SEARCH · PubMed Health

Results for “Toxicogenetics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources

PubMed2004

Applying new biotechnologies to the study of occupational cancer--a workshop summary.

As high-throughput technologies in genomics, transcriptomics, and proteomics evolve, questions arise about their use in the assessment of occupational cancers. To address these questions, the National Institute for Occupational Safety and Health, the National Cancer Institute, the National Institute of Environmental Health Sciences, and the American Chemistry Council sponsored a workshop 8-9 May 2002 in Washington, DC. The workshop brought together 80 international specialists whose objective was to identify the means for best exploiting new technologies to enhance methods for laboratory investigation, epidemiologic evaluation, risk assessment, and prevention of occupational cancer. The workshop focused on identifying and interpreting markers for early biologic effect and inherited modifiers of risk.

Biomarkers↗

PubMed2003

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

The mapping of the human genome and the determination of corresponding gene functions, pathways, and biological mechanisms are driving the emergence of the new research fields of toxicogenomics and systems toxicology. Many technological advances such as microarrays are enabling this paradigm shift that indicates an unprecedented advancement in the methods of understanding the expression of toxicity at the molecular level. At the National Center for Toxicological Research (NCTR) of the U.S. Food and Drug Administration, core facilities for genomic, proteomic, and metabonomic technologies have been established that use standardized experimental procedures to support centerwide toxicogenomic research. Collectively, these facilities are continuously producing an unprecedented volume of data. NCTR plans to develop a toxicoinformatics integrated system (TIS) for the purpose of fully integrating genomic, proteomic, and metabonomic data with the data in public repositories as well as conventional (Italic)in vitro(/Italic) and (Italic)in vivo(/Italic) toxicology data. The TIS will enable data curation in accordance with standard ontology and provide or interface a rich collection of tools for data analysis and knowledge mining. In this article the design, practical issues, and functions of the TIS are discussed through presenting its prototype version, ArrayTrack, for the management and analysis of DNA microarray data. ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to gene information in the LIB.

Databases, Factual↗

PubMed2004

Toxicogenomics in risk assessment: an overview of an HESI collaborative research program.

The value of genomic approaches in hypothesis generation is being realized as a tool for understanding toxicity and consequently contributing to an assessment of drug and chemical safety. In 1999 the membership of the International Life Sciences Institute Health and Environmental Sciences Institute formed a committee to develop a collaborative scientific program to address issues, challenges, and opportunities afforded by the emerging field of toxicogenomics. Experts and advisors from academia and government laboratories participate on the committee, along with approximately 30 corporate member organizations from the pharmaceutical, agrochemical, chemical, and consumer products industries. The committee has designed, conducted, and analyzed numerous toxicogenomic experiments within the broad fields of hepatotoxicity, nephrotoxicity, and genotoxicity. The considerable body of data generated by these programs has been instrumental in increasing understanding of sources of biological and technical variability in the alignment of toxicant-induced transcription changes with the accepted mechanism of action of these agents and the challenges in the consistent analysis and sharing of the voluminous data sets generated by these approaches. Recognizing the importance of standardized microarray data formats and public repository databases as the mechanism by which microarray data can be compared and interpreted by the scientific community, the committee has partnered with the European Bioinformatics Institute to develop a database to house the data generated by its collaborative research.

Gene Expression Profiling↗

PubMed2004

Database development in toxicogenomics: issues and efforts.

