Rappaport et al. metabolite level predicted under Equation 2 (184 µM/ppm) was, indeed, more reasonable than that from Equation 1 (68.6 µM/ppm) at parts per billion levels of exposure. In order to estimate metabolite levels for a typical non- smoking Chinese female exposed to benzene at parts per billion levels, information is required regarding the rates of inhalation and urine pro- duction and the fractions of the inhaled dose retained in the lung and excreted as urinary metabolites. The first two pieces of informa- tion are relatively straightforward because a typical Chinese female working at light exercise should have a breathing rate of 0.863 m3/hr (Yu et al. 2001) and should produce 63.8 mL of urine per hour (Fitzgerald and Brubaker 2003). However, lung retention of benzene at parts per billion exposure levels is less obvious because relatively few studies have reported both inhaled and exhaled breath concentrations of benzene among persons exposed at parts per billion levels. Based on the original data from another study conducted in our labora- tory among 19 nonsmoking garage mechanics (Egeghy et al. 2002), we estimated a median value of 73% lung retention of benzene (range, 45–86%) based on geometric mean inhaled air (range, 7–204 ppb) and breath concentrations (range, 1.9–54.6 ppb) for three independent measurements per subject (breath levels were measured immediately after 4-hr personal measurements of inhaled air). Regarding the fractional excretion of benzene metabolites at parts per billion levels (free of background effects), we relied upon the estimated median excretion value of 48% among four subjects experimentally exposed to 40 ppb 13C-benzene for 2 hr (Weisel et al. 2003). Using these val- ues, the exposure-specific metabolite level for a typical nonsmoking female exposed to ben- zene for several hours at parts per billion levels should be 3.19 mg/m3 ppm × 0.863 m 3 h × h 63.8 mL × 103 mL L 103 µmol mmol × 0.73 × 0.48 × = mmol 78.1 mg 194 µM ppm × . [4] Clearly, this value of 194 µM/ppm (Equation 4) is similar to that of 184 µM/ppm predicted under our two-pathway model and is substantially larger than that of 68.6 µM/ ppm predicted under our one-pathway model. Percentages of benzene metabolized by the two pathways. The two solid curves in Figure 3A represent the background-adjusted partial metabolite trends corresponding to the two metabolic pathways, again based on the origi- nal regression. These partial trends indicate that pathway 1 began to saturate at a benzene concentration of about 200 ppm, and that 950 pathway 2 began to saturate at concentra- tions < 0.1 ppm and was near full saturation at 1 ppm. Figure 3B shows relative percent- ages of benzene metabolites attributable to the two metabolic pathways at increasing levels of benzene exposure. At air concen- trations < 0.04 ppm, about 73% of ben- zene metabolites derived from pathway 2. As the benzene concentration increased, the proportion of benzene metabolites derived from pathway 2 dropped to 50% at about 1 ppm and to 10% at about 12 ppm. Above 12 ppm, pathway 1 accounted for virtually all metabolism of benzene. Discussion We previously used regression splines to characterize nonlinear relationships between levels of individual benzene metabolites and air exposures in 386 Chinese workers (Kim et al. 2006b, 2007). Although spline models offered useful basis functions for evaluating the effects of physiologic, lifestyle, and genetic factors upon benzene metabolism, they shed little light on the underlying toxicokinetics, other than to suggest some inconsistency with the notion that benzene was metabolized by a single saturable pathway. This led us to ques- tion whether an unrecognized high-affinity/ low-capacity pathway might contribute sub- stantially to human benzene metabolism at air concentrations < 1 ppm. Previous investiga- tors noted dose-related differences in excretion patterns of muconic acid and/or hydroqui- none between rats and mice (Medinsky et al. 1989, 1996; Sabourin et al. 1989) and between strains of mice (Witz et al. 1990), which they attributed variously to competi- tion across benzene and its metabolites for the same enzymes, competition across phase I and phase II pathways for elimination of individual metabolites, and different activities of benzene-metabolizing enzymes across spe- cies or strains. Also, Yu and Weisel (1996a, 1996b) noted that humans exposed to sub- parts per million levels of benzene absorbed significantly larger doses and excreted larger proportions of the absorbed dose as muconic acid than did those exposed at parts per mil- lion levels. However, to our knowledge no one has previously suggested that dose-related behavior might arise, at least in part, from the presence of two benzene-metabolizing path- ways having vastly different affinities. To determine whether human benzene metabolism involves two saturable path- ways, we examined the fits of two Michaelis- Menten-like models (Equations 1 and 2) with air and total metabolite data from 263 nonsmoking female subjects, exposed to esti- mated benzene air concentrations ranging from < 1 ppb to 299 ppm. Because we wished to model the quantitative metabolism of ben- zene per se, we focused on total metabolites rather than individual benzene metabolites, which reflect additional saturable processes (see Figure 1). In doing so, we modified the usual kinetic formulations in several ways. First, we used the metabolite level (Y) as a sur- rogate for the enzymatic velocity (v) and the air concentration of benzene (X) as a surrogate for the substrate concentration, recognizing that Y and X were not strictly proportional to v and the substrate concentration, respec- tively. Second, it was necessary to include a background level (Y0) for total metabolites, to account for dietary and endogenous sources of these compounds. After fitting Equations 1 and 2 to the data, we found substantial statis- tical evidence (AIC difference = 5.473) favor- ing the model with two metabolic pathways (Equation 2). Based on the Akaike weights (Equation 3) of 0.939 and 0.061 for the two- pathway and one-pathway models, respec- tively, the odds are 15.4 to 1 (0.939/0.061) that Equation 2 provides a better depiction of true benzene metabolism than does Equation 1, given these data. The finding is bolstered by the independent prediction that a typical nonsmoking Chinese female exposed to non- saturating (parts per billion) levels of benzene should produce 194 µM of urinary metabo- lites per parts per million concentration of benzene compared with 184 µM/ppm pre- dicted under our two-pathway model. In preliminary analyses, we fit Equation 2 to the full set of data representing both males and females and smokers and non- smokers (n = 428), after adjustment for age, sex, and smoking status (data not shown). This led to unrealistically high predicted rates of benzene metabolism at low exposure levels. Upon further analysis, we attributed this result to interaction effects among sex, smoking, and the kinetic parameters, notably X50,2. Because sex and smoking were highly correlated in our Chinese subjects (most of the males were smokers and virtually all of the females were nonsmokers), we could not fully explore the interaction effect(s) and therefore focused on nonsmoking females where results were unambiguous. Future studies should seek to clarify the potential interactions of sex, smoking and benzene kinetics, using larger numbers of smoking and nonsmoking subjects of both sexes. The affinities of the two metabolic path- ways are indicated by the Km analogs, desig- nated X50,1 and X50,2, respectively, in Table 2. [Note that factors other than Km can influ- ence X50,1 and X50,2; see, e.g., Hildebrand et al. (1981).] The estimated values of X50,1 and X50,2 were 301 ppm and 0.594 ppm, respectively, indicating a 507-fold differ- ence in enzyme affinities. Because the high- affinity metabolic pathway 2 would be essentially saturated at a benzene level of 1 ppm, it is perhaps not surprising that previous ovlume 117 | number 6 | June 2009 • Environmental Health Perspectives