>> I want to let you
know this webinar is there is is also supporting an upcoming
NIEHS NHLBI workshop.
Understanding the combined effects of environmental chemical and non-chemical
stressors.
After cirrhosis as a model. It will take place at the North Carolina
-- April third and fourth 2018.
The goals is to work and have mechanisms and pathways of the
combined effects of chemical and nonchemical stresses associated
with atherosclerosis.
It is a biological mechanism and effects of exposure
for both environmental stressors, over time and the roles they play
with the development of disease this will bring together experts
to discuss the state -- underlying biological pathways associated with
chemical and nonchemical stresses in relation to atherosclerosis.
It will use the AOP framework to assist in the discussion of the
pathways considered by workshop purchase offense. We welcome you
to join us -- please contact me if you have
any questions or would like more information.
>> With that we are ready to get started.
>> First we will talk to Carole Yauk, Ph.D. She is
the lead of the generics laboratory and the environmental health science
and research in health Canada.
Dr.
-- Carole Yauk, Ph.D cochair and a cochair of
the application of genomics risk assessment technical committee of
the health and environmental science to. She is a Canadian delicate.
Inactive participant in the adverse pathway
program. Her current research is focused on the development
and implementation of approaches to improve and expedite risk assessment.
To assess potential effects of environmental exposures. She has published over
140 papers in this area. I would like to turned
it over to you.
>> Thank you very much.
Can you hear me?
>> Yes.
>> Thank you. Good afternoon.
Thank you for joining. Thank you to the organizes to present to
the AOP.
This AOP used as a test case in
developing the user handbook supplement.
I refer the viewers to this handbook so,
which I believe has provided a entry material for the webinar.
It provides detailed information about how to build and AOP.
Excellent source of information with examples.
>> Today, I am going to briefly spend about
five minutes, to give you the highlights for those who may have missed the
last webinar. I will spend most of my time talking about our case
study. I will introduce some of the relevant background.
I will tell you about how we went about selecting our key events.
And how we have the relationships.
And the overall weight of evidence for the
pathway.
>> Above we have an example of AOP.
Given to me by [ Indiscernible ] one of the previous speakers. They
were derived from him.
As you can see, it is located by a
green and red event.
Molecular initiating event prospectively. Between
the yellow events are the key events.
>> The pathway is a conceptual framework that portrays existing
knowledge concerning the linkage between
a direct molecular initiating event in a adverse outcome.
It provides a hypothesis and a set of measurements we can
make to test that hypothesis.
Events spend levels of biological organization relevant to
risk assessment, --.
>> These are five main intervals that I view as important
in AOP development. The first AOP are not chemical specific. This
is what differentiates them from part of action. Relying on
Seri similar -- very similar principles.
It begins with the molecular initiating event.
>> AOP are modular.
This is an important principle, we can use these modules to build
other AOP. The AOP are pragmatic simplifications of biology.
They do not describe every aspect of biology. And
critically, to the efforts of this series, it is AOP networks
that are the functional units of prediction. This will be very
important when considering combined effects of chemicals. Finally
AOP is a living document. Constantly evolving.
As it is finalized, nothing is truly ever completely closed on any issue,
and as more research emerges, these can be updated.
>> There are two primary building blocks for AOP. We have
key events which are the functional unit of observation of.
-- Importantly measurable states. And also essential
but not necessarily sufficient.
The other building block are key relationships
with help with our toxicological model these relationships are functional
unit of inference/ extrapolation. Directed relationship.
Describing how Kate provide some ability to predict
or infer stated he.
-- KE.
Finally, in describing the event relationship we need
to consider the degree of quantitative understanding. This is
probably the least well developed part of the AOP program at
this stage. Information should come out in the near future to help explain,
in more detail, how to assess the quantitative understanding of key
that relationships.
>> They are depicted with either solid arrows are dashed arrows.
The solid arrows represent adjacent events, or direct relationships.
The dashed arrows leap over events. These
are referred to as indirect relationships nonadjacent.
These will be referred to as adjacent and nonadjacent key event relationships.
>> I will focus primarily on the key event relationships
this is the most challenging aspect of AOP development
when you develop an AOP, you will be on a KERO page.
That asks for the title of the case are. --. -- KER.
>> Describing the event is providing information that
is upstream or downstream.
It is important to always keep the module nature of these
in mind, as you develop things, with the understanding others
may use the key events and relationships.
>> The next entries that a required -- that are required
are the biological plausibility, based on normal biology,
and understanding of structural and functional relationship
of key events. And also diving into the literature and
data to have support. play, and demonstrate how
it leads up to down.
>> And you document
inconsistencies and uncertainties and quantitative understanding of
your key event relationships.
>> Finally, at the end of mapping at your events, you are
asked to conduct an overall weight of evidence assessment for your
overall AOP. The Bradford Hill criteria used for
this.
There is excellent information in the user handbook to help guide
you on how to assign weight of evidence to your overall
AOP. The first considerable -- consideration is biological plausibility.
Is there a mechanistic relationship between the upstream and downstream
KE. And users handbook
-- there are guidelines.
>> Next consider essentiality of the KEs within your
pathway. Are the KEs downstream of your event block?
When you block a particular KEs is the adverse outcome prevented?
Again, there is instructions on how you make it or
the weights of evidence to be high, moderate, or low. Finally considering
empirical support.
>> As I mentioned, and very
critically for your exercise and purpose, most real-world applications
on AOP networks is the functional unit of production.
>> We have the original AOP that
I demonstrated on the first slide.
You can see how this has leveraged
this parental AOP, and broadened other molecular initiating
and key events that come in later stages.
We can see how all of these molecular initiating events.
There may be other adverse outcomes that result from any particular
one of these in my ease.
>> MI E.
>> When it comes to developing your AOP these are recommendations.
The first is to create a flow diagram similar to the one in the middle
of the screen.
The next step is to search through the existing
content in the AOP knowledge base, to look for related
key events and key event relationships once you have identified that existing
content, you can't figure out the AOP links to it, and you can begin
your AOP development. When we go into the AOP, you can build it
by existing content, and creating new pages as needed.
>> Let's get to the case study on alkylation on DNA
leading to heritable genetic effects.
If there is -- this journaling genetic
damage occurs in sperm or egg and can be transmitted to an offspring.
Germline mutations are [ Indiscernible ]
it can result in genetic disease.
And contribute to the population gene pool.
>> Our motivation for this AOP is
to begin with something that we know a lot about. This is one of
the first AOP reviewed under the program. In genetic
toxicology it is very well study, the first chemical stresses
identified and we felt a good place to start. Also new methods interested
in.
It provides a context of use and technologies. And our AOP builds
both somatic and germ cell mutations facts. We feel this is a great
tool for us to provide context of these methods.
>> We also want to emphasize, despite research going on for decades,
there are still gaps in research in this field. Anyone
developing a AOP, can realize how effective the framework is to identify
research gaps.
>> Most apparently, the mutations are increasingly
record status contributing to a large array of human genetic diseases.
