Proceedings of the National Academy of Sciences,
Journal Year:
2013,
Volume and Issue:
110(19)
Published: April 25, 2013
Significance
It
has
been
proposed
that
differential
physical
interactions
of
apolipoprotein
E
(apoE)
isoforms
with
soluble
amyloid-β
(Aβ)
in
brain
fluids
influence
the
metabolism
Aβ,
providing
a
major
mechanism
to
account
for
how
APOE
influences
Alzheimer’s
disease
risk.
The
current
study
challenges
this
proposal
and
clearly
shows
lipoproteins
containing
apoE
are
unlikely
play
significant
role
Aβ
by
binding
directly
physiological
such
as
cerebrospinal
fluid
or
interstitial
fluid.
Our
vitro
vivo
results
suggest
competing
same
clearance
pathways
within
brain.
Cold Spring Harbor Perspectives in Medicine,
Journal Year:
2012,
Volume and Issue:
2(3), P. a006312 - a006312
Published: Jan. 10, 2012
Apolipoprotein
E
(APOE)
genotype
is
the
major
genetic
risk
factor
for
Alzheimer
disease
(AD);
ε4
allele
increases
and
ε2
protective.
In
central
nervous
system
(CNS),
apoE
produced
by
glial
cells,
present
in
high-density-like
lipoproteins,
interacts
with
several
receptors
that
are
members
of
low-density
lipoprotein
receptor
(LDLR)
family,
a
protein
binds
to
amyloid-β
(Aβ)
peptide.
There
variety
mechanisms
which
isoform
may
influence
AD.
substantial
evidence
differential
effects
on
AD
influenced
ability
affect
Aβ
aggregation
clearance
brain.
Other
also
likely
play
role
CNS
function
as
well
AD,
including
synaptic
plasticity,
cell
signaling,
lipid
transport
metabolism,
neuroinflammation.
ApoE
receptors,
LDLRs,
Apoer2,
very
(VLDLRs),
receptor-related
1
(LRP1)
appear
both
metabolism
toxicity.
Therapeutic
strategies
based
include
influencing
apoE/Aβ
interactions,
structure,
lipidation,
LDLR
family
member
function,
signaling.
Understanding
normal
disease-related
biology
connecting
apoE,
provide
novel
insights
into
pathogenesis
treatment.
Journal of Molecular Medicine,
Journal Year:
2016,
Volume and Issue:
94(7), P. 739 - 746
Published: June 9, 2016
Apolipoprotein
(apo)
E
was
initially
described
as
a
lipid
transport
protein
and
major
ligand
for
low
density
lipoprotein
(LDL)
receptors
with
role
in
cholesterol
metabolism
cardiovascular
disease.
It
has
since
emerged
risk
factor
(causative
gene)
Alzheimer's
disease
other
neurodegenerative
disorders.
Detailed
understanding
of
the
structural
features
three
isoforms
(apoE2,
apoE3,
apoE4),
which
differ
by
only
single
amino
acid
interchange,
elucidated
their
unique
functions.
ApoE2
apoE4
increase
heart
disease:
apoE2
increases
atherogenic
levels
(it
binds
poorly
to
LDL
receptors),
preferentially
triglyceride-rich,
very
lipoproteins,
leading
downregulation
receptors).
ApoE4
also
diseases,
decreases
age
onset,
or
alters
progression.
likely
causes
neurodegeneration
secondary
its
abnormal
structure,
caused
an
interaction
between
carboxyl-
amino-terminal
domains,
called
domain
interaction.
When
neurons
are
stressed
injured,
they
synthesize
apoE
redistribute
neuronal
repair
remodeling.
However,
because
altered
undergoes
neuron-specific
proteolysis,
generating
neurotoxic
fragments
(12–29
kDa)
that
escape
secretory
pathway
cause
mitochondrial
dysfunction
cytoskeletal
alterations,
including
tau
phosphorylation.
