean et al., 2004b).
We may not have been able to detect a significant smoking effect on OH-Pyr because milling workers (i.e., workers who did not work with hot-mix asphalt) were not included in our final statistical models.
In general, further research is needed to determine how smoking affects urinary biomarkers of PAH exposure, especially U-Nap, OH-Nap, and OH-Pyr, where PAH exposure levels (from both dermal and inhalation routes) and smoking intensity (rather than smoking status) are well characterized for all study participants.
According to the study's findings, the biomarkers U-Nap, U-Phe, and OH-Phe, along with the gold standard OH-Pyr, are helpful indicators of exposure to PAHs/PACs coming from hot asphalt sources.
The short half-lives of these analytes, which ranged from 8 to 14 h, suggest that representative samples should be taken right away after the work shift and that urinary biomarker levels reflect short-term occupational exposures to PAHs.
Even for unmetabolized PAHs in the urine, which are primarily eliminated by passive diffusion, the effect of hydration level on analyte concentrations should be carefully considered when analyzing biomarker levels.
Future evaluations of the health risks for paving workers should take into account the significant differences in the levels of U-Nap, U-Phe, OH-Phe, and OH-Pyr across work assignments, which show that workers are exposed to PAHs differently during the work shift depending on the particular tasks they perform.
OH-Nap is not a useful PAH exposure biomarker, according to our findings, given the confounding effects of smoking and the absence of a work assignment effect on analyte levels.
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