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REVIEWS
MONITORING OF STORED AND
AVAILABLE FUEL BY THE CNS:
IMPLICATIONS FOR OBESITY
Randy J. Seeley and Stephen C. Woods
Adult mammals do a masterful job of matching caloric intake to caloric expenditure. To accomplish
this, the central nervous system (CNS) must be able to monitor the status of peripheral energy
stores and ongoing fuel availability. Recent observations support the hypothesis that ongoing fuel
availability can be monitored directly in the CNS by mechanisms that extend beyond the sensing of
glucose (the primary neuronal fuel). Questions remain as to how signals from stored and available
fuel are integrated, and it will be vital to answer these key neuroscience questions to develop
biological therapies to curb the growing human and monetary costs of obesity.
Department of Psychiatry
and Obesity Research
Center, University of
Cincinnati, Cincinnati,
Ohio 45267-0559, USA.
Correspondence to R.J.S.
e-mail: [email protected]
doi:10.1038/nrnXXX
Eating encompasses a complex series of behaviours that
are influenced by various environmental and biological
factors. The history of biology and neuroscience
includes numerous attempts to understand the neural
underpinnings of eating, and these attempts have taken
on an unfortunate urgency over the last decade owing
to the exponential increase in obesity in both the developed and developing world. The Surgeon General of
the United States estimates that more than 300,000
deaths in the United States each year can be attributed
to the effects of obesity (compared with the estimated
400,000 deaths that are attributable to tobacco)1. It is
particularly troubling that children are not being spared
by this epidemic — 15.5% of children aged from 12 to
19 are now considered to be obese, a rise of 50% in just
the last 10 years2. The human and monetary costs of
obesity will continue to rise unless effective preventive
and/or therapeutic strategies can be developed.
Although our growing waistlines might indicate
otherwise, the system that matches caloric intake to
caloric expenditure is remarkably accurate. A typical
male human consumes approximately 900,000 calories
per year. To gain just one extra pound per year requires
him to eat approximately 4000 calories more than are
burned in that year (or just 11 calories per day). So, a
gain of one pound per year reflects an error of less than
half of one percent. In fact, the average yearly increase of
NATURE REVIEWS | NEUROSCIENCE
weight in the U.S. population is less than one pound per
adult. However, it should be stressed that this statistic
does not take into account the considerable variability
between individuals, and environmental and genetic
factors both contribute to susceptibility to weight gain.
There are two stories to tell about how the body
weight-regulatory system relates to the crisis of obesity.
The first focuses on the small, cumulative inaccuracies of
the system, which result in gradual weight gain in some
individuals. Considerable controversy surrounds this
topic, with disagreements about the dietary and environmental contributions that have brought us to this
situation. Clearly, something about our lives has changed
over the last 50 years that has resulted in the increasing
prevalence of obesity, and identifying these factors and
understanding how they alter the regulatory system is an
area of intense investigation3–5. Although such work is
vital, this topic is outside the scope of this review.
The second story concerns how, under most circumstances, the biological system that matches caloric
intake to caloric expenditure achieves its remarkable
degree of accuracy. In this article, we will focus on
this accuracy and review some of the advances over the
past decade that have shed light on how this system
maintains energy balance. We suggest that to achieve
such accurate regulation, the system integrates signals
from both stored fuel and currently available fuel6.
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Understanding how such signals are generated and how
they are integrated are important neuroscience questions whose answers will provide new opportunities for
interventions to treat obesity.
The history of obesity research
LIMBIC
A term that refers to a system of
cortical and subcortical
structures that are important for
processing memory and
emotional information.
Prominent structures include
the hippocampus and amygdala.
Research on the neural control of energy balance began
in earnest with the observation that lesions of specific
nuclei in the hypothalamus could produce either
profound increases or decreases in food intake and body
weight, depending on the exact location of the lesion7,8.
These observations focused an enormous amount of
research attention on how specific hypothalamic nuclei
control ingestive behaviour. Recent work has clearly
shown that ingestive behaviour is influenced by a distributed neural network, which includes caudal brainstem, LIMBIC and cortical structures9,10, yet most research
continues to focus on critical hypothalamic circuits.