The marriage of toxicology and genomics has created not only opportunities but also novel informatics challenges. As with the larger field of gene expression analysis, toxicogenomics faces the problems of probe annotation and data comparison across different array platforms. Toxicogenomics studies are generally built on standard toxicology studies generating biological end point data, and as such, one goal of toxicogenomics is to detect relationships between changes in gene expression and in those biological parameters. These challenges are best addressed through data collection into a well-designed toxicogenomics database. A successful publicly accessible toxicogenomics database will serve as a repository for data sharing and as a resource for analysis, data mining, and discussion. It will offer a vehicle for harmonizing nomenclature and analytical approaches and serve as a reference for regulatory organizations to evaluate toxicogenomics data submitted as part of registrations. Such a database would capture the experimental context of in vivo studies with great fidelity such that the dynamics of the dose response could be probed statistically with confidence. This review presents the collaborative efforts between the European Molecular Biology Laboratory-European Bioinformatics Institute ArrayExpress, the International Life Sciences Institute Health and Environmental Science Institute, and the National Institute of Environmental Health Sciences National Center for Toxigenomics Chemical Effects in Biological Systems knowledge base. The goal of this collaboration is to establish public infrastructure on an international scale and examine other developments aimed at establishing toxicogenomics databases. In this review we discuss several issues common to such databases: the requirement for identifying minimal descriptors to represent the experiment, the demand for standardizing data storage and exchange formats, the challenge of creating standardized nomenclature and ontologies to describe biological data, the technical problems involved in data upload, the necessity of defining parameters that assess and record data quality, and the development of standardized analytical approaches.

Animals↗

PubMed2004

The utility of DNA microarrays for characterizing genotoxicity.

Microarrays provide an unprecedented opportunity for comprehensive concurrent analysis of thousands of genes. The global analysis of the response of genes to a toxic insult (toxicogenomics), as opposed to the historical method of examining a few select genes, provides a more complete picture of toxicologically significant events. Here we examine the utility of microarrays for providing mechanistic insights into the response of cells to DNA damage. Our data indicate that the value of the technology is in its potential to provide mechanistic insight into the mode of action of a genotoxic compound. Array-based expression profiling may be useful for differentiating compounds that interact directly with DNA from those compounds that are genotoxic via a secondary mechanism. As such, genomic microarrays may serve as a valuable alternative methodology that helps discriminate between these two classes of compounds. Key words: biomarkers, gene expression profile, genetic toxicology, mechanism of action, toxicogenomics.

Animals↗

PubMed2004

Human genetics, environment, and communities of color: ethical and social implications.

A conference titled "Human Genetics, Environment, and Communities of Color: Ethical and Social Implications" and a workshop symposium titled "Human Genetics and Environmental Justice" were held by West Harlem Environmental Action, Inc., with cosponsorship by the National Institute of Environmental Health Sciences (NIEHS), the Community Outreach and Education Program of the NIEHS P30 Center for Environmental Health at the Mailman School of Public Health at Columbia University, New York, and the U.S. Environmental Protection Agency. The conference and symposium took place at Columbia University in New York City on 4-5 February 2002. Expert panels composed of public health practitioners, genetic researchers, ethicists, lawyers, social scientists, and community organizations were assembled to explore how genetic research will affect communities of color, specifically in environmental health research. The goal of the conference was to educate participants on the science and ethics of genetic research and to explore the potential benefits and pitfalls of genetic research vis-à-vis new trends in environmental health research, specifically with reference to communities of color. The goal of the symposium was to discuss the major perceptions and concerns for community-based environmental justice advocates and other communities of color regarding environmental health genetic research. The conference and symposium drew more than 300 participants and articulated important perspectives on the opportunities and challenges for environmental justice advocates and other communities of color posed by rapid advances in environmental health genetic research and toxicogenomics.

Biomedical Research↗

PubMed2004

Cross-site comparison of gene expression data reveals high similarity.

Consistency and coherence of gene expression data across multiple sites depends on several factors such as platform (oligo, cDNA, etc.), environmental conditions at each laboratory, and data quality. The Hepatotoxicity Working Group of the International Life Sciences Institute Health and Environmental Sciences Institute consortium on the application of genomics to mechanism-based risk assessment is investigating these factors by comparing high-density gene expression data sets generated on two sets of RNA from methapyrilene (MP) experiments conducted at Abbott Laboratories and Boehringer-Ingelheim Pharmaceuticals, Inc. using a single platform (Affymetrix Rat Genome U34A GeneChip) at seven different sites. This article focuses on the evaluation of data quality and statistical models that facilitate the comparison of such data sets at the probe level. We present methods for exploring and quantitatively assessing differences in the data, with the principal goal being the generation of lists of site-insensitive genes responsive to low and high doses of MP. A combination of numerical and graphical techniques reveals important patterns and partitions of variability in the data, including the magnitude of the site effects. Although the site effects are significantly large in the analysis results, they appear to be primarily additive and therefore can be adjusted in the statistical calculations in a way that does not bias conclusions regarding treatment differences.

