The shape of low-concentration dose–response functions for benzene: implications for human health risk assessment

Abstract

Are dose-response relationships for benzene and health effects such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) supra-linear, with disproportionately high risks at low concentrations, e.g. below 1 ppm? To investigate this hypothesis, we apply recent mode of action (MoA) and mechanistic information and modern data science techniques to quantify air benzene-urinary metabolite relationships in a previously studied data set for Tianjin, China factory workers. We find that physiologically based pharmacokinetics (PBPK) models and data for Tianjin workers show approximately linear production of benzene metabolites for air benzene (AB) concentrations below about 15 ppm, with modest sublinearity at low concentrations (e.g. below 5 ppm). Analysis of the Tianjin worker data using partial dependence plots reveals that production of metabolites increases disproportionately with increases in air benzene (AB) concentrations above 10 ppm, exhibiting steep sublinearity (J shape) before becoming saturated. As a consequence, estimated cumulative exposure is not an adequate basis for predicting risk. Risk assessments must consider the variability of exposure concentrations around estimated exposure concentrations to avoid over-estimating risks at low concentrations. The same average concentration for a specified duration is disproportionately risky if it has higher variance. Conversely, if chronic inflammation via activation of inflammasomes is a critical event for induction of MDS and other health effects, then sufficiently low concentrations of benzene are predicted not to cause increased risks of inflammasome-mediated diseases, no matter how long the duration of exposure. Thus, we find no evidence that the dose-response relationship is supra-linear at low doses; instead sublinear or zero excess risk at low concentrations is more consistent with the data. A combination of physiologically based pharmacokinetic (PBPK) modeling, Bayesian network (BN) analysis and inference, and partial dependence plots appears a promising and practical approach for applying current data science methods to advance benzene risk assessment.

Prediction and assessment of xenoestrogens mixture effects using the in vitro ERα-CALUX assay

“…However, this approach does not allow us to assess the synergy between endogenous and exogenous agonists, i.e., the sigmoid curve of the mixture shifts to the left and its "apparent potency" increases (EC 50 decreases). Such synergies have been less frequently reported and might occur at lower concentration ratios (Cox et al, 2021). Interaction is, therefore, expressed as changes in amplitude (increase/decrease in efficacy), potency (increase/decrease in binding affinity to the receptor), sensitivity (increase/decrease in slope response) or all three together (Indurthi and Auerbach, 2021).…”

Accurate low-dose exposure assessment of benzene and monoaromatic compounds by diffusive sampling: sampling and analytical method validation according to ISO 23320 for radiello® samplers packed with activated charcoal

“…In particular, the shape of low-concentration dose-response functions and their implications for human health risk assessment should be investigated in order to investigate the hypothesis of non-linear dose-response relationships at low exposure concentrations. In fact, whereas previous studies were based on extrapolated data (14), the aim of this study was to develop a validated standard method that allows monitoring of benzene covering the range from 0.0003 to at least 0.1 ppm (i.e., from 0.001 to at least 0.3 mg/m 3 ) over an 8-h exposure duration, tested according to the proper and more recent European standards and to generate highquality data in a low-dose exposure range. The study has been developed by the Environmental Research Center of Istituti Clinici Scientifici Maugeri SpA SB and was aimed at producing a fully validated sampling and analytical method fit for obtaining reliable personal exposure data for the oil and gas, foundry, chemical, and pharmaceutical industry employees.…”

Validation of Analysis of S-Phenyl Mercapturic Acid in Urine by High-Performance Liquid Chromatography – Photodiode Array

“…Benzene undergoes liver metabolism, resulting in the formation of a series of 2024, 21(6): 2028-2038 https://doi.org /10.21123/bsj.2023.8107 P-ISSN: 2078-8665 -E-ISSN: 2411 Baghdad Science Journal hydroxyl compounds and metabolites that conjugate with glutathione. Other products containing opened rings are also formed, which are eliminated through urine 13 .…”