As a result we have been opposed to change in the way heritable
hazards are assessed and are being applied.
>> Now a little bit of background to
help understand the AOP.
Alkylating agents, chemicals that add acral groups.
This is extremely well studied and understood. On the left-hand
side you can see a diagram of where alkyl addicts are
formed on -- [ Indiscernible ].
It is important to note each of these different having different
degrees of stability. AOP is not chemical specific. But they
have heavily prototype agents. Quite
reasonably, much of the data in one area may be biased
toward work on one agent in particular.
>> In this case the majority of data is based on the
chemical ENU. An established prototype alkylating
agent. It came from a lot of different sources.
For our germ cell work primarily on ENU. That is
the acronym for the chemical.
>> An important concept, they can be repaired.
It needs to be overcome before the will be mutation manifested
alkylating agent. The primary repair protein is AGT.
These and signs irresistibly blind.
They are inactivated. They are dead after they have been accepted.
This means they are efficient at repairing
alkylation of DNA at low dosage, but they become overwhelmed
high dosage.
Alkyl retained. Not necessarily good at repairing all types of Attucks.
>> In addition to creating
and adduct, the next critical step is to replication of DNA.
Replication over and alkyl adduct can cause
insertion of an incorrect base in the DNA duplex. Mutation
becomes fixed and can be -- can propagate to daughter cells.
>> At the bottom I have noted some addicts
are not mutagenic.
>> Our target cells for
the overall AOP are spermatic O'Neill stem cells. --
Spermatic O'Neill.
This is the most critical target cell. Sperm derived from these
stem cells will carry these new stations. Fertilization of an egg
with the sperm carrying rotations can result in a offspring mentation.
>> -- Mutation.
>> Select the endpoints in our AOP that can be measured.
This schematic shows checkmarks next to endpoints that we can measure.
And X that we cannot measure our do not measure.
>> First we can readily measure DNA adduct.
These are repaired or not repaired.
There are different ways to measure.
The attic needs -- the DNA needs to be replicated
permutation. We do not -- mutation. We do not
measure replication.
>> Mutations manifest and we can measure in
both somatic cells and sperm. If these mutations occur in sperm they
need to fertilize an egg. We do not measure.
Instead, we measure whether office has mutations.
One of the motivations is to have -- it is extremely difficult
to measure. They are rare events. One of the motivations
is to see how our early events are able to predict the number of offspring.
>> Here is our AOP. Beginning with
mapping out molecular initiating event. Alkylation of
DNA. Meeting Phil insufficient or incorrect repair. Mutations and
finally inherited locations.
>> The final key event relationship, occurs in male
pre-allotted germ cells.
This AOP is only as broad overall, as the
effects of germ cells. We have both direct or adjacent relationships.
The reason we have inserted these is because there
are not a lot of studies measuring insufficient are correct repair.
It is a lot easy to find studies that have measured alkylation of
DNA or mutations and inherited mutations.
This allows us to strengthen the overall evidence, as
do not only need to look at Jason Vance.
>> -- Adjacent events.
>> This is the wiki page.
Here is a summary of key events and relationships. You
can see that he events. You can click on the hyperlinks.
You will see the table of KER. If you click
on the link it will take you to the summary of information that
we have put together, to assess and present one event leads to
the next.
>> Finally, do you have created your relationship, the
wiki represents a network.
It shows my molecular initiating event.
It shows the adjacent relationships, the solid bar and
dashed bar. And it is linked to other AOP.
>> Let's talk about the weight of evidence
for key event relationships. I have describe the biological plausibility.
Each event as well characterized and understood. Highly
biologically positive -- plausible.
>> We are trying to find evidence that
KE one occurs before Katie to.
And we want to examine in detail the concordance
of the dose and response relationship.
One of the mistakes that people make when they develop AOP, is
describing an individual key event and its response relationship, rather
than putting it in the context of the downstream key
event that they are trying to confirm a linkage.
>> In this example I will focus on these indirect key event relationships.
Ideally what you want to do is find studies that measured more
than one of your key events in a single paper. This is not always
possible. It was possible only for a few things, and in general, we
had to look across papers. Here is an
example. On the left is a paper from 1997.
It shows when you expose a hamster to ENU or
-- you see an increase of DNA Attucks.
As you can see, the Attucks form early on. It performs
metabolism and it takes time. And ENU our highest
immediately after exposure.
It declines back to baseline levels after a few days.
>> In contrast when we look at sperm, of rodents, we do not
see mutations occurring immediately, much later. They example on
the right, from Jason O'Brien in 2015. you can see these
animals, which are utilized, were exposed for 28 days to ENU.
At this first point we measured after 28 date
exposure, we waited three days to see mutations in sperm.
Not much of anything going on.
After we waited 70 days, we could see a advocate increase of sperm.
The Attucks occur early, mentation, later.
>> This has been a fantastic plot that I
have found in a paper from Jim in 2018 -- 2008.
You see alkyl Attucks clotted with the
diamonds and the solid diamonds. You can see them increasing with
the dose of alkylating agent.
These circles are the mutations occurring. You can see clearly we
have to past this threshold before we see mentation. The
incident of adducts is higher than the incident of rotations.
>> -- Mutations.
>> In terms of looking at this evidence
in germ cells overall, this is a table comprising of all literature
I found last buddies on mutations in sperm and mutations and offspring.
This is about eight different studies.
They used different dosage.
They were all from the same route of exposure. You can see incidents
pertain to the seven.
They are higher. This is two hours post exposure in rodent sperm cells
they are higher of the number of mutations.
I needed to convert everything to a nucleotide metric.
You can see the adducts or higher. The mutations in
sperm are quite similar to mutations in the offspring. We need to wait
for the extra step, they have been exposed, and the animals have
made it, and we are looking at the offspring. --
Made it.
The best way to look at this is in a diagram. We have incidents
per 10 the seven nucleotides. These are the
alkyl adducts.
>> Consider
uncertainties and inconsistencies with data gaps.
The most important for the germ cell aspect, the empirical
evidence came entirely from the chemical ENU. Limited evidence
for other alkylating agents, this evidence not extensive.
There has been some inconsistencies in incidents concordance, not
appropriate to quantitatively compare some endpoints.
In our case, comparing mutations, which [ Indiscernible ]
to mutations in seven genes,
it is probably not the fairest of comparisons.
>> It has been a bit challenging at times to compare experience,
there are differences in the design.
>> I will now go to the overall weight of evidence for
the entire AOP, rather than focusing on the event relationships.
The overall AOP based on 32-polity studies across three rodent species,
flies and fish no single strong study that compared
multiple events, but we can make extrapolations across studies by
expressing the units per nucleotide different studies. Smack
>> As I describe there is a broad
understanding and extensive knowledge of the biological plausibility of
all the key event relationships generally a very widely accepted
ENU prototypical germ cell. In terms of the finding, we
would say it is strong.
>> Essentiality is something we have
not touched on.
Essentiality in this case could only be considered for one key event.
The insufficient event.
