In this study of 390 Chinese workers, we observed that benzene exposures were associated with increased production of albumin adducts of BO, 1,4-BQ and 1,2-BQ. These findings confirm earlier associations between levels of BO-Alb and 1,4-BQ-Alb and benzene exposures in two other populations of Chinese workers (Rappaport et al. 2002a
; Yeowell-O’Connell et al. 2001
) and show that levels of 1,2-BQ-Alb, which had not been reported heretofore in humans, were also associated with benzene exposure at ≥ 1 ppm.
The shapes of exposure–adduct relationships in persons exposed to low levels of benzene from environmental air have not been reported previously. In the present study, we modeled adduct concentrations over about 5 orders of magnitude of benzene exposures (range, < 0.01–54.5 ppm), using benzene concentrations that had been predicted for control subjects from measurements of urinary benzene (Kim et al. 2006
). The results, shown in , point to hockey-stick-shaped relationships in log-scale between each of the three adducts and benzene exposure. The inflection points, which ranged from 0.5 to 5 ppm, represent air concentrations at which benzene contributed marginally to the pools of background adducts. Based on the curves in , it appears that 1,4-BQ-Alb was the most responsive to benzene exposure, with an inflection point of about 0.5 ppm, followed by BO-Alb (~ 1–3 ppm) and 1,2-BQ-Alb (~ 5 ppm). Interestingly, the inflection points for 1,4-BQ-Alb and 1,2-BQ-Alb are comparable to those observed for urinary levels of hydroquinone and catechol (their respective precursors) in this same population of workers (Kim et al. 2006
Our results also indicate that none of the three albumin adducts would be useful biomarkers of benzene exposure in ambient populations, where air concentrations rarely exceed 0.1 ppm, or in working populations where exposures are consistently maintained at < 1 ppm. Indeed, among workers exposed to air concentrations < 1 ppm, only 1,4-BQ-Alb showed a significant effect of benzene exposure (, ), and this reflects exposures between 0.1 and 1 ppm. When we fit the same regression model to levels of 1,4-BQ-Alb for workers exposed to ≤ 0.1 ppm benzene, the coefficient (± SE) for benzene exposure decreased from 0.030 (± 0.011) to 0.002 (± 0.032), with no hint of statistical significance (p = 0.940).
Because all exposure–adduct relationships were reasonably modeled by simple linear models (in log-scale) > 1 ppm (), we fit separate multiple regression models to workers exposed to benzene either < 1 ppm or ≥ 1 ppm. This allowed us to compare effects of benzene exposure on adduct production after adjusting for the blood-collection medium, age, BMI, and smoking (–). For workers exposed to benzene ≥ 1 ppm, the log-scale regression coefficients for benzene exposure and their upper 95% confidence limits (UCL) were all < 1 [i.e., BO-Alb: β = 0.668 (UCL = 0.770); 1,2-BQ-Alb: β = 0.393 (UCL = 0.495); and 1,4-BQ-Alb: β = 0.391 (UCL = 0.469)]. This indicates that the natural-scale relationships between adduct levels and benzene exposures were concave downward in all cases, as observed previously for BO-Alb and 1,4-BQ-Alb (Rappaport et al. 2002a
). Furthermore, the magnitude of each adjusted coefficient for benzene exposure in – indicates the degree of concavity of the respective exposure–adduct relationship in natural scale; that is, the smaller the log-scale coefficient, the greater the concavity in natural scale. This is illustrated in , which shows predicted natural-scale relationships corresponding to the coefficients estimated from the multiple linear regression models. These curves represent adduct levels in serum of nonsmoking workers of average age and average BMI with GM benzene exposures of ≥ 1 ppm. The relationships for the two benzoquinone adducts show greater concavity than that of BO-Alb. If these concave-downward relationships are the result of saturable metabolism of benzene, as suggested previously in studies of animals (Medinsky et al. 1989
; Sabourin et al. 1988
) and of humans (Rappaport et al. 2002a
), then our results indicate that the saturable effects are greater for metabolism to the benzoquinones than for metabolism to BO ().
Figure 3 Predicted natural-scale relationships between levels of BO-Alb (A), 1,2-BQ-Alb (B), and 1,4-BQ-Alb (C). Data points represent adduct levels derived from serum from nonsmoking subjects of average weight and BMI, with benzene exposure of ≥ 1 ppm; (more ...)
We found that levels of 1,2-BQ-Alb and 1,4-BQ-Alb were much higher in plasma containing EDTA than in either serum or plasma containing heparin (). While we do not know the underlying reason for this result, it probably explains the large difference in 1,4-BQ-Alb levels, which had been observed previously in two studies of benzene-exposed workers (Rappaport et al. 2005
). In those studies, plasma containing EDTA contained much higher levels of 1,4-BQ-Alb than plasma containing citrate, and the difference disappeared when adduct levels were adjusted for concurrent controls. Because EDTA is a well-known chelating agent, it is worth speculating that chelation of iron would stabilize benzoquinone adducts, possibly by inhibiting Fenton chemistry. Additional work should be conducted to determine why the blood-collection medium would have such a large effect upon levels of albumin adducts of the benzoquinones.