Animals↗

PubMed2005

Personalized exposure assessment: promising approaches for human environmental health research.

New technologies and methods for assessing human exposure to chemicals, dietary and lifestyle factors, infectious agents, and other stressors provide an opportunity to extend the range of human health investigations and advance our understanding of the relationship between environmental exposure and disease. An ad hoc Committee on Environmental Exposure Technology Development was convened to identify new technologies and methods for deriving personalized exposure measurements for application to environmental health studies. The committee identified a "toolbox" of methods for measuring external (environmental) and internal (biologic) exposure and assessing human behaviors that influence the likelihood of exposure to environmental agents. The methods use environmental sensors, geographic information systems, biologic sensors, toxicogenomics, and body burden (biologic) measurements. We discuss each of the methods in relation to current use in human health research; specific gaps in the development, validation, and application of the methods are highlighted. We also present a conceptual framework for moving these technologies into use and acceptance by the scientific community. The framework focuses on understanding complex human diseases using an integrated approach to exposure assessment to define particular exposure-disease relationships and the interaction of genetic and environmental factors in disease occurrence. Improved methods for exposure assessment will result in better means of monitoring and targeting intervention and prevention programs.

Biomarkers↗

PubMed2005

Ushering in the new toxicology: toxicogenomics and the public interest.

New scientific tools spawned by the genomics revolution promise to improve our ability to identify causative factors in human diseases. But as these new tools elucidate the complex interactions between chemical toxins and biologic systems, the strain on traditional ways of understanding toxic effects grows. Despite major advances in the science and technology of these new toxicogenomics tools, scientific and political complexities threaten to delay the use of toxicogenomics to further the public interest or--worse--to advance its use initially to weaken the regulation and safety of widely used chemicals. To gain further insight into the scientific and political landscape of the new toxicology, we interviewed 27 experts from a variety of disciplines and sectors. Interviewees expressed widespread agreement that the new toxicology promises a significant increase in the amount of information available on toxic effects of chemicals. But the interviews show that the promise of the new toxicology will be realized only if technical and political obstacles can be overcome. Although scientific rigor is necessary for the new toxicology to move forward, the scientific and public-interest communities must ensure that inappropriate definitions of rigor, as well as proprietary interests, do not create unnecessary barriers to more effective public health protection.

Gene Expression↗

PubMed2006

Gene expression analysis of the hepatotoxicant methapyrilene in primary rat hepatocytes: an interlaboratory study.

Genomics technologies are used in several disciplines, including toxicology. However, these technologies are relatively new, and their applications require further investigations. When investigators apply these technologies to in vitro experiments, two major issues need to be clarified: a) can in vitro toxicity studies, in combination with genomics analyses, be used to predict the toxicity of a compound; and b) are the generated toxicogenomics data reproducible between laboratories? These questions were addressed by an interlaboratory study with laboratories of four pharmaceutical companies. We evaluated gene expression patterns from cultured rat primary hepatocytes after a 24-hr incubation with methapyrilene (MP). Extensive data analysis showed that comparison of genomics data from different sources is complex because both experimental and statistical variability are important confounding factors. However, appropriate statistical tools allowed us to use gene expression profiles to distinguish high-dose-treated cells from vehicle-treated cells. Moreover, we correctly identified MP in an independently generated in vitro database, underlining that in vitro toxicogenomics could be a predictive tool for toxicity. From a mechanistic point of view, despite the observed site-to-site variability, there was good concordance regarding the affected biologic processes. Several subsets of regulated genes were obtained by analyzing the data sets with one method or using different statistical analysis methods. The identified genes are involved in cellular processes that are associated to the exposure of primary hepatocytes to MP. Whether they are specific for MP and are cause or consequence of the toxicity requires further investigations.

