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Background Depression of peripheral blood cells is a well-known indicator of benzene hematotoxicity. Previous studies of its effects on specific types of blood cells have yielded inconsistent results. We examine hematological findings and their possible relations with exposure markers validated in a recent biomarker project conducted in Tianjin, China. Methods Personal benzene exposures were sampled with 3-M organic vapor monitors, and analyzed by gas chromatography. The peripheral blood cells were counted by a cell counter. The WBC differential was manually counted on a total of 900 cells by a US commercial laboratory. Results A total of 130 exposed workers and 51 age- and gender-matched unexposed subjects were recruited in this study. Benzene exposure levels monitored on the day of biological sample collection for exposed workers ranged from 0.06 to 122 ppm. Their 4-week average and cumulative benzene exposure levels were 0.08–54.5 ppm and 6.1–623.2 ppm-years, respectively. Significant decreases of red blood cells (RBC), white blood cells (WBC), and neutrophils were observed and correlated with both personal benzene exposures and levels of urinary metabolites (S-phenylmercapuric acid and t,t-muconic acid) and albumin adducts of benzene oxide and 1,4-benzeoquinone. Conclusions The depressions in RBC, WBC, and neutrophils observed in this study are not only exposure dependent, but also significantly different in the lowest exposed group (at or below 0.25 ppm) compared with unexposed subjects. The results of the present study appear to suggest that lymphocytes may not be more sensitive to chronic benzene exposure than neutrophils. Am. J. Ind. Med. 42:275–285, 2002. © 2002 Wiley-Liss, Inc.

Benzene is an important industrial chemical and environmental contaminant that causes leukemia. To obtain mechanistic insight into benzene's mechanism of action, we examined the impact of benzene on the human serum proteome in a study of exposed healthy shoe-factory workers and unexposed controls. Two sequential studies were performed, each using sera from 10 workers exposed to benzene (overall mean benzene air level >30 ppm) and 10 controls. Serum samples were subjected to anion-exchange fractionation and bound to three types of ProteinChip arrays (Ciphergen Biosystems, Fremont, CA) [hydrophobic (H50), metal affinity (IMAC3-Cu), and cation exchange (WCX2)]. Protein-expression patterns were detected by surface-enhanced laser desorption/ionization (SELDI)-TOF MS. Three proteins (4.1, 7.7, and 9.3 kDa) were consistently down-regulated in exposed compared with control subjects in both studies. All proteins were highly inversely correlated with individual estimates of benzene exposure ( r > 0.75). The 7.7- and 9.3-kDa proteins were subsequently identified as platelet factor (PF)4 and connective tissue activating peptide (CTAP)-III. Initial proteomic results for PF4 and CTAP-III were subsequently confirmed in a single experiment using a ProteinChip-array-based immunoassay(Ciphergen Biosystems). The altered expression of the platelet-derived CXC-chemokines (40% and 63% for PF4 and CTAP-III, respectively) could not be explained by changes in absolute platelet counts. Thus, SELDI-TOF analysis of a limited number of exposed and unexposed subjects revealed that lowered expression of PF4 and CTAP-III proteins is a potential biomarker of benzene's early biologic effects and may play a role in the immunosuppressive effects of benzene.

This report is part of an extensive biomarker study conducted in a Chinese occupational population with benzene exposures ranging from 0.06 to 122 ppm (median exposure of 3.2 ppm). All urinary benzene metabolites measured in this study were significantly elevated after exposure to benzene at or above 5 ppm. Among these metabolites, however, only S-phenylmercapturic acid (S-PMA) and trans,trans-muconic acid (t,t-MA) showed a significant exposure-response trend over the exposure range from 0 to 1 ppm (for S-PMA, p0.0001 and for t,t-MA, p=0.006). For benzene exposure monitoring, both S-PMA and t,t-MA were judged to be good and sensitive markers, which detected benzene exposure at around 0.1 and 1 ppm, respectively. Polymorphisms of the metabolic genes, including CYP2E1, quinone oxidoreductase (NQO1), GSTT1, and myeloperoxidase (MPO), were identified and did not show significant effects on the formation of metabolites, except GSTT1 on S-PMA. The production rate of S-PMA from benzene in exposed workers with GSTT1 null alleles (24.72+/-32.48 microg/g creatinine/ppm benzene) was significantly lower than that in subjects with the wild type of GSTT1 (59.84+/-47.66 microg/g creatinine/ppm benzene, p0.0001). Further regression analysis of S-PMA production rate on GSTT1 genotype with adjustment of sex, age, benzene exposure, and cotinine levels indicated that the genotype of GSTT1 plays a critical role in determining the inter-individual variations of S-PMA formation from benzene exposure. Therefore, the individual genotype of GSTT1 needs to be identified and considered while using S-PMA as a marker to estimate the personal exposure levels of benzene in future population studies.

