A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling
Frontiers in Toxicology,
Год журнала:
2024,
Номер
6
Опубликована: Март 21, 2024
Perfluorooctanoic
acid
(PFOA)
is
a
persistent
environmental
contaminant
that
can
accumulate
in
the
human
body
due
to
its
long
half-life.
This
substance
has
been
associated
with
liver,
pancreatic,
testicular
and
breast
cancers,
liver
steatosis
endocrine
disruption.
PFOA
member
of
large
group
substances
also
known
as
“forever
chemicals”
vast
majority
this
lack
toxicological
data
would
enable
their
effective
risk
assessment
terms
health
hazards.
study
aimed
derive
health-based
guidance
value
for
intake
(ng/kg
BW/day)
from
vitro
transcriptomics
data.
To
end,
we
developed
an
silico
workflow
comprising
five
components:
(i)
sourcing
hepatic
concentration-response
data;
(ii)
deriving
molecular
points
departure
using
BMDExpress3
performing
pathway
analysis
gene
set
enrichment
(GSEA)
identify
most
sensitive
pathways
exposure;
(iii)
estimating
freely-dissolved
concentrations
mass
balance
model;
(iv)
vivo
doses
by
reverse
dosimetry
PBK
model
part
quantitative
extrapolation
(QIVIVE)
algorithm;
(v)
calculating
tolerable
daily
(TDI)
PFOA.
Fourteen
percent
interrogated
genes
exhibited
relationships.
GSEA
revealed
“fatty
metabolism”
was
exposure.
In
free
were
calculated
be
2.9%
nominal
applied
concentrations,
these
input
into
QIVIVE
workflow.
Exposure
virtual
population
3,000
individuals
estimated,
which
TDI
0.15
ng/kg
BW/day
benchmark
dose
modelling
software,
PROAST.
comparable
previously
published
values
1.16,
0.69,
0.86
European
Food
Safety
Authority.
conclusion,
demonstrates
combined
utility
“omics”-derived
point
setting
anticipation
acceptance
measurements
chemical
assessment.
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl1
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl5
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl3
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl2
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl6
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl7
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
underlying
mechanisms
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
in
vitro
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis
or
necrosis.
Benchmark
concentration-response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
benchmark
concentrations
(BMCs)
gain
insight
into
hepatotoxic
effects.
BMCs
derived
by
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
deregulated
genes
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
point
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
concentration
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
BMCs,
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
systems
when
are
paired
with
chemical
exposure
assessment.
Plain
language
summaryRisk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
(hepatocyte)
have
developed
hazard
models,
HepaRG,
toxic
chemicals.
Biological
changes
expression
measured
range
which
response
perturbed
modelling.
Genes
belonging
same
process
joined
an
average
process.
animal-free
related
expected
Язык: Английский
Qualitative and quantitative concentration-response modelling of gene co-expression networks to unlock hepatotoxic mechanisms for next generation chemical safety assessment_Suppl8
ALTEX,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Next
generation
risk
assessment
of
chemicals
revolves
around
the
use
mechanistic
information
without
animal
experimentation.
In
this
regard,
toxicogenomics
has
proven
to
be
a
useful
tool
elucidate
mechanisms
underlying
adverse
effects
xenobiotics.
present
study,
two
widely
used
human
hepatocyte
culture
systems,
namely
primary
hepatocytes
(PHH)
and
hepatoma
HepaRG
cells,
were
exposed
liver
toxicants
known
induce
cholestasis,
steatosis,
or
necrosis.
Benchmark
concentration
(BMC)
response
modelling
was
applied
transcriptomics
gene
co-expression
networks
(modules)
derive
BMCs
gain
insight
into
hepatotoxic
effects.
derived
by
concentration-response
modules
recapitulated
individual
genes.
Although
PHH
cells
showed
overlap
in
genes
deregulated
toxicants,
demonstrated
higher
responsiveness,
based
on
lower
co-regulated
modules.
Such
can
as
points
departure
(tPOD)
for
assessing
module-associated
cellular
(stress)
pathways/processes.
This
approach
identified
clear
tPODs
maximum
systemic
(Cmax)
levels
tested
drugs,
while
cosmetics
ingredients
10-100-fold
than
estimated
plasma
concentrations.
could
serve
next
practice
identify
early
responsive
at
low
that
linked
key
events
outcome
pathways.
turn,
assist
delineating
potential
hazards
new
test
using
vitro
systems
where
are
paired
with
chemical
exposure
assessment.
Plain
language
summary
Risk
traditionally
been
focused
experiments.
contrast,
uses
biological
obtained
from
experiments
cell
models
animals
hazards.
Since
is
main
target
organ
toxicity,
many
have
developed
hazard
toxic
chemicals.
Biological
changes
expression
measured
range
which
started
perturbed
mathematical
approach.
Genes
belonging
same
biological
process
an
average
process.
animal-free
relating
concentrations
expected
Язык: Английский