Exposure to benzene constitutes a major environmental concern, since it is considered as an established cause of acute myeloid leukemia (AML), myelodisplastic syndromes (MDS), and probably lymphocytic leukemia and non-Hodgkin lymphoma (NHL) in humans. Even though benzene is leukemogenic at relatively low occupational levels of exposure, its association with leukemia in the general population exposed to benzene in the ppb range is somehow questionable. Identification of molecular markers of exposure and effect at real life environmental exposure levels is expected to provide additional insights on this association. It is widely accepted that the transcriptome is dynamic and that it reflects the organism’s immediate and genome-wide response to environmental exposure and endogenous cues. From previous studies, it has been found that benzene exposure on the transcriptome of peripheral blood mononuclear cells (PBMCs) from a population of shoe factory workers, resulted on differentially expressed genes. A subsequent analysis of PBMCs from a population with well-characterized occupational exposure to benzene using two microarray platforms (Affimetrix and Illumina) revealed a large number of differentially expressed genes to be associated with benzene exposure. Gene pathway and ontology analysis demonstrated over-representation of genes involved in apoptosis and immune/inflammatory response. Furthermore, highly significant widespread perturbation of gene expression at all exposure levels has been observed, while, the AML pathway was among the pathways most significantly associated with benzene exposure, while a 16-gene expression signature associated with all levels of benzene exposure was identified.
The aim of the current study is to focus on the leukemogenic benzene potential for the general population, experiencing exposure to benzene at the levels of few ppb (μg/m3) within an exposomics approach. The later relies on the evaluation of sensors technology for exposure assessment, the use of internal dosimetry and biology based dose response for risk estimation as well as the use of transcriptomcs for the assessment of exposure to effect modifiers. A major differentiation to existing studies, is that benzene is not treated alone, but co-existing to the homologous compounds toluene, ethylbenzene and xylene; this is reflecting the actual mixtures people are encountering in real environmental setttings. The variable levels of biological organization involved in this holistic view of mixture toxicology and cumulative exposure and risk assessment suggest that different technologies need to be brought to bear in order to obtain a comprehensive view of how co-exposure to multiple chemicals affects the overall phenotypic response of individuals. Technological variability introduces the need for better data integration and assimilation and for the development of novel data analysis and hypothesis generation and testing procedures in order to best elucidate the biological mechanisms underlying mixture toxicity.
This systems toxicology approach to mechanistically-based risk assessment of environmental chemical mixtures can be tackled with an integrated, multi-layer computational methodology, ideally comprising the following steps:
a) Characterization of exposure factors quantifying the parameters that affect human exposure to environmental chemicals, such as time-activity relationships, seasonal and climatic variation, and consumer choice. These exposure factors can be used to derive aggregate and cumulative exposure models, leading in probabilistic exposure assessments. Aggregation can be done across exposure pathways and routes and even across different exposure scenarios, if the relevant exposure metric or the imputable biological or physiological effect can be related to these scenarios. For instance, exposure to volatile organic compounds (VOCs) such as benzene or toluene and mixtures thereof may occur both from environmental media and in specific occupational settings. A cumulative exposure scenario for these substances would have to take stock of the actual variability of exposure across these different settings throughout typical days for the same period in an individual’s lifespan.
b) Current toxicological state of the art combines estimations of biologically effective dose with early biological events to derive dose-effect models, which can be used in combination with the probabilistic exposure estimates to derive biomarkers of exposure and/or effect. Combined use of epidemiological, clinical and genetic analysis data may shed light on the effect of risk modifying factors such as lifestyle choices and DNA polymorphisms. Observation of real clinical data and /or results of biomonitoring, if coupled with the exposure/effect biomarker discovery systems, can produce biomarkers of individual susceptibility and thus allow estimations of individual response to toxic insults. Transcriptomics, are key technology to this kind of analytical and data interpretation process.
c) The analysis of the biomarker data (including results on biomarkers of exposure, effects and individual susceptibility) results in the integrated assessment of risk factors. Use of information on risk factors with molecular dosimetry data (i.e. estimation of the actual internal and biologically effective dose of xenobiotic substance found in the target organ and, indeed, perturbing cellular response) enables population risk studies to be done, by converting generic exposure profiles into population risk metrics having taken into account inter-individual variability of response and exposure uncertainty.
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, occupational or not. Internal exposure to benzene and its toxic metabolites was assessed through a Physiology Based BioKinetic (PBBK) model, for a quaternary mixture of BTEX. To translate the estimated internal dose (concentration of toxic metabolites in the bone marrow) into actual risk estimates, a biology-based dose- response model (BBDR) that links external exposure to a specific end-point, which, in the case of benzene, is primarily the risk of leukemia was developed. In this work a method was applied, based on the decomposition of the dose-response relationship into a set of causal micro-relations each one describing a biologic process separately. Instead of evaluating the relationship between administered dose and cancer risk “directly” through an empirical-statistical model, here this relationship is decomposed into two different parts: the first one links the administered dose to the total amount of metabolites produced (internal dose), while the second one connects the internal dose to the probability of cancer. The statistical relation between internal dose and cancer probability was calculated parameterizing function as given by Crump and Allen. In particular the administered dose was calculated assuming an average person of 70 kg (adult) who inhales 10 m3of air in 8 hours for an occupation period of 40 years over a life of 70 years.
Transcriptomics analysis showed that 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 benzene:toluene ratio; At short exposure regimes, low concentrations seem to produce hormesis. At higher exposure regimes, the activation of homeostasis results seem to be counterbalanced, thus responses are dose-dependent 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. Pathway analysis of the results mentioned above indicated that the apoptosis signaling pathway is activated under the co-exposure to the BTEX chemical mixture. Using quantitative PCR analysis the extent of modulation in the expression of cytochrome P450 (CyP450) as a function of exposure to BTEX mixtures with variable toluene:benzene ratio was quantitatively investigated; CyP450 is generally known to regulate benzene metabolism. They are time-dependent (i.e., several differences can be observed in gene expression modulation after 4 and 24 hours). In general, the toluene-richer mixture induces suppression of the difference in gene expression compared to the controls for practically all the CyP450 gene family. The phenotypic outcome of the CyP450 suppression would be reduction of its catalytic activity in VOC metabolism. This would support the metabolic inhibition hypothesis for the interaction between the constituents of the quaternary BTEX mixture. Overall, the toxicogenomics results would suggest that co-exposure to BTEX reduces benzene metabolism.
Based on the above exposure measurements and translating them into internal exposure, it was estimated that general population of the city runs an average lifetime leukemia risk (due to benzene exposure) equal to 4.1∙10-5 (2.1∙10-5 to 8.2∙10-5), while for the occupational groups the estimated risk is as high as 11∙10-5. The leukemia risk distributions derived herein, represent the variation in activity patterns that result in different levels of exposure and the variability of the population physiological response to environmental stressors. Benzene toxicity is intimately tied to its complex metabolism and distribution. Key enzymes involved in the metabolism of benzene, including CYP2E1, the quinone reductase NQO1, and myeloperoxidase are polymorphic. For example, a 7.6-fold difference in benzene-induced hematotoxicity in workers was observed among gene variants of CYP2E1 and NQO1. Thus the expression of genetic polymorphisms may modulate the susceptibility of an individual or ethnic group to the effects of benzene exposure.
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