Genome-wide
association
studies
(GWAS)
have
been
remarkably
successful
in
identifying
associations
between
genetic
variants
and
imaging-derived
phenotypes.
To
date,
the
main
focus
of
these
analyses
has
on
established,
clinically-used
imaging
features.
We
sought
to
investigate
if
deep
learning
approaches
can
detect
more
nuanced
patterns
image
variability.
Psychiatry Research,
Год журнала:
2024,
Номер
339, С. 116106 - 116106
Опубликована: Июль 26, 2024
We
examined
the
relationship
between
genetic
risk
for
schizophrenia
(SZ),
using
polygenic
scores
(PRSs),
and
retinal
morphological
alterations.
Retinal
structural
vascular
indices
derived
from
optical
coherence
tomography
(OCT)
color
fundus
photography
(CFP)
PRSs
SZ
were
analyzed
in
N
=
35,024
individuals
prospective
cohort
study,
United
Kingdom
Biobank
(UKB).
Results
indicated
that
macular
ganglion
cell-inner
plexiform
layer
(mGC-IPL)
thickness
was
significantly
inversely
related
to
PRS
SZ,
this
strongest
within
higher
quintiles
independent
of
potential
confounders
age.
PRS,
however,
unrelated
characteristics,
with
exception
venular
tortuosity,
other
(macular
nerve
fiber
[mRNFL],
inner
nuclear
[INL],
cup-to-disc
ratio
[CDR]).
Additionally,
association
greater
reduced
mGC-IPL
only
significant
participants
40-49
50-59
age
groups,
not
those
60-69
group.
These
findings
suggest
thinning
is
associated
a
predisposition
may
reflect
neurodevelopmental
and/or
neurodegenerative
processes
inherent
SZ.
microvasculature
alterations,
be
secondary
consequences
do
appear
Journal of Advanced Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Март 1, 2024
The
clinical
presentations
of
dry
eye
disease
(DED)
and
depression
(DEP)
often
comanifest.
However,
the
robustness
mechanisms
underlying
this
association
were
undetermined.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 6, 2024
The
human
retina
is
part
of
the
central
nervous
system
and
can
be
easily
non-invasively
imaged
with
optical
coherence
tomography.
While
imaging
may
provide
insights
on
system-related
disorders
such
as
schizophrenia,
a
typical
challenge
are
confounders
often
present
in
schizophrenia
which
negatively
impact
retinal
health.
Here,
we
therefore
aimed
to
investigate
changes
context
common
genetic
variations
conveying
risk
measured
by
polygenic
scores.
We
used
population
data
from
UK
Biobank,
including
White
British
Irish
individuals
without
diagnosed
estimated
score
for
based
newest
genome-wide
association
study
(PGC
release
2022).
hypothesized
that
greater
susceptibility
associated
thinning,
especially
within
macula.
To
gain
additional
mechanistic
insights,
conducted
pathway-specific
associations
analyses,
focusing
gene
pathways
related
schizophrenia.
Of
65484
recruited,
48208
participants
available
matching
imaging-genetic
were
included
analysis
whom
22427
(53.48%)
female
25781
(46.52%)
male.
Our
robust
principal
component
regression
results
showed
scores
thinning
while
controlling
confounding
factors
(b
=
−0.03,
p
0.007,
pFWER
0.01).
Similarly,
found
specific
neuroinflammation
sets
revealed
significant
self-contained
0.041
(reflecting
level
association),
competitive
0.05
enrichment)).
These
go
beyond
previous
studies
suggesting
relationship
between
manifested
phenotypes.
They
indicate
mirror
reflecting
complexities
alterations
observed
connected
an
inherent
predisposition
neurodegenerative
aspects
condition.
also
suggest
potential
involvement
neuroinflammatory
pathway,
indications
overlap
findings
further
this
pathway
high
could
contribute
through
acute-phase
proteins
structural
retina.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Апрель 20, 2023
The
UK
Biobank
(UKB)
imaging
project
is
a
crucial
resource
for
biomedical
research,
but
limited
to
100,000
participants
due
cost
and
accessibility
barriers.
