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.