We cannot remove mutations from sperm, and then make the organism
to see if it creates an offspring.
We can modulate DNA repair.
The example I'm showing, from 1999. we have again
a rodent assay [ Indiscernible ]. And if
I miss and the lever, both wild type and ATT overexpressing animals
treated with the chemical ENU.
There hasn't -- there has been a major increase. Largely suppressed
by ADT overexpression. There is great
evidence from a variety of different studies, showing overcoming DNA
repair is required, knockdown of DNA repair, following alkylation
agent exposure, we see increases in mentation
and overexpression of DNA repair decreases limitation. Recall
the overall essentiality for this is moderate, since only based on
one key event. Excellent evidence.
>> We consider the empirical support.
Looking across all key events.
Asking if there is evidence in a change of tray can up or down.
Does KEs occur in earlier dosage?
Is a greater?
>> In our case, it is strong primarily for the indirect and nonadjacent
KER. These are based on OE
CD test liner gold standard approaches and data
collection.
>> Overall, we rank this as moderate
to strong. To wrap it up, we are currently leveraging key
events and key event relationships within this AOP to build others.
You can find is in the wiki.
Number 15. It has undergone external and development.
I would be happy to take questions about this. This
is honestly very critical to how these LPs are
-- AOP.
And how they are useful to regulatory degree and scrutiny they
have been subjected.
>> You can also see our paper
describing how we use this as a test case. One thing I
want to point out, some people have been a lot in the past to make AOP.
There is a significant amount of work and does not necessarily
lead to publication. We have the series of
adverse pathway.
It has been endorsed by OE CD and published in the
series and becomes an official publication can find.
>> I will stop and I am happy to answer any questions.
For have a discussion about the review
process. And listen to your comments.
>> Thank you so much for your excellent presentation. I think
it is great background information and a description of
your is a big AOP.
We will take questions from the Q&A hot. You may submit your questions
using the Q&A pod on the lower right-hand corner.
>> The first question.
Is it difficult to get your AOP started?
Also do you have a team working with you on this AOP? Or is it
something you can do on your own?
>> Those are great questions. We were sort of guinea pigs in the
program we started immediately.
We started to think about how we can develop AOP in the area germ
cell. The way I have started was getting together, a group of
people with a half-day workshop, to talk about
what AOP in the area we thought were important and worth developing
and which ones we would have enough evidence to build. That was back
in 2013.
From that we came up with a number of different AOP. This is first
identified as a priority. I did this much the first draft of
my own. And then I solicited input from all the experts that I had
engaged previously.
Our experience has been one of my far --
for one of my PhD students has developed a AOPs on her own. It is something
that you can do on your own, or as a part of a group. I recommend
collaborating as much as possible.
People tend to be experts on key event rather than [ Indiscernible ]
It is helpful to get others involved
in the process.
>> Thank you. The next question is a two-part question.
Can or should you give others permission
to modify your KER or other evidence?
What do you do if there is a disagreement amongst researchers of the best
KER are AOPs to study?
>> I think that is a great question.
Yes, you can modify the KER and
KEs. That is why we call it a living document. You
need to get developer rights to modify.
In order to do that you need to apply through the AOPs society,
or from the OE CD.
There is information on the wiki.
Everyone is free to comment. Only people who have registered and have
a login.
>> The polite thing to do, is leased to contact the office
and work with them. The office of the KER that you want
to use to modify the key event. A lot of people in
the initial enthusiasm started a lot of AOPs and did
not get far in their descriptions of KER, and left things and complete.
Those AOPs are free to be developed,
but it is important to contact the office to work with them.
And to get consensus on how to modify those.
>> When and AOPs has undergone the final external review
process, I think you think -- you need
to think a little bit more about how things should be modified. All
of the AOPs authors are experts in the area. You can work with them
to determine how best to modify them.
>> In terms of discrepancy or disagreement, these AOPs
that are published have been extensively reviewed by subject matter experts.
It might be something that you need to take up with the
need office as well the committee to have significant modifications
to something.
>> Thank you.
What would you say is the critical impact of having formalized
so successfully AOPs for mutation from alkylating agents?
A hypothesis that has been well around's what it for years?
>> [ Laughter ] the original idea of course,
is to learn how to build a AOPs. And to have a case
study that can show us how we can use old and empirical data to build
a AOPs. We wanted to have this as a case study. The
advantage, we have new assays that we can use. Measuring heritable
mutations in an offspring is extremely difficult and must never done.
The gold standard use tends if not hundreds
of animals. And we are trying to build the case that we should be
able to measure mutations in offspring.
And to look to see how -- mutations
in sperm and to be able to predict the probability that this mentation
would be manifested from the Osprey.
Also, we want to be able to see how much our somatic support [ Indiscernible ]
and we can test methods being developed and plug into this AOPs
to help and predict toxicology.
I hope that answers the question. That is a good question
initially to provide a prototype, but most importantly also on the
new tests we used to predict endpoints that are difficult, if not impossible
to measure, using today's standards.
>> Thank you. I
think we have time for one more question. How do you handle influences
within your pathway, and key events occurring simultaneously?
>> Simultaneous 's concordance. If key events
are occurring at the same time, that is a concordant relationship.
That is fine. In terms of temporal concordance, sometimes
it is difficult to find good studies that done a time series analysis.
In our case, we were fortunate for adducts and
mutations, it has been done. You need to look across studies in order
to get the temporal relationship nailed down.
I'm not sure if that answers your question. But I can confirm to you,
when two things are happening at the same time, it is still a concordant
sortation in terms of timing -- Association.
>> Thank you.
We will hold off on other questions for now. I would like
to thank you for your presentation.
I am sure we will have time to ask more questions at the end of the
webinar.
>> Now we will hear from the next speaker. He
is a staff exposure scientist.
At the Pacific Northwest national laboratory.
He serves as a director for the AOPs research
Center.
He directs Texas A& M science core.
It focuses on exposure assessment of humans,
animals [ Indiscernible ]. His research team focuses on utilization
of technologies, and methods for solving public health challenges
related to human exposure to chemicals. He is the director
of the Pacific Northwest national laboratory.
And achieve exposure scientist.
Meeting efforts are not targeted [ Indiscernible ].
I will turn it over to you.
>> Thank you for the introduction.
I hope you guys would not read the
whole thing. I appreciate it.
It's like a presentation in and of itself. My apologies for that.
Greetings to everyone out there.
>> After a series of great talks on the mechanism experts.
In the form of AOPs, my charge is the type of demonstration to
have exposure science. As we think about constructing a
complete framework, that promotes what
is largely -- what I think is likely to separate feels of inquiry.
Chemical stressors and its involvement in environmental
health. And on chemical stressors and involvement in public health.
Environmental health research side of things.
We are looking to think about ways we can promote the intersection
between those two fields.
>> To get us started thinking along those lines, I
want to stop by contrasting these two research paradigms.
