Predicting environmental chemical factors associated with disease-related gene expression data

Extracellular Vesicles in Environmental Toxicological Studies: Association between Urinary Concentrations of Phthalate Metabolites and Exosomal miRNA Expression Profiles

Phthalates are chemical compounds, mainly used as additives in plastics, which are known to induce harmful impacts to the environment and human health due to their ability to act as hormone-mimics. Few studies have been reported on the relationship between human exposure to phthalates and the level of circulating microRNAs (miRs), especially those miRs encapsulated in extracellular vesicles/exosomes or exosome-like vesicles (ELVs). We examined the relationship of ELV-miR expression patterns and urine of adult men with five phthalate metabolites (i.e., mono isobutyl phthalate, mono-n-butyl phthalate, mono benzyl phthalate, mono-(2-ethyl-5-oxohexyl) phthalate, mono-(2-ethylhexyl) phthalate) to identify potential biomarkers and relevant pathways. We found significant positive associations which were further confirmed by multivariable analysis. Overall, our analyses showed that the Σ phthalate metabolite concentration was associated with a significant increase in the expression level of two miRs found in ELV: miR-202 and miR-543. Different pathways including cancer and immune-related responses were predicted to be involved in this relationship. Analyzing the specific downstream target genes of miR-202 and miR-543, we identified the phosphatase and tensin homolog (PTEN) as the key gene in several converging pathways. In summary, the obtained results demonstrate that exposure to environmental phthalates could be related to altered expression profiles of specific ELV-miRs in adult men, thereby demonstrating the potential of miRs carried by exosomes to act as early effect biomarkers.

Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases

Traditional methods for chemical risk assessment are too time-consuming and resource-intensive to characterize either the diversity of chemicals to which humans are exposed or how that diversity may manifest in population susceptibility differences. The advent of novel toxicological data sources and their integration with bioinformatic databases affords opportunities for modern approaches that consider gene-environment (GxE) interactions in population risk assessment. Here, we present an approach that systematically links multiple data sources to relate chemical risk values to diseases and gene-disease variants. These data sources include high-throughput screening (HTS) results from Tox21/ToxCast, chemical-disease relationships from the Comparative Toxicogenomics Database (CTD), hazard data from resources like the Integrated Risk Information System, exposure data from the ExpoCast initiative, and gene-variant-disease information from the DisGeNET database. We use these integrated data to identify variants implicated in chemical-disease enrichments and develop a new value that estimates the risk of these associations toward differential population responses. Finally, we use this value to prioritize chemical-disease associations by exploring the genomic distribution of variants implicated in high-risk diseases. We offer this modular approach, termed DisQGOS (Disease Quotient Genetic Overview Score), for relating overall chemical-disease risk to potential for population variable responses, as a complement to methods aiming to modernize aspects of risk assessment.

Epigenetics as a mechanism linking developmental exposures to long-term toxicity

A variety of experimental and epidemiological studies lend support to the Developmental Origin of Health and Disease (DOHaD) concept. Yet, the actual mechanisms accounting for mid- and long-term effects of early-life exposures remain unclear. Epigenetic alterations such as changes in DNA methylation, histone modifications and the expression of certain RNAs have been suggested as possible mediators of long-term health effects of environmental stressors. This report captures discussions and conclusions debated during the last Prenatal Programming and Toxicity meeting held in Japan. Its first aim is to propose a number of criteria that are critical to support the primary contribution of epigenetics in DOHaD and intergenerational transmission of environmental stressors effects. The main criteria are the full characterization of the stressors, the actual window of exposure, the target tissue and function, the specificity of the epigenetic changes and the biological plausibility of the linkage between those changes and health outcomes. The second aim is to discuss long-term effects of a number of stressors such as smoking, air pollution and endocrine disruptors in order to identify the arguments supporting the involvement of an epigenetic mechanism. Based on the developed criteria, missing evidence and suggestions for future research will be identified. The third aim is to critically analyze the evidence supporting the involvement of epigenetic mechanisms in intergenerational and transgenerational effects of environmental exposure and to particularly discuss the role of placenta and sperm. While the article is not a systematic review and is not meant to be exhaustive, it critically assesses the contribution of epigenetics in the long-term effects of environmental exposures as well as provides insight for future research.

