The Comparative Toxicogenomics Database (CTD): Predicting mechanisms of toxicity Carolyn J. Mattingly The Mount Desert Island Biological Laboratory Salisbury Cove, Maine
Chemicals in commerce > 80,000 ~2,000 added/year ~8,000 are carcinogens No toxicity data for ~40% of the 3,300 “high production volume” chemicals Full toxicity data for only 25% of chemicals in consumer products
Time, 1947
What’s the relationship between chemicals and disease? Genes/Proteins Cell Death/ Differentiation DNA Repair Cell Cycle Control Chemical Distribution/ Metabolism Disease DISEASE
Exploring environment-gene-disease connections What diseases are associated with Bisphenol A (BPA)? Which BPA-induced genes function during development? What biological functions are affected by BPA? Which molecular pathways are affected by exposure to BPA? Which other chemicals have interaction profiles similar to BPA? What are target genes that are common to BPA and arsenic?
Curated Data MeSH® (modified) CTD interactions chemical-gene Chemicals MeSH® (modified) CTD interactions chemical-gene interactions chemical-disease relationships Genes Diseases gene-disease relationships Entrez-Gene MeSH/OMIM
Prioritizing Curation EPA Superfund EPA ToxCast NTP Users/Collaborators
Curated Data chemical-gene interactions chemical-disease relationships Chemicals chemical-gene interactions chemical-disease relationships 199,453 9,524 6,143 Genes Diseases gene-disease relationships
Integrated Data chemical-gene interactions chemical-disease Chemicals chemical-gene interactions chemical-disease relationships Genes Diseases gene-disease relationships
Creating inferences chemical-gene interactions chemical-disease Chemicals chemical-gene interactions chemical-disease relationships Genes Diseases gene-disease relationships
Creating inferences chemical-gene interactions chemical-disease Chemicals chemical-gene interactions chemical-disease relationships Genes Diseases gene-disease relationships
Inferred chemical-disease relationships BPA AGR2… Prostatic Neoplasms Inferred chemical-disease relationships
Cancer and urologic diseases BPA-Prostate cancer genes Cancer and urologic diseases Generated using Ingenuity Pathway Analysis
Chemical-disease inferences ~190,000 transitive inferences between chemicals and diseases Transitive Inference If ‘A’ interacts with ‘B’ and ‘C’ interacts with ‘B’, then infer that ‘A’ interacts with ‘C’ How to assess which inferences are “good” or not? A B C
Bisphenol A and Lung Neoplasms Geometric Cvw = |N(v) N(w)|2 |N(v)| . |N(w)| 457 other genes or diseases BPA g1 g2 22 Genes g3 139 other Chemicals or genes … Lung Neoplasms g22
Geometric Cvw for “Real” C-D Inferences Geometric Cvw for shuffled C-D Inferences
Inferred chemical-pathway relationships BPA IKBKB… AML Inferred chemical-pathway relationships
Tools
Tools
Tools
Tools: VennViewer 127 1357 118 4 76 21 Interacting Genes/Proteins Folic acid Arsenicals Pathways 4 76 21 Folic acid Arsenicals
Tools
MDIBL: Effects of arsenic on immune function 64 1689 20 Array data CTD data 0 10 100
MDIBL: Effects of arsenic on immune function 64 1689 20 Array data CTD data 0 10 100 Mattingly, C. J., T. Hampton, K. Brothers, N. E. Griffin and A. J. Planchart (2009). Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos. Environ Health Perspect doi:10.1289/ehp.0900555.
NIEHS: Identifying chemical-gene-disease networks Gohlke, J., R. Thomas, Y. Zhang, M. D. Rosenstein, A. P. Davis, C. Murphy, C. J. Mattingly, K. G. Becker and C. J. Portier (2009). The Genetic And Environmental Pathways to Complex Diseases. BMC Syst Biol.May 5 3:46.
EPA: Exploring the environmental etiology of autistic disorders Characterizing these chemicals Structure Regulatory features (e.g., High production, Carcinogen) Function (e.g., Associated pathways) Other associated diseases (e.g., Neurological) 2096 Chemicals 213 Genes 213 Genes Autism Mark Coralles, EPA
In Progress Tag Clouds Text mining Statistical analysis of data inferences Gene Ontology enrichment analysis
Coming Up Analysis tools and visualization capabilities Integration of additional data sets (SNPs, Chemical codes) Exposure data curation
Curating exposure data Develop exposure ontology Define scope of data to be curated Test curation protocol Curate and integrate data in CTD Exposure data Diseases Genes Chemicals chemical-disease relationships chemical-gene interactions gene-disease
Acknowledgements Allan Peter Davis, PhD Cindy Murphy, PhD Scientific Curators Allan Peter Davis, PhD Cindy Murphy, PhD Cynthia Saraceni-Richards, PhD Susan Mockus, PhD Scientific Software Engineers Michael C Rosenstein, JD Thomas Wiegers System Administrator Roy McMorran James L. Boyer, MD (Yale) http://ctd.mdibl.org/ Zebrafish work Antonio Planchart, PhD Thomas Hampton (Dartmouth) Funding NIEHS AND NLM (ES014065) NCRR (RR016463) Contact Us! cmattin@mdibl.org ctd@mdibl.org