title: Validation and evaluation of biomarkers in workers exposed to benzene in China.
abstract: 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.
authors.affiliation: Nelson Institute of Environmental Medicine, New York University School of Medicine. 57 Old Forge Rd, Tuxedo NY 10987, USA.
authors.forename: Qingshan
authors.initials: Q
authors.lastname: Qu
authors.forename: Roy
authors.initials: R
authors.lastname: Shore
authors.forename: Guilan
authors.initials: G
authors.lastname: Li
authors.forename: Ximei
authors.initials: X
authors.lastname: Jin
authors.forename: Lung Chi
authors.initials: LC
authors.lastname: Chen
authors.forename: Beverly
authors.initials: B
authors.lastname: Cohen
authors.forename: Assieh A
authors.initials: AA
authors.lastname: Melikian
authors.forename: David
authors.initials: D
authors.lastname: Eastmond
authors.forename: Stephen
authors.initials: S
authors.lastname: Rappaport
authors.forename: Heyi
authors.initials: H
authors.lastname: Li
authors.forename: Doppalapudi
authors.initials: D
authors.lastname: Rupa
authors.forename: Suramya
authors.initials: S
authors.lastname: Waidyanatha
authors.forename: Songnian
authors.initials: S
authors.lastname: Yin
authors.forename: Huifang
authors.initials: H
authors.lastname: Yan
authors.forename: Min
authors.initials: M
authors.lastname: Meng
authors.forename: Witold
authors.initials: W
authors.lastname: Winnik
authors.forename: Eric S C
authors.initials: ES
authors.lastname: Kwok
authors.forename: Yuying
authors.initials: Y
authors.lastname: Li
authors.forename: Ruidong
authors.initials: R
authors.lastname: Mu
authors.forename: Bohong
authors.initials: B
authors.lastname: Xu
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Zhang
authors.forename: Keqi
authors.initials: K
authors.lastname: Li
mesh_terms: D000328:Adult; D000818:Animals; D001555:Benzene Derivatives / Q000097:blood / Q000633:toxicity* / Q000652:urine; D015415:Biomarkers / Q000032:analysis*; D001772:Blood Cell Count; D002681:China / Q000453:epidemiology; D002869:Chromosome Aberrations; D005260:Female; D006801:Humans; D008297:Male; D016273:Occupational Exposure / Q000032:analysis* / Q000706:statistics & numerical data
chemical_list: D001555:Benzene Derivatives; D015415:Biomarkers