This is a summary of together. I would say the biomedical research
paradigm funded through government agencies. This starts
with the disease, whether identified through civilians or other means,
there is a tremendous amount of effort looking -- on
mechanism and research. A lot of research has been done, and building
on that understanding, starting to look at issues and
questions surrounding human susceptibility.
And the drivers to it. Eventually, as
the research moves along, we can find the draggable target, and looking
for candidate therapeutics. At the end of the paradigm, there
is an important exposure for effective therapy. One of
the most important questions, if we have a draggable target,
can we actually design a drug that gets us to sufficient exposure for
the molecular initiating event?
To actually give us an effective therapy? By nature, this
is asking whether or not we can create a viable
drug. And I would argue to the audience, the
research on the left is in general of lower impact. And then the research
on the right side. We are getting to the question about
whether exposure gives us the drug and therapy. If I was writing a
grant my preference would be writing an impact in this particular area,
rather than earlier areas.
>> Thinking in contrast what I call the paradigm for
toxicology and environmental health research. We started with this.
I tremendous amount of research and hazard identification.
Again we move on to mechanism, and a tremendous
amount of work done and studies and toxicology. And moving onto
genetic understanding susceptibility.
We do not work in this paradigm.
This might be a box that comes later
when we think about exposure strategies.
In the end, the key question,
is there sufficient exposure for the health effect to drive the hazard
in the disease? Not something funded at high level of
gets a lot of attention and focus.
Not to the same extent of the biological [ Indiscernible ] that leaves us
with the problem. We are not sure whether for hazards and such,
studied very deeply, whether or not there is a true risk associated
with that particular closure.
>> -- Exposure.
>> This is an observation that he may have made yourself,
especially with risk assessment work toxicologist might do their
studies in petro -- in vitro.
Epidemiologist may pick up on this by the particular chemical.
They may have observed it themselves and their studies.
They see endpoints in humans that clearly relate to things that have
been identified, or related effects in the test systems. That two communities
in publication, begin referring to the other. The toxicologist
referred to the epidemiology as supporting evidence, and vice
versa. This is reinforcing involving datasets that emerge,
and applies high-impact. The question is whether or not science is being
used properly as a bridge between those two fundamental exploratory
studies.
Ultimately, we often find is the test concentration designed for
hazard mechanism, much higher than those observed in humans.
Which leads to a key question.
Thinking about those two paradigms, we are looking for high enough exposure
for effective drugs, but on the mitigation site for environmental
explosion, the question is are these diseases addressable?
If the exposure is low, and high the dockside things, I
think it implies -- toxicology.
It will not help stop to have environmental health problem.
>> I have a few quick points. I want
to make this last two points.
Key part of this is whether or not on the toxicology
side, when we identify hazards, or
dividing AOPs, whether or not the biology is very different at the
doses we are using exposure for testing. In humans, with
a need to be lower on test system. The second layer, how
do we relate exposures to test systems?
In most publications, the comparison between two studies is made at the
level of, I saw the effect in sales and animals, where
there has been reported effects in humans. It is difficult to make
these associations on the exposure across the system. It is a critical
thing we do.
>> For example, here is the way might look. Researchers are working
in a rodent system. On the left, or in the in vitro model.
The first question, how do the biological responses compare?
In a human are [ Indiscernible ]. Whether or not
there is enough fidelity biologically, say we expect to be able
to see the effects that you see in the system. The second
fundamental question, whether or not the exposure compares?
We have described why that is important.
It is not either natural or is it to make comparisons about these
exposures.
It is fundamentally, if the exposure is in one system, higher allowing
the other system, it seems unlikely that biology that
you are recording, it is related to one another. It becomes a problem
of concordance that is something that AOPs developers
need to address.
>> This is a problem that is somewhat confounded
by all the innovation and the development of various test
systems. It is no longer that would -- that we work on the entire animal,
but we are innovating and developing self free systems, organs on a,
air liquid interface.
Particle exposures. Liquid systems are much more challenging
to use. Each of these systems that we are working, having very
different processes that influence the exposure to the tissues, and
those models. For example, even in self
free systems you can protein binding issues that remove the active compound,
you can have finding of the active compound, beside plasticware, etc..
On top of that, and you have issues like metabolism, partitioning,
particle density.
And these are processes we need to know if we try to figure
out how to come up and understand the system well enough. Then we
can define existing measures that allows us to align the responses
across these systems, through aligned exposures. Without doing
this it is a challenge of understanding how the biology that we are recording
informs us about risks or exposures, and
the likelihood of causing effects is limited. This is an important
challenge.
>> I want to show you what I think is the
impact of absence of that type of thinking, or those capabilities
in this large research community focusing on understanding hazards
and mechanisms. This is an assemblage of dose and exposure data for
[ Indiscernible ].
One of the most highly study compounds.
On the left, we have study concentration for in
vitro studies. The X axis is the study number.
Each dot is a dose in that study.
That is why there are vertical lines. This is the same on the right
side. External concentration. More crude measures of exposure.
>> Because we have tremendous information on the
pharmacokinetics, from multiple human studies that were designed
as PK studies, and studies in nonhuman primates,
we have a lot of information on the level of motion in humans, as
this [ Indiscernible ] urine which means urine is
informative about total exposure.
We can put those together and make height accuracy estimates.
They have also been measured as well. We are confident this is the
human blood concentration.
>> These studies also -- all
self identified by authors like low-dose.
[ Indiscernible ] they cross about orders of magnitude.
Multiple exposures higher than human blood concentrations.
For tissue concentration. If we look at the external exposure side,
the same conclusion can be made.
>> This is a case where years and years of research was probably not
focused in the right exposure domain, which means that you need to ask
a question about relevancy, to human hazards.
>> This has also been to in the nano toxicology.
It can be characterized in early years as heroic particle exposures
in vitro. We have some of the same challenges working with
submerged exposure.
Air liquid interface where becomes very challenging
for people to understand without direct measurement, how a micro
particle is actually relating to a number of particles, or a
massive particles reaching the sales.
>> This image of these two containers with
carbon makes this point well.
These are [ Indiscernible ] on the left and on the right. The one on
the right has a different [ Indiscernible ]. You can see at the time, this
carbon which is a large harbor, -- fiber.
The authors reported the ones on the right were more toxic than the
left. That could be because intrinsically more toxic,
or because a much larger proportion of a dose mass in the in vitro system
settled out, and in debt being exposed to a much higher dose. These
are the types of things that are important. And understanding
the dosage, the particle systems, might reflect human exposure or
inhaled particles. Very similar in the nano particle world.
>> I want to contrast the penetrance of
mechanistic and exposure frameworks in environmental health
training and research.
>> This is my opinion.
First of all, starting with the title, most of us
would probably acknowledge there is a widely accepted opinion. Producing
ecological outcomes.
-- Toxicological. Mechanism and thinking overall has impacted
almost every aspect of toxicology.
We can think of that in terms of mechanism of action,
or mode of action. These are some overarching organizational framework
for toxicology that influences every aspect of the field.
