RASS

1
Providing the Missing Link The
Exposure Ontology ExO

• RASS
• December 11, 2013
• Elaine Cohen HubalChemical Safety for
  Sustainability Research Program

Disclaimer. Although this work was reviewed by
EPA and approved for presentation, it may not
necessarily reflect official Agency policy.
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What Is Exposure Science?

• The bridge between the sources of chemical,
  physical and biological agents and human health
• Provides crucial information to estimate
  real-life risks to health and to identify the
  most effective ways to prevent and reduce these
  risks.

www.isesweb.org
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Exposure for Risk Evaluation Approaches

• Questionnaire based metrics (epidemiology)
• Surrogate exposure metrics (ambient measures)
• Exposure measurement (direct or point-of-contact)
• Biomonitoring (NHANES)
• Modeled estimates (indirect or scenario
  evaluation)

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Systems Biology Exposure at All Levels of
Biological Organization
Cohen Hubal, JESEE, 2008
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Exposure for Translation
Susceptibility (Genetic Variants / Epigentic
Modifications)
Improved Measures of Individual Etiological
Processes and Individual Exposures
Biological Insight (Toxicity Pathways)
Environmental Factors (Exposure)
Key Perturbations Key Targets
Personal Risk Profile
Biomarkers Indicators Metrics
Information
Extrapolation for Risk Assessment
Education
Personal Risk Management
Public Health Policy Prevention
Cohen Hubal, et al. JTEH, 2010
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Knowledge Systems Enabling Hypothesis
Development

• Computational Techniques Two Branches
• A combination of discovery and engineering
  (mechanistic)-based modeling approaches required
  for hypothesis development and testing
• Knowledge-discovery
• Data-collection, mining, and analysis
• Required to extract information from extant data
  on critical exposure determinants, link exposure
  information with toxicity data, and identify
  limitations and gaps in exposure data.
• Mechanistic (dynamic) simulation
• Mathematical modeling at various levels of detail
  
• Required to model the human-environment system
  and to test our understanding of this system.

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Exposure-Hazard Knowledge System

• Translation of HTP hazard information requires
  holistic risk assessment knowledge system
• Include ontologies, databases, linkages
• Facilitate computerized collection, organization,
  and retrieval of exposure, hazard, and
  susceptibility information
• Define relationships, allow automated reasoning,
  facilitate meta analyses
• Standardized exposure ontologies required to
• Develop biologically-relevant exposure metrics
• Design and interpret in vitro toxicity tests
• Incorporate information on susceptibility and
  background exposures to assess individual and
  population-level risks

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Schematic of ontologies, databases and
ontology/database linkages needed for the
efficient development of a Foods-for-Health
Knowledge System
MC Lange, et al. (2007) A multi-ontology
framework to guide agriculture and food towards
diet and health. J Sci Food and Ag 87(8)1427-34.
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Exposure Data Sources
Peter Egeghy, NERL

• http//actor.epa.gov

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Exposure Data Landscape
Network of exposure taxonomy used in ACToR
Egeghy et al, 2011
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Exposure Data Landscape
Number of unique chemicals by data type in ACToR
Egeghy et al, 2011
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Exposure Data Collection and Access ACToR,
Aggregated Computational Toxicology Resource
http//actor.epa.gov/
ACToR API
Chemical ID Structure QC, Inventory Tracking
Chemical
DSSTox
Chemical ID, Structure
ToxRefDB
ToxCastDB
ExpoCastDB
ACToR Core
Tabular Data, Links to Web Resources
In Vivo Study Data - OPP
ToxCast Data NCCT, ORD, Collaborators
Exposure Data NERL, NCCT
Internet Searches
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Exposure Data Collection and Access ExpoCastDB
Goals

• Consolidate observational human exposure data,
  improve access and provide links to health
  related data
• House measurements from human exposure studies
• Encourage standardized reporting of observational
  exposure information
• Provide separate interface with inner workings of
  ACToR
• Facilitate linkages with toxicity data,
  environmental fate data, chemical manufacture
  information
• Provide basic user functions
• Visualization (e.g., scatterplots, probability
  plots, goodness-of-fit)
• Obtain summary statistics and estimate
  distributional parameters
• Download customized datasets

http//actor.epa.gov/
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Exposure Data Collection and Access ExpoCastDB

Generic_chemical table in ACToR

• Four initial studies from National Exposure
  Research Laboratory
• Full raw data sets available for download
• Browse data capability
• Descriptive statistics capabilities

Laboratory method
1
1
N
Technique / sampling method
Measure (Chemical)
N
N
N
N
1
Location_CV (cont vocab.)
N
N
Medium (serum, air, soil, etc.)
1
1
Sample
N
N
N
N
N
Location
N
N
N
N
N
Exposure Taxonomy (Assay_ category_ CV table in
ACToR)
N
N
N
1
N
Subject
N
N
N
N
N
N
N
Study
N
N
Sources
N
Study_CV cont. vocab
1
N
N
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ExO An Ontology for Exposure Science
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Exposure Data Collection and Access Design and
Evaluation of the Exposure Ontology, ExO

