- Dan Villeneuve from the US EPA gave a webinar on adverse outcome pathways (AOPs) and quantitative understanding.
- Key event relationships in AOPs describe how changes in one biological event can be expected to cause changes in another, and quantitative understanding involves characterizing the response-response relationship between events.
- Factors like time-scale, modulating factors, and feedback need to be considered to accurately model relationships and make predictions.
- With sufficient quantitative understanding of relationships in an AOP, it can become a quantitative adverse outcome pathway (qAOP) that allows predicting the probability or severity of effects based on chemical exposure levels.
IFLA ENSULIB Webinar Series #12: Sustainability - Bringing Nature and Communi...
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?
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.
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.