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. 2017 Jan 4;45(D1):D972-D978.
doi: 10.1093/nar/gkw838. Epub 2016 Sep 19.

The Comparative Toxicogenomics Database: update 2017

Allan Peter Davis  1 , Cynthia J Grondin  2 , Robin J Johnson  2 , Daniela Sciaky  2 , Benjamin L King  3 , Roy McMorran  3 , Jolene Wiegers  2 , Thomas C Wiegers  2 , Carolyn J Mattingly  2   4
Affiliations

The Comparative Toxicogenomics Database: update 2017

Allan Peter Davis et al. Nucleic Acids Res. .

Abstract

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) provides information about interactions between chemicals and gene products, and their relationships to diseases. Core CTD content (chemical-gene, chemical-disease and gene-disease interactions manually curated from the literature) are integrated with each other as well as with select external datasets to generate expanded networks and predict novel associations. Today, core CTD includes more than 30.5 million toxicogenomic connections relating chemicals/drugs, genes/proteins, diseases, taxa, Gene Ontology (GO) annotations, pathways, and gene interaction modules. In this update, we report a 33% increase in our core data content since 2015, describe our new exposure module (that harmonizes exposure science information with core toxicogenomic data) and introduce a novel dataset of GO-disease inferences (that identify common molecular underpinnings for seemingly unrelated pathologies). These advancements centralize and contextualize real-world chemical exposures with molecular pathways to help scientists generate testable hypotheses in an effort to understand the etiology and mechanisms underlying environmentally influenced diseases.

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Figures

Figure 1.
Figure 1.
Integration of exposure data curation into CTD framework. Core CTD is composed of interactions between chemicals, genes, diseases, Gene Ontology (GO) terms and pathway annotations (colored circles in top diagram). In March 2015, CTD released an exposure science module (light orange circle in top diagram). For this paradigm, CTD manually curates exposure statements (bottom light blue box, with light orange categories connected by black lines) describing how environmental stressors interact with human receptors during an exposure event to result in an exposure outcome. This curation paradigm uses many of the same controlled vocabularies as those used in core CTD to allow seamless data integration and connectivity between the two projects: exposure stressors are chemicals (blue arrow); exposure events report biomarker measurements for chemicals (blue arrow) and proteins (green arrow); and exposure outcomes can be either altered phenotypes (defined as GO terms, gray arrow) or diseases (red arrow).
Figure 2.
Figure 2.
CTD's new exposure curation content. (A) CTD's new ‘Exposure Studies’ query page (http://ctdbase.org/query.go?type=expStudies) allows users to retrieve study information using a variety of search parameters, including exposure chemical stressor (e.g. air pollutants, blue circle), receptor description (e.g. study subjects) and countries (e.g. the USA) as the study location (blue arrows). (B) The results display curated exposure studies meeting the query parameters (highlighted in yellow) with integrated links to any mentioned genes, chemicals, diseases, phenotypes (GO-BP terms) and source references (blue dotted boxes with orange callout labels). The ‘Author's Summary’ column provides the take-home point of each study, and the ‘Details’ link in the ‘Measurements’ column takes the user to the specific assay measurements. As well, all exposure content is reciprocally displayed on the aforementioned pages (i.e. gene, chemical, disease, phenotype and source references), making the information seamlessly integrated into the broader biological context of the CTD framework. (C) Data status for CTD exposure module as of July 2016 includes over 70 600 manually curated statements from more than 1250 references (updated monthly at: http://ctdbase.org/about/dataStatus.go).
Figure 3.
Figure 3.
Landscape view of real-world measurements and outcomes curated for exposure science. The ‘Exposure Details’ data-tab (red arrow) on CTD's chemical page for air pollutants lists 2591 results (red circle) for air pollution markers (e.g. particulate matter, sulfates and carbon), including the type of medium in which the marker was assayed, the units of measurements, the statistics associated with the measurement (blue box), as well as any disease/phenotype outcomes. This view aggregates the data from all germane articles for the chemical-of-interest. Column headers in the table will sort the information by clicking (blue arrow) and embedded terms are hyperlinked to their respective CTD pages (green arrow and green inset box), allowing users to easily navigate to other concepts. At the bottom of every CTD page, a link allows users to download the information onto a desktop in a variety of formats.
Figure 4.
Figure 4.
CTD's new dataset generates novel inferences between GO terms and diseases. (A) Every GO term has its own page in CTD, and GO terms can be inferred to diseases based upon shared genes. Data integration via shared genes (here, genes IL4 and TNF, green box) allows the GO biological process (GO-BP) term ‘positive regulation of mononuclear cell migration’ (orange oval) to be inferred to the disease cardiomyopathies (red circle). (B) An example of how users can leverage this information. Two diseases (cardiomyopathies and contact dermatitis) initially appear to be unrelated because they share no genes; however, when instead viewed using inferred GO-BP terms, the two diseases overlap significantly with 583 inferred GO-BP terms (P = 4.72 × 10-201, Fisher's exact test), suggesting potential molecular underpinnings common between the two pathologies. This discovery can have implications for recognizing co-morbidities (especially for exposure science), identifying avenues to reposition therapeutic drugs or creating alerts to potentially new side effects. CTD's files for ‘GO-Disease-Gene Inference Networks’ (as well as all CTD curated content) are freely available from our ‘Data Downloads’ page (http://ctdbase.org/downloads/).
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References

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    1. Davis A.P., Grondin C.G., Lennon-Hopkins K., Saraceni-Richards C., Sciaky D., King B.L., Wiegers T.C., Mattingly C.J. The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. Nucleic Acids Res. 2015;43:D914–D920. - PMC - PubMed
    1. Davis A.P., Wiegers T.C., Rosenstein M.C., Murphy C.G., Mattingly C.J. The curation paradigm and application tool used for manual curation of the scientific literature at the Comparative Toxicogenomics Database. Database. 2011 doi:10.1093/database/bar034. - PMC - PubMed

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