Metabolomics in human nutrition: opportunities and challenges.
ABSTRACT Metabolomics has been widely adopted in pharmacology and toxicology but is relatively new in human nutrition. The ultimate goal, to understand the effects of exogenous compounds on human metabolic regulation, is similar in all 3 fields. However, the application of metabolomics to nutritional research will be met with unique challenges. Little is known of the extent to which changes in the nutrient content of the human diet elicit changes in metabolic profiles. Moreover, the metabolomic signal from nutrients absorbed from the diet must compete with the myriad of nonnutrient signals that are absorbed, metabolized, and secreted in both urine and saliva. The large-bowel microflora also produces significant metabolic signals that can contribute to and alter the metabolome of biofluids in human nutrition. Notwithstanding these possible confounding effects, every reason exists to be optimistic about the potential of metabolomics for the assessment of various biofluids in nutrition research. This potential lies both in metabolic profiling through the use of pattern-recognition statistics on assigned and unassigned metabolite signals and in the collection of comprehensive data sets of identified metabolites; both objectives have the potential to distinguish between different dietary treatments, which would not have been targeted with conventional techniques. The latter objective sets out a well-recognized challenge to modern biology: the development of libraries of small molecules to aid in metabolite identification. The purpose of the present review was to highlight some early challenges that need to be addressed if metabolomics is to realize its great potential in human nutrition.
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ABSTRACT: Successful therapy for chronic diseases must normalize a targeted aspect of metabolism without disrupting the regulation of other metabolic pathways essential for maintaining health. Use of a limited number of single molecule surrogates for disease, or biomarkers, to monitor the efficacy of a therapy may fail to predict undesirable side effects. In this study, a comprehensive metabolomic assessment of lipid metabolites was employed to determine the specific effects of the peroxisome proliferator-activated receptor gamma (PPARgamma) agonist rosiglitazone on structural lipid metabolism in a new mouse model of Type 2 diabetes. Dietary supplementation with rosiglitazone (200 mg/kg diet) suppressed Type 2 diabetes in obese (NZO x NON)F1 male mice, but chronic treatment markedly exacerbated hepatic steatosis. The metabolomic data revealed that rosiglitazone i) induced hypolipidemia (by dysregulating liver-plasma lipid exchange), ii) induced de novo fatty acid synthesis, iii) decreased the biosynthesis of lipids within the peroxisome, iv) substantially altered free fatty acid and cardiolipin metabolism in heart, and v) elicited an unusual accumulation of polyunsaturated fatty acids within adipose tissue. These observations suggest that the phenotypes induced by rosiglitazone are mediated by multiple tissue-specific metabolic variables. Because many of the effects of rosiglitazone on tissue metabolism were reflected in the plasma lipid metabolome, metabolomics has excellent potential for developing clinical assessments of metabolic response to drug therapy.The Journal of Lipid Research 12/2002; 43(11):1809-17. · 5.56 Impact Factor
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ABSTRACT: The later that a molecule or molecular class is lost from the drug development pipeline, the higher the financial cost. Minimizing attrition is therefore one of the most important aims of a pharmaceutical discovery programme. Novel technologies that increase the probability of making the right choice early save resources, and promote safety, efficacy and profitability. Metabonomics is a systems approach for studying in vivo metabolic profiles, which promises to provide information on drug toxicity, disease processes and gene function at several stages in the discovery-and-development process.dressNature Reviews Drug Discovery 03/2002; 1(2):153-61. · 29.01 Impact Factor