Over the last 50 years, there has been considerable
debate about what these CNS circuits actually monitor
to maintain energy balance. Two main philosophical
positions emerged and competed for the research spotlight. One of these is based on the hypothesis that the
hypothalamus monitors the storage and metabolism of
fat (lipostatic theory), and the other is based on the
hypothesis that the hypothalamus monitors the storage
and use of carbohydrate (glucostatic theory). The lipostatic hypothesis was first postulated by G. Kennedy in
the 1950s (REF. 11), and it posited that the function of
energy homeostasis (food intake and energy expenditure) is to regulate total body fat in response to feedback
signals from fat depots to the brain. Glucostatic
hypotheses were first championed by Carlson in the
early twentieth century, but were articulated and popularized by J. Mayer in the 1950s (REF. 12). They were based
on the observation that neurons use glucose as their
primary fuel, and that fluctuations in glucose availability
or usage are monitored and linked to the control of food
intake. By eating when glucose availability or usage is
low, energy intake can keep up with energy expenditure
and thereby maintain energy balance.
Scientific debate has focused on which of these positions offers more insight into the process of energy
homeostasis and which will yield better therapeutic
strategies to treat obesity. In fact, each has significant
problems in explaining the richness of ingestive behaviour and the dynamic regulation of energy balance. We
suggest that the important question is not which of
these positions is correct, but rather how the signals from
these two disparate systems are integrated to control
ingestive behaviour. At the heart of this issue is a set of
classic neuroscience questions that provide a unique
opportunity for the neuroscience community to make
vital contributions to stem the tide of obesity and
reduce the resulting financial and human toll.
BLOOD–BRAIN BARRIER
A barrier that is formed by
endothelial tight junctions that
limit the entry of leukocytes,
immunoglobulins, cytokines
and complement proteins into
the central nervous system.
2
Lipostatic regulation
Adiposity signals. The central challenge of Kennedy’s
lipostatic hypothesis is to understand how the CNS
can monitor the collective status of adipocytes that are
dispersed throughout the body. Although direct neural
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signals are a possibility, several lines of research point
to a key role for humoral signals13. To be an ‘adiposity’
signal, a circulating compound must meet several criteria.
First, it must circulate in proportion to the total amount
of stored fat. Second, it should interact with the brain
directly, presumably by crossing the BLOOD–BRAIN BARRIER
to act on specific receptors in regions of the CNS that
are involved in the regulation of food intake and energy
expenditure. Finally, changes in its level or activity
should produce predictable changes in energy balance
by altering food intake and energy expenditure14,15.
The discovery of the hormone leptin by positional
cloning of the obesity (ob) locus in 1994 made the concept of a circulating adiposity signal a reality16, and it
irrevocably changed the landscape for understanding
the regulation of energy balance. Leptin is made
primarily in white fat (although some is made by the
stomach as well)17, and it circulates in direct proportion
to total adiposity, with increasing levels seen as energy
stores in the form of adipose tissue increase18,19. It
should be noted that leptin secretion is more dynamic
than was first appreciated, and it seems to be linked to
energy flux within adipocytes20,21. As a result, during
periods of negative energy balance, levels of leptin fall
considerably faster than the rate at which adipose tissue
is consumed.
Leptin receptors are found in numerous peripheral
tissues, as well as in several regions of the brain, with the
highest concentrations being found in the arcuate
nucleus of the hypothalamus22. Leptin can interact with
these CNS neurons because it crosses the blood–brain
barrier through what seems to be a saturable transport
process19,23,24. On the basis of these observations, the
prediction is that increased CNS leptin signalling would
be interpreted as if body fat had suddenly increased, and
the brain would respond by decreasing food intake with
consequent weight loss. Conversely, decreased CNS
leptin signalling would elicit increased food intake and
weight gain. Soon after the identification of leptin, these
predictions were confirmed25–29.
Although leptin has received the lion’s share of
experimental attention, other hormones have also been
hypothesized to function as adiposity signals. Before
leptin was discovered, compelling evidence implicated
insulin as an adiposity signal30. Insulin is produced by
pancreatic β-cells rather than by adipocytes. Like leptin,
insulin is secreted in response to changes in energy flux
within β-cells31. However, insulin secretion in response
to local energy is in turn influenced by the amount of
stored fat, with the consequence that insulin secretion is
directly proportional to stored fat32,33. Lean animals
(including humans) have lower plasma levels of insulin
than do obese animals. So, although insulin levels
fluctuate broadly as nutrients are ingested and absorbed,
both the basal level of insulin and the total area under
the 24-hour insulin curve are accurate indicators of
body adiposity32,33. Like leptin, insulin penetrates the
blood–brain barrier34, and insulin receptors are found in
the CNS and concentrated in the arcuate nucleus35,36.
