RNA methylation patterns, immune characteristics, and autophagy-related mechanisms mediated by N6-methyladenosine (m6A) regulatory factors in venous thromboembolism
BMC Genomics,
Год журнала:
2024,
Номер
25(1)
Опубликована: Апрель 24, 2024
Abstract
Recent
studies
have
found
a
link
between
deep
vein
thrombosis
and
inflammatory
reactions.
N6-methyladenosine
(m6A),
crucial
element
in
immunological
regulation,
is
believed
to
contribute
the
pathophysiology
of
venous
thromboembolism
(VTE).
However,
how
m6A-modified
immune
microenvironment
involved
VTE
remains
unclear.
In
present
study,
we
identified
relationship
expression
several
m6A
regulatory
elements
by
analyzing
peripheral
blood
samples
from
177
patients
with
88
healthy
controls
public
GEO
databases
GSE19151
GSE48000.
We
used
machine
learning
identify
essential
genes
constructed
diagnostic
model
for
using
multivariate
logistic
regression.
Unsupervised
cluster
analysis
revealed
marked
difference
modification
patterns
terms
cell
infiltration,
reactivity,
autophagy.
two
m6A-related
autophagy
(i.e.,
CHMP2B
SIRT1)
regulator
YTHDF3
bioinformatics.
also
examined
potential
mechanisms
through
which
may
affect
VTE.
modification,
immunity,
are
closely
linked
VTE,
offering
novel
mechanistic
therapeutic
insights.
Язык: Английский
Exploring hub pyroptosis-related genes, molecular subtypes, and potential drugs in ankylosing spondylitis by comprehensive bioinformatics analysis and molecular docking
BMC Musculoskeletal Disorders,
Год журнала:
2023,
Номер
24(1)
Опубликована: Июнь 29, 2023
Ankylosing
spondylitis
(AS)
is
a
chronic
inflammatory
autoimmune
disease,
and
the
diagnosis
treatment
of
AS
have
been
limited
because
its
pathogenesis
still
unclear.
Pyroptosis
proinflammatory
type
cell
death
that
plays
an
important
role
in
immune
system.
However,
relationship
between
pyroptosis
genes
has
never
elucidated.GSE73754,
GSE25101,
GSE221786
datasets
were
collected
from
Gene
Expression
Omnibus
(GEO)
database.
Differentially
expressed
pyroptosis-related
(DE-PRGs)
identified
by
R
software.
Machine
learning
PPI
networks
used
to
screen
key
construct
diagnostic
model
AS.
patients
clustered
into
different
subtypes
according
DE-PRGs
using
consensus
cluster
analysis
validated
principal
component
(PCA).
WGCNA
was
for
screening
hub
gene
modules
two
subtypes.
Ontology
(GO)
terms
Kyoto
Encyclopedia
Genes
Genomes
(KEGG)
pathways
enrichment
elucidate
underlying
mechanisms.
The
ESTIMATE
CIBERSORT
algorithms
reveal
signatures.
connectivity
map
(CMAP)
database
predict
potential
drugs
Molecular
docking
calculate
binding
affinity
gene.Sixteen
detected
compared
healthy
controls,
some
these
showed
significant
correlation
with
cells
such
as
neutrophils,
CD8
+
T
cells,
resting
NK
cells.
Enrichment
mainly
related
pyroptosis,
IL-1β,
TNF
signaling
pathways.
(TNF,
NLRC4,
GZMB)
screened
machine
protein-protein
interaction
(PPI)
network
establish
ROC
had
good
properties
GSE73754
(AUC:
0.881),
GSE25101
0.797),
0.713).
Using
16
DE-PRGs,
divided
C1
C2
subtypes,
differences
infiltration.
A
module
WGCNA,
suggested
function.
Three
drugs,
including
ascorbic
acid,
RO
90-7501,
celastrol,
selected
based
on
CMAP
analysis.
Cytoscape
GZMB
highest-scoring
gene.
Finally,
molecular
results
acid
formed
three
hydrogen
bonds,
ARG-41,
LYS-40,
HIS-57
(affinity:
-5.3
kcal/mol).
RO-90-7501
one
bond,
CYS-136
-8.8
celastrol
TYR-94,
HIS-57,
LYS-40
-9.4
kcal/mol).Our
research
systematically
analyzed
may
play
essential
microenvironment
Our
findings
will
contribute
further
understanding
Язык: Английский
Identification of key genes with abnormal RNA methylation modification and selected m6A regulators in ankylosing spondylitis
Immunity Inflammation and Disease,
Год журнала:
2024,
Номер
12(8)
Опубликована: Авг. 1, 2024
Abstract
Background
N6‐methyladenosine
(m6A)
has
been
identified
as
the
most
abundant
modification
of
RNA
molecules
and
aberrant
m6A
modifications
have
associated
with
development
autoimmune
diseases.
However,
role
in
ankylosing
spondylitis
(AS)
not
adequately
investigated.
Therefore,
we
aimed
to
explore
significance
regulator‐mediated
methylation
AS.
Methods
The
methylated
immunoprecipitation
sequencing
(meRIP‐seq)
digital
(Digital
RNA‐seq)
were
conducted
using
peripheral
blood
mononuclear
cells
from
three
AS
cases
healthy
controls,
identify
genes
affected
by
abnormal
methylation.
different
peaks
cross‐referenced
AS‐related
obtained
GeneCards
Suite.
Subsequently,
expression
levels
shared
differentially
expressed
(DEGs)
key
regulators
evaluated
data
68
36
controls
two
sets
(GSE25101
GSE73754).
In
addition,
results
validated
through
quantitative
polymerase
chain
reaction
(qPCR).
Results
meRIP‐seq
Digital
RNA‐seq
analyses
28
upregulated
but
downregulated
expression,
52
expression.
By
intersecting
2184
Suite,
a
total
five
DEGs:
BCL11B
,
KAT6B
IL1R1
TRIB1
ALDH2
.
Through
analysis
qPCR,
found
that
Moreover,
regulators,
WTAP
heterogeneous
nuclear
ribonucleoprotein
C,
identified.
Conclusions
conclusion,
current
study
revealed
plays
crucial
might
hence
provide
new
treatment
strategy
for
disease.
Язык: Английский