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ABSTRACT: Gas chromatography-mass spectrometry based metabolite profiling of biological samples is rapidly becoming one of the cornerstones of functional genomics and systems biology. Thus, the technology needs to be available to many laboratories and open exchange of information is required such as those achieved for transcript and protein data. The key-step in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations with composite structure. Collections of mass spectra, which comprise frequently observed identified and non-identified metabolites, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here, we describe a platform for mass spectral and retention time index libraries that will enable this process (MSRI; www.csbdb.mpimp-golm.mpg.de/gmd.html). This resource should ameliorate many of the problems that each laboratory will face both for the initial establishment of metabolome analysis and for its maintenance at a constant sample throughput.FEBS Letters 03/2005; 579(6):1332-7. · 3.54 Impact Factor
Metabolomics in human nutrition: opportunities and challenges1–3
Michael J Gibney, Marianne Walsh, Lorraine Brennan, Helen M Roche, Bruce German, and Ben van Ommen
Metabolomics has been widely adopted in pharmacology and toxi-
understand the effects of exogenous compounds on human meta-
metabolomics to nutritional research will be met with unique chal-
over, the metabolomic signal from nutrients absorbed from the diet
must compete with the myriad of nonnutrient signals that are ab-
sorbed, metabolized, and secreted in both urine and saliva. The
large-bowel microflora also produces significant metabolic signals
nutrition. Notwithstanding these possible confounding effects, ev-
for the assessment of various biofluids in nutrition research. This
potential lies both in metabolic profiling through the use of pattern-
and in the collection of comprehensive data sets of identified me-
tabolites; both objectives have the potential to distinguish between
different dietary treatments, which would not have been targeted
with conventional techniques. The latter objective sets out a well-
ies of small molecules to aid in metabolite identification. The pur-
pose of the present review was to highlight some early challenges
that need to be addressed if metabolomics is to realize its great
metabolic pathways, pattern recognition, metabolic profiling
Such profiling has been targeted at specific ranges of plasma
nutrients and metabolites, depending on the hypothesis being
tested. Today, with rapid advances in analytic chemistry tech-
nologies such as nuclear magnetic resonance (NMR) spectros-
copy and mass spectrometry (MS), the capacity exists for a far
pounds in various human biofluids. This approach to human
assessment can be either open-ended through total data capture
(1) or highly targeted, such as measuring the full spectrum of
lipids (2). Of course, the assessment can also be both, and this
comprehensive spectrum of metabolites and nutrients is known
as the metabolome. Whereas the potential of metabolomics in
bonomics, 2 terms that in effect mean the same thing, have
emerged from the fields of plant science and pharmacology,
respectively. The former term is now more widely accepted (4),
both terms. Metabolomics will be central to biology in the com-
ing decades because it has been highlighted for funding in the
recently published roadmap of the US National Institutes of
Health (NIH) (5). Note that this review focuses on the study of
human nutrition and excludes studies of animal models, which
were extensively reviewed previously (6).
center around the vast output of spectral data on compounds in
1From the Nutrition Unit, Department of Clinical Medicine, Trinity Col-
lege, Dublin, Ireland (MJG, MW, and HMR); the Department of Biochem-
istry, Conway Institute of Biomolecular and Biomedical Research, Univer-
sity College, Dublin, Ireland (LB); the Department of Nutrition, University
of California, Davis, CA and the Nestle Nutrition Research Centre, Lau-
2Supported by the Irish Research Council for Science, Engineering, and
Technology (postgraduate studentship to MW); the Health Research Board,
Ireland (LM); an EU funded Integrated Project (Lipgene; www.lipgene.tc-
Blood Fellowship Programme (HR); an EU funded Network of Excellence
(NuGo; www.nugo.org; directorship to BvO); and the Center for Children’s
Environmental Health & The CHARGE Study University of California,
Davis (grant P01 ES11269 to BG).
Unit, Department of Clinical Medicine, Trinity Health Science Centre, St
James’s Hospital, Dublin 8, Ireland. E-mail: firstname.lastname@example.org.
Received February 22, 2005.
Accepted for publication May 16, 2005.