Animals↗

PubMed2005

Meeting report: Structural determination of environmentally responsive proteins.

The three-dimensional structure of gene products continues to be a missing lynchpin between linear genome sequences and our understanding of the normal and abnormal function of proteins and pathways. Enhanced activity in this area is likely to lead to better understanding of how discrete changes in molecular patterns and conformation underlie functional changes in protein complexes and, with it, sensitivity of an individual to an exposure. The National Institute of Environmental Health Sciences convened a workshop of experts in structural determination and environmental health to solicit advice for future research in structural resolution relative to environmentally responsive proteins and pathways. The highest priorities recommended by the workshop were to support studies of structure, analysis, control, and design of conformational and functional states at molecular resolution for environmentally responsive molecules and complexes; promote understanding of dynamics, kinetics, and ligand responses; investigate the mechanisms and steps in posttranslational modifications, protein partnering, impact of genetic polymorphisms on structure/function, and ligand interactions; and encourage integrated experimental and computational approaches. The workshop participants also saw value in improving the throughput and purity of protein samples and macromolecular assemblies; developing optimal processes for design, production, and assembly of macromolecular complexes; encouraging studies on protein-protein and macromolecular interactions; and examining assemblies of individual proteins and their functions in pathways of interest for environmental health.

Environmental Health↗

PubMed2006

Recent applications of DNA microarray technology to toxicology and ecotoxicology.

Gene expression is a unique way of characterizing how cells and organisms adapt to changes in the external environment. The measurements of gene expression levels upon exposure to a chemical can be used both to provide information about the mechanism of action of the toxicant and to form a sort of "genetic signature" for the identification of toxic products. The development of high-quality, commercially available gene arrays has allowed this technology to become a standard tool in molecular toxicology. Several national and international initiatives have provided the proof-of-principle tests for the application of gene expression for the study of the toxicity of new and existing chemical compounds. In the last few years the field has progressed from evaluating the potential of the technology to illustrating the practical use of gene expression profiling in toxicology. The application of gene expression profiling to ecotoxicology is at an earlier stage, mainly because of the the many variables involved in analyzing the status of natural populations. Nevertheless, significant studies have been carried out on the response to environmental stressors both in model and in nonmodel organisms. It can be easily predicted that the development of stressor-specific signatures in gene expression profiling in ecotoxicology will have a major impact on the ecotoxicology field in the near future. International collaborations could play an important role in accelerating the application of genomic approaches in ecotoxicology.

Animals↗

PubMed2006

Meeting report: Validation of toxicogenomics-based test systems: ECVAM-ICCVAM/NICEATM considerations for regulatory use.

This is the report of the first workshop "Validation of Toxicogenomics-Based Test Systems" held 11-12 December 2003 in Ispra, Italy. The workshop was hosted by the European Centre for the Validation of Alternative Methods (ECVAM) and organized jointly by ECVAM, the U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM), and the National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM). The primary aim of the workshop was for participants to discuss and define principles applicable to the validation of toxicogenomics platforms as well as validation of specific toxicologic test methods that incorporate toxicogenomics technologies. The workshop was viewed as an opportunity for initiating a dialogue between technologic experts, regulators, and the principal validation bodies and for identifying those factors to which the validation process would be applicable. It was felt that to do so now, as the technology is evolving and associated challenges are identified, would be a basis for the future validation of the technology when it reaches the appropriate stage. Because of the complexity of the issue, different aspects of the validation of toxicogenomics-based test methods were covered. The three focus areas include a) biologic validation of toxicogenomics-based test methods for regulatory decision making, b) technical and bioinformatics aspects related to validation, and c) validation issues as they relate to regulatory acceptance and use of toxicogenomics-based test methods. In this report we summarize the discussions and describe in detail the recommendations for future direction and priorities.

