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Human Environmental Disease Network: A computational model to assess toxicology of contaminants.

Abstract During the past decades, many epidemiological, toxicological and biological studies have been performed to assess the role of environmental chemicals as potential toxicants associated with diverse human disorders. However, the relationships between diseases based on chemical exposure rarely have been studied by computational biology. We developed a human environmental disease network (EDN) to explore and suggest novel disease-disease and chemical-disease relationships. The presented scored EDN model is built upon the integration of systems biology and chemical toxicology using information on chemical contaminants and their disease relationships reported in the TDDB database. The resulting human EDN takes into consideration the level of evidence of the toxicant-disease relationships, allowing inclusion of some degrees of significance in the disease-disease associations. Such a network can be used to identify uncharacterized connections between diseases. Examples are discussed for type 2 diabetes (T2D). Additionally, this computational model allows confirmation of already known links between chemicals and diseases (e.g., between bisphenol A and behavioral disorders) and also reveals unexpected associations between chemicals and diseases (e.g., between chlordane and olfactory alteration), thus predicting which chemicals may be risk factors to human health. The proposed human EDN model allows exploration of common biological mechanisms of diseases associated with chemical exposure, helping us to gain insight into disease etiology and comorbidity. This computational approach is an alternative to animal testing supporting the 3R concept.
PMID
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Authors

Mayor MeshTerms
Keywords

computational method

environmental contaminants

human disease network

predictive toxicology

systems biology

Journal Title altex
Publication Year Start




PMID- 27768803
OWN - NLM
STAT- MEDLINE
DCOM- 20171010
LR  - 20171010
IS  - 1868-596X (Print)
IS  - 1868-596X (Linking)
VI  - 34
IP  - 2
DP  - 2017
TI  - Human Environmental Disease Network: A computational model to assess toxicology
      of contaminants.
PG  - 289-300
LID - 10.14573/altex.1607201 [doi]
AB  - During the past decades, many epidemiological, toxicological and biological
      studies have been performed to assess the role of environmental chemicals as
      potential toxicants associated with diverse human disorders. However, the
      relationships between diseases based on chemical exposure rarely have been
      studied by computational biology. We developed a human environmental disease
      network (EDN) to explore and suggest novel disease-disease and chemical-disease
      relationships. The presented scored EDN model is built upon the integration of
      systems biology and chemical toxicology using information on chemical
      contaminants and their disease relationships reported in the TDDB database. The
      resulting human EDN takes into consideration the level of evidence of the
      toxicant-disease relationships, allowing inclusion of some degrees of
      significance in the disease-disease associations. Such a network can be used to
      identify uncharacterized connections between diseases. Examples are discussed for
      type 2 diabetes (T2D). Additionally, this computational model allows confirmation
      of already known links between chemicals and diseases (e.g., between bisphenol A 
      and behavioral disorders) and also reveals unexpected associations between
      chemicals and diseases (e.g., between chlordane and olfactory alteration), thus
      predicting which chemicals may be risk factors to human health. The proposed
      human EDN model allows exploration of common biological mechanisms of diseases
      associated with chemical exposure, helping us to gain insight into disease
      etiology and comorbidity. This computational approach is an alternative to animal
      testing supporting the 3R concept.
FAU - Taboureau, Olivier
AU  - Taboureau O
AD  - INSERM UMR-S973, Molecules Therapeutiques in silico, Paris, France.
AD  - University of Paris Diderot, Paris, France.
AD  - Novo Nordisk Foundation Center for Protein Research, Faculty of Health and
      Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
FAU - Audouze, Karine
AU  - Audouze K
AD  - INSERM UMR-S973, Molecules Therapeutiques in silico, Paris, France.
AD  - University of Paris Diderot, Paris, France.
LA  - eng
PT  - Journal Article
DEP - 20161021
PL  - Germany
TA  - ALTEX
JT  - ALTEX
JID - 100953980
RN  - 0 (Environmental Pollutants)
RN  - 0 (Hazardous Substances)
SB  - IM
MH  - Animal Testing Alternatives
MH  - Animals
MH  - Computational Biology/*methods
MH  - Databases, Factual
MH  - Diabetes Mellitus, Type 2
MH  - Environmental Illness/*chemically induced
MH  - Environmental Pollutants/*toxicity
MH  - Hazardous Substances/toxicity
MH  - Humans
MH  - Systems Biology
MH  - Toxicology/*methods
OTO - NOTNLM
OT  - computational method
OT  - environmental contaminants
OT  - human disease network
OT  - predictive toxicology
OT  - systems biology
EDAT- 2016/10/22 06:00
MHDA- 2017/10/11 06:00
CRDT- 2016/10/22 06:00
PHST- 2016/07/20 00:00 [received]
PHST- 2016/10/18 00:00 [accepted]
PHST- 2016/10/22 06:00 [pubmed]
PHST- 2017/10/11 06:00 [medline]
PHST- 2016/10/22 06:00 [entrez]
AID - 10.14573/altex.1607201 [doi]
PST - ppublish
SO  - ALTEX. 2017;34(2):289-300. doi: 10.14573/altex.1607201. Epub 2016 Oct 21.