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Dan Villeneuve, US EPA, Center for Computational Toxicology and Exposure
Adverse Outcome Pathway (AOP) Webinar
Wednesday January 15, 2020
ADVERSE OUTCOME PATHWAYS
QUANTITATIVE UNDERSTANDING OF RELATIONSHIPS
AND
WHY THAT’S IMPORTANT
KEY EVENT
RELATIONSHIPS
• A biological “if then” statement
• If A occurs, then B can be expected
• Biological plausibility
• Evidence (past experience)
• Domain for which the relationship applies
Aromatase
inhibition
Plasma E2
Upstream
Event
(A)
Downstream
Event
(B)
• AOPs are described with the assumption that the magnitude/duration
of perturbation at the MIE is sufficient to drive the pathway to the AO.
• Adaptive, compensatory, and repair mechanisms are assumed to be
overwhelmed.
• In this context, AOPs are useful for hazard characterization
• What could happen and why
HAZARD ≠ RISK
HAZARD ≠ RISK
Cyp7b,
inhibition
7ɑ-
hyroxypregnenolone
synthesis, decreased
Dopamine
release,
decreased
Locomotor
activity,
decreased
Reproductive
success,
decreased
Population
trajectory,
decreased
Not enough to know this could happen and
why
Need to know whether it is likely to happen in
a given scenario.
Risk = probability
Quantitative
Understanding
What’s the tipping point?
Hazard:
Standing at the edge of a cliff
Exposure:
How hard the wind is
blowing?
How hard are you being
pushed?
Vulnerability:
Is there a guard rail?
Are you anchored?
What is your strength and
balance as an individual?
Quantitative Understanding of KERs
• Quantitative Understanding: What is known about how
much change in A, and under what conditions, is needed to evoke some unit
of change in B?
Considerations Description
Response-response
relationship
What type of function, model, or plot describes the
change in B as a function of change in A?
Time-scale How long after a change in A is B impacted?
Known modulating factors What intrinsic or extrinsic variables are known to
shift or alter the response-response relationship
between A and B?
Known positive or negative
feedback loops
Is B known to influence A – if so, what is the nature
of that relationship?
Toxicologists
think dose-
response
-20
0
20
40
60
80
100
120
-6 -4 -2 0 2 4 6
MagnitudeofEffect
Chemical X [Log Concentration]
Response-Response
Relationship
-20
0
20
40
60
80
100
120
0 50 100 150 200
MagnitudeofEffectonKEB
Magnitude of Effect on KEA
Upstream
Event
(A)
Downstrea
m Event
(B)
Change in a biological measurement
(KEB) as a function of change in another
biological parameter (KEA) on which it is
dependent.
fx
Population
size,
reduced
A
B
C
D
A
Aromatase
inhibition Plasma E2
In vitro, HTS In vivo
https://aopwiki.org/aops/25
y= -8e-7x2 – 7e-5x + 0.016
Response-Response
Relationship
Example
Conolly RB, Ankley GT, Cheng W, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. Quantitative Adverse Outcome Pathways and Their Application to
Predictive Toxicology. Environ Sci Technol. 2017 Apr 18;51(8):4661-4672. doi: 10.1021/acs.est.6b06230.