OBJECTIVES We carried out a detailed exposure assessment of benzene and toluene in two shoe factories in Tianjin, China. Our goal was to identify workers with a broad range of benzene exposures, for an epidemiologic study relating exposure to early biologic effects. METHODS A comprehensive exposure survey program was initiated. Over a period of 16 months, 2783 personal solvent exposure samples were collected in two workplaces from 250 workers. Mixed-effects models were used to identify factors affecting exposure. Principal component analyses (PCA) and subsequent regression analyses on the scores of the identified principal components were used to relate potential co-exposures to various exposure sources present in the workplace. RESULTS The mean benzene exposure level was 21.86 p.p.m. (10th-90th percentiles 5.23-50.63 p.p.m.) in the smaller shoe factory (factory A) and 3.46 p.p.m. (10th-90th percentiles 0.20-7.00 p.p.m.) in the larger shoe factory (factory B). Within-factory exposure levels differed among job titles and were higher for subjects directly involved in handling glues. In contrast, mean toluene levels were relatively similar in the two factories (factory A, 9.52 p.p.m.; factory B, 15.88 p.p.m.). A seasonal trend was identified for both benzene and toluene in factory B. This could be explained in part by changes in air movement and ventilation patterns occurring during the year. A seasonal trend was not present in the smaller shoe factory, where general ventilation was absent. Supplemental analysis showed that exposure levels to other hydrocarbons were low (< or =5 p.p.m.), less than 5% of their respective ACGIH threshold limit values, and generally comparable in the two factories. PCA showed that co-exposures in factory B could largely be explained by glue sources that were used in distinct areas in the workplace. CONCLUSIONS We demonstrated the occurrence of a broad range of benzene exposure levels in two shoe manufacturing factories in Tianjin, China. Benzene and toluene exposures were determined in part by the degree of contact with glues, the benzene and toluene content of each glue, air movement and ventilation patterns. The availability of long-term monthly personal monitoring data provides an excellent opportunity to estimate individual exposures at different times during the 1 yr period of observation.

This article reports an extensive program to monitor individual personal exposures of subjects recruited for a study conducted in a Chinese occupational population to determine whether selected biological markers of exposure to benzene are reliable and sensitive enough to detect low-level benzene exposure in people. The monitoring program reported here was to assure an appropriate range of exposure for subject selection as well as to provide data for the exposure response assessment. The overall study resulted in correlation of the measured exposures with the measured concentrations of two minor urinary benzene metabolites, trans,trans-muconic acid and S-phenylmercapturic acid. The study design and evaluation of biological end points are presented in separate publications. Recruitment of 130 exposed subjects was based on personal exposure measurements collected with passive organic vapor monitors at weekly intervals for 3 to 4 weeks prior to collection of biological samples. Two monitors, side by side, were used for all of the personal monitoring in the first year of the study and about 10 percent of subsequent monitoring. One of each pair was analyzed immediately in Beijing at the Institute of Occupational Medicine, and the other was shipped to the United States and analyzed at the New York University Institute of Environmental Medicine. Exposure concentrations measured over 4-5 weeks were reasonably stable with average coefficients of variation of 0.58, 0.59, and 0.46 for benzene, toluene, and xylene, respectively. Benzene exposure averaged 10 +/- 13 ppm benzene with a median of 3.8 ppm for the recruited exposed workers. Excellent correlation was obtained between samples analyzed for benzene at the two laboratories. The extensive effort to document exposures was important to the exposure-response relationship demonstrated in the full study, which concluded that S-phenylmercapturic acid appears to be a good biomarker for detecting and evaluating benzene exposure at concentrations less than 0.25 ppm.