Regarding effects of smoking, age, and BMI, results of multiple regression models varied among the three types of adducts and between exposure categories (–). Among subjects exposed to benzene ≥ 1 ppm, smoking was positively associated with levels of BO-Alb (β = 0.209), 1,2-BQ-Alb (β = 0.286), and 1,4-BQ-Alb (β = 0.242), indicating that GM adduct levels were between 23% (i.e., e0.209
) and 33% (i.e., e0.286
) higher in smokers than in nonsmokers. For subjects exposed to < 1 ppm of benzene, smokers had 15% more 1,2-BQ-Alb (β = 0.139) and 58% more 1,4-BQ-Alb (β = 0.456) than nonsmokers, whereas levels of BO-Alb were virtually unaffected by smoking (β = 0.016). These results point to the likely contributions of hydroquinone and catechol (precursors of 1,4-BQ and 1,2-BQ, respectively) in cigarette smoke (Kim et al. 2006
Adducts of the benzoquinones decreased with age at about 0.8%/year of life for 1,2-BQ-Alb in low-exposed workers (β = −0.008) and 1,4-BQ-Alb in high-exposed workers (β = −0.008). In a previous study of Chinese workers exposed over a similar range of air concentrations, 1,4-BQ-Alb levels decreased by 1.9%/year of life among both exposed and control workers (Rappaport et al. 2002a
Workers were also exposed to toluene at a median concentration of 3.36 ppm (range, < 0.3–80.9 ppm) (data not shown). Because toluene competes with benzene for cytochrome P450 2E1 metabolism, we anticipated that levels of albumin adducts would decrease with toluene exposure among workers exposed to benzene at ≥ 1 ppm. However, when toluene exposure was added to models of the three albumin adducts, the effects were not significant and regression coefficients for benzene exposure were only marginally reduced (3–4%).
Because 28 exposed subjects had two blood specimens (collected about 16 months apart), it was possible to estimate within-person and between-person variance components for the (logged) levels of albumin adducts, after adjustment for blood-collection media. The estimated within-person variance component (
) increased in the order BO-Alb < 1,4-BQ-Alb < 1,2-BQ-Alb, whereas the estimated between-person variance component (
) showed the opposite behavior. Because
tends to decrease with increasing residence time of a biomarker (Lin et al. 2005
), this finding is consistent with a previous report that BO-Alb was chemically stable in humans, turning over with albumin (half life = 21 days), whereas 1,4-BQ-Alb was marginally unstable (half life = 13.5 days) (Rappaport et al. 2002a
); the finding also suggests that 1,2-BQ-Alb is very unstable in humans.
This disparity in values of
for the three albumin adducts influenced the corresponding values of the
a measure of reliability (larger is better), and of the variance ratio
a measure of the biasing potential of the biomarker as a surrogate for exposure (smaller is better) (Lin et al. 2005
). Because BO-Alb had the largest ICC (0.901) and the smallest
(0.110), followed by 1,4-BQ-Alb (ICC = 0.620,
= 0.612) and 1,2-BQ-Alb (ICC = 0.080,
= 11.4), BO-Alb should be the most reliable and least biasing biomarker of occupational exposure to benzene of the three adducts measured in our study.
The estimated within-person variance components for BO-Alb (
= 0.175) and 1,4-BQ-Alb (
= 0.319) in the present study were larger than those estimated previously (
= 0.079 and 0.044, respectively) from 11 benzene exposed workers in China who provided blood samples on three consecutive Mondays (Rappaport et al. 2002a
). The larger estimates of
in the present study were probably influenced by the much larger interval between blood samples (about 16 months) (Lin et al. 2005
In conclusion, the present study confirms and extends previous observations of concave downward relationships between albumin adducts of biologically reactive benzene metabolites and benzene exposure () (Rappaport et al. 2005
). We attribute this nonlinear behavior to saturable metabolic processes involving the production of BO, 1,2-BQ, and 1,4-BQ in humans (). Because levels of these reactive and hematotoxic (at least in the case of 1,4-BQ) benzene metabolites were less than proportional to benzene exposure at air concentrations in the range of 1–10 ppm (), risk assessments that were based largely upon linear fits of leukemia mortality among workers exposed to hundreds of parts per million of benzene could well underestimate risks from benzene metabolites in persons exposed at lower (non-saturating) air concentrations (Rappaport et al. 2005
). In addition, this study highlights the importance of nonoccupational sources that also contribute to benzene-related adducts. These background adducts limit the usefulness of albumin adducts as biomarkers of benzene exposure below about 1 ppm. On the other hand, given the established causal association between human leukemia and benzene exposure, further investigation of these adducts in low-exposed subjects may help explain unknown causes for leukemia in the general population (Lin et al. 2006
; McDonald et al. 1994
; Smith 1996