| Mixture toxicity revisited from a toxicogenomic perspective. | |
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MedLine Citation:
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PMID: 22283441 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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The advent of new genomic techniques has raised expectations that central questions of mixture toxicology such as for mechanisms of low dose interactions can now be answered. This review provides an overview on experimental studies from the past decade that address diagnostic and/or mechanistic questions regarding the combined effects of chemical mixtures using toxicogenomic techniques. From 2002 to 2011 41 studies were published with a focus on mixture toxicity assessment. Primarily multiplexed quantification of gene transcripts was performed, though metabolomic and proteomic analysis of joint exposures have also been undertaken. It is now standard to explicitly state criteria for selecting concentrations and provide insight into data transformation, and statistical treatment with respect to minimising sources of undue variability. Bioinformatic analysis of toxicogenomic data, by contrast, is still a field with diverse and rapidly evolving tools. The reported combined effect assessments are discussed in the light of established toxicological dose-response and mixture toxicity models. Receptor-based assays seem to be the most advanced towards establishing quantitative relationships between exposure and biological responses. Often transcriptomic responses are discussed based on the presence or absence of signals, where the interpretation may remain ambiguous due to methodological problems. The majority of mixture studies design their studies to compare the recorded mixture outcome against responses for individual components only. This stands in stark contrast to our existing understanding of joint biological activity at the levels of chemical target interactions and apical combined effects. By joining established mixture effect models with toxicokinetic and -dynamic thinking, we suggest a conceptual framework that may help to overcome the current limitation of providing mainly anecdotal evidence on mixture effects. To achieve this we suggest (i) to design studies to establish quantitative relationships between dose and time dependency of responses and (ii) to adopt mixture toxicity models. Moreover, (iii) utilisation of novel bioinformatic tools and (iv) stress response concepts could be productive to translate multiple responses into hypothesis on the relationships between general stress and specific toxicity reactions of organisms. |
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Authors:
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Rolf Altenburger; Stefan Scholz; Mechthild Schmitt-Jansen; Wibke Busch; Beate I Escher |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-1-27 |
Journal Detail:
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Title: Environmental science & technology Volume: - ISSN: 1520-5851 ISO Abbreviation: - Publication Date: 2012 Jan |
Date Detail:
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Created Date: 2012-1-30 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0213155 Medline TA: Environ Sci Technol Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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