Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Дек. 28, 2024
Parkinson's
disease
(PD)
is
the
second
most
common
age-related
neurodegenerative
after
Alzheimer's
disease.
Despite
numerous
studies,
specific
factors
remain
unidentified.
This
study
employed
a
multi-omics
approach
to
investigate
link
between
PD
and
aging.
We
integrated
blood
gene
expression
profiles,
quantitative
trait
loci,
genome-wide
association
predictive
models,
conducted
clinical
validation.By
analyzing
datasets,
total
of
953
differentially
expressed
genes
(DEGs)
10
intersecting
aging
(ADEGs)
were
identified.
Enrichment
analysis
revealed
that
regulatory
pathways
these
ADEGs
involve
classical
Wnt
signaling
pathway,
endoplasmic
reticulum
stress,
neuronal
apoptosis.
Mendelian
randomization
(MR)
showed
MAP3K5
significantly
reduces
risk
PD.
Multivariate
regression
identified
MXD1,
CREB1,
SIRT3
as
key
diagnostic
constructed
model
aid
decision-making.
Enzyme-linked
immunosorbent
assay
experiments
validated
levels
in
serum
patients.This
utilized
identify
their
mechanisms
PD,
leading
establishment
model.
The
resource
accessible
at
this
link:
https://yunhaihupo.shinyapps.io/DynNomapp
.
web
application
can
be
used
standalone
explore
changes
transcription
profiles
relationship
aspects,
generating
new
research
hypotheses.
CNS Neuroscience & Therapeutics,
Год журнала:
2024,
Номер
30(5)
Опубликована: Май 1, 2024
Parkinson's
disease
(PD)
is
a
degenerative
neurological
condition
marked
by
the
gradual
loss
of
dopaminergic
neurons
in
substantia
nigra
pars
compacta.
The
precise
etiology
PD
remains
unclear,
but
emerging
evidence
suggests
significant
role
for
disrupted
autophagy-a
crucial
cellular
process
maintaining
protein
and
organelle
integrity.
Computer Methods in Biomechanics & Biomedical Engineering,
Год журнала:
2025,
Номер
unknown, С. 1 - 13
Опубликована: Янв. 1, 2025
The
effect
of
ferroptosis-related
long
non-coding
RNAs
(lncRNAs)
in
predicting
immunotherapy
response
to
glioblastoma
(GBM)
remains
obscure.
This
study
established
a
11-lncRNAs
prognostic
signature.
Differential
gene
expression
analysis,
univariate
and
multivariate
Cox
regression
analyses
the
least
absolute
shrinkage
selection
operator
(LASSO)
algorithm
were
used
identify
genes
establish
nomogram
model
risk
score.
Kaplan-Meier
survival
plots
receiver
operating
characteristic
(ROC)
curve
analysis
evaluate
accuracy
TCGA-GBM
cohort.
To
verify
these
signatures,
we
analyzed
levels
three
lncRNAs
(AGAP2-AS1,
OSMR-AS1,
UNC5B-AS1)
LN229
U87
cells.
ROC
showed
that
area
under
(AUC)
this
signature
is
0.814,
suggesting
it
has
promising
performance
on
GBM
prediction.
rate
patients
high-risk
group
was
significantly
lower
than
low-risk
group,
prediction
superior
conventional
clinicopathological
factors.
Further
qRT-PCR
experiment
also
confirmed
our
lncRNA
signatures.
These
might
be
therapeutic
targets
for
glioblastoma,
targeting
can
improve
efficacy
immunotherapy,
especially
immune
checkpoint
inhibitors.
Mechanistically,
findings
attribute
N6-methyladenosine
(m6A)
mRNA
modification
lncRNAs.
