Frontiers in Immunology,
Год журнала:
2022,
Номер
13
Опубликована: Июнь 6, 2022
The
molecular
mechanisms
of
osteoarthritis,
the
most
common
chronic
disease,
remain
unexplained.
This
study
aimed
to
use
bioinformatic
methods
identify
key
biomarkers
and
immune
infiltration
in
osteoarthritis.
Gene
expression
profiles
(GSE55235,
GSE55457,
GSE77298,
GSE82107)
were
selected
from
Expression
Omnibus
database.
A
protein-protein
interaction
network
was
created,
functional
enrichment
analysis
genomic
performed
using
Ontology
(GO)
Kyoto
Encyclopedia
Genes
Genome
(KEGG)
databases.
Immune
cell
between
osteoarthritic
tissues
control
analyzed
CIBERSORT
method.
Identify
patterns
ConsensusClusterPlus
package
R
software
a
consistent
clustering
approach.
Molecular
biological
investigations
discover
important
genes
cartilage
cells.
total
105
differentially
expressed
identified.
Differentially
enriched
immunological
response,
chemokine-mediated
signaling
pathway,
inflammatory
response
revealed
by
GO
KEGG
Two
distinct
(ClusterA
ClusterB)
identified
ConsensusClusterPlus.
Cluster
patients
had
significantly
lower
resting
dendritic
cells,
M2
macrophages,
mast
activated
natural
killer
cells
regulatory
T
than
B
patients.
levels
TCA1,
TLR7,
MMP9,
CXCL10,
CXCL13,
HLA-DRA,
ADIPOQSPP1
higher
IL-1β-induced
group
osteoarthritis
an
vitro
qPCR
experiment.
Explaining
differences
normal
will
contribute
understanding
development
Endocrine Reviews,
Год журнала:
2022,
Номер
43(6), С. 984 - 1002
Опубликована: Фев. 19, 2022
Abstract
More
than
2.1
million
age-related
fractures
occur
in
the
United
States
annually,
resulting
an
immense
socioeconomic
burden.
Importantly,
deterioration
of
bone
structure
is
associated
with
impaired
healing.
Fracture
healing
a
dynamic
process
which
can
be
divided
into
four
stages.
While
initial
hematoma
generates
inflammatory
environment
mesenchymal
stem
cells
and
macrophages
orchestrate
framework
for
repair,
angiogenesis
cartilage
formation
mark
second
period.
In
central
region,
endochondral
ossification
favors
soft
callus
development
while
next
to
fractured
bony
ends,
intramembranous
directly
forms
woven
bone.
The
third
stage
characterized
by
removal
calcification
cartilage.
Finally,
chronic
remodeling
phase
concludes
process.
Impaired
fracture
due
aging
related
detrimental
changes
at
cellular
level.
Macrophages,
osteocytes,
chondrocytes
express
markers
senescence,
leading
reduced
self-renewal
proliferative
capacity.
A
prolonged
“inflammaging”
results
extended
phase,
senescent
microenvironment
deteriorating
Although
there
evidence
that
setting
injury,
least
some
tissues,
may
play
beneficial
role
facilitating
tissue
recent
data
demonstrate
clearing
enhances
repair.
this
review,
we
summarize
physiological
as
well
pathological
processes
during
endocrine
disease
order
establish
broad
understanding
biomechanical
molecular
mechanisms
involved
Abstract
Cellular
senescence,
which
is
a
major
cause
of
tissue
dysfunction
with
aging
and
multiple
other
conditions,
known
to
be
triggered
by
p16
Ink4a
or
p21
Cip1
,
but
the
relative
contributions
each
pathway
toward
inducing
senescence
are
unclear.
Here,
we
directly
addressed
this
issue
first
developing
validating
‐
ATTAC
mouse
promoter
driving
“suicide”
transgene
encoding
an
inducible
caspase‐8
which,
upon
induction,
selectively
kills
‐expressing
senescent
cells.
Next,
used
established
INK
compare
versus
in
cellular
condition
where
phenotype
(bone
loss
increased
marrow
adiposity)
clearly
driven
senescence—specifically,
radiation‐induced
osteoporosis.
Using
RNA
situ
hybridization,
confirmed
reduction
‐driven
transcripts
following
cell
clearance
both
models.
However,
only
+,
not
cells
prevented
osteoporosis
adiposity.
Reduction
dysfunctional
telomeres
also
reduced
several
pro‐inflammatory
senescence‐associated
secretory
factors.
Thus,
comparing
using
two
parallel
genetic
models,
demonstrate
that
predominantly
rather
than
‐mediated
senescence.
Further,
approach
can
dissect
these
pathways
including
across
tissues.
Frontiers in Immunology,
Год журнала:
2022,
Номер
13
Опубликована: Июнь 6, 2022
The
molecular
mechanisms
of
osteoarthritis,
the
most
common
chronic
disease,
remain
unexplained.
This
study
aimed
to
use
bioinformatic
methods
identify
key
biomarkers
and
immune
infiltration
in
osteoarthritis.
Gene
expression
profiles
(GSE55235,
GSE55457,
GSE77298,
GSE82107)
were
selected
from
Expression
Omnibus
database.
A
protein-protein
interaction
network
was
created,
functional
enrichment
analysis
genomic
performed
using
Ontology
(GO)
Kyoto
Encyclopedia
Genes
Genome
(KEGG)
databases.
Immune
cell
between
osteoarthritic
tissues
control
analyzed
CIBERSORT
method.
Identify
patterns
ConsensusClusterPlus
package
R
software
a
consistent
clustering
approach.
Molecular
biological
investigations
discover
important
genes
cartilage
cells.
total
105
differentially
expressed
identified.
Differentially
enriched
immunological
response,
chemokine-mediated
signaling
pathway,
inflammatory
response
revealed
by
GO
KEGG
Two
distinct
(ClusterA
ClusterB)
identified
ConsensusClusterPlus.
Cluster
patients
had
significantly
lower
resting
dendritic
cells,
M2
macrophages,
mast
activated
natural
killer
cells
regulatory
T
than
B
patients.
levels
TCA1,
TLR7,
MMP9,
CXCL10,
CXCL13,
HLA-DRA,
ADIPOQSPP1
higher
IL-1β-induced
group
osteoarthritis
an
vitro
qPCR
experiment.
Explaining
differences
normal
will
contribute
understanding
development