Therefore, insulin fulfills the first two criteria for an
adiposity signal.
www.nature.com/reviews/neuro
involved in the control of food intake and body weight [Au: please
explain* and edit title to one line only please]
REVIEWS
Box 1 | List of peptides and neurotransmitters hypothesized to be
Anabolic
agouti-related protein | beacon | β-endorphin | corticosterone | dopamine | dynorphin |
endocannibinoids | ghrelin | interleukin-1 receptor antagonist | melanin-concentrating
hormone | noradrenaline | neuropeptide Y | orexins/hypocretins
Catabolic
α-melanocyte-stimulating hormone | amylin | brain-derived neurotrophic factor |
ciliary neurotrophic factor | cocaine- and amphetamine-related transcript* |
corticotropin-releasing hormone | galanin-like peptide | glucagon-like peptide 1 |
glucagon-like peptide 2 | histamine | insulin | interleukin-1 | interleukin-2 | leptin |
neurotensin | oxytocin | oxyntomodulin | prolactin-releasing peptide | serotonin | tumor
necrosis factor-α | urocortin | urocortin II | urocortin III
ANTISENSE OLIGONUCLEOTIDES
Single-stranded RNA molecules
that are complementary to a
portion of a messenger RNA
(mRNA). They bind to the
mRNA and arrest translation by
physical blockade of ribosomal
machinery and/or by activation
of endogenous RNases.
HYPERPHAGIA
Increased feeding.
Assessing whether insulin signalling in the CNS influences overall energy balance is more complicated than in
the case of leptin, because circulating insulin is the main
mediator of glucose uptake into muscle and adipose
tissue. When insulin is administered systemically, plasma
glucose levels decline rapidly, thereby compromising
glucose availability to the CNS. The resulting hypoglycaemia in turn elicits increased caloric intake37.
Furthermore, targeted disruption of either insulin or the
insulin receptor causes animals to die before reaching
adulthood. These factors have made it difficult to build
a compelling argument for the role of insulin as an
adiposity signal.
Nevertheless, the function of insulin signalling in the
CNS has been revealed by administering insulin directly
into the CNS and by disrupting insulin receptors locally
in the brain. When insulin is administered into the
brain’s ventricular system in either baboons or rats, it
elicits a dose-dependent reduction of food intake and
body weight38–40 that is not secondary to incapacitation
or illness41. Targeted disruption of the insulin receptor in
all neurons in mice results in higher food intakes, more
body fat and increased susceptibility to diet-induced
weight gain42. Moreover, ventricular administration of
insulin receptor ANTISENSE OLIGONUCLEOTIDES produces
43
HYPERPHAGIA and weight gain .
In the past few years, compounds known as insulin
mimetics have been identified that penetrate cell membranes and mimic insulin’s actions by interacting
directly with the intracellular β-subunit of the insulin
receptor44. These compounds are lipid soluble, and they
cross the blood–brain barrier at a higher rate than
insulin itself. Administration of an insulin mimetic,
either systemically or directly into the brain, potently
reduces food intake and body weight, and when it is
mixed directly with the diet it reduces weight gain on a
high-fat diet45. All of these findings indicate that insulin
fulfils the third criterion for an adiposity signal, thereby
completing the parallel with the actions of leptin.
Although insulin and leptin each convey a signal that
is proportional to body fat stores, there are important
differences between them. For example, leptin provides
a relatively stable signal, having a half-life of around 45
minutes in the plasma46. Insulin secretion, on the other
hand, changes with meals, exercise, stress and most
other behaviours, and its half-life is between 2 and 3
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minutes. However, the magnitude of each of these rapid
fluctuations of insulin is directly proportional to the size
of the adipose mass. So, insulin provides the brain with
information about ongoing glucose availability and use,
as well as about body fat. Another difference is that leptin is a better correlate of subcutaneous fat47,48, whereas
insulin correlates better with visceral fat49–51. Because
visceral fat poses a much greater risk than subcutaneous
fat for developing the metabolic complications that are
associated with obesity, plasma insulin is more predictive
of these metabolic disorders than is plasma leptin. On
average, males have more visceral fat, whereas females
have more subcutaneous fat, so males have a greatly
increased risk of developing hypertension, type 2
diabetes, cardiovascular disease and many cancers49.