Brain
Malformation
(heterotopia)
↓TH
release
TPO
Enzyme
Inhibition
↓ Serum
TH
↓ Brain
TH
↓TH
synthesis
https://aopwiki.org/aops/42
Decreased
dam serum
T4
Increased
brain
malformatio
n
Response-Response
Relationship
Example
Hassan I, El-Masri H, Kosian PA, Ford J, Degitz SJ, Gilbert ME. Neurodevelopment and Thyroid Hormone Synthesis Inhibition in the Rat: Quantitative Understanding Within the Adverse
Outcome Pathway Framework. Toxicol Sci. 2017 Nov 1;160(1):57-73. doi: 10.1093/toxsci/kfx163
Molecule Cell Tissue Organ Organ
System
Individual
TIME SCALE
• Impacts which assays / measurements are practical to perform
• Impacts how you design experiments to derive R-R relationships or verify model
predictions
• Impacts whether modeling is needed (too short or too long to practically measure)
Chung et al. 2009. International Journal of
Cancer, Volume: 125, Issue: 4, Pages: 767-773,
DOI: (10.1002/ijc.24464)
High fat diet, whole
life
Normal diet, whole
life
In utero and post-natal exposure to high fat
diet
MODULATING FACTORS
Diet
Genetic predispositions
Disease states
Previous exposures
Co-exposures
Environmental stressors
POSITIVE OR NEGATIVE FEEDBACK
Aromatase
inhibition
Plasma E2
aromatase
gene
expression
Villeneuve et al. 2009 Environ. Health Perspect. 117: 624-631Event B can exert influence on A
Upstream
Event (A)
Downstream
Event (B)
• Influences dose-response, time-course behaviors - must be taken into account to provide accurate
predictions
• Dictate point(s) of departure or tipping points
• May involve biology that is not explicitly represented in the KERs of the AOP
Upstream
Event
(A)
Downstream
Event
(B)
fx
Summary
Quantitative Understanding of KERs
• R-R relationship
• Time-scale of the transition
• Modulating factors that can shift or alter
the R-R relationship
• Feedback mechanisms that may both
dictate the R-R relationship and lead to
complex interactions with other AOPs.
Collectively KERs can be linked
input-to-output to construct a
qAOP
Foran, et al. 2019. ALTEX 36(3), 353-362. doi: 10.14573/altex.1810181.
Quantitative adverse outcome pathway (qAOP): An AOP for which the
quantitative understanding of relationships that underlie transitions from one KE to
the next, as well as critical factors that modulate those relationships, are sufficiently
well defined to allow quantitative prediction of the probability or severity
of the AO for a given level of activation/perturbation of the MIE.
Conolly RB, Ankley GT, Cheng W, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. Quantitative Adverse Outcome Pathways and Their Application to Predictive
Toxicology. Environ Sci Technol. 2017 Apr 18;51(8):4661-4672. doi: 10.1021/acs.est.6b06230.
i.e., - no longer need to assume tipping points, we can
evaluate whether the exposure is likely to surpass the
tipping points along the pathway.
qAOP
Take Home Message
Coupled with exposure
considerations…..,
quantitative understanding of the
relationships underlying an AOP,
facilitate the use of AOPs to support
hazard characterization and risk
assessment.

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Adverse outcome pathways quantitative understanding of relationships

  • 1. Dan Villeneuve, US EPA, Center for Computational Toxicology and Exposure Adverse Outcome Pathway (AOP) Webinar Wednesday January 15, 2020 ADVERSE OUTCOME PATHWAYS QUANTITATIVE UNDERSTANDING OF RELATIONSHIPS AND WHY THAT’S IMPORTANT
  • 2. KEY EVENT RELATIONSHIPS • A biological “if then” statement • If A occurs, then B can be expected • Biological plausibility • Evidence (past experience) • Domain for which the relationship applies Aromatase inhibition Plasma E2 Upstream Event (A) Downstream Event (B)
  • 3. • AOPs are described with the assumption that the magnitude/duration of perturbation at the MIE is sufficient to drive the pathway to the AO. • Adaptive, compensatory, and repair mechanisms are assumed to be overwhelmed. • In this context, AOPs are useful for hazard characterization • What could happen and why
  • 5. HAZARD ≠ RISK Cyp7b, inhibition 7ɑ- hyroxypregnenolone synthesis, decreased Dopamine release, decreased Locomotor activity, decreased Reproductive success, decreased Population trajectory, decreased Not enough to know this could happen and why Need to know whether it is likely to happen in a given scenario. Risk = probability
  • 6. Quantitative Understanding What’s the tipping point? Hazard: Standing at the edge of a cliff Exposure: How hard the wind is blowing? How hard are you being pushed? Vulnerability: Is there a guard rail? Are you anchored? What is your strength and balance as an individual?
  • 7. Quantitative Understanding of KERs • Quantitative Understanding: What is known about how much change in A, and under what conditions, is needed to evoke some unit of change in B? Considerations Description Response-response relationship What type of function, model, or plot describes the change in B as a function of change in A? Time-scale How long after a change in A is B impacted? Known modulating factors What intrinsic or extrinsic variables are known to shift or alter the response-response relationship between A and B? Known positive or negative feedback loops Is B known to influence A – if so, what is the nature of that relationship?