Am J Clin Nutr 2005;82:497–503. Printed in USA. © 2005 American Society for Clinical Nutrition
by on November 3, 2006
biofluids, which are generated by advanced 1- or 2-dimensional
MS and NMR technologies (Figure 1). The first challenge must
be to identify all the chemicals in different biofluids that are
be to gain a consensus for the definition of a metabolome in
human nutrition. The second biggest challenge associated with
the large NMR and MS outputs is how to work with these large
total data-capture data sets in which many compounds remain
with these partially resolved data sets and, thus far, have been
very successful in identifying the metabolic signatures of many
offers enormous potential. These are the core issues of this re-
as the value of different biofluids in nutritional metabolomics,
and the linkage of metabolomics with the wider elements of
Creating the human nutrition metabolome
Metabolomics is about small molecules, and one of the key
aims of metabolomics is to identify those small molecules that
so doing, deepen our knowledge of human health and the inter-
acting and regulatory roles of nutrition. Comparable goals exist
pounds in chromatograms. However, only a limited capacity to
a comprehensive library of small molecules for NMR and MS
spectra is not yet publicly available. Although some compounds
can be identified, the complete identification of all compounds
will require considerable additional analyses, in many instances
beyond the scope of the average researcher. For example, in a
detailed study of deproteinized plasma, 38 compounds were
identified with the use of1H NMR but 14 (25%) were unidenti-
fied (7). Because MS is a far more sensitive method than NMR,
nology. Thus, it is not surprising that the application of gas
chromatography–time-of-flight–MS technology to understand
the metabolome of Corynebacterium glutamicus led to the iden-
tification of only one-half of the metabolome (8).
this initiative, the Molecular Libraries Screening Center Net-
work was established, a new chemoinformatics database was
on 500 000 chemicals. Many of these chemicals will be used in
the rapidly expanding field of small-molecule microarrays for
to sequester compounds that have a binding affinity with the
small molecule. In the plant sciences, a new initiative to create a
tion times has been established (8). The Standard Reference
Database of the National Institute of Standards and Technology
will also be valuable in this regard (11). The challenges for the
nutrition sciences will be to create a consensus of small mole-
cules that are important for the study of metabolomics and then
to create the standards needed for their identification with MS,
NMR, and other emerging technologies.
This then begs the question of how we might create a list of
nutrients and metabolites that might populate the ideal metabo-
lome. Recently, the enzyme classification number mapping of
FIGURE 1. A typical 500-MHz1H nuclear magnetic resonance spectrum of human urine. The identification of the major metabolites is highlighted. 1,
GIBNEY ET AL
by on November 3, 2006
metabolically active enzymes to metabolic pathway and to ge-
database was used to assign 2709 human enzymes to 135 pre-
dicted metabolic pathways (12). Many metabolites will exist in
signaling, receptor binding, translocation, and other reaction
pathways. However, it must be possible to begin to list the key
metabolites of the various metabolic pathways that nutrients are
involved in and to begin to build up a library of compounds that
particularly interest nutritionists. A first priority must be to an-
ways along with the mineral, trace element, and vitamin metab-
olism pathways. These pathways will involve anabolic and
ways. Subsequently, we will need to address reproductive, in-
flammatory, satiety, and other such pathways as well as tissue-
specific pathways, signaling pathways, and cell regulatory
their relevance in human nutrition.
Pattern-recognition techniques and their application to
The large data sets produced with the use of metabolomic
analyses in pharmacology and toxicology have been used to
to the uses described in the previous section, and they have also
is supervised and separates classes of individuals or animals. To
date, pattern-recognition techniques have been used in metabo-
for cardiovascular disease (1), for multiple sclerosis (14), for
hypertension (15), for epithelial ovarian cancer (16), for the
detection of inborn errors of metabolism (17), for species of
animals (18), for strains of animals within a species (19), for
animals treated with drugs (3) or fed different diets, for humans
locations (21, 22). This application of metabolomics may have
great potential in nutrition research, but the issues raised in en-
suing parts of this review that relate to the nonnutrient elements
of human foods will need to be factored in when comparing
different diets. If these effects can be either eliminated or con-
trolled for in some way, then pattern-recognition approaches
offer enormous opportunities for the identification of the meta-
bolic signatures of different diets. If a protocol for linking NMR
or MS metabolomics to phenotypes can be established and an-
notated to an international standard, and if corresponding data-
human nutrition will experience a giant leap. So great is that
thorough and collaborative efforts. Thus, any expert group that
sets out to define a consensus on the nutritional metabolome, as
described in the previous section, should also be charged with
setting up the standards that will allow the creation of databases
that link metabolomes to phenotypes.