Our recent observation that females rats are more sensitive to leptin than to insulin, and that the converse is
true of male rats52, is consistent with these findings and
implies that therapeutic approaches to the treatment of
obesity might differ in males and females.
Catabolic and anabolic effector pathways. Since the
identification of leptin, there has been a considerable
research effort to identify the neural circuits that mediate
the effects of adiposity signals in the CNS to limit food
intake and elevate energy expenditure53. The success of
these efforts has been impressive, and dozens of neurotransmitter systems with actions in the hypothalamus
and other brain regions have been identified that influence food intake and/or body weight (BOX 1). An important challenge is to organize this expanding list into
functional circuits to identify opportunities to intervene
and produce significant and sustained weight loss.
One first-order approach is to partition the roster of
neurotransmitters that are linked to the control of energy
balance into two functionally opposite categories54. The
first includes neurotransmitters whose main action is to
decrease food intake, increase energy expenditure and
consequently induce negative energy balance. These
transmitters are integral components of catabolic effector
circuits, and they are thought to be stimulated by
increased levels of adiposity signals such as leptin and
insulin. The second category includes neurotransmitters
that increase food intake, decrease energy expenditure
and induce positive energy balance. They are components of anabolic effector circuits, and they are predicted
to be inhibited by adiposity signals. This organization
implies a strict negative feedback model that can respond
robustly to changes in the amount of stored fat and
thereby maintain a relatively constant level of total
adipose mass (FIG. 1). For example, when recent food
intake has not provided sufficient calories to match
ongoing energy expenditure (as occurs when one is
dieting), calories are liberated from adipose tissue to fill
the gap. As adipose tissue is consumed, levels of both
leptin and insulin decline, resulting in suppressed CNS
catabolic activity and enhanced anabolic activity.
Together, these changes result in an increased drive
to decrease energy expenditure and to consume extra
calories when they become available, thereby returning
the adipose mass to its previous level. The model is
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Energy balance
Positive
Negative
Low insulin & leptin
High insulin & leptin
+
–
Anabolic
Catabolic
Increased food intake
and weight gain
+
–
Catabolic
Anabolic
Decreased food intake
and weight loss
Figure 1 | The relationship between energy balance, adiposity signals and the activity of
anabolic and catabolic effector pathways. During periods of negative energy balance, the levels of
adiposity signals (insulin and leptin) fall. As a result, the balance of activity between anabolic and catabolic
pathways is altered to favour increased anabolic activity. Increased anabolic activity results in increased food
intake and decreased energy expenditure. This combination results in the accretion of stored fuel in the form of
adipose tissue. During periods of positive energy balance, the levels of adiposity signals rise, tipping the balance
towards catabolic activity, which leads to decreased food intake and weight loss.
symmetrical, in that consumption of calories beyond
expenditure would result in elevated leptin and insulin,
and consequent loss of any gained body fat. However,
although it is clear that animals, including humans,
respond to positive energy balance, it is less clear that
this response is mediated by increasing levels of adiposity
signals. Several lines of evidence indicate that these
signals are more important for signalling energy deficit
than surfeit55,56.
INVERSE AGONIST
A ligand that reduces the
proportion of receptors that are
in an active configuration,
thereby producing the opposite
effects to an agonist.
4
The CNS melanocortin system. Although the
catabolic/anabolic dichotomy depicted in FIG. 1 provides
useful predictions about how the CNS control system
is influenced by levels of adiposity signals, it does not
identify the components of the CNS circuits that are the
primary targets for the actions of leptin and insulin.
One logical path to identify the most crucial circuits is to
focus on neurotransmitter systems that have the highest
levels of leptin and insulin receptor expression. These
are located in the hypothalamic arcuate nucleus (FIG. 2).
Two distinct neuronal populations, each of which
expresses leptin and insulin receptors, have been identified in the arcuate. Considerable attention has been
focused on neurons that express the large precursor
molecule pro-opiomelanocortin (POMC). POMC has
many post-translational products, two families of which
are important in the control of energy homeostasis —
the endorphins and the melanocortins57. Melanocortin
peptides include adrenocorticotropic hormone (ACTH)
and α-melanocyte stimulating hormone (α-MSH).