  • 8. Toxicologists think dose- response -20 0 20 40 60 80 100 120 -6 -4 -2 0 2 4 6 MagnitudeofEffect Chemical X [Log Concentration]
  • 9. Response-Response Relationship -20 0 20 40 60 80 100 120 0 50 100 150 200 MagnitudeofEffectonKEB Magnitude of Effect on KEA Upstream Event (A) Downstrea m Event (B) Change in a biological measurement (KEB) as a function of change in another biological parameter (KEA) on which it is dependent. fx
  • 10. Population size, reduced A B C D A Aromatase inhibition Plasma E2 In vitro, HTS In vivo https://aopwiki.org/aops/25 y= -8e-7x2 – 7e-5x + 0.016 Response-Response Relationship Example Conolly RB, Ankley GT, Cheng W, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. Environ Sci Technol. 2017 Apr 18;51(8):4661-4672. doi: 10.1021/acs.est.6b06230.
  • 11. Brain Malformation (heterotopia) ↓TH release TPO Enzyme Inhibition ↓ Serum TH ↓ Brain TH ↓TH synthesis https://aopwiki.org/aops/42 Decreased dam serum T4 Increased brain malformatio n Response-Response Relationship Example Hassan I, El-Masri H, Kosian PA, Ford J, Degitz SJ, Gilbert ME. Neurodevelopment and Thyroid Hormone Synthesis Inhibition in the Rat: Quantitative Understanding Within the Adverse Outcome Pathway Framework. Toxicol Sci. 2017 Nov 1;160(1):57-73. doi: 10.1093/toxsci/kfx163
  • 12. Molecule Cell Tissue Organ Organ System Individual TIME SCALE • Impacts which assays / measurements are practical to perform • Impacts how you design experiments to derive R-R relationships or verify model predictions • Impacts whether modeling is needed (too short or too long to practically measure)
  • 13. Chung et al. 2009. International Journal of Cancer, Volume: 125, Issue: 4, Pages: 767-773, DOI: (10.1002/ijc.24464) High fat diet, whole life Normal diet, whole life In utero and post-natal exposure to high fat diet MODULATING FACTORS Diet Genetic predispositions Disease states Previous exposures Co-exposures Environmental stressors
  • 14. POSITIVE OR NEGATIVE FEEDBACK Aromatase inhibition Plasma E2 aromatase gene expression Villeneuve et al. 2009 Environ. Health Perspect. 117: 624-631Event B can exert influence on A Upstream Event (A) Downstream Event (B) • Influences dose-response, time-course behaviors - must be taken into account to provide accurate predictions • Dictate point(s) of departure or tipping points • May involve biology that is not explicitly represented in the KERs of the AOP
  • 15. Upstream Event (A) Downstream Event (B) fx Summary Quantitative Understanding of KERs • R-R relationship • Time-scale of the transition • Modulating factors that can shift or alter the R-R relationship • Feedback mechanisms that may both dictate the R-R relationship and lead to complex interactions with other AOPs. Collectively KERs can be linked input-to-output to construct a qAOP Foran, et al. 2019. ALTEX 36(3), 353-362. doi: 10.14573/altex.1810181.
  • 16. Quantitative adverse outcome pathway (qAOP): An AOP for which the quantitative understanding of relationships that underlie transitions from one KE to the next, as well as critical factors that modulate those relationships, are sufficiently well defined to allow quantitative prediction of the probability or severity of the AO for a given level of activation/perturbation of the MIE. Conolly RB, Ankley GT, Cheng W, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. Environ Sci Technol. 2017 Apr 18;51(8):4661-4672. doi: 10.1021/acs.est.6b06230. i.e., - no longer need to assume tipping points, we can evaluate whether the exposure is likely to surpass the tipping points along the pathway. qAOP
  • 17. Take Home Message Coupled with exposure considerations….., quantitative understanding of the relationships underlying an AOP, facilitate the use of AOPs to support hazard characterization and risk assessment.