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.

Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database—MirGeneDB ( http://mirgenedb.org )—to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.

Glaucoma is one of the most common neurodegenerative diseases. Despite this, the earliest stages of this complex disease are still unclear. This study was specifically designed to identify early stages of glaucoma in DBA/2J mice. To do this, we used genome-wide expression profiling of optic nerve head and retina and a series of computational methods. Eyes with no detectable glaucoma by conventional assays were grouped into molecularly defined stages of disease using unbiased hierarchical clustering. These stages represent a temporally ordered sequence of glaucoma states. We then determined networks and biological processes that were altered at these early stages. Early-stage expression changes included upregulation of both the complement cascade and the endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in complement component 1a (C1qa) were protected from glaucoma. Similarly, inhibition of the endothelin system with bosentan, an endothelin receptor antagonist, was strongly protective against glaucomatous damage. Since endothelin 2 is potently vasoconstrictive and was produced by microglia/macrophages, our data provide what we believe to be a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early molecular events, such as complement and endothelin induction, may provide effective new treatments for human glaucoma.

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.