In pharmacology and toxicology, a major international col-
laborative project (the Consortium on Metabonomics in Toxi-
cology) is underway to fully characterize the NMR-derived
to 150 drug-development compounds of interest (19). A similar
lomics works with both the knowns and unknowns in the large
NMR and MS outputs, in ensuing sections we discuss that in
exogenous and endogenous factors that may influence the
metabolome under question are taken into account (Figure 2).
Metabolomics and food
magnitude. For example, plants accumulate secondary metabo-
lites for defense, reproduction, and so forth; however, none of
these are essential nutrients. In traditional nutrition, these phy-
FIGURE 2. Exogenous and endogenous factors likely to influence the human nutritional metabolome.
METABOLOMICS IN HUMAN NUTRITION
by on November 3, 2006
estrogen analogues in cancer (23). These nonnutrients with po-
red wine, coffee, fruit, fish, and vegetables, nonnutrients also
exist in the food supply, some of which are man-made and are
present either intentionally or accidentally (Figure 3).
A few examples of the effects of nonnutrients are worth con-
sidering. Salicyluric and salicylic acids, which are generally
found in fruit and vegetables, are excreted in urine at higher
concentrations in vegetarians than in omnivores (24). Allylmer-
capturic acid, found in garlic, is recovered in urine in high con-
centrations after garlic ingestion (25). This study also showed
is 6 h, which indicates the potential of nonnutrients from plant
a fact borne out by other examples cited in this review. Certain
foods are known to produce obvious changes in urine in some,
some individuals, beetroot produces red urine; in others, aspar-
agus gives rise to malodorous urine (26). Metabolites of coffee
are detected in urine collected 4–5 h after coffee ingestion (27).
In that study, the concentrations of the compounds that were
metabolized by the cytochrome P450 1A2 pathway were in-
creased by as much as 13-fold over baseline. The appearance of
270 g fried onions has been studied (28), and 18 of the quercitin
metabolites were found in urine collected 0–4 h after the test
30) and in saliva (31); epoxy resins from food-packaging mate-
rial have also been detected in urine (32).
Finally, we need to consider the chemical transformation of
the food matrix after foods are cooked or digested. This brings
animal food into consideration as sources of significant nonnu-
trient signals. In one study, concentrations of heterocyclic
amines, which are produced when meats are grilled, were found
to increase 14–38-fold in urine on the day after grilled beef was
eaten and returned to baseline concentrations within 48–72 h
after the cessation of meat intake (33). These compounds have
a single meal of grilled chicken; in this study, most of the target
metabolites were excreted within 12 h of the test meal, and very
low concentrations were found at hour 18 (34). Clearly, careful
chronic dietary interventions could be undone by the acute in-
gestion of different foods the evening before final biofluid sam-
ples are taken. Thus, dietary nonnutrients, which may not be
important in pharmacology or toxicology, may be critically im-
portant in human dietary studies that seek to use metabolomics.
A major consensus decision for the field of nutritional metabo-
lomics will be how to address endogenous human metabolites
and exogenous components of food that coexist at least tran-
siently in human biofluids.
The gut microflora is often associated only with the large
oral microflora and of gastric colonization by Helicobacter py-
lori may also need to be factored into nutritional metabolomics.
bowel microflora. Healthy humans have ?400–500 microbial
species in their large bowel that can directly deliver compounds
substrates) or are not considered metabolically important. Re-
gardless of their diverse origin, metabolites can be broadly clas-
sified as being either endogenous (from directly regulated reac-
However, because of the various interactions from entities such
as the gut microflora, intermediate categories of metabolites
have been proposed (35). These intermediate classes of metab-
olites have been categorized as symendogenous compounds,
symxenobiotic compounds, and transxenobiotic compounds.
The microflora can change constituents in food and make them
available to themselves or to the host for additional metabolism.
For example, microbial enzymes hydrolyze soy isoflavones to
release aglycons, daidzein, genistein, and glycitein. These com-
pounds may be absorbed as such and contribute to the metabo-
lome or may enter the microbial metabolome for conversion to
the following other compounds: daidzein to equol or to
O-desmethylangolensin and genistein to p-ethyl phenol (35).