Animal Testing Alternatives↗

PubMed2006

Global gene expression associated with hepatocarcinogenesis in adult male mice induced by in utero arsenic exposure.

Our previous work has shown that exposure to inorganic arsenic in utero produces hepatocellular carcinoma (HCC) in adult male mice. To explore further the molecular mechanisms of transplacental arsenic hepatocarcinogenesis, we conducted a second arsenic transplacental carcinogenesis study and used a genomewide microarray to profile arsenic-induced aberrant gene expression more extensively. Briefly, pregnant C3H mice were given drinking water containing 85 ppm arsenic as sodium arsenite or unaltered water from days 8 to 18 of gestation. The incidence of HCC in adult male offspring was increased 4-fold and tumor multiplicity 3-fold after transplacental arsenic exposure. Samples of normal liver and liver tumors were taken at autopsy for genomic analysis. Arsenic exposure in utero resulted in significant alterations (p < 0.001) in the expression of 2,010 genes in arsenic-exposed liver samples and in the expression of 2,540 genes in arsenic-induced HCC. Ingenuity Pathway Analysis revealed that significant alterations in gene expression occurred in a number of biological networks, and Myc plays a critical role in one of the primary networks. Real-time reverse transcriptase-polymerase chain reaction and Western blot analysis of selected genes/proteins showed > 90% concordance. Arsenic-altered gene expression included activation of oncogenes and HCC biomarkers, and increased expression of cell proliferation-related genes, stress proteins, and insulin-like growth factors and genes involved in cell-cell communications. Liver feminization was evidenced by increased expression of estrogen-linked genes and altered expression of genes that encode gender-related metabolic enzymes. These novel findings are in agreement with the biology and histology of arsenic-induced HCC, thereby indicating that multiple genetic events are associated with transplacental arsenic hepatocarcinogenesis.

Animals↗

PubMed2004

Gene interaction network suggests dioxin induces a significant linkage between aryl hydrocarbon receptor and retinoic acid receptor beta.

Gene expression arrays (gene chips) have enabled researchers to roughly quantify the level of mRNA expression for a large number of genes in a single sample. Several methods have been developed for the analysis of gene array data including clustering, outlier detection, and correlation studies. Most of these analyses are aimed at a qualitative identification of what is different between two samples and/or the relationship between two genes. We propose a quantitative, statistically sound methodology for the analysis of gene regulatory networks using gene expression data sets. The method is based on Bayesian networks for direct quantification of gene expression networks. Using the gene expression changes in HPL1A lung airway epithelial cells after exposure to 2,3,7,8-tetrachlorodibenzo-(Italic)p(/Italic)-dioxin at levels of 0.1, 1.0, and 10.0 nM for 24 hr, a gene expression network was hypothesized and analyzed. The method clearly demonstrates support for the assumed network and the hypothesis linking the usual dioxin expression changes to the retinoic acid receptor system. Simulation studies demonstrated the method works well, even for small samples.

Animals↗

PubMed2004

Valproic acid teratogenicity: a toxicogenomics approach.

