Brain,
Journal Year:
2024,
Volume and Issue:
147(7), P. 2414 - 2427
Published: Feb. 6, 2024
Abstract
Synaptic
dysfunction
and
degeneration
is
likely
the
key
pathophysiology
for
progression
of
cognitive
decline
in
various
dementia
disorders.
status
can
be
monitored
by
measuring
synaptic
proteins
CSF.
In
this
study,
both
known
new
were
investigated
compared
as
potential
biomarkers
dysfunction,
particularly
context
Alzheimer's
disease
(AD).
Seventeen
quantified
CSF
using
two
different
targeted
mass
spectrometry
assays
prospective
Swedish
BioFINDER-2
study.
The
study
included
958
individuals,
characterized
having
mild
impairment
(MCI,
n
=
205),
AD
(n
149)
a
spectrum
other
neurodegenerative
diseases
171),
addition
to
cognitively
unimpaired
individuals
(CU,
443).
protein
levels
between
diagnostic
groups
their
associations
with
neuroimaging
measures
(amyloid-β-PET,
tau-PET
cortical
thickness)
assessed.
Among
17
examined,
14
specifically
elevated
continuum.
SNAP-25,
14-3-3
zeta/delta,
β-synuclein,
neurogranin
exhibited
highest
discriminatory
accuracy
differentiating
from
controls
(areas
under
curve
0.81–0.93).
SNAP-25
zeta/delta
also
had
strongest
tau-PET,
amyloid-β-PET
thickness
at
baseline
associated
longitudinal
changes
these
imaging
[β(standard
error,
SE)
−0.056(0.0006)
0.058(0.005),
P
<
0.0001].
was
predictor
non-demented
(hazard
ratio
2.11).
contrast,
neuronal
pentraxins
decreased
all
(except
Parkinson's
disease),
NPTX2
showed
subsequent
[longitudinal
Mini-Mental
State
Examination:
β(SE)
0.57(0.1),
≤
0.0001;
mPACC:
0.095(0.024),
0.001]
across
Interestingly,
utilizing
that
displayed
higher
AD,
such
or
over
improved
biomarkers'
brain
atrophy.
We
found
especially
promising
pathophysiological
AD.
Neuronal
identified
general
indicators
neurodegeneration
dementias.
Cognitive
atrophy
best
predicted
ratios
SNAP-25/NPTX2
zeta/delta/NPTX2.
Annals of Neurology,
Journal Year:
2025,
Volume and Issue:
97(5), P. 993 - 1006
Published: Jan. 6, 2025
Objective
The
Clarity
AD
phase
III
trial
showed
that
lecanemab
reduced
amyloid
markers
in
early
Alzheimer's
disease
(AD)
and
resulted
less
decline
on
measures
of
cognition
function
than
placebo.
Herein,
we
aimed
to
characterize
amyloid‐β
(Aβ)
protofibril
(PF)
captured
by
human
cerebrospinal
fluid
(CSF)
from
living
participants
with
different
stages
AD,
which
enable
an
enhanced
understanding
the
dynamic
changes
lecanemab‐associated
Aβ‐PF
(Lec‐PF)
vivo.
Methods
We
newly
developed
a
unique
highly
sensitive
immunoassay
method
using
selectively
captures
Lec‐PF.
CSF
level
Lec‐PF,
Aβ42,
Aβ40,
p‐tau181,
p‐tau
217,
total
tau,
neurogranin
were
measured
Japanese
(n
=
163).
this
study
consisted
48
cognitively
unimpaired
Aβ‐negative
(CU–),
8
impaired
diagnosed
as
suspected
non‐Alzheimer's
pathophysiology,
9
Aβ‐positive
(CU+),
34
mild
cognitive
impairment
(MCI+),
64
dementia
(AD+).
Results
Lec‐PF
levels
significantly
increased
groups
MCI+
AD+
compared
CU–
group.
Notably,
modest
correlation
plaque‐associated
biomarkers
stronger
neurodegeneration
biomarkers,
such
tau
neurogranin,
suggesting
proximally
reflect
well
amount
senile
plaques.
Interpretation
This
is
first
report
describing
species
supporting
correlated
may
explain
mechanism
clinical
effect
lecanemab.