BCScreen: A gene panel to test for breast carcinogenesis in chemical safety screening

Targeted gene lists have been used in clinical settings to specify breast tumor type, and to predict breast cancer prognosis and response to treatment. Separately, panels have been curated to predict systemic toxicity and xenoestrogen activity as a part of chemical screening strategies. However, currently available panels do not specifically target biological processes relevant to breast development and carcinogenesis. We have developed a gene panel called the Breast Carcinogen Screen (BCScreen) as a tool to identify potential breast carcinogens and characterize mechanisms of toxicity. First, we used four seminal reviews to identify 14 key characteristics of breast carcinogenesis, such as apoptosis, immunomodulation, and genotoxicity. Then, using a hybrid data and knowledge-driven framework, we systematically combined information from whole transcriptome data from genomic databases, biomedical literature, the CTD chemical-gene interaction database, and primary literature review to generate a panel of 500 genes relevant to breast carcinogenesis. We used normalized pointwise mutual information (NPMI) to rank genes that frequently co-occurred with key characteristics in biomedical literature. We found that many genes identified for BCScreen were not included in prognostic breast cancer or systemic toxicity panels. For example, more than half of BCScreen genes were not included in the Tox21 S1500+ general toxicity gene list. Of the 230 that did overlap between the two panels, representation varied across characteristics of carcinogenesis ranging from 21% for genes associated with epigenetics to 82% for genes associated with xenobiotic metabolism. Enrichment analysis of BCScreen identified pathways and processes including response to steroid hormones, cancer, cell cycle, apoptosis, DNA damage and breast cancer. The biologically-based systematic approach to gene prioritization demonstrated here provides a flexible framework for creating disease-focused gene panels to support discovery related to etiology. With validation, BCScreen may also be useful for toxicological screening relevant to breast carcinogenesis.

The role of cognitive activity in cognition protection: from Bedside to Bench

BACKGROUND

Cognitive decline poses a great concern to elderly people and their families. In addition to pharmacological therapies, several varieties of nonpharmacological intervention have been developed. Most training trials proved that a well-organized task is clinically effective in cognition improvement.

MAIN BODY

We will first review clinical trials of cognitive training for healthy elders, MCI and AD patients, respectively. Besides, potential neuroprotective and compensatory mechanisms in animal models of AD are discussed. Despite controversy, cognitive training has promising effect on cognitive ability. In animal model of AD, environmental enrichment showed beneficial effect for cognitive ability, as well as neuronal plasticity. Neurotrophin, neurotransmitter and neuromodulator signaling pathway were also involved in the process. Well-designed cognitive activity could benefit cognitive function, and thus life quality of patients and their families.

CONCLUSION

The positive effects of cognitive activity is closely related with neural plasticity, neurotrophin, neurotransmitter and neuromodulator signaling pathway changes.

Changes in mammary histology and transcriptome profiles by low-dose exposure to environmental phenols at critical windows of development

Exposure to environmental chemicals has been linked to altered mammary development and cancer risk at high doses using animal models. Effects at low doses comparable to human exposure remain poorly understood, especially during critical developmental windows. We investigated the effects of two environmental phenols commonly used in personal care products - methyl paraben (MPB) and triclosan (TCS) - on the histology and transcriptome of normal mammary glands at low doses mimicking human exposure during critical windows of development. Sprague-Dawley rats were exposed during perinatal, prepubertal and pubertal windows, as well as from birth to lactation. Low-dose exposure to MPB and TCS induced measurable changes in both mammary histology (by Masson's Trichrome Stain) and transcriptome (by microarrays) in a window-specific fashion. Puberty represented a window of heightened sensitivity to MPB, with increased glandular tissue and changes of expression in 295 genes with significant enrichment in functions such as DNA replication and cell cycle regulation. Long-term exposure to TCS from birth to lactation was associated with increased adipose and reduced glandular and secretory tissue, with expression alterations in 993 genes enriched in pathways such as cholesterol synthesis and adipogenesis. Finally, enrichment analyses revealed that genes modified by MPB and TCS were over-represented in human breast cancer gene signatures, suggesting possible links with breast carcinogenesis. These findings highlight the issues of critical windows of susceptibility that may confer heightened sensitivity to environmental insults and implicate the potential health effects of these ubiquitous environmental chemicals in breast cancer.

Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking

The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis, we found that the combination of smoking-modified, genome-wide gene (including miRNA) expression and DNA methylation profiles predicts with remarkable reliability most diseases and conditions independently known to be causally associated with smoking (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively). Bioinformatics analysis reveals the importance of a small number of smoking-modified, master-regulatory genes and suggest a central role for altered ubiquitination. The smoking-induced gene expression profiles overlap significantly with profiles present in blood cells of patients with lung cancer or coronary heart disease, diseases strongly associated with tobacco smoking. These results provide proof-of-principle support to the suggestion that omic profiling in peripheral blood has the potential of identifying early, disease-related perturbations caused by toxic exposures and may be a useful tool in hazard and risk assessment.

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles

A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

The transcriptional profile of an organism contains clues about the environmental context in which it has evolved and currently lives, its behavior and cellular state. It is yet unclear, however, how much information can be efficiently extracted and how it can be used to classify new samples with respect to their environmental and genetic characteristics. Here, we have constructed an extensive transcriptome compendium of Escherichia coli that we have further enriched via an iterative learning approach. We then apply an ensemble of various machine learning algorithms to infer environmental and cellular information such as strain, growth phase, medium, oxygen level, antibiotic and carbon source. Functional analysis of the most informative genes provides mechanistic insights and palpable hypotheses regarding their role in each environmental or genetic context. Our work argues that genome-scale gene expression can be a multi-purpose marker for identifying latent, heterogeneous cellular and environmental states and that optimal classification can be achieved with a feature set of a couple hundred genes that might not necessarily have the most pronounced differential expression in the respective conditions.

The microRNAs as potential biomarkers for predicting the onset of aflatoxin exposure in human beings: a review

The identification of aflatoxins as human carcinogens has stimulated extensive research efforts, which continue to the present, to assess potential health hazards resulting from contamination of the human food supply and to minimize exposure. The use of biomarkers that are mechanistically supported by toxicological studies will be important tools for identifying stages in the progression of development of the health effects of environmental agents. miRNAs are small non-coding mRNAs that regulate post-transcriptional gene expression. Also, they are molecular markers of cellular responses to various chemical agents. Growing evidence has demonstrated that environmental chemicals can induce changes in miRNA expression. miRNAs are good biomarkers because they are well defined, chemically uniform, restricted to a manageable number of species, and stable in cells and in the circulation. miRNAs have been used as serological markers of HCC and other tumors. The expression patterns of different miRNAs can distinguish among HCC-hepatitis viruses related, HCC cirrhosis-derivate, and HCC unrelated to either of them. The main objective of this review is to find unreported miRNAs in HCC related to other causes, so that they can be used as specific molecular biomarkers in populations exposed to aflatoxins and as early markers of exposure, damage/presence of HCC. Until today specific miRNAs as markers for aflatoxins-exposure and their reliability are currently lacking. Based on their elucidated mechanisms of action, potential miRNAs that could serve as possible markers of HCC by exposure to aflatoxins are miR-27a, miR-27b, miR-122, miR-148, miR-155, miR-192, miR-214, miR-221, miR-429, and miR-500. Future validation for all of these miRNAs will be needed to assess their prognostic significance and confirm their relationship with the induction of HCC due to aflatoxin exposure.

Development of a stable cell line with an intact PGC-1α/ERRα axis for screening environmental chemicals

The estrogen-related receptor α (ERRα) and the peroxisome proliferator-activated receptor γ (PPARγ) coactivator 1α (PGC-1α) play critical roles in the control of several physiological functions, including the regulation of genes involved in energy homeostasis. However, little is known about the ability of environmental chemicals to disrupt or modulate this important bioenergetics pathway in humans. The goal of this study was to develop a cell-based assay system with an intact PGC-1α/ERRα axis that could be used as a screening assay for detecting such chemicals. To this end, we successfully generated several stable cell lines expressing PGC-1α and showed that the reporter driven by the native ERRα hormone response unit (AAB-Luc) is active in these cell lines and that the activation is PGC-1α-dependent. Furthermore, we show that this activation can be blocked by the ERRα selective inverse agonist, XCT790. In addition, we find that genistein and bisphenol A further stimulate the reporter activity, while kaempferol has minimal effect. These cell lines will be useful for identifying environmental chemicals that modulate this important pathway.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

Background

Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles.

Methods

We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals.

Results

Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals.

Conclusions

Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect.

