Novel insight of critical genes involved in breast cancer brain metastasis: evidence from a cross-tissue transcriptome association study and validation through external clinical cohorts
BMC Cancer,
Journal Year:
2025,
Volume and Issue:
25(1)
Published: April 16, 2025
Breast
cancer
represents
the
most
prevalent
form
of
tumors
among
females
and
is
characterized
by
a
significant
genetic
component.
The
brain
frequent
site
metastasis
for
breast
cancer.
Although
numerous
loci
associated
with
(BCBM)
have
been
identified,
critical
regulatory
genes
underlying
BCBM
remain
largely
unclear.
FinnGen
R11
dataset
was
combined
Genotype-Tissue
Expression
Project
(GTEx)
Transcriptome-wide
Association
Study
(TWAS).
Unified
Test
Molecular
Signatures
(UTMOST),
Multimarker
Analysis
Genomic
Annotation
(MAGMA),
Functional
Summary-based
Imputation
(FUSION)
were
used
to
identify
candidate
genes.
Summary-data-based
mendelian
randomization
(SMR)
co-localization
performed
further
elucidate
association
between
key
BCBM.
Finally,
multiple
external
cohorts
obtained
validate
findings.
In
our
study,
12
new
identified
TWAS.
Subsequently,
both
SMR
shown
that
CAPS8
only
expressed
in
tissues
including
frontal
cortex
cerebellar
hemispheres
Potential
regulation
CASP8
could
occur
findings
ultimately
validated
clinical
cohorts.
Our
study
gene
CASP8,
which
BCBM,
providing
insights
into
occurrence
Language: Английский
A cross-tissue transcriptome-wide association study reveals GRK4 as a novel susceptibility gene for COPD
Guanglei Chen,
No information about this author
Yaxian Jin,
No information about this author
Cancan Chu
No information about this author
et al.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Nov. 18, 2024
Abstract
Chronic
obstructive
pulmonary
disease
(COPD)
is
a
prevalent
respiratory
disorder
with
environmental
factors
being
the
primary
risk
determinants.
However,
genetic
also
substantially
contribute
to
susceptibility
and
progression
of
COPD.
Although
genome-wide
association
studies
(GWAS)
have
identified
several
loci
associated
COPD
susceptibility,
specific
pathogenic
genes
underlying
these
loci,
along
their
biological
functions
roles
within
regulatory
networks,
remain
unclear.
This
lack
clarity
constrains
our
ability
achieve
deeper
understanding
basis
study
leveraged
FinnGen
R11
dataset,
comprising
21,617
cases
372,627
controls,
GTEx
V8
eQTLs
data
conduct
cross-tissue
transcriptome-wide
(TWAS).
Initially,
we
performed
TWAS
analysis
using
Unified
Test
for
Molecular
Signatures
(UTMOST),
followed
by
validation
UTMOST
findings
in
single
tissues
Functional
Summary-based
Imputation
(FUSION)
method
conditional
joint
(COJO)
analyses
genes.
Subsequently,
candidate
were
screened
Multi-marker
Analysis
Genomic
Annotation
(MAGMA).
The
causal
relationship
between
was
further
evaluated
through
summary
data-based
Mendelian
randomization
(SMR),
colocalization
analysis,
(MR).
Additionally,
results
validated
against
dataset
GWAS
Catalog
(GCST90399694).
GeneMANIA
employed
explore
functional
significance
In
17
Among
these,
novel
gene,
G
protein-coupled
receptor
kinase
4
(GRK4),
single-tissue
MAGMA
analyses,
confirmation
via
SMR,
MR,
analyses.
Moreover,
GRK4
an
independent
dataset.
identifies
as
potential
gene
COPD,
which
may
influence
exacerbating
inflammatory
responses.
address
gaps
previous
studies,
revealing
consistent
expression
function
across
different
tissues.
considering
study’s
limitations,
investigation
’s
role
are
warranted.
Language: Английский
A Cross-Tissue Transcriptome-Wide Association Study Identifies WDPCP as a Potential Susceptibility Gene for Coronary Atherosclerosis
Xinyue Hu,
No information about this author
Guanglei Chen,
No information about this author
Xiaofang Yang
No information about this author
et al.
Atherosclerosis Plus,
Journal Year:
2024,
Volume and Issue:
58, P. 59 - 74
Published: Nov. 23, 2024
Coronary
atherosclerosis
(CAS)
is
a
complex
chronic
inflammatory
disease
with
significant
genetic
and
environmental
contributions.
While
genome-wide
association
studies
(GWAS)
have
pinpointed
many
risk
loci,
over
75
%
are
in
non-coding
regions,
complicating
functional
analysis
understanding
gene-disease
mechanisms.
Language: Английский