A physiologically-based kinetic (PBK) model for work-related diisocyanate exposure: Relevance for the design and reporting of biomonitoring studies

Diisocyanates are highly reactive substances and known causes of occupational asthma. Exposure occurs mainly in the occupational setting and can be assessed through biomonitoring which accounts for inhalation and dermal exposure and potential effects of protective equipment. However the interpretation of biomonitoring data can be challenging for chemicals with complex kinetic behavior and multiple exposure routes, as is the case for diisocyanates. To better understand the relation between external exposure and urinary concentrations of metabolites of diisocyanates, we developed a physiologically based kinetic (PBK) model for methylene bisphenyl isocyanate (MDI) and toluene di-isocyanate (TDI). The PBK model covers both inhalation and dermal exposure, and can be used to estimate biomarker levels after either single or chronic exposures. Key parameters such as absorption and elimination rates of diisocyanates were based on results from human controlled exposure studies. A global sensitivity analysis was performed on model predictions after assigning distributions reflecting a mixture of parameter uncertainty and population variability. Although model-based predictions of urinary concentrations of the degradation products of MDI and TDI for longer-term exposure scenarios compared relatively well to empirical results for a limited set of biomonitoring studies in the peer-reviewed literature, validation of model predictions was difficult because of the many uncertainties regarding the precise exposure scenarios that were used. Sensitivity analyses indicated that parameters with a relatively large impact on model estimates included the fraction of diisocyanates absorbed and the binding rate of diisocyanates to albumin relative to other macro molecules.We additionally investigated the effects of timing of exposure and intermittent urination, and found that both had a considerable impact on estimated urinary biomarker levels. This suggests that these factors should be taken into account when interpreting biomonitoring data and included in the standard reporting of isocyanate biomonitoring studies

An update on the strategies in multicomponent activity monitoring within the phytopharmaceutical field

<p>Abstract</p> <p>Background</p> <p>To-date modern drug research has focused on the discovery and synthesis of single active substances. However, multicomponent preparations are gaining increasing importance in the phytopharmaceutical field by demonstrating beneficial properties with respect to efficacy and toxicity.</p> <p>Discussion</p> <p>In contrast to single drug combinations, a botanical multicomponent therapeutic possesses a complex repertoire of chemicals that belong to a variety of substance classes. This may explain the frequently observed pleiotropic bioactivity spectra of these compounds, which may also suggest that they possess novel therapeutic opportunities. Interestingly, considerable bioactivity properties are exhibited not only by remedies that contain high doses of phytochemicals with prominent pharmaceutical efficacy, but also preparations that lack a sole active principle component. Despite that each individual substance within these multicomponents has a low molar fraction, the therapeutic activity of these substances is established via a potentialization of their effects through combined and simultaneous attacks on multiple molecular targets. Although beneficial properties may emerge from such a broad range of perturbations on cellular machinery, validation and/or prediction of their activity profiles is accompanied with a variety of difficulties in generic risk-benefit assessments. Thus, it is recommended that a comprehensive strategy is implemented to cover the entirety of multicomponent-multitarget effects, so as to address the limitations of conventional approaches.</p> <p>Summary</p> <p>An integration of standard toxicological methods with selected pathway-focused bioassays and unbiased data acquisition strategies (such as gene expression analysis) would be advantageous in building an interaction network model to consider all of the effects, whether they were intended or adverse reactions.</p

Exposome: connecting the dots for effective prevention of disease

Our health is impacted by the environment we grow up, live, work, sport, sleep and relax in. The combination of exposures during daily activities and over the lifetime constitutes a major risk factor for disease. Many common disorders are closely linked to these exposures ranging from lifestyle factors, to chemical exposures, social interactions and stress. All together such exposures have a huge health impact in society. They contribute to the development and progression of diseases like cancer, respiratory and cardiovascular disease. Many of these combined exposures can potentially be modified to prevent disease. However, the complex interrelations between exposures and effects are still a scientific challenge. We often do not know why one person develops a disease and the other does not

Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals

Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicological assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole. © 2005 Elsevier Inc. All rights reserved

Systems toxicology: applications of toxicogenomics, transcriptomics, proteomics and metabolomics in toxicology

Toxicogenomics can facilitate the identification and characterization of toxicity, as illustrated in this review. Toxicogenomics, the application of the functional genomics technologies (transcriptomics, proteomics and metabolomics) in toxicology enables the study of adverse effects of xenobiotic substances in relation to structure and activity of the genome. The advantages and limitations of the different technologies are evaluated, and the prospects for integration of the technologies into a systems biology or systems toxicology approach are discussed. Applications of toxicogenomics in various laboratories around the world show that the crucial steps and sequence of events at the molecular level can be studied to provide detailed insights into mechanisms of toxic action. Toxicogenomics allowed for more sensitive and earlier detection of adverse effects in (animal) toxicity studies. Furthermore, the effects of exposure to mixtures could be studied in more detail. This review argues that in the (near) future, human health risk assessment will truly benefit from toxicogenomics (systems toxicology)

A quantitative meta-analysis of the relation between occupational benzene exposure and biomarkers of cytogenetic damage

Background: The genotoxicity of benzene has been investigated in dozens of biomonitoring studies, mainly by studying (classical) chromosomal aberrations (CAs) or micronuclei (MN) as markers of DNA damage. Both have been shown to be predictive of future cancer risk in cohort studies and could, therefore, potentially be used for risk assessment of genotoxicity-mediated cancers. Objectives: We sought to estimate an exposure–response curve (ERC) and quantify between-study heterogeneity using all available quantitative evidence on the cytogenetic effects of benzene exposure on CAs and MN respectively. Methods: We carried out a systematic literature review and summarized all available data of sufficient quality using meta-analyses. We assessed the heterogeneity in slope estimates between studies and conducted additional sensitivity analyses to assess how various study characteristics impacted the estimated ERC. Results: Sixteen CA (1,356 individuals) and 13 MN studies (2,097 individuals) were found to be eligible for inclusion in a meta-analysis. Studies where benzene was the primary genotoxic exposure and that had adequate assessment of both exposure and outcomes were used for the primary analysis. Estimated slope estimates were an increase of 0.27% CA [(95% CI: 0.08%, 0.47%); based on the results from 4 studies] and 0.27% MN [(95% CI: −0.23%, 0.76%); based on the results from 7 studies] per parts-per-million benzene exposure. We observed considerable between-study heterogeneity for both end points (I2>90%). Discussion: Our study provides a systematic, transparent, and quantitative summary of the literature describing the strong association between benzene exposure and accepted markers of genotoxicity in humans. The derived consensus slope can be used as a best estimate of the quantitative relationship between real-life benzene exposure and genetic damage in future risk assessment. We also quantitate the large between-study heterogeneity that exists in this literature, a factor which is crucial for the interpretation of single-study or consensus slopes