It does not matter if you are
doing risk assessment, investigative toxicology,
or designing studies based on AOPs that have
been developed. This mechanistic thinking is always a part of what
toxicology does, and a fundamental part of training.
>> In contrast, exposure networks, some people recognize
also produce exposure outcomes, much like mechanistic mechanism
producing ecological outcomes. It is much less completely
embraced by the broad environment for community. It is by those that
work on faith and transport models, and the EP are all representations
of an overarching organizational and work for exposure science people
who work in environmental monitoring are
biomonitoring, typically think about exposure as a part of a large
network that delivers exposures to -- site
of action, [ Indiscernible ].
>>@Led a group of us from Morgan State University,
and some of my colleagues, essentially writing a paper, a
sister paradigm our concept to the AOPs concept. --
EP.
I want to spend a lot of time -- and the point we are to trying
to do is twofold. To remind the border community, we have
pathways that exist. When one is working within any aspect,
they should about the network, and about how to design studies and
collect data in a way that optimizes use for
organizing the data and its application, for whatever the need. Whether
identifying or mitigating sources.
And/or delivering specific exposure data to people working
with this assessment.
And it will allow them to make risk based decisions on
those data.
>> I do not want to spend too much
time on this framework. I will say a few things. We design the framework
and its most structured way.
This should be very flexible. I like the AEP. You do not work across
all boxes if you want to work on pharmacokinetics, that is fine
you are working with part of a aggregated exposure pathway. None
the less it is designed to look like AEP. Here
we have on the left one AEP for a chemical. All
we are trying to show is that these describe the movement of the compound
from source to exposure media, perhaps environmental
media etc., to reach external exposure in humans are test animals,
and eventually to create target site exposure, and finally to intersect
AOPs -- molecular initiating event.
>> Can also have a second compound.
That goes to some environmental transformation or metabolism in
vivo that produces a metabolite equal to the first compound. These
AEP can intersect to drive exposure to the AEP.
>> Similarly we can aggregate exposure pathways for
multiple compounds. For example, if interested in
estrogen receptor binding, and all compounds
exposed. You can't aggregate fees AEP. You can use
those exposure networks to create the information needed to
identify the exposure concentrations at the cited action
that drives a particular AEP.
This is a structured and formalized approach that we have described
for the AEP. It does not need to be that structured
in its use.
>> I want to give you an example when you do this. We linked out
the AEP on AOPs for this compound. We think about the
mullah regulator initiating event being binding to estrogen
binding receptors.
For TPR 30.
-- TPR.
We asked the question, given the concentrations that we
see in people's blood, or we simulate these lines for women
of childbearing age and children and infants. If we ask
the question, what fraction of the estrogen effects --
effects should be found? Even -- we
are talking about exceptionally low receptor bindings. For
example, during pregnancy, you end up with much higher levels,
estrogen receptors found from normal levels of
estradiol, in the body.
This is very low compared to what we would expect to be [ Indiscernible ].
>> It becomes important and we get a different conclusion about
the importance of the mechanism work that has been done, and has
its identify when you link those AOPs in AEP. I want to move quickly
into some conceptual ideas how you link chemical and
nonchemical stressors. Thinking about the workshop planned for the
spring.
>> The linkages through mechanisms.
Some basic intervals to think about. Talking mostly about
this, mechanisms described how stressors cause --
cause disease. There are different ways to defer
to those mechanisms and to describe.
>> Second intervals molecules that are the
transducers are chemical and nonchemical stressors that caused disease.
If you have a nonchemical stressor that is going to be the effect.
It is through the body and to another monocle -- molecule.
Here are some basic AOPs mechanisms that describe
critical outcomes.
>> This one is shown, you can have chemical stress, in fish
that influences estradiol levels in the blood, and eventually ends
up reducing spawning behavior and ovulation
and reduces population. You can also imagine that social stress
are other environmental stress, can also reduce spawning behaviors.
There is a intersection between nonchemical stress and chemicals
dresses. There is a new hypothesis about the relationship between
stressors, and chemical stressors, and effect on narrow
behavioral outcomes. -- It can trigger a stress response
that releases cortisol.
Cortisol can have an effect on narrow behavioral outcomes.
And certainly chemicals that we know love. Lead and heavy metals
that can work within the brain to -- or the Gino glands.
-- Adrenal glands.
They can cause influence. New evidence.
[ Indiscernible ] there is good evidence that we have these
points between chemical and nonchemical stress. It should be clear most
cases come stressors and not chemical and [ Indiscernible ] it
can converge through common mechanisms and transducers
to cause disease.
>> These are just good examples. I
do not want to spend too much time.
This example on the right side is rarely interesting. Again hypothesis
that psychological stress, can actually see a
change in cortisol levels and other hormones. Those, levels can
have an impact on [ Indiscernible ]
levels and me to immunosuppression. These can also be implicated
as key molecules that drive fatigue when they reach the
brain. Similarly as a point of intersection between chemical and
nonchemical, chemicals can cause oxidative damage.
And proteins implicated in driving PT signals in the brain.
Is a natural intersection between chemical
and nonchemical stress, leading to multiple endpoints. Immunosuppression
and or fatigue.
>> There is an exposure science component
to this. Again the point is, even if you have molecular
intersecting events, we want to be careful as we think about these
mechanisms, we know exposure levels are sufficient to drive those
to cause the initiation of the biology, leading to adverse
outcomes.
>> The exposure level is going to have a strong influence, not
just on the mechanism Excel but the severity and the probability
of the outcome and the onset.
>> I want to show you this, as this field of
intersection between chemical and nonchemical stresses
moves forward, we want to be
careful that we have complementary hypotheses
that have been explored and that research. I would argue the highest
impact from the emerging field will come when including testing of hypothesis
regarding exposure as a part of the paradigm. Not just mechanism.
Is there hypothesis in a mechanistic basic?
Similarly, a level of nonchemical stress measured in humans, and the
levels of chemical stress in humans is sufficient to induce the key
events common to that AOPs for that particular disease. It is important
in all three of these hypotheses receive equal attention by research
and how it moves forward.
>> A couple of conclusions.
There has been a long preference in the field for finding the discovery
of more specific assays for biological response and mechanistic
research. I would argue that needs to shift toward a greater balance
between that particular type of work and exposure related research
for the reasons I mentioned.
>> I also think that AOPs in AEP concept,
as they integrate is a great conceptual framework. My
hope is this would push the field to evolve toward more coordinating,
mutually supportive hypotheses regarding exposure,
and the rest of what we talked about.
Mechanism, biomarkers and accessibility and resistance. I
hope the field moods toward studies and hazard studies conducted
at human relevant exposure levels.
My hope it will stimulate new research programs
at the intersection of exposure and environmental disease equally
grounded in mechanism and exposure.
Necessary to ensure high impact than significance.
>> I think this has been pushed as they are hoping for
a more comprehensive understanding as to how environmental disease
involves. And higher impact and higher research, he says
research is being done.
I will end with a large
acknowledgment slide of funding sources and my colleagues who have
tribute. Thank you for your time -- contributed.