ANN
NEUROL
2025;97:993–1006
EBioMedicine,
Journal Year:
2025,
Volume and Issue:
112, P. 105557 - 105557
Published: Jan. 31, 2025
Synapse
preservation
is
key
for
healthy
cognitive
ageing,
and
synapse
loss
represents
a
critical
anatomical
basis
of
dysfunction
in
Alzheimer's
disease
(AD),
predicting
dementia
onset,
severity,
progression.
viewed
as
primary
pathologic
event,
preceding
neuronal
brain
atrophy
AD.
Synapses
may,
therefore,
represent
one
the
earliest
clinically
most
meaningful
targets
neuropathologic
processes
driving
AD
dementia.
The
highly
selective
particularly
vulnerable
synapses
while
leaving
others,
termed
resilient,
largely
unaffected.
Yet,
anatomic
molecular
hallmarks
resilient
populations
their
association
with
changes
(e.g.
amyloid-β
plaques
tau
tangles)
memory
remain
poorly
understood.
Characterising
selectively
may
be
to
understanding
mechanisms
versus
enable
development
robust
biomarkers
disease-modifying
therapies
Molecular Neurodegeneration,
Journal Year:
2025,
Volume and Issue:
20(1)
Published: March 14, 2025
Abstract
Alzheimer’s
disease
(AD)
is
neuropathologically
characterized
by
the
extracellular
deposition
of
amyloid-β
peptide
(Aβ)
and
intraneuronal
accumulation
abnormal
phosphorylated
tau
(τ)-protein
(p-τ).
Most
frequently,
these
hallmark
lesions
are
accompanied
other
co-pathologies
in
brain
that
may
contribute
to
cognitive
impairment,
such
as
vascular
lesions,
transactive-response
DNA-binding
protein
43
(TDP-43),
and/or
α-synuclein
(αSyn)
aggregates.
To
estimate
extent
AD
patients,
several
biomarkers
have
been
developed.
Specific
tracers
target
visualize
Aβ
plaques,
p-τ
αSyn
pathology
or
inflammation
positron
emission
tomography.
In
addition
imaging
biomarkers,
cerebrospinal
fluid,
blood-based
biomarker
assays
reflecting
AD-specific
non-specific
processes
either
already
clinical
use
development.
this
review,
we
will
introduce
pathological
brain,
related
discuss
what
respective
determined
at
post-mortem
histopathological
analysis.
It
became
evident
initial
stages
plaque
not
detected
with
currently
available
biomarkers.
Interestingly,
precedes
deposition,
especially
beginning
when
unable
detect
it.
Later,
takes
lead
accelerates
pathology,
fitting
well
known
evolution
measures
over
time.
Some
still
lack
clinically
established
today,
TDP-43
cortical
microinfarcts.
summary,
specific
for
AD-related
pathologies
allow
accurate
diagnosis
based
on
pathobiological
parameters.
Although
current
excellent
pathologies,
they
fail
which
analysis
required.
Accordingly,
neuropathological
studies
remain
essential
understand
development
early
stages.
Moreover,
there
an
urgent
need
co-pathologies,
limbic
predominant,
age-related
encephalopathy-related
modify
interacting
p-τ.
Novel
approaches
vesicle-based
cryptic
RNA/peptides
help
better
future.
Frontiers in Molecular Neuroscience,
Journal Year:
2024,
Volume and Issue:
16
Published: Jan. 5, 2024
Amyotrophic
Lateral
Sclerosis
(ALS)
and
Frontotemporal
Dementia
(FTD)
are
debilitating
neurodegenerative
diseases
with
shared
pathological
features
like
transactive
response
DNA-binding
protein
of
43
kDa
(TDP-43)
inclusions
genetic
mutations.
Both
involve
synaptic
dysfunction,
contributing
to
their
clinical
features.
Synaptic
biomarkers,
representing
proteins
associated
function
or
structure,
offer
insights
into
disease
mechanisms,
progression,
treatment
responses.
These
biomarkers
can
detect
early,
track
its
evaluate
therapeutic
efficacy.
ALS
is
characterized
by
elevated
neurofilament
light
chain
(NfL)
levels
in
cerebrospinal
fluid
(CSF)
blood,
correlating
progression.
TDP-43
another
key
biomarker,
mislocalization
linked
dysfunction.
In
FTD,
tau
studied
as
biomarkers.
neuronal
pentraxins
(NPs),
including
pentraxin
2
(NPTX2),
receptor
(NPTXR),
FTD
pathology
cognitive
decline.
Advanced
technologies,
machine
learning
(ML)
artificial
intelligence
(AI),
aid
biomarker
discovery
drug
development.
Challenges
this
research
include
technological
limitations
detection,
variability
across
patients,
translating
findings
from
animal
models.
