Dataset Information

The Comparative Toxicogenomics Database: update 2013.

ABSTRACT: The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) provides information about interactions between environmental chemicals and gene products and their relationships to diseases. Chemical-gene, chemical-disease and gene-disease interactions manually curated from the literature are integrated to generate expanded networks and predict many novel associations between different data types. CTD now contains over 15 million toxicogenomic relationships. To navigate this sea of data, we added several new features, including DiseaseComps (which finds comparable diseases that share toxicogenomic profiles), statistical scoring for inferred gene-disease and pathway-chemical relationships, filtering options for several tools to refine user analysis and our new Gene Set Enricher (which provides biological annotations that are enriched for gene sets). To improve data visualization, we added a Cytoscape Web view to our ChemComps feature, included color-coded interactions and created a 'slim list' for our MEDIC disease vocabulary (allowing diseases to be grouped for meta-analysis, visualization and better data management). CTD continues to promote interoperability with external databases by providing content and cross-links to their sites. Together, this wealth of expanded chemical-gene-disease data, combined with novel ways to analyze and view content, continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases.

SUBMITTER: Davis AP

PROVIDER: S-EPMC3531134 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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The Comparative Toxicogenomics Database: update 2013.

Davis Allan Peter AP Murphy Cynthia Grondin CG Johnson Robin R Lay Jean M JM Lennon-Hopkins Kelley K Saraceni-Richards Cynthia C Sciaky Daniela D King Benjamin L BL Rosenstein Michael C MC Wiegers Thomas C TC Mattingly Carolyn J CJ

Nucleic acids research 20121023 Database issue

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) provides information about interactions between environmental chemicals and gene products and their relationships to diseases. Chemical-gene, chemical-disease and gene-disease interactions manually curated from the literature are integrated to generate expanded networks and predict many novel associations between different data types. CTD now contains over 15 million toxicogenomic relationships. To navigate this sea of data, we a ...[more]

PMID: 23093600

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Project description:Exposure to chemicals in the environment is believed to play a critical role in the etiology of many human diseases. To enhance understanding about environmental effects on human health, the Comparative Toxicogenomics Database (CTD; http://ctdbase.org) provides unique curated data that enable development of novel hypotheses about the relationships between chemicals and diseases. CTD biocurators read the literature and curate direct relationships between chemicals-genes, genes-diseases, and chemicals-diseases. These direct relationships are then computationally integrated to create additional inferred relationships; for example, a direct chemical-gene statement can be combined with a direct gene-disease statement to generate a chemical-disease inference (inferred via the shared gene). In CTD, the number of inferences has increased exponentially as the number of direct chemical, gene and disease interactions has grown. To help users navigate and prioritize these inferences for hypothesis development, we implemented a statistic to score and rank them based on the topology of the local network consisting of the chemical, disease and each of the genes used to make an inference. In this network, chemicals, diseases and genes are nodes connected by edges representing the curated interactions. Like other biological networks, node connectivity is an important consideration when evaluating the CTD network, as the connectivity of nodes follows the power-law distribution. Topological methods reduce the influence of highly connected nodes that are present in biological networks. We evaluated published methods that used local network topology to determine the reliability of protein-protein interactions derived from high-throughput assays. We developed a new metric that combines and weights two of these methods and uniquely takes into account the number of common neighbors and the connectivity of each entity involved. We present several CTD inferences as case studies to demonstrate the value of this metric and the biological relevance of the inferences.

Project description:BackgroundExposure science studies the interactions and outcomes between environmental stressors and human or ecological receptors. To augment its role in understanding human health and the exposome, we aimed to centralize and integrate exposure science data into the broader biological framework of the Comparative Toxicogenomics Database (CTD), a public resource that promotes understanding of environmental chemicals and their effects on human health.ObjectivesWe integrated exposure data within the CTD to provide a centralized, freely available resource that facilitates identification of connections between real-world exposures, chemicals, genes/proteins, diseases, biological processes, and molecular pathways.MethodsWe developed a manual curation paradigm that captures exposure data from the scientific literature using controlled vocabularies and free text within the context of four primary exposure concepts: stressor, receptor, exposure event, and exposure outcome. Using data from the Agricultural Health Study, we have illustrated the benefits of both centralization and integration of exposure information with CTD core data.ResultsWe have described our curation process, demonstrated how exposure data can be accessed and analyzed in the CTD, and shown how this integration provides a broad biological context for exposure data to promote mechanistic understanding of environmental influences on human health.ConclusionsCuration and integration of exposure data within the CTD provides researchers with new opportunities to correlate exposures with human health outcomes, to identify underlying potential molecular mechanisms, and to improve understanding about the exposome.CitationGrondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ. 2016. Advancing exposure science through chemical data curation and integration in the Comparative Toxicogenomics Database. Environ Health Perspect 124:1592-1599; http://dx.doi.org/10.1289/EHP174.

