Elevated urinary phytoestrogens are associated with delayed biological aging: a cross-sectional analysis of NHANES data
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Март 12, 2025
Dietary
phytoestrogens
have
been
suggested
to
provide
protection
against
numerous
age-related
diseases.
However,
their
effects
on
biological
aging
remain
unclear.
In
this
study,
we
cross-sectionally
investigated
the
relationship
between
urinary
phytoestrogen
levels
and
indicators
of
using
data
from
7,981
adults
who
participated
in
National
Health
Nutrition
Examination
Survey
1999–2010.
Urinary
concentrations
six
phytoestrogens,
including
four
isoflavones
two
enterolignans,
were
measured
high-performance
liquid
chromatography
(HPLC)-tandem
mass
spectrometry
(MS)
or
HPLC-atmospheric
pressure
photoionization-tandem
MS,
standardized
creatinine.
Three
age
(BA),
namely
Klemera-Doubal
method
(KDM-BA),
phenotypic
(PA),
homeostatic
dysregulation
(HD),
derived
12
clinical
biomarkers,
advanced-BAs
calculated
quantify
differences
individuals'
BAs
chronological
age,
individuals
with
all
positive
defined
as
accelerated-aging.
Weighted
linear
regression
analysis
showed
that
after
adjusting
for
demographic
lifestyle
factors
history
chronic
diseases,
elevated
total
enterolignans
significantly
associated
less
advanced-KDM,
advanced-PA,
advanced-HD,
whereas
was
advanced-KDM
advanced-PA
but
not
advanced-HD.
logistic
higher
(highest
Q4
vs.
lowest
Q1:
OR
=
0.60,
95%CI:
0.44,
0.80;
P-trend
0.002)
(Q4
0.59,
0.45,
0.76;
<
0.001)
lower
odds
accelerated-aging,
significant
0.78,
1.08;
0.05).
Subgroup
analyses
negative
associations
attenuated
non-overweight/obese
participants
current
cigarette
smokers.
conclusion,
are
related
markers
slower
aging,
suggesting
an
anti-aging
effect
dietary
consumption,
which
warrants
further
investigations
longitudinal
interventional
settings.
Язык: Английский
Epigenetic Aging Acceleration in Obesity Is Slowed Down by Nutritional Ketosis Following Very Low-Calorie Ketogenic Diet (VLCKD): A New Perspective to Reverse Biological Age
Nutrients,
Год журнала:
2025,
Номер
17(6), С. 1060 - 1060
Опубликована: Март 18, 2025
Background/Objectives:
Epigenetic
clocks
have
emerged
as
a
tool
to
quantify
biological
age,
providing
more
accurate
estimate
of
an
individual’s
health
status
than
chronological
helping
identify
risk
factors
for
accelerated
aging
and
evaluating
the
reversibility
therapeutic
strategies.
This
study
aimed
evaluate
potential
association
between
epigenetic
acceleration
age
obesity,
well
determine
whether
nutritional
interventions
body
weight
loss
could
slow
down
this
acceleration.
Methods:
Biological
was
estimated
using
three
(Horvath
(Hv),
Hannum
(Hn),
Levine
(Lv))
based
on
leukocyte
methylome
analysis
individuals
with
normal
(n
=
20),
obesity
24),
patients
following
VLCKD
10).
We
analyzed
differences
in
estimates,
relationship
impact
VLCKD.
Correlations
were
assessed
acceleration,
BMI,
various
metabolic
parameters.
Results:
Analysis
revealed
(Hv
+3.4(2.5),
Hn
+5.7(3.2),
Lv
+3.9(2.7))
compared
slight
deceleration
weight.
correlated
BMI
(p
<
0.0001).
Interestingly,
showed
both
ketosis
−3.3(4.0),
−6.3(5.3),
−8.8(4.5))
at
endpoint
−1.1(4.3),
−7.4(5.6),
−8.2(5.3)).
Relevantly,
slowdown
is
associated
0.0001),
ketonemia
≤
0.001),
parameters
0.05).
Conclusions:
Our
findings
highlight
applicability
monitor
obesity-related
precision
medicine
show
efficacy
slowing
aging.
Язык: Английский
Osteoarthritis as an Evolutionary Legacy: Biological Ageing and chondrocyte Hypertrophy
Osteoarthritis and Cartilage Open,
Год журнала:
2025,
Номер
unknown, С. 100624 - 100624
Опубликована: Май 1, 2025
Язык: Английский
Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis
npj Digital Medicine,
Год журнала:
2025,
Номер
8(1)
Опубликована: Май 29, 2025
Artificial
intelligence
(AI)-ECG-derived
age
(AI-ECG
age)
and
Heart
Delta
Age
(HDA)-the
difference
between
AI-ECG
chronological
age-are
emerging
tools
for
assessing
cardiovascular
health.
We
systematically
searched
PubMed,
Embase,
Web
of
Science,
Scopus
from
inception
through
September
2024.
Seventeen
original
studies
utilizing
AI
algorithms
to
measure
HDA
risk
factors,
outcomes,
or
mortality
were
included.
Data
pooled
using
random-
fixed-effects
models
meta-analysis.
Hypertension
diabetes
mellitus
emerged
as
the
most
prevalent
factors
contributing
higher
HDA,
while
cardiac
diseases
including
myocardial
infarction
heart
failure
demonstrated
significant
impact.
Pooled
analysis
revealed
a
association
elevated
increased
risks
all-cause
(hazard
ratio
[HR]
1.62,
95%
confidence
interval
[CI]
1.49-1.77)
(HR
2.12,
CI
1.71-2.63).
could
enhance
existing
play
critical
role
in
primary
healthcare
prevention.
Язык: Английский