Our objective is to provide a centralized, publicly available resource with comprehensive, well-annotated data and analysis tools that informs design and interpretation of environmental health studies and promotes novel insights into the etiologies of environmentally influenced diseases. Most human diseases involve interactions between genetic and environmental factors; however, the basis of these complex interactions are not well understood and limit improvements in toxicity prediction, risk assessment, research prioritization and therapeutic interventions. We developed the Comparative Toxicogenomics Database (CTD; http://ctdbase.org) to enhance understanding about environment-disease connections by providing manually curated data describing chemical-gene interactions and chemical- and gene-disease relationships from the peer-reviewed literature and integrating these data with select external data sets (e.g., pathways and biological process data) and novel data analysis tools. We propose to develop and implement a new module of manually curated data describing cross-species chemical-phenotype information and analytical capabilities that will incorporate these data into the broader biological context of CTD. These additions will significantly increase the impact of CTD and specifically aim to advance: a) understanding of environmental disease progression via pre-disease phenotypes, b) identification of potential biomarkers of exposure, c) the capacity to conduct and interpret studies across species and experimental systems, and d) development of biological networks that associate chemicals, genes, phenotypes, and diseases. This project will leverage our interdisciplinary team's expertise in toxicology, software development, curation, bioinformatics and statistics, as well as the flexible infrastructure and demonstrated value of CTD to facilitate understanding of critical environmental health issues in direct alignment with emerging research priorities.

Public Health Relevance

Despite the thousands of chemicals used in commerce, our understanding of their effects on human health is not well understood. The Comparative Toxicogenomics Database (CTD) is a unique, publicly available resource that provides information about chemical-gene-disease relationships (or networks). This project will introduce curated chemical-phenotype data and new analysis tools with the goal of providing additional insights into how chemical exposures influence human diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES023788-04
Application #
9405002
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Balshaw, David M
Project Start
2015-01-01
Project End
2019-12-31
Budget Start
2018-01-01
Budget End
2018-12-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
North Carolina State University Raleigh
Department
Biochemistry
Type
Earth Sciences/Resources
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695
Davis, Allan Peter; Grondin, Cynthia J; Johnson, Robin J et al. (2017) The Comparative Toxicogenomics Database: update 2017. Nucleic Acids Res 45:D972-D978
Zhang, Guozhu; Roell, Kyle R; Truong, Lisa et al. (2017) A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades. Toxicol Appl Pharmacol 314:109-117
Davis, Allan Peter; Wiegers, Thomas C; King, Benjamin L et al. (2016) Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database. PLoS One 11:e0155530
Mattingly, Carolyn J; Boyles, Rebecca; Lawler, Cindy P et al. (2016) Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences. Environ Health Perspect 124:1136-40
Reif, David M; Truong, Lisa; Mandrell, David et al. (2016) High-throughput characterization of chemical-associated embryonic behavioral changes predicts teratogenic outcomes. Arch Toxicol 90:1459-70
Zhang, Guozhu; Marvel, Skylar; Truong, Lisa et al. (2016) Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure. Reprod Toxicol 62:92-9
Davis, Allan Peter; Grondin, Cynthia J; Lennon-Hopkins, Kelley et al. (2015) The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. Nucleic Acids Res 43:D914-20