>> Thank you Justin. You have done a great job.
It helps to make sense of the biology. And how
AOPs can be used in risk assessment. I appreciate how you have introduced
the audience again. I nonchemical stressor workshop, and
arteriosclerosis that will happen April. We will take some questions
from the Q&A pod.
>> The first question, this is more of a philosophical question.
Should exposure in all studies be standardized some way.
For example, how human, animals and in vitro studies or
conduct?
>> People tend to rebel against the standardization
as it applies to the research environment.
I think what I would say about that is, I do not think we
are ready to fully standardize both request these systems. What I would
argue, that people who are working with
[ Indiscernible ] in vitro systems, begin to do a better job of either
directly measuring exposures over the course of an in vitro system.
For example measuring the concentrations over time. To assure it for example,
the compound is not degrading rapidly over time you have a
zero exposure, or it is sticking to the sides of the plate and essentially
to know the exposures and animal studies, blood concentrations, we
have some sort of common basis.
Connecting not only the concentrations to blood concentrations,
to bio monitor blood concentrations
in humans. That is what I would push for rather than a false anodization.
A movement toward meeting that basic goal.
>> Thank you.
The next question, can you go through slide number 14 again? In particular
the class on the right-hand side is not clear. What do the colors
mean and what is scam?
>> -- What is the scale?
>> I'm sorry.
I read through it. -- Breezed through it. On the left side
we have the serum BPA concentration. Days of
exposure so we can lie out these lines. These lines
here, represent model simulations of women of childbearing age,
and infant in the red. Simulated serum concentrations.
You can see this concentration overlap the measured concentrations.
The green is intended to indicate
a level of finding. As the green gets darker you are reaching higher
levels of receptor occupancy.
You are approaching 100 percent when the colors get
dark. As they fadeaway lower receptor.
It is better to look on the right side, this is
the fraction of receptor found exposure.
>> I hope that clarifies things. These
receptor occupancies are calculated using equilibrium conditions
assumptions.
I hope I have explained it.
>> Maybe they can confirm via Q&A.
>> Yes, that is a great idea.
We have extended this work into -- including all hormones,
all the endogenous estrogens and the dietary estrogens,
isoflavones. During pregnancy in women measured by monitoring
[ Indiscernible ]. We carried this forward with more experiment
[ Indiscernible ].
>> Thank you. We have time for my question.
How do you develop atmost exposure Messieurs are in human
epic and logical studies retrospective?
>> Again, one of the
points that I would make, our intent is not to put people
in the position of having to construct an entire AEP if interest is only
an biomonitoring alone.
For example, if there is an interest in understanding
how a particular compound moves from source to a human receptor,
for identifying sources and mitigating exposures, you might
construct the entire AEP that I have described.
If instead a person working on biomonitoring, I would suggest for
example, your interest would be in understanding how moving one
step back, if you will, if you have external exposure and
measures relating to the internal measures that you may have made
in blood. For example the urine concentrations measured.
How all three relate to each other quantitatively. What we have found
several times is, back at school that can tell you whether
or not the external measures made are sufficient to drive concentrations
measured in urine, or in blood.
If you can get cordons, because you understand
external exposure and the pharmacokinetic elements of the AEP the
blood concentrations. In urine concentrations. If you can
get that cordons you have high confidence in your exposure
measure, that you are using to correlate now,. Someone in the future,
you can -- someone working in a different part of the field, they
can connect the environmental monitoring side of things.
And they can feed into the part of the AEP that describes
external exposure to internal exposure.
We are helping people approach it that way, module A, rather than
constructing the whole thing.
>> Okay. Thank you.
We will move on to the next presentation. I encourage the
audience members to continue to submit questions during our
third presentation.
>> Now we will move on to Dr. Perkins. He
serves as a senior research scientist in the U.S.
Army engineer research and development center. He received a
PhD at Washington State University.
In molecular my lodging.
-- Molecular phylogeny -- biology.
Dr. Perkins worked in the development of transgenic plants.
Molecular measures.
He joined the ER DC in 1996
where he established genetic research laboratories.
A wide range of species, rats, quails,
Japanese quails, earthworms, fish. [ Indiscernible ]
and Quarles his current work focuses on advancing methods.
The AEP framework.
The development of application of tools approaching
or alternative methods of toxicology.
Dr. Perkins, thank you. I will turn it over to you.
>> A quick reminder, Dr.
Perkins, I will help you come off of you-commute.
>> MUTE.
>> I would like to talk to you about how we are trying to use the AEP
framework to understand [ Indiscernible ].
>> We have been trying to bridge biological
networks which is where we make a lot of measured using 'omics
data. It is a wonderful framework for thinking possible effects
-- molecular events of [ Indiscernible ]
[ Indiscernible - low volume ]
>> As you have heard over the series of talks,
pragmatic and simple representations of essential
events. It leads to adverse outcomes.
What is nice is they are composed of three events,
measurable that represent in vitro or in people as a.
-- In vitro or in Beeville assay.
>> -- In vivo.
>> AEP is linear.
If you think about earlier talks, more than one AOPs is
linked together to form a network.
One of the problems trying to use AOPs
[ Indiscernible - low volume ]
life is very complicated. As
an illustration, this is a map of the thyroid signaling pathway.
There is a lot going on. Often when we develop AOPs,
we try to minimize the number of steps.
>> These steps are in vitro.
These are essentially sub networks representing
cyclical pathways.
>> When we try to apply technologies,
we can tell you what is happening with tissue. It becomes problematic
when you try to do a simple AOPs. This is a
transcriptional concept with fish exposed to the
environment of cancer. The will Mac are upregulated --
[ Indiscernible ]. You can see a number of genes related
very closely. There are a number of genes related to cancer
[ Indiscernible ] genes upregulated
-- P5
three upregulated. And we can start understanding pathways
that may be impacted related to cancer.
>> One thing I want to talk about, trying
to approach bridging the gap between biological networks. [ Indiscernible
- low volume ] to a more regulatory biology in
terms of AOPs. Right now we are developing
AOPs Explorer.
Basically it is supposed to prevent simple and
complex networks that will bridge biological pathways.
They are using key event communities.
A key event is eventually component that
are inside are a part of a [ Indiscernible ].
And a number of key events in her [ Indiscernible ].
They are often several events that cause that key event.
What we are doing is extracting out the key event
component, making a key event essentially are subnetwork of interacting
genes are pathways.
We are making it so that you can collapse the pathway.
And expended back out into the community.
>> This lets you have multiple components
for key events. Ultimately it lets you relate AOPs more directly to
biological networks. Myself, I like working on
biological networks.
AOPs is very useful for trying to communicate and understand what
measuring and how it relates to something regulatory.
>> We are trying to develop this approach
as complex networks where sub networks can collapse into the
key event that they support.
>> If you remember,
she talked about the wiki. There are a number of places
key event components are on the page where research describes eight
key event. Seller homeostasis and or a proptosis.
Essentially, you can list different
objects that your event is composed of. Whether a multiple
gene are signaling cascade.