These in turn can then enter the host metabolome. Perhaps these
less defined and facile reactions are partly responsible for idio-
syncrasies that are observed in response to a diet. It has been
xenobiotics, and this can result in various metabolic fates or
endpoints. Major metabolites stem from reactions that have a
FIGURE 3. Nutrients and nonnutrients in the human food supply.
GIBNEY ET AL
by on November 3, 2006
high probability of occurring whereas micrometabolites stem
from reactions that have a lower probability of occurring (35).
Metabolomic studies in rat urine have shown very marked dif-
ferences between rats with a germ-free status and rats with a
conventional status (36). However, whereas large differences
between the total absence of a gut microflora and its presence
might be expected in urinary metabolomes, exactly how diet-
related changes in the composition of the gut microflora of hu-
mans influence the metabolomic profiles of his different bioflu-
ids remains to be determined.
Having considered these various potential confounding fac-
what role they might play in the field are worth considering.
Blood, urine, and saliva are the most likely sources of biofluids
for human metabolomics. Fecal water offers an opportunity to
study gut microflora metabolomics but must be treated cau-
tiously because this biofuluid cannot indicate the metabolites
host. Obtaining other metabolomes (eg, cerebrospinal fluid,
liver, gut, or muscle biopsy specimens) is more invasive, but we
human cells such as peripheral blood mononuclear cells or fi-
broblasts, for metabolomic studies. Nonetheless, the 3 main
biofluids that will probably be used in nutritional metabolomics
are saliva, blood, and urine.
Saliva is not widely used in human nutrition research, but a
case for its inclusion in nutritional metabolomics can be made.
as 17-OH progesterone, testosterone, estradiol, and free cortisol
(37). Its fatty acid composition has been used as a biomarker of
for its antioxidant capacity (39). Although saliva has not been
used in metabolomic studies, its potential for distinguishing be-
tween metabolic profiles and for monitoring changes in meta-
bolic profiles induced by diet would be worth exploring. Both
serum and plasma will undoubtedly be used for nutritional
metabolomic analyses, but they will yield very different NMR
and MS spectra because of the large number of small molecules
The nature of the anticoagulant used when the plasma samples are
obtained may also have an effect on the metabolomic analysis.
A major difference between urine and plasma is the ratio of
metabolites (signal) to nonmetabolites that are derived from
retained in blood as much as possible and only spill over into
urine when their concentrations in plasma rise and exceed the
compounds that are not involved in metabolism are rendered
more polar to decrease their renal threshold, which favors their
entry into urine. The major function of urine is to dispose of
unwanted compounds in the body; consequently, the concentra-
tion of nonnutrient compounds is usually higher in urine than in
plasma. In the study of the acute effects of onion ingestion on
quercitin metabolism, 11 quercitin metabolites unique to urine
plasma (28). Thus, if the objective is to study the direct effect of
dietary intervention on the urinary metabolome, then a relative
enrichment of urine in nonnutrient compounds represents an
has become a major biofluid of choice in pharmacologic and
importance for many nutritionists.
These examples point to the necessity of standardizing the
of sample collection and preparation and of standardization of
for comparison of dietary or other treatment groups and the
identification of discriminating metabolites makes sense only if
certain minimal criteria are met for all elements of the data
collection. Several initiatives are being undertaken to standard-
ize approaches (40–42). Such standardization has been estab-
Adjusting metabolomic profiles for the experimental
Toxicological and pharmacologic studies apply an external
compound, drug, or toxin and then measure the effects on
metabolomic profiles. However, the drug or chemical and their
metabolites should not, as signals, be confused with the meta-
bolic consequences of the signal and are normally deleted from
compounds such as vitamin C or folic acid, this correction will
not be possible in nutritional studies that involve complex mix-
differences between the effects of soy protein and the effects of
and the frequently used statistical techniques, which involve
treatment groups. Will this difference be due to the metabolic
consequences of differences in amino acid compositions, to dif-
ferences in the metabolic effects of soy- or milk-derived pep-
tides, or simply to the appearance of soy phytochemicals in
Another example of the problems or challenges we face in
nutrition is when removing the direct effect of the input is not
feasible. The addition of fatty acids to a diet will lead to their
acids that are already present therein. In other instances, meta-
bolic pools will resist change, eg, pools of ionizable calcium in
plasma or pools of any mineral or trace elements in plasma.
