379499 Biology Based Dose Response (BBDR) of Chemical Mixtures Using Exposomics
Benzene, toluene, ethylbenzene, and xylene (BTEX) are volatile monoaromatic hydrocarbons commonly found together in gasoline; they are also common components of outdoor and indoor air mixtures due to their widespread use in many commercial products. Vehicle exhaust is considered to be the main source but non-professional use of paints, glues, adhesives, varnishes, lacquers, shoe polish and cigarette smoke contribute significantly to the levels of these four VOCs in the indoor environment and to personal exposure.
The aim of the current study is to focus on the potential risk of leukaemia for the general population, experiencing co-exposure to the BTEX mixture at the level of a few ppb (μg/m3) following an exposomics approach. Exposomics includes methodologies for comprehensive individualized exposure assessment, including taking into account molecular signatures of exposure and early effect. A key feature of our study is that benzene is not treated alone, but co-existing to the homologous compounds toluene, ethylbenzene and xylene; this reflects the actual mixtures people are encountering in real environmental setttings. Environmental and personal exposure to benzene were retrieved from a series of studies carried out by the authors, including several environmental settings and population groups. Leukemia risk was assessed through a Physiology Based BioKinetic (PBBK) model, coupled to a Biology Based Dose Response (BBDR) model developed and validated based on toxicological and clinical phenotypic data. Mechanistic approaches at carcinogenic risk assessment process started by the development of biologically motivated cancer risk models. Low-dose estimates of leukemia risk are in compliance to the latest findings on leukaemia etiology, which report that benzene is more efficient as a carcinogen at very low doses. The added value of coupled PBPK-BBDR models in comparison to solely epidemiological exposure response functions is that they provide biology based knowledge of the mechanisms of chemical toxicity. This is a more rational and sophisticated way for estimating potential health implications than statistical relations extrapolated from studies which tend to derive from occupational epidemiology and, consequently, relate to much higher dose range. As such, they can be valuable tools for improving the physiological and biological basis of regulatory health risk assessment.
Of particular interest is the methodological approach used to evaluate leukemia risk due to exposure to benzene. For this purpose, a Physiologically based pharmacokinetic/dynamic (PBBK/BD) model was coupled to a biology based dose-response (BBDR) model for risk assessment. The PBBK/BD model for BTEX was developed and validated against experimental data. These aromatic compounds co-exist in the majority of environmental settings (occupational and residential) and compete with one another for cytochrome P450 isozyme (CYP2E1). Consequently, these co-exposures might potentially reduce the overall metabolism of benzene and thus the concentration of carcinogenic benzene metabolites in systemic circulation and the bone marrow. Thus, the quantification of this interaction to the overall internal dose is of great interest. According to our modeling approach we consider that the interaction between two or more chemicals causes a modification of the rate of metabolism of each chemical due to the presence of the other chemicals that compete for the binding sites resulting in a mutual inhibition of metabolism. The PBBK model for a mixture of chemicals is represented as a combination of “single chemical” models interconnected at level of hepatic metabolism where the effect of the interaction is evaluated according to the potential mechanism of action (competitive, non-competitive, and uncompetitive metabolic inhibitions). The BTEX mixture shows competitive inhibition since the four VOC’s considered are known substrates for CYP2E1. The models used for toluene, ethylbenzene and all the family of xylenes are all four-compartment models encompassing richly perfused tissues (RPT), poorly perfused tissues (PPT), adipose tissues (FAT), and liver (metabolising tissue), interconnected by systemic circulation and a gas exchange lung. The model for benzene is a six-compartment model adding the kidney as a further site of metabolism. The bone marrow was further included because it is the main site where benzene toxicity (i.e. onset of leukaemia) is manifested and because it is, together with the kidney, a potential site for benzene metabolism. The liver was further subdivided into three equal volume sub-compartments according to the zonal distribution of enzymes that mediate benzene metabolism. Since the cancer risk associated to benzene is mainly related to its metabolites and, more in detail, to their internal dose, a more biology-based approach that takes into account the internal dose of metabolites produced should represent an improvement over the traditional risk assessment as it based on more robust biological and physiological data. Furthermore, starting from prior distributions of the most important physiological and biochemical parameters influencing the determination of the internal dose of benzene metabolites we can derive a distribution function of health risk to the exposed population rather than a unique value representing an “individual” risk using Markov Chain Monte Carlo techniques. The cancer risk model developed in this work is based on the decomposition of the dose-response relation into two distinct sub-relations: the first one links the administered dose to the total amount of metabolites produced (internal dose) while the second connects the internal dose to the cancer probability through a statistical model derived from clinical data. The first relation is provided by the PBBK/BD model while the second one was derived trough the development of an empirical-statistical relation that links the internal doses to the cancer probability.