ML/AI
accelerate
analyzing
complex
data
predicting
outcomes.
early
personalized
strategies,
mechanisms.
While
challenges
persist,
advancements
interdisciplinary
efforts
promise
revolutionize
the
understanding
management
FTD.
This
review
will
explore
present
comprehension
discuss
significance
emphasize
prospects
obstacles.
npj Parkinson s Disease,
Journal Year:
2024,
Volume and Issue:
10(1)
Published: May 17, 2024
Abstract
Lysosomal
and
synaptic
dysfunctions
are
hallmarks
in
neurodegeneration
potentially
relevant
as
biomarkers,
but
data
on
early
Parkinson’s
disease
(PD)
is
lacking.
We
performed
targeted
mass
spectrometry
with
an
established
protein
panel,
assessing
autophagy
function
cerebrospinal
fluid
(CSF)
of
drug-naïve
de
novo
PD,
sex-/age-matched
healthy
controls
(HC)
cross-sectionally
(88
46
HC)
longitudinally
(104
58
over
10
years.
Multiple
markers
autophagy,
plasticity,
secretory
pathways
were
reduced
PD.
added
samples
from
prodromal
subjects
(9
cross-sectional,
12
longitudinal)
isolated
REM
sleep
behavior
disorder,
revealing
secretogranin-2
already
decreased
compared
to
controls.
Machine
learning
identified
neuronal
pentraxin
receptor
neurosecretory
VGF
most
for
discriminating
between
groups.
CSF
levels
LAMP2,
pentraxins,
syntaxins
PD
correlated
clinical
progression,
showing
predictive
potential
motor-
non-motor
symptoms
a
valid
basis
future
drug
trials.
Alzheimer s Research & Therapy,
Journal Year:
2024,
Volume and Issue:
16(1)
Published: June 22, 2024
Studies
suggest
that
cerebrospinal
fluid
(CSF)
levels
of
amyloid-β
(Aβ)42
and
Aβ40
present
a
circadian
rhythm.
However
sustained
sampling
large
volumes
CSF
with
indwelling
intrathecal
catheters
used
in
most
these
studies
might
have
affected
dynamics
thereby
confounded
the
observed
fluctuations
biomarker
levels.
SLAS TECHNOLOGY,
Journal Year:
2025,
Volume and Issue:
unknown, P. 100257 - 100257
Published: Feb. 1, 2025
Alzheimer's
disease
(AD)
is
a
progressive
neurological
condition
characterized
by
cognitive
decline,
memory
loss,
and
aberrant
behaviour.
It
affects
millions
of
people
globally
one
the
main
causes
dementia.
The
neurodegenerative
known
as
AD
has
intricate,
multifaceted
mechanisms
that
make
it
difficult
to
comprehend
identify
in
its
early
stages.
Conventional
diagnostic
techniques
frequently
fail
detect
By
combining
Natural
Language
Processing
(NLP)
Large
Models
(LLMs),
this
research
suggests
novel
approach
for
identifying
potential
biomarkers
underlying
AD.
Clinical
data
gathered
from
publicly
accessible
databases
healthcare
facilities,
including
genetic
information,
neuroimaging
scans,
medical
records.
pre-processing
unstructured
clinical
notes
involves
tokenization
profiles
are
normalized
Z-score
normalization
consistency.
Multi-Input
Convolutional
Neural
Networks
(MI-CNN)
employed
efficiently
fuse
diverse
sources,
allowing
thorough
analysis.
Key
linked
identified
categorized
using
Genetic
Algorithm
combined
with
Bidirectional
Encoder
Representations
Transformers
(BERT)
(GenBERT).
fine-tuning
BERT's
hyperparameters
optimization
approaches,
GenBERT
enables
effective
analysis
large
datasets,
such
patient
histories,
data,
notes.
combination
strategy
increases
feature
selection
model's
capacity
minute
genomic
linguistic
patterns
suggestive
goal
integrated
provide
tools
new
insights
into
pathogenesis
disease,
which
could
transform
methods
detecting
treating
As
concerns
prediction,
model
performs
better
than
current
techniques,
obtaining
highest
accuracy
(98.30%)
F1-score
(0.97),
well
greater
precision
(0.95)
recall
(0.92).
Additionally,
demonstrates
reliably
both
positive
negative
cases
sensitivity
(98.65%)
specificity
(99.73%).
Overall,
offers
trustworthy
useful
tool
diagnosis.
