BMC Medicine,
Journal Year:
2022,
Volume and Issue:
20(1)
Published: Jan. 11, 2022
Epidemiological
and
experimental
evidence
has
linked
chronic
inflammation
to
cancer
aetiology.
It
is
unclear
whether
associations
for
specific
inflammatory
biomarkers
are
causal
or
due
bias.
In
order
examine
altered
genetically
predicted
concentration
of
circulating
cytokines
associated
with
development,
we
performed
a
two-sample
Mendelian
randomisation
(MR)
analysis.
BMJ,
Journal Year:
2021,
Volume and Issue:
unknown, P. n2233 - n2233
Published: Oct. 26, 2021
Mendelian
randomisation
(MR)
studies
allow
a
better
understanding
of
the
causal
effects
modifiable
exposures
on
health
outcomes,
but
published
evidence
is
often
hampered
by
inadequate
reporting.
Reporting
guidelines
help
authors
effectively
communicate
all
critical
information
about
what
was
done
and
found.
STROBE-MR
(strengthening
reporting
observational
in
epidemiology
using
mendelian
randomisation)
assists
their
MR
research
clearly
transparently.
Adopting
should
readers,
reviewers,
journal
editors
evaluate
quality
studies.
This
article
explains
20
items
checklist,
along
with
meaning
rationale,
terms
defined
glossary.
Examples
transparent
are
used
for
each
item
to
illustrate
best
practices.
Cold Spring Harbor Perspectives in Medicine,
Journal Year:
2021,
Volume and Issue:
12(1), P. a040501 - a040501
Published: Aug. 23, 2021
Mendelian
randomization
(MR)
is
a
method
of
studying
the
causal
effects
modifiable
exposures
(i.e.,
potential
risk
factors)
on
health,
social,
and
economic
outcomes
using
genetic
variants
associated
with
specific
interest.
MR
provides
more
robust
understanding
influence
these
because
germline
are
randomly
inherited
from
parents
to
offspring
and,
as
result,
should
not
be
related
confounding
factors
that
exposure-outcome
associations.
The
variant
can
therefore
used
tool
link
proposed
factor
outcome,
estimate
this
effect
less
bias
than
conventional
epidemiological
approaches.
We
describe
scope
MR,
highlighting
range
applications
being
made
possible
data
sets
resources
become
larger
freely
available.
outline
approach
in
detail,
covering
concepts,
assumptions,
estimation
methods.
cover
some
common
misconceptions,
provide
strategies
for
overcoming
violation
discuss
future
prospects
extending
clinical
applicability,
methodological
innovations,
robustness,
generalizability
findings.
Science,
Journal Year:
2021,
Volume and Issue:
374(6569)
Published: Nov. 11, 2021
Detangling
gene-disease
connections
Many
diseases
are
at
least
partially
due
to
genetic
causes
that
not
always
understood
or
targetable
with
specific
treatments.
To
provide
insight
into
the
biology
of
various
human
as
well
potential
leads
for
therapeutic
development,
Pietzner
et
al
.
undertook
detailed,
genome-wide
proteogenomic
mapping.
The
authors
analyzed
thousands
between
disease-associated
mutations,
proteins,
and
medical
conditions,
thereby
providing
a
detailed
map
use
by
future
researchers.
They
also
supplied
some
examples
in
which
they
applied
their
approach
contexts
varied
connective
tissue
disorders,
gallstones,
COVID-19
infections,
sometimes
even
identifying
single
genes
play
roles
multiple
clinical
scenarios.
—YN
Nature Immunology,
Journal Year:
2023,
Volume and Issue:
24(9), P. 1540 - 1551
Published: Aug. 10, 2023
Circulating
proteins
have
important
functions
in
inflammation
and
a
broad
range
of
diseases.
To
identify
genetic
influences
on
inflammation-related
proteins,
we
conducted
genome-wide
protein
quantitative
trait
locus
(pQTL)
study
91
plasma
measured
using
the
Olink
Target
platform
14,824
participants.
We
identified
180
pQTLs
(59
cis,
121
trans).
Integration
pQTL
data
with
eQTL
disease
association
studies
provided
insight
into
pathogenesis,
implicating
lymphotoxin-α
multiple
sclerosis.