α-MSH exerts a net catabolic action in the CNS.
POMC-expressing neurons are found largely in the
arcuate nucleus, and leptin and insulin both decrease
POMC gene expression there58–60. Administration of
exogenous α-MSH or synthetic analogues also potently
suppresses food intake and produces weight loss61–63.
This is consistent with the hypothesis that the
melanocortins predominate and that arcuate POMC
neurons are primarily catabolic.
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Five melanocortin (MC) receptor subtypes have been
identified. The MC3 and MC4 receptors are strongly
expressed in the CNS, particularly in the hypothalamus64–66. Global disruption of the MC4 receptor
results in mice that show increased food intake and body
weight67, implying that MC4 receptor signalling provides
crucial inhibitory tone that restrains food intake and
weight gain, as would be predicted for an important
catabolic effector system. The general hypothesis is that
an important aspect of the ability of leptin and insulin to
reduce food intake when administered to the CNS is
stimulation of arcuate POMC neurons, leading to release
of α-MSH and increased MC4 signalling in several
hypothalamic nuclei. Consistent with this, leptin
increases electrical activity in arcuate POMC neurons68,
and the catabolic actions of both leptin and insulin
are ameliorated by pretreatment with low doses of an
antagonist for the MC4 receptor69–71.
Melanocortins are so-named because circulating
α-MSH regulates skin and hair pigmentation by stimulating MC1 receptors72. Pigmentation is also regulated
by a second hormone called agouti signalling protein
(ASP), which is a competitive antagonist/INVERSE AGONIST
at MC1 receptors73. So, the control of pigmentation is
determined by the relative activity of an endogenous
agonist and an endogenous antagonist, and this unusual
control system also exists in the CNS. Agouti-related
peptide (AGRP), a CNS neurotransmitter that is
expressed only in the arcuate, was identified on the basis
of its sequence homology with ASP74. AGRP is a competitive antagonist/inverse agonist at CNS MC4 receptors, so
its actions oppose those of α-MSH75. Consistent with an
important role as an anabolic effector,AGRP expression is
increased in fasting and leptin-deficient mice76. AGRP is
made exclusively in a population of arcuate neurons that
co-express neuropeptide Y (NPY), another transmitter
that stimulates food intake and weight gain77,78 (FIG. 2).
Administration of AGRP into the CNS increases
food intake, a response that starts within a few hours
and persists for as long as six days79,80. The basis for this
unusually long-term stimulation of food intake remains
unclear, but it is not mediated by continued MC4 receptor occupation79. It should be noted, however, that in
contrast to the marked effects of either AGRP administration or genetic overexpression in eliciting food intake
and weight gain, genetic disruption of AGRP results in
little or no change in these parameters81.
To summarize, the arcuate melanocortin system is
quite complex, with both catabolic and anabolic transmitters that have opposing actions at the same MC4 (and
to a lesser extent, MC3) receptors. Both the POMC and
the AGRP/NPY neurons in the arcuate are important
targets of leptin and insulin. The arcuate therefore
provides an anatomical and functional basis for the lipostatic regulation that was hypothesized by Kennedy. As
implied by the transmitters and hormones listed in BOX 1,
many other signals are involved in the complex calculations that are involved in adipose-store regulation, and
unravelling their interactions and circuitry presents an
enormous challenge to establish an understanding of the
regulation of energy balance. Nonetheless, it is now well
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Target
Neuron
Food
intake
NPY/
AGRP
Energy
expenditure
POMC
Third
ventrical
–
+
Leptin
Insulin
Insulin/leptin receptor
MC4 receptor
MC3 receptor
NPY Y1/5 receptor
Pancreas
Adipose tissue
Figure 2 | Actions of leptin and insulin on distinct neuronal populations in the arcuate
nucleus of the hypothalamus. Leptin and insulin inhibit activity of neuropeptide Y/agoutirelated peptide (NPY/AGRP) neurons while stimulating activity of pro-opiomelanocortin (POMC)
neurons. NPY and AGRP (a melanocortin receptor antagonist) can potently increase food intake
and result in accumulation of increased stored calories. POMC is a precursor for several
biologically active peptides, including α-melanocyte stimulating hormone (αMSH). αMSH acts as
a melanocortin receptor agonist. Through these disparate actions on distinct cell types in the
arcuate nucleus, adiposity signals can influence the amount of NPY and melanocortin signalling in
downstream target neurons. MC, melanocortin.
accepted that Kennedy was correct in surmising that
body fat is regulated by circulating signals.
