PLoS ONE,
Journal Year:
2017,
Volume and Issue:
12(3), P. e0173615 - e0173615
Published: March 9, 2017
Metabolomic
approaches
are
increasingly
used
to
identify
new
disease
biomarkers,
yet
normal
values
of
many
plasma
metabolites
remain
poorly
defined.
The
aim
this
study
was
define
the
"normal"
metabolome
in
healthy
volunteers.
We
included
800
French
volunteers
aged
between
18
and
86,
equally
distributed
according
sex,
free
any
medication
considered
on
basis
their
medical
history,
clinical
examination
standard
laboratory
tests.
quantified
185
metabolites,
including
amino
acids,
biogenic
amines,
acylcarnitines,
phosphatidylcholines,
sphingomyelins
hexose,
using
tandem
mass
spectrometry
with
Biocrates
AbsoluteIDQ
p180
kit.
Principal
components
analysis
applied
main
factors
responsible
for
variability
orthogonal
projection
latent
structures
employed
confirm
observed
patterns
pattern-related
metabolites.
established
a
metabolite
reference
dataset
144/185
Total
blood
cholesterol,
gender
age
were
identified
as
principal
explaining
variability.
High
total
cholesterol
levels
associated
higher
phosphatidylcholines
concentrations.
Compared
women,
men
had
concentrations
creatinine,
branched-chain
acids
lysophosphatidylcholines,
lower
phosphatidylcholines.
Elderly
subjects
than
young
subjects.
human
large
well-defined
population
This
provides
an
essential
baseline
defining
its
sources
variation.
American Journal of Clinical Nutrition,
Journal Year:
2015,
Volume and Issue:
102(6), P. 1518 - 1526
Published: Oct. 29, 2015
Background:
Human
metabolism
is
influenced
by
dietary
factors
and
lifestyle,
environmental,
genetic
factors;
thus,
men
who
exclude
some
or
all
animal
products
from
their
diet
might
have
different
metabolic
profiles
than
meat
eaters.
Objective:
We
aimed
to
investigate
differences
in
concentrations
of
118
circulating
metabolites,
including
acylcarnitines,
amino
acids,
biogenic
amines,
glycerophospholipids,
hexose,
sphingolipids
related
lipid,
protein,
carbohydrate
between
male
eaters,
fish
vegetarians,
vegans
the
Oxford
arm
European
Prospective
Investigation
into
Cancer
Nutrition.
Design:
In
this
cross-sectional
study,
metabolites
were
measured
mass
spectrometry
plasma
379
categorized
according
group.
Differences
mean
metabolite
across
groups
tested
using
ANOVA,
a
false
discovery
rate–controlling
procedure
was
used
account
for
multiple
testing.
Principal
component
analysis
patterns
profiles.
Results:
Concentrations
79%
differed
significantly
vast
majority
these
cases,
had
lowest
concentration,
whereas
eaters
most
often
highest
sphingolipids,
vegetarians
acids
amine.
A
clear
separation
4
seen,
with
being
noticeably
other
because
lower
glycerophospholipids
sphingolipids.
Conclusions:
Metabolic
could
effectively
differentiate
habitual
groups,
especially
vegan
compared
consume
products.
The
difference
mainly
explained
vegans.
British Journal Of Nutrition,
Journal Year:
2020,
Volume and Issue:
124(3), P. 330 - 340
Published: April 1, 2020
Primary
liver
cancer
is
the
third
leading
cause
of
cancer-related
death
worldwide.
Most
patients
are
diagnosed
at
late
stages
with
poor
prognosis;
thus,
identification
modifiable
risk
factors
for
primary
prevention
urgently
needed.
The
well-established
include
chronic
infection
hepatitis
B
virus
(HBV)
or
C
(HCV),
heavy
alcohol
consumption,
metabolic
diseases
such
as
obesity
and
diabetes,
aflatoxin
exposure.
However,
a
large
proportion
cases
worldwide
cannot
be
explained
by
current
known
factors.
Dietary
have
been
suspected
important,
but
dietary
aetiology
remains
poorly
understood.
In
this
review,
we
summarised
evaluated
observational
studies
diet
including
single
nutrients,
food
groups,
well
patterns
developing
cancer.
Although
there
knowledge
gaps
between
risk,
epidemiological
evidence
supports
an
important
role
in
development.
For
example,
exposure
to
aflatoxin,
drinking
possibly
dairy
product
(not
yogurt)
intake
increase,
while
coffee,
fish
tea,
light-to-moderate
several
healthy
(e.g.
Alternative
Healthy
Eating
Index)
may
decrease
risk.
Future
sample
size
accurate
measurement
warranted
need
consider
issues
possible
aetiological
heterogeneity
subtypes,
influence
HBV
HCV
infection,
high-risk
populations
cirrhosis)
potential
interplay
host
gut
microbiota
genetic
variations.
BMC Medicine,
Journal Year:
2018,
Volume and Issue:
16(1)
Published: Nov. 5, 2018
Environment
and
diet
in
early
life
can
affect
development
health
throughout
the
course.
Metabolic
phenotyping
of
urine
serum
represents
a
complementary
systems-wide
approach
to
elucidate
environment-health
interactions.
However,
large-scale
metabolome
studies
children
combining
analyses
these
biological
fluids
are
lacking.
Here,
we
sought
characterise
major
determinants
child
define
metabolite
associations
with
age,
sex,
BMI
dietary
habits
European
children,
by
exploiting
unique
biobank
established
as
part
Human
Early-Life
Exposome
project
(
http://www.projecthelix.eu
).Metabolic
phenotypes
matched
samples
from
1192
(aged
6-11)
recruited
birth
cohorts
six
countries
were
measured
using
high-throughput
1H
nuclear
magnetic
resonance
(NMR)
spectroscopy
targeted
LC-MS/MS
metabolomic
assay
(Biocrates
AbsoluteIDQ
p180
kit).We
identified
both
urinary
creatinine
be
positively
associated
age.
z-score
included
novel
association
4-deoxyerythreonic
acid
addition
valine,
carnitine,
short-chain
acylcarnitines
(C3,
C5),
glutamate,
BCAAs,
lysophosphatidylcholines
(lysoPC
C14:0,
lysoPC
C16:1,
C18:1,
C18:2)
sphingolipids
(SM
C16:0,
SM
C18:1).
Dietary-metabolite
creatine
phosphatidylcholines
(4)
meat
intake,
(12)
fish,
hippurate
vegetables,
proline
betaine
fruit
intake.
Population-specific
variance
(age,
BMI,
ethnicity,
country
origin)
was
better
captured
than
profile;
factors
explained
median
9.0%
amongst
metabolites
versus
5.1%
metabolites.
pathway
correlations
identified,
concentrations
corresponding
significantly
correlated
(r
>
0.18)
between
serum.We
have
pan-European
reference
for
healthy
gathered
critical
resources
not
previously
available
future
investigations
into
influence
on
health.
The
cohort
populations
studied
share
common
metabolic
main
habits.
Furthermore,
threonine
catabolism
children.