• Background
• Significant progress has been made in collecting
  and improving access to genomic, toxicology, and
  health data
• These information resources lack exposure data
  required to
• translate molecular insights
• elucidate environmental contributions to diseases
• assess human health risks at the individual and
  population levels
• Aim
• Facilitate centralization and integration of
  exposure data to inform understanding of
  environmental health
• Bridge gap between exposure science and other
  environmental health disciplines
• Vehicle
• Carolyn Mattingly, Mount Desert Island Biological
  Laboratory
• LRI seed funding, followed by NIEHS RO1

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Ontologies

• An ontology is a formal representation of
  knowledge within a domain and typically consists
  of classes, the properties of those classes, and
  the relationships between these
• Many fields are developing ontologies to
• Organizing and analyzing large amounts of complex
  information from multiple scientific disciplines
• Provide unprecedented perspective
• Enable more informed hypothesis development

(Gruber, Int. J. Human-Computer Studies, 1995)
(http//www.obofoundry.org/)
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Design and Evaluation of the Exposure Ontology
ExO

• Develop an exposure ontology consistent with
  those being used in toxicology and other health
  sciences
• Facilitate centralization and integration of
  exposure data to inform understanding of
  environmental health
• Bridge gap between exposure science and other
  environmental health disciplines
• Initially focus development on human exposure to
  chemicals
• Ultimately, provide domains that can be extended
  to encompass exposure data for the full range of
  receptors and stressors

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Exposure Ontology Working Group
Working Group Member Institution Role/expertise
Carolyn Mattingly, PhD Mount Desert Island Biological Laboratory Facilitator/curated database development
Judith Blake, PhD. The Jackson Laboratory Facilitator/ontology development
Michael Callahan, PhM. MDB, Inc. Core Member/ exposure assessment
Elaine Cohen Hubal, PhD US EPA NCCT Core Member/ exposure research
Robin Dodson, ScD. Silent Spring Institute (SSI) Member/exposure research
Peter Egeghy, PhD. US EPA, NERL Member/exposure research
Jane Hoppin, ScD. NIEHS Member/epidemiology
Thomas McKone, PhD. Lawrence Berkeley National Laboratory (LBNL) Core Member/ exposure research
Ruthann Rudel, MS. Silent Spring Institute (SSI) Member/exposure research
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Phases of Exposure Ontology Development
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Definitions of Central Concepts

• Exposure Stressor - An agent, stimulus, activity,
  or event that causes stress or tension on an
  organism and interacts with an exposure receptor
  during an exposure event.
• Exposure Receptor - An entity (e.g., a human,
  human population, or a human organ) that
  interacts with an exposure stressor during an
  exposure event.
• Exposure Event - An interaction between an
  exposure stressor and an exposure receptor.
• Exposure Outcome - Entity that results from the
  interaction between an exposure receptor and an
  exposure stressor during an exposure event.

Mattingly et al, submitted
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Biolog. Agent
Relational View of Selected ExO Domains
Public Policy
Chem. Agent

• Source
• Location
• Process
• Transport Path

Inter- vention
Exposure Outcome
Exposure Stressor
Biomech. Agent
Disease
Biolog. Response
Phys. Agent
Symptom
Psychosoc. Agent
Molecular Response
Exposure Receptor
Anthro- sphere
Human Pop.

• Location
• Temporal Pattern
• Intensity
• Route
• Assay
• Medium
• Method
• Location

Individual

• Location
• Genetic Background
• Lifestage
• Health Status
• Socioeconomic Status
• Occupation

Mattingly et al, submitted
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High-level schematic of Exposure Ontology (ExO)
integration within a broader biological context.
Encode
Annotated with
Biological Process Molecular Function Cellular
Component (e.g., Gene Ontology
Chemical (e.g., MeSH)
Genes
Gene Products
Interacts with (e.g., CTD)
Interact via
Is a
Pathways, Networks Reactions (e.g., KEGG,
Reactome)
Exposure Stressor (e.g., ExO)


Occur within
Interacts with
Interacts with (e.g., CTD)
Biological System (e.g., Functional model of
anatomy)
Exposure Receptor (e.g., ExO)
Is a
Assessed by
Via an
Exposure Outcome Phenotype (e.g., OMIM, MeSH)
Exposure Event (e.g., ExO, ExpoCastDB)
Results in an
Mattingly et al, submitted
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Next Steps

• Open source approach
• With input from the scientific community, further
  specify branches
• Leverage existing ontologies (e.g., CHEBI and
  MeSH for Chemical agent Stressors DO, OMIM and
  MeSH for Disease Outcomes).
• Cross-referencing will underscore where ExO fits
  into a broader knowledge space and where it may
  add value to existing ontologies.

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Beyond EPA Pilot Curation of Exposure Data into
CTD
Carolyn Mattingly
pathway data
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Acknowledgements

• ExO
• Carolyn Mattingly,
• Tom McKone,
• Judy Blake,
• Mike Callahan

ExpoCastDB -- Richard Judson, Peter Egeghy,
Sumit Gangwal