Here
we
used
genetic
data
predict
heritable
imaging-derived
phenotypes
(IDPs)
larger
cohort.
We
developed
evaluated
4,375
IDP
scores
(IGS)
derived
from
UKB
brain
body
images.
When
applied
who
were
not
imaged,
IGS
revealed
links
numerous
stratified
at
increased
risk
both
somatic
diseases.
For
example,
identified
individuals
higher
Alzheimer's
disease
multiple
sclerosis,
offering
additional
insights
beyond
traditional
polygenic
of
these
independent
external
cohorts,
also
those
high
in
the
All
Us
Research
Program
Disease
Neuroimaging
Initiative
study.
Our
results
demonstrate
that,
while
cohort
largely
healthy
may
be
most
enriched
management,
it
holds
immense
potential
stratifying
various
diseases
broader
cohorts.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Июнь 20, 2023
ABSTRACT
Genome-wide
association
studies
(GWAS)
have
been
remarkably
successful
in
identifying
associations
between
genetic
variation
and
imaging-derived
phenotypes.
To
date,
the
main
focus
of
these
analyses
has
established,
clinically-used
imaging
features.
Here,
we
sought
to
investigate
if
deep
learning
approaches
can
help
detect
more
nuanced
patterns
image
variability.
this
end,
used
an
autoencoder
represent
retinal
optical
coherence
tomography
(OCT)
images
from
31,135
UK
Biobank
participants.
For
each
study
subject,
obtained
a
64-dimensional
vector
representing
features
structure.
GWAS
autoencoder-derived
parameters
identified
118
statistically
significant
loci;
17
also
reached
genome-wide
significance
replication
analysis
that
included
10,409
volunteers.
These
loci
encompassed
variants
previously
linked
with
thickness
measurements,
ophthalmic
disorders
and/or
neurodegenerative
conditions
(including
dementia).
Notably,
generated
phenotypes
were
found
contribute
predictive
models
for
glaucoma
cardiovascular
disorders.
Overall,
demonstrate
self-supervised
phenotyping
OCT
enhances
discoverability
factors
influencing
morphology
provides
epidemiologically
informative
biomarkers.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 12, 2024
AbstractBackground:
Single-cell
multimodal
techniques
have
advanced
the
functional
elucidation
of
disease-relevant
loci
identified
in
genome-wide
association
studies
(GWASs).
However,
interpretation
these
variants
remains
challenging.
It
is
still
unclear
how
modulate
core
gene-regulatory
networks
specific
cell
types
to
influence
eye-and
brain-related
diseases.
Methods:
We
developed
a
computational
framework
integrate
bulk
and
single-cell
multiomic
(scRNA-seq
scATAC-seq)
profiles
with
GWAS
summary
statistics
for
identifying
critical
transcription
factor
(TF)-regulatory
regulons
through
which
genetic
eight
neuropsychiatric
five
ocular
Various
methods
were
utilized
uncover
pleiotropic
loci,
risk
genes,
key
pathways
Results:
Our
analysis
revealed
latent
factors
explaining
61.7%
variances
across
13
eye
brain
diseases,
showing
diverse
correlational
patterns
among
conditions.
We
45
91
candidate
genes
contributing
disease
risk.
Integration
sequencing
data
implicated
excitatory
neurons
microglia
eye-brain
connections.
Network-based
polygenic
enrichment
15
exhibitory
neurons,
including
BCL11A,
STAT4,
GLS1,
16
microglia,
such
as
SPI1,
FOXP2,
MEF2C.
Exhibitory
neuron-specific
functionally
involved
axon
guidance
synaptic
activity,
while
microglia-specific
related
immune
response
activation.
Conclusions:
study
reinforces
link
between
psychiatric
diseases
provides
biological
insights
into
potential
regulatory
mechanisms
implications
future
therapeutic
development.