ApoE4-associated
pathology
can
be
prevented
small-molecule
structure
correctors
block
converting
molecule
resembles
apoE3
both
structurally
functionally.
Structure
potential
therapeutic
approach
reduce
neurological
PLoS ONE,
Journal Year:
2010,
Volume and Issue:
5(11), P. e13950 - e13950
Published: Nov. 15, 2010
Background
Late
Onset
Alzheimer's
disease
(LOAD)
is
the
leading
cause
of
dementia.
Recent
large
genome-wide
association
studies
(GWAS)
identified
first
strongly
supported
LOAD
susceptibility
genes
since
discovery
involvement
APOE
in
early
1990s.
We
have
now
exploited
these
GWAS
datasets
to
uncover
key
pathophysiological
processes.
Methodology
applied
a
recently
developed
tool
for
mining
data
biologically
meaningful
information
dataset.
The
principal
findings
were
then
tested
an
independent
Principal
Findings
found
significant
overrepresentation
signals
pathways
related
cholesterol
metabolism
and
immune
response
both
two
largest
LOAD.
Significance
Processes
innate
previously
been
implicated
by
pathological
epidemiological
disease,
but
it
has
unclear
whether
those
reflected
primary
aetiological
events
or
consequences
process.
Our
evidence
from
demonstrates
that
processes
are
aetiologically
relevant,
suggests
they
may
be
suitable
targets
novel
existing
therapeutic
approaches.
Signal Transduction and Targeted Therapy,
Journal Year:
2019,
Volume and Issue:
4(1)
Published: Aug. 23, 2019
Abstract
Alzheimer’s
disease
(AD)
is
a
neurodegenerative
characterized
by
progressive
memory
loss
along
with
neuropsychiatric
symptoms
and
decline
in
activities
of
daily
life.
Its
main
pathological
features
are
cerebral
atrophy,
amyloid
plaques,
neurofibrillary
tangles
the
brains
patients.
There
various
descriptive
hypotheses
regarding
causes
AD,
including
cholinergic
hypothesis,
tau
propagation
mitochondrial
cascade
calcium
homeostasis
neurovascular
inflammatory
metal
ion
lymphatic
system
hypothesis.
However,
ultimate
etiology
AD
remains
obscure.
In
this
review,
we
discuss
related
clinical
trials.
Wealthy
puzzles
lessons
have
made
it
possible
to
develop
explanatory
theories
identify
potential
strategies
for
therapeutic
interventions
AD.
The
combination
hypometabolism
autophagy
deficiency
likely
be
causative
factor
We
further
propose
that
fluoxetine,
selective
serotonin
reuptake
inhibitor,
has
treat
Journal of Neurology Neurosurgery & Psychiatry,
Journal Year:
2011,
Volume and Issue:
83(2), P. 124 - 137
Published: Nov. 5, 2011
Abstract
Cell
plasticity
operates
alongside
other
sources
of
cell-to-cell
heterogeneity,
such
as
genetic
mutations
and
variation
in
signaling,
together
preventing
most
cancer
therapies
from
being
curative.
The
predominant
methods
quantifying
tumor-drug
response
operate
on
snapshot,
population-level
measurements
therefore
lack
evolutionary
dynamics,
which
are
particularly
critical
for
dynamic
processes
plasticity.
Here
we
apply
a
lineage
tree-based
adaptation
hidden
Markov
model
that
employs
single
cell
lineages
input
to
learn
the
characteristic
patterns
phenotypic
heterogeneity
state
transitions
an
unsupervised
fashion.
To
benchmark
our
model,
paired
fate
with
either
lifetimes
or
individual
cycle
phase
lengths
synthetic
data
demonstrated
successfully
classifies
cells
within
experimentally
tractable
dataset
sizes.
As
application,
analyzed
experimental
same
non-cancer
populations
under
various
treatments.
We
find
each
case
multiple
phenotypically
distinct
states
exist,
significant
unique
drug
responses.
In
total,
this
framework
allows
flexible
classification
across
lineages.