The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study

Abstract

Background: The etiology of many chronic diseases involves interactions between environmental factors and genes that modulate physiological processes. Understanding interactions between environmental chemicals and genes/proteins may provide insights into the mechanisms of chemical actions, disease susceptibility, toxicity, and therapeutic drug interactions. The Comparative Toxicogenomics Database (CTD; http://ctd.mdibl.org) provides these insights by curating and integrating data describing relationships between chemicals, genes/proteins, and human diseases. To illustrate the scope and application of CTD, we present an analysis of curated data for the chemical arsenic. Arsenic represents a major global environmental health threat and is associated with many diseases. The mechanisms by which arsenic modulates these diseases are not well understood.

Methods: Curated interactions between arsenic compounds and genes were downloaded using export and batch query tools at CTD. The list of genes was analyzed for molecular interactions, Gene Ontology (GO) terms, KEGG pathway annotations, and inferred disease relationships.

Results: CTD contains curated data from the published literature describing 2,738 molecular interactions between 21 different arsenic compounds and 1,456 genes and proteins. Analysis of these genes and proteins provide insight into the biological functions and molecular networks that are affected by exposure to arsenic, including stress response, apoptosis, cell cycle, and specific protein signaling pathways. Integrating arsenic-gene data with gene-disease data yields a list of diseases that may be associated with arsenic exposure and genes that may explain this association.

Conclusion: CTD data integration and curation strategies yield insight into the actions of environmental chemicals and provide a basis for developing hypotheses about the molecular mechanisms underlying the etiology of environmental diseases. While many reports describe the molecular response to arsenic, CTD integrates these data with additional curated data sets that facilitate construction of chemical-gene-disease networks and provide the groundwork for investigating the molecular basis of arsenic-associated diseases or toxicity. The analysis reported here is extensible to any environmental chemical or therapeutic drug.

Figure 1

Venn diagram of arsenic-interacting genes. Sodium arsenite, arsenic trioxide, and sodium arsenate interact with 793, 500, and 230 genes, respectively. The 20 genes common to all three arsenic compounds are listed.

Figure 2

Arsenic-responsive interactome. Arsenic-interacting genes were evaluated for enrichment of molecular interactions. Ingenuity Pathway Analysis identified a large interaction network of 105 proteins enriched with roles in cell cycle control, apoptosis, DNA repair, and associated significantly with cancer (p < 10^-34 based on the hypergeometric distribution and calculated with the right-tailed Fisher's Exact Test; dotted and solid lines indicate indirect and direct interactions, respectively).

Figure 3

Arsenic-gene-disease predictions. CTD describes a molecular interaction between arsenic (As) and 1,456 genes; 424 of those genes are also directly associated with a disease. The integration of these two data sets predicts diseases that parallel those already known to be associated with arsenic exposure, underscoring the potential value and validity of these inferred relationships.