A Quantitative Meta-Analysis of the Relation between Occupational Benzene Exposure and Biomarkers of Cytogenetic Damage

Combined exposure of MAHs and PAHs enhanced amino acid and lipid metabolism disruption in epithelium leading asthma risk

Monoaromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) are ubiquitous air pollutants from industry, with multiple adverse effects on respiratory system. However, the underlying mechanisms of their mixture to induce asthma is still unclear. Here, we examined mixture of 8 MAHs, mixture of 16 PAHs and a total mixture (MIX) on human bronchial epithelial (16-HBE) cells. Exposure to MIX resulted in increased expressions of asthma alarm cytokines (TSLP, IL-25 and IL-33), indicating potential asthma risk. Exposure to MIX led to significant upregulation of transcriptional level of oxidative stress and inflammation biomarkers through aryl hydrocarbon receptor activation, including SOD-2, NQO-1, IL-1β, IL-6 and IL-8 with 3.1, 19.9, 3.5, 23.4, 18.7, 28.1-fold change, indicated asthma related epithelial cell lesions. A total of 25, 49 and 59 differential metabolites were identified in cells response to MAH, PAH and MIX exposure, respectively, and enrichment analysis demonstrated MIX exposure disturbing alanine, aspartate and glutamate metabolism, glutathione metabolism, methionine metabolism and sphingolipid metabolism, involved in antioxidative defense and inflammation response. Combined exposure of MAHs and PAHs may result in increased toxic risks, and provide evidence to asthma onset and deterioration.

Benzene Exposure and Lung Cancer Risk: A Systematic Review and Meta-Analysis of Human Studies

Lung cancer is a leading cause of death with nearly 1.8 million deaths estimated worldwide in 2020. Although benzene is classified as a human carcinogen (Group 1) on the basis of its association with acute myeloid/non-lymphocytic leukaemia, there is still limited evidence that it may influence lung cancer risk. This study examined the potential link between benzene exposure and risk of lung cancer using a systematic review of epidemiological studies and meta-analysis. We searched through PubMed, Web of Science and Scopus databases up to 10 February 2023 to identify all articles on the association between benzene exposure and lung cancer (incidence or prevalence) and/or mortality. We extracted the risk estimates of the highest and the lowest reported categories of benzene exposure and conducted a meta-analysis using a random-effects model. Heterogeneity and publication bias were analysed using an I2 test and funnel plots asymmetry, respectively. Twenty-one studies were included in the final analysis, with a total of 10,750 lung cancer cases and 2899 lung cancer deaths. Overall, risk estimates of lung cancer prevalence and mortality in association with benzene exposure were 1.20 (n = 14; 95% CI 1.05-1.37) and 1.15 (n = 13; 95% CI 1.02-1.30), respectively. In all cases, heterogeneity was quite large, while no significant publication bias was observed. When only studies that adjusted for smoking habit were selected, the risk for lung cancer increased by up to 34% (n = 9; 95% CI 1.10-1.64). Our data, which show a strong association between benzene exposure and lung cancer risk, may have important public health implications. However, further studies are needed to identify the lung cancer risk associated with benzene exposure considering different smoking conditions.

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

Moderate body lipid accumulation in mice attenuated benzene-induced hematotoxicity via acceleration of benzene metabolism and clearance

Recent population and animal studies have revealed a correlation between fat content and the severity of benzene-induced hematologic toxicity. However, the precise impact of lipid deposition on benzene-induced hematotoxicity and the underlying mechanisms remain unclear. In this study, we established a mouse model with moderate lipid accumulation by subjecting the mice to an 8-week high-fat diet (45% kcal from fat, HFD), followed by 28-day inhalation of benzene at doses of 0, 1, 10, and 100 ppm. The results showed that benzene exposure caused a dose-dependent reduction of peripheral white blood cell (WBC) counts in both diet groups. Notably, this reduction was less pronounced in the HFD-fed mice, suggesting that moderate lipid accumulation mitigates benzene-related hematotoxicity. To investigate the molecular basis for this effect, we performed bioinformatics analysis of high-throughput transcriptome sequencing data, which revealed that moderate lipid deposition alters mouse metabolism and stress tolerance towards xenobiotics. Consistently, the expression of key metabolic enzymes, such as Cyp2e1 and Gsta1, were upregulated in the HFD-fed mice upon benzene exposure. Furthermore, we utilized a real-time exhaled breath detection technique to monitor exhaled benzene metabolites, and the results indicated that moderate lipid deposition enhanced metabolic activation and increased the elimination of benzene metabolites. Collectively, these findings demonstrate that moderate lipid deposition confers reduced susceptibility to benzene-induced hematotoxicity in mice, at least in part, by accelerating benzene metabolism and clearance.

Environmental Exposures and Anti-Müllerian Hormone: A Mixture Analysis in the Nurses' Health Study II

BACKGROUND

Previous studies have linked environmental exposures with anti-Müllerian hormone (AMH), a marker of ovarian reserve. However, associations with multiple environment factors has to our knowledge not been addressed.