Annual fasting; the early calories restriction for cancer prevention

Essentially, people's diet and nutritional status has been changed substantially worldwide and several lines of evidence suggest that these changes are to the detriment of their health. Additionally, it has been well documented that unhealthy diet especially the fast foods, untraditional foods or bad-eating-habits influence the human gut microbiome. The gut microbiota shapes immune responses during human life and affects his/her metabolomic profiles. Furthermore, many studies highlight the molecular pathways that mediate host and symbiont interactions that regulate proper immune function and prevention of cancer in the body. Intriguingly, if cancer forms in a human body due to the weakness of immune system in detriment of microbiome, the removal of cancer stem cells can be carried out through early Calories Restriction with Annual Fasting (AF) before tumor development or progress. Besides, fasting can balance the gut microbiome for enhancement of immune system against cancer formation.

Genetic variability in molecular responses to chemical exposure

Individuals differ in their response to environmental exposures. In the following, we describe examples and paradigms of studying heritable differences in response to exposure-commonly known as "gene-environment interaction" or "ecogenetics"-and their relation to disease etiology and susceptibility. Our discussion is framed in three parts. In the first, we describe replicated examples of studies that have typified the field, single genetic variant, and exposure associations to disease. Second, we describe how studies have scaled up search for interaction using genome-wide measurement modalities, bioinformatics, and model organisms. Finally, we discuss a more comprehensive representation of chemical exposures as the "envirome" and how we may use the envirome to examine interplay between genetics and the environment.

Preferential regulation of miRNA targets by environmental chemicals in the human genome

Background

microRNAs (miRNAs) represent a class of small (typically 22 nucleotides in length) non-coding RNAs that can degrade their target mRNAs or block their translation. Recent disease research showed the exposure to some environmental chemicals (ECs) can regulate the expression patterns of miRNAs, which raises the intriguing question of how miRNAs and their targets cope with the exposure to ECs throughout the genome.

Results

In this study, we comprehensively analyzed the properties of genes regulated by ECs (EC-genes) and found miRNA targets were significantly enriched among the EC-genes. Compared with the non-miRNA-targets, miRNA targets were roughly twice as likely to be EC-genes. By investigating the collection methods and other properties of the EC-genes, we demonstrated that the enrichment of miRNA targets was not attributed to either the potential collection bias of EC-genes, the presence of paralogs, longer 3'UTRs or more conserved 3'UTRs. Finally, we identified 1,842 significant concurrent interactions between 407 miRNAs and 497 ECs. This association network of miRNAs-ECs was highly modular and could be separated into 14 interconnected modules. In each module, miRNAs and ECs were closely connected, providing a good method to design accurate miRNA markers for ECs in toxicology research.

Conclusions

Our analyses indicated that miRNAs and their targets played important roles in cellular responses to ECs. Association analyses of miRNAs and ECs will help to broaden the understanding of the pathogenesis of such chemical components.

Environmental chemicals and microRNAs

MicroRNAs (miRNAs) are short single-stranded non-coding molecules that function as negative regulators to silence or suppress gene expression. Aberrant miRNA expression has been implicated in a several cellular processes and pathogenic pathways of a number of diseases. Evidence is rapidly growing that miRNA regulation of gene expression may be affected by environmental chemicals. These environmental exposures include those that have frequently been associated with chronic diseases, such as heavy metals, air pollution, bisphenol A, and cigarette smoking. In this article, we review the published data on miRNAs in relation to the exposure to several environmental chemicals, and discuss the potential mechanisms that may link environmental chemicals to miRNA alterations. We further discuss the challenges in environmental-miRNA research and possible future directions. The accumulating evidence linking miRNAs to environmental chemicals, coupled with the unique regulatory role of miRNAs in gene expression, makes miRNAs potential biomarkers for better understanding the mechanisms of environmental diseases.

NCBI GEO: archive for functional genomics data sets--10 years on

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

The Comparative Toxicogenomics Database: update 2011

The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the interaction of environmental chemicals with gene products, and their effects on human health. Biocurators at CTD manually curate a triad of chemical–gene, chemical–disease and gene–disease relationships from the literature. These core data are then integrated to construct chemical–gene–disease networks and to predict many novel relationships using different types of associated data. Since 2009, we dramatically increased the content of CTD to 1.4 million chemical–gene–disease data points and added many features, statistical analyses and analytical tools, including GeneComps and ChemComps (to find comparable genes and chemicals that share toxicogenomic profiles), enriched Gene Ontology terms associated with chemicals, statistically ranked chemical–disease inferences, Venn diagram tools to discover overlapping and unique attributes of any set of chemicals, genes or disease, and enhanced gene pathway data content, among other features. Together, this wealth of expanded chemical–gene–disease data continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases. CTD is freely available at http://ctd.mdibl.org.