With regard to the analysis of the data from the integrated approach outlined above the key features is the identification of biological process / gene network-level interactions, which may be used as early event biomarkers. The latter should be able to provide early warning flags on potential interactions higher doses. This information can then be exploited to inform PBBK models that would allow us to capture the dose-dependence of the beyond-than-additive behaviour of the mixture. In this context, PBBK/D models permit the analysis not only of the steady state behaviour of the biological system in question. Rather, these models capture the biological/physiological system dynamics, allowing us to perform a comprehensive assessment of the system behaviour under more realistic, transient conditions. Based on the current exposure scenarios where benzene, toluene, ethylbenzene and xylenes levels were equal to 5.3, 14.2, 3.8 and 6.7 μg/m3 respectively, estimated lifetime leukaemia risk was estimated up to 1.5E-06. However, for highly exposed occupational groups such as gasoline station employees, exposure levels were up to 85 μg/m3, and the respective lifetime risk was up to 3E-05. At these exposure levels, inhibition due to co-exposure starts affects the overall risk outcome by a factor of almost 3%. However, at higher exposure levels, close to the Threshold Limit Value (TLV) order of magnitude (0.5 ppm or 1.6 mg/m3). To evaluate the effect of the interaction we compared the internal dose of benzene in the bone marrow when workers are exposed to benzene alone at ¼ the TLV vs. when they are co-exposed to the quaternary BTEX mixture, assuming for each chemical exposure levels at ¼ the respective TLV. The exposure scenario considered was the same except for the fact that occupational exposure was set at ¼ of the TLV. Benzene concentration in the bone marrow is higher under combined exposure to BTEX with respect to exposure to benzene alone. The increment can be estimated between 25 and 30% leading to an increased risk of neurotoxicity and analogously reduced risk of leukaemia to healthy individuals after lifelong exposure.
In addition, molecular signatures of co-exposure to BTEX were identified through transcriptomics. The latter confirmed that BTEX co-exposure significantly alters the initiation of early biological effects than single exposure to benzene. Among the most important molecular pathways differentially expressed were the ones regarding inflammation mediated by chemokine and cytokine signaling, apoptosis as well as oxidative stress. The extent of modulation was proportional to the time of exposure, and to the increase of the toluene:benzene ratio. It has been suggested that chemically-induced chronic inflammation, apoptosis and oxidative stress may lead to carcinogenesis; the latter is one of the most important adverse health effects of benzene. Competitive inhibition of metabolism from co-exposure to BTEX was confirmed from quantitative PCR on Cyp450. This information, coupled with the epidemiologically known cancer effects of benzene would support the formation of mechanistic hypotheses regarding the modulation of benzene toxicity from co-exposure to other VOCs such as the ones present in the BTEX mixture. The conclusions of this study are of paramount importance to the effective regulation of volatile and semi-volatile compound levels in occupational settings and public spaces. The exposomics approach applied herein opens the way towards more cost-effective public health protection by prevention of exposure set-ups that may pose enhanced health risk from combined exposure to multiple chemicals.
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