Embryonic development is a highly coordinated set of processes that depend on hierarchies of signaling and gene regulatory networks, and the disruption of such networks may underlie many cases of chemically induced birth defects. The antiepileptic drug valproic acid (VPA) is a potent inducer of neural tube defects (NTDs) in human and mouse embryos. As with many other developmental toxicants however, the mechanism of VPA teratogenicity is unknown. Using microarray analysis, we compared the global gene expression responses to VPA in mouse embryos during the critical stages of teratogen action in vivo with those in cultured P19 embryocarcinoma cells in vitro. Among the identified VPA-responsive genes, some have been associated previously with NTDs or VPA effects [vinculin, metallothioneins 1 and 2 (Mt1, Mt2), keratin 1-18 (Krt1-18)], whereas others provide novel putative VPA targets, some of which are associated with processes relevant to neural tube formation and closure [transgelin 2 (Tagln2), thyroid hormone receptor interacting protein 6, galectin-1 (Lgals1), inhibitor of DNA binding 1 (Idb1), fatty acid synthase (Fasn), annexins A5 and A11 (Anxa5, Anxa11)], or with VPA effects or known molecular actions of VPA (Lgals1, Mt1, Mt2, Id1, Fasn, Anxa5, Anxa11, Krt1-18). A subset of genes with a transcriptional response to VPA that is similar in embryos and the cell model can be evaluated as potential biomarkers for VPA-induced teratogenicity that could be exploited directly in P19 cell-based in vitro assays. As several of the identified genes may be activated or repressed through a pathway of histone deacetylase (HDAC) inhibition and specificity protein 1 activation, our data support a role of HDAC as an important molecular target of VPA action in vivo.

Animals↗

PubMed2004

Discriminating different classes of toxicants by transcript profiling.

Male rats were treated with various model compounds or the appropriate vehicle controls. Most substances were either well-known hepatotoxicants or showed hepatotoxicity during preclinical testing. The aim of the present study was to determine if biological samples from rats treated with various compounds can be classified based on gene expression profiles. In addition to gene expression analysis using microarrays, a complete serum chemistry profile and liver and kidney histopathology were performed. We analyzed hepatic gene expression profiles using a supervised learning method (support vector machines; SVMs) to generate classification rules and combined this with recursive feature elimination to improve classification performance and to identify a compact subset of probe sets with potential use as biomarkers. Two different SVM algorithms were tested, and the models obtained were validated with a compound-based external cross-validation approach. Our predictive models were able to discriminate between hepatotoxic and nonhepatotoxic compounds. Furthermore, they predicted the correct class of hepatotoxicant in most cases. We provide an example showing that a predictive model built on transcript profiles from one rat strain can successfully classify profiles from another rat strain. In addition, we demonstrate that the predictive models identify nonresponders and are able to discriminate between gene changes related to pharmacology and toxicity. This work confirms the hypothesis that compound classification based on gene expression data is feasible.

Algorithms↗

PubMed2004

Assessment of prediction confidence and domain extrapolation of two structure-activity relationship models for predicting estrogen receptor binding activity.

Quantitative structure-activity relationship (QSAR) methods have been widely applied in drug discovery, lead optimization, toxicity prediction, and regulatory decisions. Despite major advances in algorithms and software, QSAR models have inherent limitations associated with a size and chemical-structure diversity of the training set, experimental error, and many characteristics of structure representation and correlation algorithms. Whereas excellent fit to the training data may be readily attainable, often models fail to predict accurately chemicals that are outside their domain of applicability. A QSAR's utility and, in the case of regulatory decisions, justification for usage increasingly depend on the ability to quantify a model's potential for predicting unknown chemicals with some known degree of certainty. It is never possible to predict an unknown chemical with absolute certainty. Here we report on two QSAR models based on different data sets for classification of chemicals according to their ability to bind to the estrogen receptor. The models were developed by using a novel QSAR method, Decision Forest, which combines the results of multiple heterogeneous but comparable Decision Tree models to produce a consensus prediction. We used an extensive cross-validation process to define an applicability domain for model predictions based on two quantitative measures: prediction confidence and domain extrapolation. Together, these measures quantify the accuracy of each prediction within and outside of the training domain. Despite being based on large and diverse training sets, both QSAR models had poor accuracy for chemicals within the domain of low confidence, whereas good accuracy was obtained for those within the domain of high confidence. For prediction in the high confidence domain, accuracy was inversely proportional to the degree of domain extrapolation. The model with a larger training set of 1,092, compared with 232 for the other, was more accurate in predicting chemicals at larger domain extrapolation, and could be particularly useful for rapidly prioritizing potential endocrine disruptors from large chemical universe.

Animals↗