We can compose a network of those. Using
that approach we started to look at how we can look at cause and
effect of complex mixtures on fish.
And use in a hypothesis driven context. By marrying
transcript results to AOPs.
>> The example I want to talk about is monitoring the
effects of chemicals in rivers uncaged fathead minnows using
[ Indiscernible ].
>> We have fish explode
-- explode in cages placed at different sites. Three
wastewater treatment plant sites.
In the Detroit River, and three other
sites in the Toledo River. And two
upstream that were used at the Clark oil site.
>> These essentially, these fish native
fish in the area, the known to have tumors, liver tumors
and tumors on them.
The area has been positive effects on native fish.
Can we detect that in fathead minnows exposed
for four days in the water?
>> We did the exposure.
We looked at gene expression in liver after exposure.
What we did, we rented two AOPs.
We wanted to see how that affects and how it links to outcome up
concern. We are interested in liver cancer, tumors
formation, and actually two AOPs in the
wiki letter being in development.
This is essentially chronic activation leading to
liver cancer. We modified it slightly.
We are looking at the hypothesis that [ Indiscernible ]
sustained activation leading to induction,
[ Indiscernible ].
[ Indiscernible - low volume ]
leading to oxidative stress.
Angiogenesis is involved. Ultimately
cancer outcomes.
[ Indiscernible - low volume ] using tran 12
[ Indiscernible ].
>> How did we do this? We used
key event components and subnetworks to relate to AOPs. We started
with literature and known pathways such as
[ Indiscernible ] and other pathway databases.
We made an AHR act evading meeting to liver cancer network.
A much more biological network with much more components.
All the actual genes and proteins,
intermediate molecules, and metabolites, that might be essential for
me going from AHR activation, leading to
liver cancer.
>> We have made subcomponents of the network.
And separate key events within the liver cancer AOPs.
We can preach both worlds of complex biology and a
relatively simple pathway in regulatory biology.
>> To do this we developed a detailed AHR cancer
network. We do most of our work in [ Indiscernible ]. Having
events within them, spontaneous
mutation, expression of specific genes or proteins.
There is cyclo one, [ Indiscernible ].
Quite a range of different data that we can enter into the network.
>> We want to see what we can do with
[ Indiscernible ].
Basically, we
fit the subnetworks of genes and pathways to the relevant events
in the AOPs. We broke them down into seven
events, whether AHR activation, and my ear leading to
CYP induction, and so forth.
>> To do this we imported transcriptomic, Jean
Richmond, PCR and inferred values for genes
in network. Using some of the transcriptomic, if you can transfer it over to
humans, you can use tools available -- pathway analysis.
You can get estimates of potential activation of
nuclear transcription factors of genes expressed.
It gives an idea of some of these proteins, whether they are
made are active in the system.
[ Indiscernible - low volume ].
Important as a cable and a line along side the protein.
[ Indiscernible - low volume ]
>> What we can now see is we can examine genes and sub works
as event components. We have the event component that
would look like for a activation in MID.
-- An IED. Each column
are bar is either a gene expression
or a Z score for enrichment.
Of a protein or reaching. This is Jean
expression of AHR.
You can see at each individual site what the expression is and
we can follow that over to expression of either CYP
one or A1 as a part of these sub networks within
sip induction.
We can also enter other [ Indiscernible - low
volume ]. And they fit within the definition of
this KEs.
>> [ Indiscernible - low volume ]
>> We can do this for all key events.
We can look at how all different events behave within the system.
As you can see some of these networks are fairly complicated. Essentially
the network for angiogenesis.
For the patio regenerative proliferation standing
out. It looks like a fairly complex network that make
these key events work.
It would be nice if we could put in proliferation assays for this
for for actual angiogenesis assays. We are
monitoring the effects of the environment of the
animal. We do not have the assays available.
>> With this we are able to see key components, we have
expression across fish.
Across genes including [ Indiscernible ]
and expression of these. These cells
shown experimental, -- [ Indiscernible -
low volume ] if you have expression of these genes can see
tumor formation.
Cancer formation.
>> We can incorporate all of these
and start looking at how behaves across the system. It does let you
incorporate other markers.
If you have [ Indiscernible ] levels you
can incorporate into estrogen receptors. If
you have other assays like cells [ Indiscernible ] histology dad
G -- data.
You can build a weights up evidence of crusher different sites,
and how much they are impacting each pathway at different levels.
>> Ultimately we are listed
in liver cancer in these fish.
One of the nice things as I said with the analysis they have
specific functions with human and that data, that they can map
to specific gene expression patterns.
>> They have several patterns of genes related to liver cancer
and carcinogenesis.
And the genes related to tomorrow Genesis
are highly -- highly expressed.
Where fish were exposed in both rivers. Actually, carcinogenesis
is highest rate here.
While wild native Nish
-- fish captured, an increase of tumor at the site.
Relative to all the sites. Actually consistent with
wild fish within the environment.
>> Basically this network helps
taking some traditional --
[ Indiscernible - low volume ].
It helps Mary the benefits of using [ Indiscernible ] with the benefits
of AOPs. Side-by-side, is a weights up evidence table
of the ARP with act ration of gene expression or enrichment
of different things. Or activation of AHR. Green is
no and red is yes. Basically this summarizes what the network
says.
>> Between these approaches, we think we can
marry that two approaches together.
The last bar I want to quickly go over
some other places where we are trying to marry data with AEP.
>> Hi throughput transcript Telmex
-- based on changes and
known pathways. Take advantage of civic pathways
that are -- specific pathways related to a regulated outcome
up concern. Take five concentration
exposures, animals and humans [ Indiscernible ].
We can identify expressed genes with
responses of monotonic concentration response.
We can take those and identify the civic pathways as they relate
to farm and AEP network -- that would
-- [ Indiscernible ].
They genes we are looking at to make points of departure, and
impacts, we can scientifically relate to actual outcomes of concern.
We have here
liver cells, and TNT's known to cause
[ Indiscernible ].
We can use the genes.
To get what is causing change in expression to the pathway.
We can use that to divide to exposure.
>> The benefit of that is that we
can use transcriptomics based on known pathways linked
to our outcome of concern.
And it can be beneficial [ Indiscernible - low volume ].
>> I want to communicate some events
that we are trying to have for [ Indiscernible ].
European joint research Council. For a quantitative
approach.
Translation of the and AOPs into a quantitative and computational
AOPs model. It happens in different ways. Going
from a qualitative AOPs which is mostly what we have been talking
about. Basically described AOPs Tway quantitative one. We have
some type of function relating concentration at the MIT and
[ Indiscernible ].
>> The qualitative AOPs ends up being very similar way
conceptual model. It operates well to help build quantitative models.
Right here is where we talked about the
AEP and how it fits in.
>> One of the big
things we need to be concerned with is that you have two have a
question and answer. If you are only interested in screeninglevel
questions, and prioritization,
we need more complex models for quantifying impacts on populations.
In a high biological fidelity.
