Chemical-Induced Phenotypes at CTD Help Inform the Predisease State and Construct Adverse Outcome Pathways

被引:43
作者
Davis, Allan Peter [1 ]
Wiegers, Thomas C. [1 ]
Wiegers, Jolene [1 ]
Johnson, Robin J. [1 ]
Sciaky, Daniela [1 ]
Grondin, Cynthia J. [1 ]
Mattingly, Carolyn J. [1 ,2 ]
机构
[1] North Carolina State Univ, Dept Biol Sci, Raleigh, NC 27695 USA
[2] North Carolina State Univ, Ctr Human Hlth & Environm, Raleigh, NC 27695 USA
关键词
phenotype; database; curation; chemical; disease; adverse outcome pathway; COMPARATIVE TOXICOGENOMICS DATABASE; MODEL; RISK; TOOL;
D O I
10.1093/toxsci/kfy131
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
The Comparative Toxicogenomics Database (CTD; http://ctdbase.org) is a public resource that manually curates the scientific literature to provide content that illuminates the molecular mechanisms by which environmental exposures affect human health. We introduce our new chemical-phenotype module that describes how chemicals can affect molecular, cellular, and physiological phenotypes. At CTD, we operationally distinguish between phenotypes and diseases, wherein a phenotype refers to a nondisease biological event: eg, decreased cell cycle arrest (phenotype) versus liver cancer (disease), increased fat cell proliferation (phenotype) versus morbid obesity (disease), etc. Chemical-phenotype interactions are expressed in a formal structured notation using controlled terms for chemicals, phenotypes, taxon, and anatomical descriptors. Combining this information with CTD's chemical-disease module allows inferences to be made between phenotypes and diseases, yielding potential insight into the predisease state. Integration of all 4 CTD modules furnishes unique opportunities for toxicologists to generate computationally predictive adverse outcome pathways, linking chemicalgene molecular initiating events with phenotypic key events, adverse diseases, and population-level health outcomes. As examples, we present 3 diverse case studies discerning the effect of vehicle emissions on altered leukocyte migration, the role of cadmium in influencing phenotypes preceding Alzheimer disease, and the connection of arsenic-induced glucose metabolic phenotypes with diabetes. To date, CTD contains over 165 000 interactions that connect more than 6400 chemicals to 3900 phenotypes for 760 anatomical terms in 215 species, from over 19 000 scientific articles. To our knowledge, this is the first comprehensive set of manually curated, literature-based, contextualized, chemical-induced, nondisease phenotype data provided to the public.
引用
收藏
页码:145 / 156
页数:12
相关论文
共 42 条
[1]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[2]   Mouse Phenome Database: an integrative database and analysis suite for curated empirical phenotype data from laboratory mice [J].
Bogue, Molly A. ;
Grubb, Stephen C. ;
Walton, David O. ;
Philip, Vivek M. ;
Kolishovski, Georgi ;
Stearns, Tim ;
Dunn, Matthew H. ;
Skelly, Daniel A. ;
Kadakkuzha, Beena ;
TeHennepe, Gregg ;
Kunde-Ramamoorthy, Govindarajan ;
Chesler, Elissa J. .
NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) :D843-D850
[3]   A new case of malonic aciduria with a presymptomatic diagnosis and an early treatment [J].
Celato, Andrea ;
Mitola, Chiara ;
Tolve, Manuela ;
Giannini, Maria Teresa ;
De Leo, Sabrina ;
Carducci, Claudia ;
Carducci, Carla ;
Leuzzi, Vincenzo .
BRAIN & DEVELOPMENT, 2013, 35 (07) :675-680
[4]   The BioGRID interaction database: 2017 update [J].
Chatr-aryamontri, Andrew ;
Oughtred, Rose ;
Boucher, Lorrie ;
Rust, Jennifer ;
Chang, Christie ;
Kolas, Nadine K. ;
O'Donnell, Lara ;
Oster, Sara ;
Theesfeld, Chandra ;
Sellam, Adnane ;
Stark, Chris ;
Breitkreutz, Bobby-Joe ;
Dolinski, Kara ;
Tyers, Mike .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D369-D379
[5]   Technical milestone - Medical subject headings used to search the biomedical literature [J].
Coletti, MH ;
Bleich, HL .
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2001, 8 (04) :317-323
[6]   The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study [J].
Davis, Allan P. ;
Murphy, Cynthia G. ;
Rosenstein, Michael C. ;
Wiegers, Thomas C. ;
Mattingly, Carolyn J. .
BMC MEDICAL GENOMICS, 2008, 1 (1)
[7]   The Comparative Toxicogenomics Database: update 2017 [J].
Davis, Allan Peter ;
Grondin, Cynthia J. ;
Johnson, Robin J. ;
Sciaky, Daniela ;
King, Benjamin L. ;
McMorran, Roy ;
Wiegers, Jolene ;
Wiegers, Thomas C. ;
Mattingly, Carolyn J. .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D972-D978
[8]   Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database [J].
Davis, Allan Peter ;
Wiegers, Thomas C. ;
King, Benjamin L. ;
Wiegers, Jolene ;
Grondin, Cynthia J. ;
Sciaky, Daniela ;
Johnson, Robin J. ;
Mattingly, Carolyn J. .
PLOS ONE, 2016, 11 (05)
[9]   The Comparative Toxicogenomics Database's 10th year anniversary: update 2015 [J].
Davis, Allan Peter ;
Grondin, Cynthia J. ;
Lennon-Hopkins, Kelley ;
Saraceni-Richards, Cynthia ;
Sciaky, Daniela ;
King, Benjamin L. ;
Wiegers, Thomas C. ;
Mattingly, Carolyn J. .
NUCLEIC ACIDS RESEARCH, 2015, 43 (D1) :D914-D920
[10]   A CTD-Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug-disease and drug-phenotype interactions [J].
Davis, Allan Peter ;
Wiegers, Thomas C. ;
Roberts, Phoebe M. ;
King, Benjamin L. ;
Lay, Jean M. ;
Lennon-Hopkins, Kelley ;
Sciaky, Daniela ;
Johnson, Robin ;
Keating, Heather ;
Greene, Nigel ;
Hernandez, Robert ;
McConnell, Kevin J. ;
Enayetallah, Ahmed E. ;
Mattingly, Carolyn J. .
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2013,