Heart,
Год журнала:
2019,
Номер
106(9), С. 691 - 697
Опубликована: Окт. 31, 2019
Objectives
We
recently
identified
a
health
conscious
food
pattern
(HCFP)
associated
with
reduced
risk
of
cardiometabolic
disease.
However,
the
molecular
events
linking
healthy
to
disease
are
unknown.
Our
aim
was
identify
plasma
metabolites
HCFP
and
test
if
such
predict
mortality.
Methods
Using
liquid-chromatography
mass-spectrometry,
112
were
measured
in
3236
participants
without
cardiovascular
(CVD)
diabetes
mellitus
from
population-based
Malmö
Diet
Cancer
study.
Metabolites
using
multivariable
adjusted
linear
regressions
followed
by
Bonferroni
correction.
The
dietary
biomarkers
subsequently
related
mortality
during
long-term
follow-up
Cox
proportional
hazards
models.
Results
During
median
time
21.4
years,
603
developed
CVD,
362
843
died.
Five
at
baseline
(p<0.0004)
four
predicted
least
one
studied
end
points
(p<0.05).
Ergothioneine
metabolite
most
strongly
connected
lower
coronary
(HR
per
1
SD
increment
ergothioneine,
HR=0.85,
p=0.01),
(HR=0.79,
p=0.002)
overall
(HR=0.86,
p=4e-5).
Conclusions
that
higher
ergothioneine
an
independent
marker
mortality,
which
potentially
can
be
induced
specific
intake.
Although
nut
consumption
has
been
associated
with
a
reduced
risk
of
cardiovascular
disease
and
all-cause
mortality,
data
on
less
common
causes
death
not
systematically
assessed.
Previous
reviews
missed
several
studies
additional
have
since
published.
We
therefore
conducted
systematic
review
meta-analysis
disease,
total
cancer,
cause-specific
mortality.
PubMed
Embase
were
searched
for
prospective
mortality
in
adult
populations
published
up
to
July
19,
2016.
Summary
relative
risks
(RRs)
95%
confidence
intervals
(CIs)
calculated
using
random-effects
models.
The
burden
attributable
low
was
selected
regions.
Twenty
(29
publications)
included
the
meta-analysis.
summary
RRs
per
28
grams/day
increase
intake
coronary
heart
0.71
(95%
CI:
0.63–0.80,
I2
=
47%,
n
11),
stroke,
0.93
0.83–1.05,
14%,
0.79
0.70–0.88,
60%,
12),
0.85
0.76–0.94,
42%,
8),
0.78
0.72–0.84,
66%,
15),
from
respiratory
0.48
0.26–0.89,
61%,
3),
diabetes,
0.61
0.43–0.88,
0%,
4),
neurodegenerative
0.65
0.40–1.08,
5.9%,
infectious
0.25
0.07–0.85,
54%,
2),
kidney
0.27
0.04–1.91,
2).
results
similar
tree
nuts
peanuts.
If
associations
are
causal,
an
estimated
4.4
million
premature
deaths
America,
Europe,
Southeast
Asia,
Western
Pacific
would
be
below
20
grams
day
2013.
Higher
is
cancer
infections.
Proceedings of the National Academy of Sciences,
Год журнала:
2016,
Номер
113(16), С. 4252 - 4259
Опубликована: Март 28, 2016
Significance
Human
blood
provides
a
rich
source
of
information
about
metabolites
that
reflects
individual
differences
in
health,
disease,
diet,
and
lifestyle.
The
coefficient
variation
for
human
enriched
red
cells
or
plasma
was
quantified
after
careful
preparation.
We
identified
14
age-related
metabolites.
Metabolites
decline
strikingly
the
elderly
include
antioxidants
compounds
involved
high
physical
activity,
including
carnosine,
UDP-acetyl-glucosamine,
ophthalmic
acid,1,5-anhydroglucitol,
NAD
+
,
leucine.
increase
significantly
related
to
declining
renal
liver
function.
Statistical
analysis
suggests
certain
either
increased
decreased
are
correlated.
Individual
variability
may
lead
identify
candidates
markers
aging
relevant
diseases.
American Journal of Clinical Nutrition,
Год журнала:
2018,
Номер
108(5), С. 1069 - 1091
Опубликована: Апрель 27, 2018
High
dietary
intake
or
blood
concentrations
(as
biomarkers
of
intake)
vitamin
C,
carotenoids,
and
E
have
been
associated
with
reduced
risk
cardiovascular
disease,
cancer,
mortality,
but
these
associations
not
systematically
assessed.
Clinical Chemistry,
Год журнала:
2017,
Номер
64(1), С. 82 - 98
Опубликована: Окт. 17, 2017
Abstract
BACKGROUND
Nutritional
metabolomics
is
rapidly
evolving
to
integrate
nutrition
with
complex
data
discover
new
biomarkers
of
nutritional
exposure
and
status.