>> As I said, AOPs can be conceptual
models for qAOPs. You need to
incorporate the AOPs.
Going from MIA to an outcome. However you
may not model all details of the AOPs, depending on the question.
For your question can require more details within it.
Such is the case when there is feedback.
That controls dynamics within it.
>> Also, what is important
in doing AOPs models is documentation.
There is recommendations that will be put out within the next month
about how to use mentation such as trace documentation for
how qAOPs is made and used. Many different types of models
depending on needs.
>> Essentially, there is a
formulation cycle that goes into making AOPs models, very similar
for environmental models.
Problem definition, conceptual model and development,
methodology, getting data and models. Testing for
uncertainty. Then you can use it and go back to the
cycle and reformulate to get a better model.
>> What we think is unique with the
AOPs model, we are trying to encourage people to use it, because of the
AOPs model with the wiki and encyclopedia, a large source of knowledge
is being built up as time goes by.
As more people contribute. You can start building models using information
useful for modeling.
>> I review as storing information that could be
useful.
[ Indiscernible - low volume ] helping to understand gaps. I am very
excited about its potential [ Indiscernible ].
>> I want to present a few applications
of qAOPs. We are developing or looking at the use
of binary state may Nason network.
-- Bayesian AOP.
Essentially, we have put together a
standard AOPs -- AOPs. For those
who do not now, Bayesian AOP is a dish --
distribution of probability model.
You have the probability of ethics are being
activated, -- FX are.
When it is out of joint, depending upon all three. You can start calculating
probabilities. And you can develop a semi-quantitative
measure using any type of algorithm.
>> Here is one inistration if you have inhibition
at the 17 before.
You would inhibit that,
all the upstream receptors become negative.
For this to be turned down user generally off.
The one downstream, is the accumulation of fatty
acid beta oxidation. In mitochondria that goes down. Since oxidation
basically inhibits the formation of fatty liver because
of metabolism, you would pause the
steatosis. Based on the biological understanding
and probabilities of this, you
can develop a simple quantitative network.
>> We have tried to make that a bit
easier to do, developing a Bayesian AOP.
And we have a partial tool [ Indiscernible - low volume ].
>> This is how it is run. It tells you your
probability note. And what has happened.
This is some of the data we have received.
Steatosis AOPs.
Basically, we were able to look at six different chemicals.
And give a 99% certainty of yes and no
on each. By using this network, we are able to take
data as mitochondrial respiration, fatty acid
and gene expression, and whether these notes are on or
off. We can take the estimation of impact on
steatosis. We think this will be really nice for screening
approach. And looking at mixture.
>> The last model is a large model of several years.
Several years to build and collaborate.
With the EPA.
Quantitative models depicting aromatase inhibitor
of ovulation of spawning. Basically
it takes and OD model
with feedback control mechanism.
Linking it to a
model. [ Indiscernible ] linking
it to a population dynamic model, which is a matrix type of model.
It makes you basically say how much chemical you have, it
takes it and virtually inhibit Tates -- it
calculates aromatase.
Depending on the question you are trying to answer,
the AOP framework is conducive to develop these types of monitors.
>> In summary, I hope I have given you a taste
on how you can use biological networks and how you
can integrate them with AOPs. It is useful for hypothesis driven
analysis of mixture effects.
>> What is also exciting, the facility for
biomarkers of proteins and other types of gene expression.
And integrate them into a context of biological network. We think
transcript to mix can be used -- transcript of monks.
One interesting concept is to have quantify
impacts at the subnetwork level.
>> I hope I have
explain to you how models vary widely.
And can be simple or complex.
>> I do not want to steer you away from it.
Overall there is a lot of potential for using data, and
on the AOPs context. Whether overlying it on top of networks,
or assessing how it is used, and
data driven models.
>> This work would not have been possible without
all of these people. [ Indiscernible ]
Congregational support and the development.
Thank you.
That is all I have.
>> Thank you so much for your perspective on AOPs.
Especially they can both be used in ecological studies.
It has been very interesting.
I will take a few questions from the Q&A pot.
>> -- Pot. If you want to combine different AOPs with each
other, how do you handle differences between the KEs
composition?
This is a follow-up, maybe KEs is the same but
the component is not.
>> The AOPs and KEs are
living documents. Potentially, that may mean that
they are missing components from the previous KEs.
A part of the design from the wiki, and adverse outcome pathways,
they are module.
Some of the variation between
species, which would be significant [ Indiscernible
- low volume ]. I would not expect it to be a variation between
a species. It can require an update.
[ Indiscernible - low volume ].
>> The next question, do you take directionality within pathways
into account within your site escape network?
>> Yes.
>> Okay.
>> I can show you.
Right here we have inhibiting cellular matrix
stabilization. Sailor matrix stabilization
results angiogenesis -- promotes.
We have that type of activation within these interactions.
You can have multiple ones with oxidative DNA damage.
Or lack of it, oxidative DNA damage is bad for
genetic stability.
It inhibits genetic stability but is good spontaneous mutation.
[ Indiscernible - low volume ] >>
The next question more of a application question. When looking at that slide
right now with carcinogenesis.
Is that linking to the general AOPs pathway?
>> No, that means
it has been selected on the network.
>> Okay. [ Indiscernible - multiple speakers ]
when you click on it it turns yellow as a default.
>> The next question, your use of gene expression in fish
liver understand cancer creates chaos for interpretation.
The liver cancer starts from a single stem cell and deliver, the
bulk of the liver has [ Indiscernible ] parasites and other
cell types.
>> [ Indiscernible - low volume ] if it
is a single cell, there are different stages. You need to have
a single scale to propagate permutation. You need to have a
background event to happen. I agree, right now we are
currently developing it. That is one of the things that we are trying
to get the key event what is actually happening in biology.
I do not know why or how we can detect it. If it
is over a certain threshold we can detect it in the [ Indiscernible ]
issue. Events happening in small amounts of the
tissue. Something we are trying to explore and understand.
>> Okay, thank you.
We are approaching our time.
We were supposed to and this at 3:00. I want to
tell all speakers once again, thank you so much. We received a number
of questions. You will receive the questions etc.. With that
being said, we need to close out.
>> Before I conclude, I want to make sure everyone
is aware of the related pod which contains seminar resources
and feedback. We have assembled resources applicable to
today's topics. This will stay with the seminar indefinitely.
You can access after the presentation.
We have a soundtrack and an archive. You will be able
to access the slide and the presentation.
Also you will find online seminar back form. We
ask you to fill out the form. We look at comments as
we tried to move content and delivery.
-- Improve.
-- >>
I also want to remind participants, there are various
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You can follow on Twitter.
We have a cleanup information LinkedIn group. You can
visit the SRP page.
>> Again, thank you to all of the speakers.
We will conclude the webinar.
If you did submit an online question, we will send
questions to the presenters you can contact the presenters
via email. That emails are on the seminar homepage.
Once again I would like to thank our speakers.
>> Thank you again.
Take care and have a good rest of your day.