Using
Mendelian
randomization
(MR)
to
assess
causality
etiology,
both
shared
distinct
effects
specific
across
immune-mediated
diseases,
including
directionally
discordant
CD40
risk
rheumatoid
arthritis
versus
sclerosis
inflammatory
bowel
disease.
MR
implicated
CXCL5
etiology
ulcerative
colitis
(UC)
show
elevated
gut
transcript
expression
patients
UC.
These
results
targets
existing
drugs
provide
powerful
resource
facilitate
future
drug
target
prioritization.
Nature,
Journal Year:
2022,
Volume and Issue:
611(7934), P. 115 - 123
Published: Sept. 30, 2022
Previous
genome-wide
association
studies
(GWASs)
of
stroke
-
the
second
leading
cause
death
worldwide
were
conducted
predominantly
in
populations
European
ancestry1,2.
Here,
cross-ancestry
GWAS
meta-analyses
110,182
patients
who
have
had
a
(five
ancestries,
33%
non-European)
and
1,503,898
control
individuals,
we
identify
signals
for
its
subtypes
at
89
(61
new)
independent
loci:
60
primary
inverse-variance-weighted
analyses
29
secondary
meta-regression
multitrait
analyses.
On
basis
internal
validation
an
follow-up
89,084
additional
cases
(30%
1,013,843
87%
risk
loci
60%
replicated
(P
<
0.05).
Effect
sizes
highly
correlated
across
ancestries.
Cross-ancestry
fine-mapping,
silico
mutagenesis
analysis3,
transcriptome-wide
proteome-wide
revealed
putative
causal
genes
(such
as
SH3PXD2A
FURIN)
variants
GRK5
NOS3).
Using
three-pronged
approach4,
provide
genetic
evidence
drug
effects,
highlighting
F11,
KLKB1,
PROC,
GP1BA,
LAMC2
VCAM1
possible
targets,
with
drugs
already
under
investigation
F11
PROC.
A
polygenic
score
integrating
ancestry-specific
GWASs
vascular-risk
factor
(integrative
scores)
strongly
predicted
ischaemic
European,
East
Asian
African
ancestry5.
Stroke
scores
predictive
clinical
factors
52,600
clinical-trial
participants
cardiometabolic
disease.
Our
results
insights
to
inform
biology,
reveal
potential
targets
derive
prediction
tools
Wellcome Open Research,
Journal Year:
2023,
Volume and Issue:
4, P. 186 - 186
Published: Aug. 4, 2023
This
paper
provides
guidelines
for
performing
Mendelian
randomization
investigations.
It
is
aimed
at
practitioners
seeking
to
undertake
analyses
and
write
up
their
findings,
journal
editors
reviewers
assess
manuscripts.
The
are
divided
into
ten
sections:
motivation
scope,
data
sources,
choice
of
genetic
variants,
variant
harmonization,
primary
analysis,
supplementary
sensitivity
(one
section
on
robust
statistical
methods
one
other
approaches),
extensions
additional
analyses,
presentation,
interpretation.
These
will
be
updated
based
feedback
from
the
community
advances
in
field.
Updates
made
periodically
as
needed,
least
every
24
months.
Cell,
Journal Year:
2021,
Volume and Issue:
184(18), P. 4784 - 4818.e17
Published: Aug. 26, 2021
Osteoarthritis
affects
over
300
million
people
worldwide.
Here,
we
conduct
a
genome-wide
association
study
meta-analysis
across
826,690
individuals
(177,517
with
osteoarthritis)
and
identify
100
independently
associated
risk
variants
11
osteoarthritis
phenotypes,
52
of
which
have
not
been
the
disease
before.
We
report
thumb
spine
differences
in
genetic
effects
between
weight-bearing
non-weight-bearing
joints.
sex-specific
early
age-at-onset
loci.
integrate
functional
genomics
data
from
primary
patient
tissues
(including
articular
cartilage,
subchondral
bone,
osteophytic
cartilage)
high-confidence
effector
genes.
provide
evidence
for
correlation
phenotypes
related
to
pain,
main
symptom,
likely
causal
genes
linked
neuronal
processes.
Our
results
insights
into
key
molecular
players
processes
highlight
attractive
drug
targets
accelerate
translation.