CONTENT
The
purpose
this
review
provide
a
broad
overview
the
measurement
techniques,
study
designs,
statistical
approaches
used
in
metabolomics,
as
well
describe
current
knowledge
from
epidemiologic
studies
identifying
metabolite
profiles
associated
intake
individual
nutrients,
foods,
dietary
patterns.
SUMMARY
A
wide
range
technologies,
databases,
computational
tools
are
available
phenotypic
information.
Biomarkers
identified
use
high-throughput
techniques
include
amino
acids,
acylcarnitines,
carbohydrates,
bile
purine
pyrimidine
metabolites,
lipid
classes.
most
extensively
studied
food
groups
fruits,
vegetables,
meat,
fish,
bread,
whole
grain
cereals,
nuts,
wine,
coffee,
tea,
cocoa,
chocolate.
We
16
that
evaluated
signatures
Dietary
patterns
examined
included
vegetarian
lactovegetarian
diets,
omnivorous
diet,
Western
patterns,
prudent
Nordic
Mediterranean
diet.
Although
many
foods
have
been
identified,
those
may
not
be
sensitive
or
specific
intakes.
Some
represent
short-term
intakes
rather
than
long-term
habits.
Nonetheless,
holds
promise
for
development
robust
unbiased
strategy
measuring
Still,
technology
intended
complementary,
replacement,
traditional
well-validated
assessment
methods
such
frequency
questionnaires
can
measure
usual
relevant
studies.
European Heart Journal,
Год журнала:
2020,
Номер
41(28), С. 2645 - 2656
Опубликована: Март 18, 2020
Abstract
Aims
To
investigate
whether
metabolic
signature
composed
of
multiple
plasma
metabolites
can
be
used
to
characterize
adherence
and
response
the
Mediterranean
diet
such
a
is
associated
with
cardiovascular
disease
(CVD)
risk.
Methods
results
Our
primary
study
cohort
included
1859
participants
from
Spanish
PREDIMED
trial,
validation
cohorts
6868
US
Nurses’
Health
Studies
I
II,
Professionals
Follow-up
Study
(NHS/HPFS).
Adherence
was
assessed
using
validated
Diet
Screener
(MEDAS),
metabolome
profiled
by
liquid
chromatography-tandem
mass
spectrometry.
We
observed
substantial
metabolomic
variation
respect
adherence,
nearly
one-third
assayed
significantly
MEDAS
(false
discovery
rate
<
0.05).
Using
elastic
net
regularized
regressions,
we
identified
signature,
comprised
67
metabolites,
robustly
correlated
in
both
NHS/HPFS
(r
=
0.28–0.37
between
MEDAS;
P
3
×
10−35
4
10−118).
In
multivariable
Cox
showed
significant
inverse
association
CVD
incidence
after
adjusting
for
known
risk
factors
(PREDIMED:
hazard
ratio
[HR]
per
standard
deviation
increment
0.71,
0.001;
NHS/HPFS:
HR
0.85,
0.001),
persisted
further
adjustment
scores
0.73,
0.004;
0.004).
Further
genome-wide
analysis
revealed
that
genetic
loci
involved
fatty
acids
amino
metabolism.
Mendelian
randomization
analyses
genetically
inferred
coronary
heart
(CHD)
stroke
(odds
ratios
SD
0.92
CHD
0.91
stroke;
0.001).
Conclusions
reflects
diet,
predicts
future
independent
traditional
factors,
cohorts.
Journal of Translational Medicine,
Год журнала:
2020,
Номер
18(1)
Опубликована: Дек. 1, 2020
Abstract
Aberrant
metabolism
is
the
root
cause
of
several
serious
health
issues,
creating
a
huge
burden
to
and
leading
diminished
life
expectancy.
A
dysregulated
induces
secretion
molecules
which
in
turn
trigger
inflammatory
pathway.
Inflammation
natural
reaction
immune
system
variety
stimuli,
such
as
pathogens,
damaged
cells,
harmful
substances.
Metabolically
triggered
inflammation,
also
called
metaflammation
or
low-grade
chronic
consequence
synergic
interaction
between
host
exposome—a
combination
environmental
drivers,
including
diet,
lifestyle,
pollutants
other
factors
throughout
span
an
individual.
Various
levels
inflammation
are
associated
with
lifestyle-related
diseases
diabetes,
obesity,
metabolic
fatty
liver
disease
(MAFLD),
cancers,
cardiovascular
disorders
(CVDs),
autoimmune
diseases,
lung
diseases.
Chronic
growing
concern
worldwide,
placing
heavy
on
individuals,
families,
governments,
health-care
systems.