Glucostatic regulation
In the wake of the discovery of leptin and the resulting
flurry of work that focused on its actions, the glucostatic
hypothesis was largely ignored. The original observation
that provided the cornerstone of the this hypothesis was
that plasma glucose fluctuates with nutrient consumption and nutrient depletion, and that when glucose levels are lowered by peripheral administration of insulin,
robust feeding results82. An important advance in our
understanding came when specific metabolic inhibitors
of glucose metabolism became available. 2-deoxy-D-glucose (2DG) is a drug that inhibits the enzymatic pathways that enable cells to derive energy from glucose, and
its systemic administration induces a rapid feeding
response83,84. Several lines of evidence implicate the CNS
as the site where 2DG’s metabolic actions activate the
neural circuits that are involved in energy homeostasis.
First, neurons depend almost entirely on glucose
for energy under most circumstances. Second, 2DG
and other glucose oxidation inhibitors are more
potent at increasing food intake when they are administered directly into the CNS than when they are given
NATURE REVIEWS | NEUROSCIENCE
systemically83,84. Finally, discrete populations of neurons
in the hypothalamus and the brainstem have increased or
decreased firing rates when glucose is applied locally85,86.
Despite evidence that the brain can respond to sudden depletions of glucose-derived energy, the primary
tenet of the glucostatic hypothesis — that fluctuations
of glucose-derived energy drive the initiation and cessation of most meals — has not been well supported.
Most neurons are relatively buffered from fluctuations
in circulating glucose, as it would be deleterious for
them to run short on metabolic fuel. Decreases in circulating glucose are quickly detected by the liver and
insulin-secreting β-cells, resulting in the immediate
secretion of more glucose into the blood. Furthermore,
the process by which glucose enters the brain from the
blood is normally saturated such that the blood glucose
would have to become unusually low before reductions
of glucose in the interstitial space surrounding brain
neurons would occur. Because of this, the increased
feeding that is observed after experimentally induced
hypoglycaemia or neuronal glucose deprivation is generally considered to represent an emergency response
that is used as a last resort to counter an acute energy
deficit. In fact, most meals occur when blood glucose is
well within the normal range. From this perspective,
fluctuations in glucose use by the CNS would
contribute minimally to the normal adjustments in
food intake that serve to maintain energy balance, and
they would only be engaged in extreme situations.
Fuel sensing in the CNS
Several hypotheses about the control of energy balance
have focused on total fuel sensing in cells as a signal, but
much of the work has focused on peripheral cells such as
hepatocytes87,88. In the last few years, there has been a
renewed interest in how certain metabolic-sensing
neurons detect and respond to their ongoing metabolic
status, and how this in turn is related to the control of
energy homeostasis (see REF. 89 for an example of early
work on this topic). This work has challenged the idea
that all neurons use glucose exclusively, and it raises the
possibility that some neurons actually monitor and
respond to a more global and integrated pool of intracellular fuel availability, and use the information to influence
nutrient consumption and energy expenditure6.