METHODS

We included a total of 2,447 premenopausal women in the Nurses' Health Study II (NHSII) who provided blood samples during 1996-1999. We selected environmental exposures linked previously with reproductive outcomes that had measurement data available in NHSII, including greenness, particulate matter, noise, outdoor light at night, ultraviolet radiation, and six hazardous air pollutants (1,3-butadiene, benzene, diesel particulate matter, formaldehyde, methylene chloride, and tetrachloroethylene). For these, we calculated cumulative averages from enrollment (1989) to blood draw and estimated associations with AMH in adjusted single-exposure models, principal component analysis (PCA), and hierarchical Bayesian kernel machine regression (BKMR).

RESULTS

Single-exposure models showed negative associations of AMH with benzene (percentage reduction in AMH per interquartile range [IQR] increase = 5.5%, 95% confidence interval [CI] = 1.0, 9.8) and formaldehyde (6.1%, 95% CI = 1.6, 10). PCA identified four major exposure patterns but only one with high exposure to air pollutants and light at night was associated with lower AMH. Hierarchical BKMR pointed to benzene, formaldehyde, and greenness and suggested an inverse joint association with AMH (percentage reduction comparing all exposures at the 75th percentile to median = 8.2%, 95% CI = 0.7, 15.1). Observed associations were mainly among women above age 40.

CONCLUSIONS

We found exposure to benzene and formaldehyde to be consistently associated with lower AMH levels. The associations among older women are consistent with the hypothesis that environmental exposures accelerate reproductive aging.

Estimation of the exposure response relation between benzene and acute myeloid leukemia by combining epidemiological, human biomarker, and animal data

Background Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure-response cure (ERC) modelling when data across the exposure range is sparse. Methods We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and non-human studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, ten human biomarker studies, and four experimental animal studies. Results A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range (<40 ppm yrs) from this model were comparable, but more precise, when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals [95%PI] at 5 ppm years were 1.58 [1.01, 3.22]) and 1.44 [0.85, 3.42], respectively. Conclusions Integrating the available epidemiological, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation. Impact By describing a framework for data-integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.

Influence of Bisphenol Compounds at Nanomolar Concentrations on Chromosome Damage Induced by Metabolically Activated Carcinogens in HepG2 Cells

Bisphenol (BP) compounds are endocrine-disrupting organic pollutants. BPs may increase the messenger RNA (mRNA) transcripts of nuclear receptors (NRs) regulating the expression of xenobiotic-metabolizing cytochrome P450 (CYP) enzymes. Their impact on the genotoxicity of metabolically activated carcinogens, however, remains unknown. In this study, effects of the bisphenols A, F, S, and AF on the expression of the aryl hydrocarbon receptor (AhR), the pregnane X receptor (PXR), the constitutive androstane receptor, and individual xenobiotic-metabolizing CYP enzymes in a human hepatoma (HepG2) cell line were investigated, along with in silico binding studies of BPs to each receptor. The results indicated that each BP at 1 to 100 nM concentrations increased the mRNA transcripts and protein levels of AhR, PXR, CYP1A1, 1A2, 1B1, 2E1, and 3A4. The predicted affinities of the BPs for binding AhR were comparable to those of potent agonists. Pretreatment of HepG2 cells with each BP potentiated the induction of micronuclei by benzo[a]pyrene, aflatoxin B1, benzene, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; this effect was abolished/reduced by inhibitors of NRs and/or CYPs. Our study suggests that BPs at human exposure levels may aggravate chromosome damage by several impactful carcinogens in human cells by inducing relevant CYP enzymes, mostly via NR modulation.

Biomarkers of Genotoxicity in Medical Workers Exposed to Low-Dose Ionizing Radiation: Systematic Review and Meta-Analyses

Medical staff represent the largest group of workers occupationally exposed to ionizing radiation (IR). Chronic exposure to low-dose IR may result in DNA damage and genotoxicity associated with increased risk of cancer. This review aims to identify the genotoxicity biomarkers that are the most elevated in IR-exposed vs. unexposed health workers. A systematic review of the literature was performed to retrieve relevant studies with various biomarkers of genotoxicity. Subsequent meta-analyses produced a pooled effect size for several endpoints. The search procedure yielded 65 studies. Chromosome aberrations (CA) and micronuclei (MN) frequencies were significantly different between IR-exposed and unexposed workers (θ_pooled = 3.19, 95% CI 1.46–4.93; and θ_pooled = 1.41, 95% CI 0.97–1.86, for total aberrant cells and MN frequencies, respectively), which was not the case for ring chromosomes and nucleoplasmic bridges. Although less frequently used, stable translocations, sister chromatid exchanges (SCE) and comet assay endpoints were also statistically different between IR-exposed and unexposed workers. This review confirms the relevance of CA and MN as genotoxicity biomarkers that are consistently elevated in IR-exposed vs. unexposed workers. Other endpoints are strong candidates but require further studies to validate their usefulness. The integration of the identified biomarkers in future prospective epidemiological studies is encouraged.