New
strategies
needed
empower
communities
worldwide
prevent
treat
these
Precision
medicine
provides
model
for
next
generation
lifestyle
modification.
This
will
capitalize
dynamic
individual’s
biology,
behavior,
environment.
The
aim
precision
design
improve
diagnosis,
therapeutics
prognostication
through
use
large
complex
datasets
that
incorporate
individual
gene,
function,
variations.
implementation
high-performance
computing
(HPC)
artificial
intelligence
(AI)
can
predict
risks
greater
accuracy
based
available
multidimensional
clinical
biological
datasets.
AI-powered
clinicians
opportunity
specifically
tailor
early
interventions
each
In
this
article,
we
discuss
strengths
limitations
existing
evolving
recent,
data-driven
technologies,
AI,
preventing,
treating
reversing
Nutrients,
Год журнала:
2019,
Номер
11(5), С. 1092 - 1092
Опубликована: Май 16, 2019
A
main
challenge
in
nutritional
studies
is
the
valid
and
reliable
assessment
of
food
intake,
as
well
its
effects
on
body.
Generally,
intake
measurement
based
self-reported
dietary
questionnaires,
which
have
inherent
limitations.
They
can
be
overcome
by
use
biomarkers,
capable
objectively
assessing
consumption
without
bias
assessment.
Another
major
goal
to
determine
biological
foods
their
impact
health.
Systems
analysis
dynamic
responses
may
help
identify
biomarkers
indicative
body
at
same
time,
possibly
relation
individuals’
health/disease
states.
Such
could
used
quantify
validate
analyse
physiological
or
pathological
certain
components
diets,
persons
with
specific
deficiency,
provide
information
inter-individual
variations
formulate
personalized
recommendations
achieve
optimal
health
for
particular
phenotypes,
currently
referred
“precision
nutrition.”
In
this
regard,
holistic
approaches
using
global
methods
(omics
approaches),
gathering
high
amounts
data,
appear
very
useful
new
enhance
our
understanding
role
disease.
The Lancet Diabetes & Endocrinology,
Год журнала:
2017,
Номер
5(3), С. 184 - 195
Опубликована: Янв. 13, 2017
BackgroundAccurate
monitoring
of
changes
in
dietary
patterns
response
to
food
policy
implementation
is
challenging.
Metabolic
profiling
allows
simultaneous
measurement
hundreds
metabolites
urine,
the
concentrations
which
can
be
affected
by
intake.
We
hypothesised
that
metabolic
profiles
urine
samples
developed
under
controlled
feeding
conditions
reflect
intake
and
used
model
classify
free-living
populations.MethodsIn
this
randomised,
controlled,
crossover
trial,
we
recruited
healthy
volunteers
(aged
21–65
years,
BMI
20–35
kg/m2)
from
a
database
clinical
research
unit
UK.
four
interventions
with
stepwise
variance
concordance
WHO
eating
guidelines
aim
prevent
non-communicable
diseases
(increase
fruits,
vegetables,
whole
grains,
fibre;
decrease
fats,
sugars,
salt).
Participants
attended
inpatient
stays
(72
h
each,
separated
at
least
5
days),
during
they
were
given
one
intervention.
The
order
diets
was
randomly
assigned
across
study
visits.
Randomisation
done
an
independent
investigator,
use
opaque,
sealed,
sequentially
numbered
envelopes
each
contained
random
order.
investigators
not
masked
intervention,
but
analysing
data
randomisation
During
period,
collected
daily
over
three
timed
periods:
morning
(0900–1300
h),
afternoon
(1300–1800
evening
overnight
(1800–0900
h);
24
obtained
pooling
these
samples.
Urine
assessed
proton
nuclear
magnetic
resonance
(1H-NMR)
spectroscopy,
diet-discriminatory
identified.
urinary
metabolite
models
for
diet
identified
associated
profiles,
then
validated
using
INTERMAP
UK
cohort
(n=225)
healthy-eating
Danish
(n=66).
This
registered
ISRCTN,
number
ISRCTN43087333.FindingsBetween
Aug
13,
2013,
May
18,
2014,
contacted
300
people
letter
invitation.
78
responded,
whom
26
eligible
invited
attend
health
screening.
Of
20
participants
who
19
completed
all
72
between
Oct
2,
July
29,
consumed
provided.
Analysis
1H-NMR
spectroscopy
indicated
distinct.
Significant
differences
seen
lowest
highest
risks.
Application
derived
validation
datasets
confirmed
association
(p<0·0001)
(p<0·0001).InterpretationUrinary
highly
environment
groups
into
consumers
lower
or
higher
disease
risk
on
basis
multivariate
patterns.
approach
enables
objective
population
settings
enhances
validity
reporting.FundingUK
National
Institute
Health
Research
Medical
Council.