This study was conducted to validate biomarkers for early detection of benzene exposure and effect in 2 phases. The main purpose of phase 1 was to determine whether these biomarkers could reliably detect differences between workers with high exposure levels and unexposed subjects, which is the minimal screening criterion for a biomarker assay. Phase 2 of the study mainly focused on evaluating the exposure-response relation, confounding factors, and sensitivities of biomarkers for low benzene exposures. The Chinese occupational population studied had a broad range of benzene exposures. On the day of biological sample collection, exposures ranged from 0.06 to 122 ppm with a median exposure of 3.2 ppm. The median of the 4-week mean benzene exposures was 3.8 ppm, and the median lifetime cumulative exposure was 51.1 ppm-years. Compared with benzene levels in collected samples, toluene levels were relatively high, with a median of 12.6 ppm (mean, 26.3 ppm), but xylene levels were low, with a median of 0.30 ppm (mean, 0.40 ppm). The biomarkers evaluated were urinary metabolites S-phenylmercapturic acid (S-PMA*), trans,trans-muconic acid (t,t-MA), hydroquinone (HQ), catechol (CAT), and phenol; albumin adducts of benzene oxide and 1,4-benzoquinone (BO-Alb and 1,4-BQ-Alb, respectively) in blood; blood cell counts; and chromosomal aberrations. Blood cell counts in this population, including red blood cells (RBCs), white blood cells (WBCs), and neutrophils, decreased significantly with increased exposures but remained in normal ranges. Chromosomal aberration data showed significant increases of chromatid breaks and total chromosomal aberrations in exposed subjects compared with unexposed subjects. Among the urinary metabolites, the levels of S-PMA and t,t-MA were significantly elevated after benzene exposures. Both markers showed significant exposure-response trends even over the exposure range from 0 to 1 ppm. However, HQ, CAT, and phenol showed significant increases only for benzene exposure levels above 5 ppm. Multiple regression analyses of these urinary metabolites on benzene exposure indicated that toluene exposure, smoking status, and cotinine levels had no significant effects on urinary metabolite levels. A time-course study estimated the half-lives of S-PMA, t,t-MA, HQ, CAT, and phenol to be 12.8, 13.7, 12.7, 15.0, and 16.3 hours, respectively. Both BO-Alb and 1,4-BQ-Alb showed strong exposure-response associations with benzene. Regression analyses showed that after adjustment for potential confounding by smoking, there was still a strong association between benzene exposure and these markers. Furthermore, the analyses for correlations among biomarkers revealed that the urinary metabolites correlated substantially with each other. The albumin adducts also correlated well with the urinary biomarkers, especially with S-PMA. BO-Alb and 1,4-BQ adducts also correlated well with each other (r = 0.74). For benzene exposure monitoring, both S-PMA and t,t-MA were judged to be good and sensitive markers, which detected benzene exposures at around 0.1 ppm and 1 ppm, respectively. But S-PMA was clearly superior to t,t-MA as a biomarker for low levels of benzene exposure.

Albumin adducts of benzene oxide (BO-Alb) and 1,4-benzoquinone (1,4-BQ-Alb) were investigated among 134 workers exposed to benzene and 51 unexposed controls in Tianjin, China. Concentrations of both adducts increased with benzene exposure [range = 0.07-46.6 parts/million (ppm); median = 3.55 ppm] and with urinary cotinine. Adduct levels were less than proportional to benzene exposure, suggesting saturable CYP 2E1 metabolism of benzene. Because the transition from linear to saturable metabolism began at approximately 1 ppm, the common assumption of linear kinetics at much higher benzene exposures could lead to substantial underestimation of leukemia risks. Adduct levels were generally lower in older workers, indicating that CYP 2E1 metabolism diminished with age, at approximately 2%/year of life. The ratio of 1,4-BQ-Alb:BO-Alb decreased with age and coexposure to toluene, and increased with alcohol consumption. This indicates that factors affecting CYP 2E1 metabolism exerted a greater role on production of 1,4-BQ than BO, presumably because of the second oxidation step from phenol to hydroquinone. The adduct ratio was also positively associated with urinary cotinine, suggesting that both benzene and hydroquinone from cigarette smoke affected adduct levels. Results of a limited time course study of 11 subjects indicated moderate chemical instability of 1,4-BQ-Alb (half life = 13.5 days compared with 21 days for normal Alb turnover), whereas no evidence of instability of BO-Alb was observed. This study illustrates that Alb adducts can be used to investigate the dispositions of reactive metabolites of procarcinogens in humans, provided that exposures are adequately characterized in the month preceding blood collection.

Background The present study was conducted among Chinese workers employed in glue- and shoe-making factories who had an average daily personal benzene exposure of 31±26 ppm (mean±SD). The metabolites monitored were S-phenylmercapturic acid (S-PMA), trans, trans-muconic acid (t,t-MA), hydroquinone (HQ), catechol (CAT), 1,2,4-trihydroxybenzene (benzene triol, BT), and phenol. Methods S-PMA, t,t-MA, HQ, CAT, and BT were quantified by HPLC-tandem mass spectrometry. Phenol was measured by GC-MS. Results Levels of benzene metabolites (except BT) measured in urine samples collected from exposed workers at the end of workshift were significantly higher than those measured in unexposed subjects (P