Project description:BackgroundMiscarriage is a prevalent public health issue and many events occur before women are aware of their pregnancy, complicating research design. Thus, risk factors for miscarriage are critically understudied. Our goal was to identify environmental chemicals with a high number of interactions with miscarriage genes, based on known toxicogenomic responses.MethodsWe used miscarriage (MeSH: D000022) and chemical gene lists from the Comparative Toxicogenomics Database in human, mouse, and rat. We assessed enrichment for gene ontology biological processes among the miscarriage genes. We prioritized chemicals (n = 25) found at Superfund sites or in the blood or urine pregnant women. For chemical-disease gene sets of sufficient size (n = 13 chemicals, n = 20 comparisons), chi-squared enrichment tests and proportional reporting ratios (PRR) were calculated. We cross-validated enrichment results.ResultsMiscarriage was annotated with 121 genes and overrepresented in inflammatory response (q = 0.001), collagen metabolic process (q = 1 × 10-13), cell death (q = 0.02), and vasculature development (q = 0.005) pathways. The number of unique genes annotated to a chemical ranged from 2 (bromacil) to 5607 (atrazine). In humans, all chemicals tested were highly enriched for miscarriage gene overlap (all p < 0.001; parathion PRR = 7, cadmium PRR = 6.5, lead PRR = 3.9, arsenic PRR = 3.5, atrazine PRR = 2.8). In mice, highest enrichment (p < 0.001) was observed for naphthalene (PRR = 16.1), cadmium (PRR = 12.8), arsenic (PRR = 11.6), and carbon tetrachloride (PRR = 7.7). In rats, we observed highest enrichment (p < 0.001) for cadmium (PRR = 8.7), carbon tetrachloride (PRR = 8.3), and dieldrin (PRR = 5.3). Our findings were robust to 1000 permutations each of variable gene set sizes.ConclusionWe observed chemical gene sets (parathion, cadmium, naphthalene, carbon tetrachloride, arsenic, lead, dieldrin, and atrazine) were highly enriched for miscarriage genes. Exposures to chemicals linked to miscarriage, and thus linked to decreased probability of live birth, may limit the inclusion of fetuses susceptible to adverse birth outcomes in epidemiology studies. Our findings have critical public health implications for successful pregnancies and the interpretation of adverse impacts of environmental chemical exposures on pregnancy.

Project description:The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the effects of environmental chemicals on human health. CTD biocurators read the scientific literature and manually curate a triad of chemical-gene, chemical-disease and gene-disease interactions. Typically, articles for CTD are selected using a chemical-centric approach by querying PubMed to retrieve a corpus containing the chemical of interest. Although this technique ensures adequate coverage of knowledge about the chemical (i.e. data completeness), it does not necessarily reflect the most current state of all toxicological research in the community at large (i.e. data currency). Keeping databases current with the most recent scientific results, as well as providing a rich historical background from legacy articles, is a challenging process. To address this issue of data currency, CTD designed and tested a journal-centric approach of curation to complement our chemical-centric method. We first identified priority journals based on defined criteria. Next, over 7 weeks, three biocurators reviewed 2425 articles from three consecutive years (2009-2011) of three targeted journals. From this corpus, 1252 articles contained relevant data for CTD and 52 752 interactions were manually curated. Here, we describe our journal selection process, two methods of document delivery for the biocurators and the analysis of the resulting curation metrics, including data currency, and both intra-journal and inter-journal comparisons of research topics. Based on our results, we expect that curation by select journals can (i) be easily incorporated into the curation pipeline to complement our chemical-centric approach; (ii) build content more evenly for chemicals, genes and diseases in CTD (rather than biasing data by chemicals-of-interest); (iii) reflect developing areas in environmental health and (iv) improve overall data currency for chemicals, genes and diseases. Database URL: http://ctdbase.org/

Project description:Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers in finding commonalities in disease mechanisms, which in turn could help identify new therapeutics, new indications for existing pharmaceuticals, potential disease comorbidities, and alerts for side effects.

Dataset Information

The Comparative Toxicogenomics Database: update 2013.

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The Comparative Toxicogenomics Database: update 2013.

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