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Identification of protein markers predictive of adverse effects for chemical mixtures
Citation:
Ge, Y., M. Bruno, A. Farraj, AND B. Chorley. Identification of protein markers predictive of adverse effects for chemical mixtures. 2019 International Congress of Toxicology, Honolulu, Hawaii, July 15 - 18, 2019.
Impact/Purpose:
From environmental and health risk assessment perspectives, the inability to assess and predict mixture toxicity creates real problems for chemical mixture risk assessment. Although protein expression patterns/signatures/biomarkers are valuable in predicting the potential toxic pathways/processes and actions of new or unknown compounds, very few studies have applied proteomics to the analysis of toxic effects and interactions of chemicals within mixtures. The highly sensitive and high-throughput proteomics results allow detection and evaluation of endpoints and chemical interactions undetected by classical toxicological testing, and need to be integrated into the chemical mixture assessment processes. This may change the ways or paradigms we use for chemical risk assessment.In the present study, a direct and quantitative identification of protein markers of predictive adverse effects for chemical mixtures is established, which is critical and very relevant to human health risk assessment of chemical mixtures. The influences this project may have on EPA’s chemical mixture research and on the risk assessment of environmental mixtures include: 1) The ability to accurately distinguish chemicals in a mixture that present little or no concern from those with the greatest likelihood of causing an adverse effect in the target species. Differentiation of chemical components is critical to future chemical mixture risk assessment. 2) The changes in protein expressions and functions or protein expression patterns/toxicity signatures that are specific to each chemical and linked to potential health outcomes are probably the most promising and useful endpoints for future toxicity testing since the protein changes and patterns are the molecular bases of cellular morphological and phenotypic changes. Based on the new and specific protein endpoints, signatures, patterns, and biomarkers, many novel toxicity bioassays for identification, categorization, prioritization, and screening of chemical mixtures can be developed. 3) The integrated proteomics approach developed for identification of protein marker predictive adverse effect is more efficient and pragmatic than toxicity pathway based approach for assessment and prediction of chemical mixture toxicity. It may also improve the ability of the current risk assessment systems and models to forecast toxicity of chemical mixtures.
Description:
Recent advances in many areas of technology developments are being incorporated into the science of toxicology and transforming toxicology from traditional animal testing to modern predictive modeling of chemical toxicity. Development and application of predictive toxicology to better evaluate safety of chemicals, materials, mixtures, and pharmaceuticals was greatly facilitated and improved by the seminal report published by the US National Academy of Science (NAS), which proposed approaching the assessment of toxicological risk of chemical exposures from the standpoint of toxicity pathways. However, the key conceptual difficulty presented by NAS’s toxicity pathway-based approach for predictive toxicology is the identification of appropriate pathways and key events since biological pathways are very complicated and regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation. How to best develop efficient and pragmatic biological approaches, to apply the developed predictive methodologies and systems for assessment of chemical toxicity, and to interpret toxicity data in a chemical risk assessment context are still the major challenges to risk assessment community. We tried to address these challenges in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+ alone and in defined mixtures, in vivo in rats exposed to multiple air pollutants of particular matter and ozone, and in mice co-exposed to environmental chemical of vinyl choride and high -fatty diet. Expression levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were measured in these experimental systems, together with cytotoxicity and other tissue apical endpoints. Least Absolute Shrinkage and Selection Operator (LASSO) multiple regression was used to identify a subset of protein markers that constitute a putative toxicity pathway capable of predicting toxicity or apical endpoints. The identified protein markers of predictive toxicity for these chemical mixtures include phospho-RPS6KB1, phospho-p53, cleaved CASP3, phospho-MAPK8, IL-10, and Hif-1α. In addition, the adverse effects such as cytotoxicity were predicted successfully using the identified protein markers. As this approach does not depend on a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations, it may be generally useful for identifying sets of protein markers predictive of adverse effects for a variety of mixtures, including complex environmental mixtures of unknown composition. (The information in this Abstract has been funded wholly by the U. S. Environmental Protection Agency. It has been subjected to review by the National Health and Environmental Effects Research Laboratory and approved for presentation. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.)