Cargando…

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

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 s...

Descripción completa

Detalles Bibliográficos
Autores principales: Davis, Allan P, Murphy, Cynthia G, Rosenstein, Michael C, Wiegers, Thomas C, Mattingly, Carolyn J
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2576347/
https://www.ncbi.nlm.nih.gov/pubmed/18845002
http://dx.doi.org/10.1186/1755-8794-1-48
_version_ 1782160389649203200
author Davis, Allan P
Murphy, Cynthia G
Rosenstein, Michael C
Wiegers, Thomas C
Mattingly, Carolyn J
author_facet Davis, Allan P
Murphy, Cynthia G
Rosenstein, Michael C
Wiegers, Thomas C
Mattingly, Carolyn J
author_sort Davis, Allan P
collection PubMed
description 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; ) 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.
format Text
id pubmed-2576347
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-25763472008-10-31 The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study Davis, Allan P Murphy, Cynthia G Rosenstein, Michael C Wiegers, Thomas C Mattingly, Carolyn J BMC Med Genomics Research Article 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; ) 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. BioMed Central 2008-10-09 /pmc/articles/PMC2576347/ /pubmed/18845002 http://dx.doi.org/10.1186/1755-8794-1-48 Text en Copyright © 2008 Davis et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Davis, Allan P
Murphy, Cynthia G
Rosenstein, Michael C
Wiegers, Thomas C
Mattingly, Carolyn J
The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title_full The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title_fullStr The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title_full_unstemmed The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title_short The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
title_sort comparative toxicogenomics database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2576347/
https://www.ncbi.nlm.nih.gov/pubmed/18845002
http://dx.doi.org/10.1186/1755-8794-1-48
work_keys_str_mv AT davisallanp thecomparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT murphycynthiag thecomparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT rosensteinmichaelc thecomparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT wiegersthomasc thecomparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT mattinglycarolynj thecomparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT davisallanp comparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT murphycynthiag comparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT rosensteinmichaelc comparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT wiegersthomasc comparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy
AT mattinglycarolynj comparativetoxicogenomicsdatabasefacilitatesidentificationandunderstandingofchemicalgenediseaseassociationsarsenicasacasestudy