Finally, for complex dietary interventions, such as altering the
impossible with nonspecific techniques such as NMR and will
only be possible with selective techniques such as MS.
Linking metabolomes with cell regulatory processes
one transcript to one protein to specific metabolites can be uni-
versally applied and that through a systems biology approach,
which integrates all connections, we will eventually obtain a
METABOLOMICS IN HUMAN NUTRITION
by on November 3, 2006
of the flux of metabolites through metabolic pools, perhaps for
very narrow or focused metabolomes (eg, the folate metabo-
lome), will somehow need to be measured with the use of stable
isotopes (45–47). Even with a comprehensive set of transcrip-
tomic and proteomic data with some elements of dynamic mea-
sures, linking metabolites back to proteins and genes will not be
simple. Cells operate many sensory, regulatory, and compensa-
tory systems that regulate the flux of metabolites through path-
ways without involving hormonal or endocrine signals, and al-
though these pathways are known, the exact sensor remains
to the ratio of AMP to ATP in cells, whereas amino acids are
positive regulators of mammalian target of rapamycin kinase,
which regulates cell size. Recently, a direct effect of metabolic
(12). A series of metabolic-related enzymes, which are named
metabolic transcription factors, act independently of their cata-
lytic properties and in direct association with enzyme cofactors
such as ATP, NAD, NADP, FAD, and S-adenosylmethionine
and appear to be key in the regulation of gene expression. For
example, S-adenosylmethionine in association with histone
methyltransferases regulates histones, and arginine 82 requires
ATP binding to modulate the arginine- and phosphate-
for systems biology.
Metabolomics—nutrition compared with pharmacology
Experimental pharmacology and toxicology differ from hu-
man nutrition in 3 major respects with regard to metabolomics.
First, much of the research in pharmacology and toxicology is
conducted in laboratory animals that are genetically and nutri-
tionally more homogeneous than are humans. Second, experi-
ments in both pharmacology and toxicology involve the direct
administration of a xenobiotic at a dose that is intended to have
in concert on the pathologic regulation of the disease have a
profound effect on the human metabolome and will affect the
application of metabolomics in clinical medicine for the detec-
tion of diseases, such as cardiovascular disease or multiple scle-
rosis. Because of these differences, the signal-to-noise ratio will
be higher in pharmacology and toxicology research than in hu-
man nutrition research. Thus, it is clear that, in human nutrition
obtained maintain the biological information that underlies the
phenotype variations of interest. The field will need this level of
accuracy to understand the separate effects of drugs, food sup-
plements, stress, physical activity, body composition, age, sex,
colonic flora, and reproductive factors.
Nutrigenomics and nutrigenetics dominate the diet-gene and
gene-diet responsiveness research in the field of personalized
nutrition, and the literature for these subjects, both in the scien-
only one peer-reviewed article on the application of metabolo-
short-lived. Individual researchers will apply this technology
metabolomics for human nutrition requires international schol-
arly reflection leading to an international collaborative project,
which should have 2 aims in mind. The first aim should be to
construct metabolomic databases that are linked to phenotype
databases, which should be rigidly constructed under various
dietary conditions that are agreed on by the collaborators. The
with the use of both NMR and MS technologies and that would
are undertaken, however, more basic studies are needed to as-
certain the acute and chronic effects of diet on biofluid metabo-
role of nonnutrients through purified and low-residue diets, and
to ascertain the rates of change of human biofluid metabolomes
in response to various dietary interventions. For all of this to
to personalized nutrition (52), and the time is nigh for the inter-
national community to spell out a technical roadmap for nutri-
tional metabolomics. To that end, the European Nutrigenomics
Organisation, the American Society for Nutritional Sciences,
and the Metabolomics Society should work together on a global
initiative to create a research roadmap and a standard of data
collection and curation for metabolomics in human nutrition.
MJG completed the literature research and prepared the first draft of the
manuscript and all subsequent drafts after feedback from all other authors.
None of the authors had any conflicts of interest.
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