The first of these challenges came from a group of
researchers at Johns Hopkins University. They were
investigating a compound called C75 that potently
inhibits fatty acid synthase (FAS). In lipogenic tissues
such as white fat, FAS catalyzes the reductive synthesis
of long-chain fatty acids from malonyl-CoA molecules
that are generated when excess cellular fuel is available
and converted to acetyl-CoA (see FIG. 3). FAS inhibitors
were developed as potential inhibitors of tumour
growth, but they produced unwanted weight loss in
patients. Systemic administration of C75 and other FAS
inhibitors potently decreases food intake and body
weight in experimental animals, and normalizes blood
glucose levels in leptin-deficient mice90,91; that is, C75
rescues animals from some of the symptoms of leptin
deficiency. Because tissue levels of malonyl-CoA have
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C75
Acetyl-CoA
ACC
Malonyl-CoA
FAS
Fatty acid
CPT1
Glucose
Oxidation
Figure 3 | A neuronal metabolic pathway that has been
implicated in the control of energy balance. Fatty acid
synthase (FAS) catalyses the reductive synthesis of long-chain
fatty acids from malonyl-CoA molecules that result when
excess cellular fuel is converted to acetyl-CoA. C75 is an
inhibitor of FAS that also potently inhibits food intake in the
CNS. Malonyl-CoA inhibits oxidation of fatty acids by inhibiting
carnitine palmitoyltransferase-1 (CPT1), which transports fatty
acids into the mitochondria. Hypothalamic infusion of oleic
acid or inhibition of CPT1 results in decreased food intake and
hepatic glucose production. [Au: please define ACC]
been considered to constitute an important intracellular
fuel ‘sensor’, it was originally hypothesized that the
increase in intracellular malonyl-CoA caused by C75
was responsible for its catabolic action. Later work from
our laboratory confirmed that C75’s ability to reduce
food intake is mediated by direct actions within the
CNS92, and showed that manipulations that reduce
neuronal glucose uptake ameliorate the ability of C75 to
inhibit food intake93.
Although hypotheses that food intake is based on
generalized energy sensors are not new87,94–97, the implications of these new observations are far reaching. Why
should neurons, which derive essentially all of their
energy from glucose, be able to synthesize large amounts
of long-chain CoAs, and how does this process influence
the ingestion or expenditure of calories throughout the
entire organism?
Current research is taking our understanding of the
control of food intake into new realms. For example,
Rossetti, Obici and their colleagues found that infusion
of oleic acid into the third cerebral ventricle reduced food
intake, as well as the output of glucose by the liver98. For a
long-chain fatty acid such as oleic acid to be oxidized
by a cell, it must first enter the mitochondrion with the
help of the enzyme carnitine palmitoyltransferase-1
(CPT1) (FIG. 3). Rosetti’s group observed that several
manipulations that inhibit CPT1 also reduce both food
intake and hepatic glucose output99. So, manipulations of
fat-producing pathways in the CNS (for example, by
C75), as well as manipulations of fat oxidation in the
CNS, cause marked changes in food intake.
These observations have collectively revealed an
enormous range of new possibilities for how neurons
monitor fuels and their oxidation, and these possibilities
extend beyond an exclusive focus on glucose. More
importantly, they directly implicate cellular fuel-sensing
mechanisms in the CNS in the organism’s overall regulation of energy homeostasis. Numerous questions have
yet to be answered. First, there is no consensus about
how neurons (and/or their associated glia) monitor
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their cellular fuel status. Rapid progress has been made
on this problem for peripheral cell types such as muscle
cells and pancreatic β-cells, but this has not been
extended to the brain. However, the capacity to transfer
these largely in vitro studies to in vivo tests of the regulation of energy balance is increasing, thereby facilitating
the testing of specific hypotheses. Second, the specific
populations of neurons that function as fuel sensors are
not known, nor is it known how the firing rates of those
neurons are influenced. However, the machinery for fuel
sensing has been identified within the brain in discrete
populations of neurons, and manipulations of the relevant enzymes alter the expression of neuropeptides that
are tied to the actions of adiposity signals100,101. Third, it
is not known how much access the CNS actually has to
various species of fatty acids, and under what circumstances. Fourth, it is not known how the actions of the
CNS fuel sensors are coordinated with the actions of
fuel sensors in peripheral tissues such as the liver.
However, the finding that the same manipulations
alter both energy intake and glucose output by the liver
in an integrated manner implies that the systems
are linked43,102. To address these issues, we will need to
draw on diverse areas of neuroscience that have not
traditionally been involved in the study of obesity.
A conjecture
This review has presented the rapid progress that is being
made in our understanding of how energy balance is regulated from both a lipostatic and glucostatic perspective.
It is our strong belief, however, that neither of these two
conceptualizations provides a complete picture of how
ingestive behaviour is controlled, nor how energy
balance is maintained. To that end, we would like to
propose a conjecture about what we consider to be the
two most important functions of the ingestion of
calories. The first is to maintain adequate stores of fuel
— it is of considerable survival value for animals to
maintain adequate stored energy to carry them through
periods of low food availability. Given that the majority
of stored fuel in mammals is in the form of adipose
tissue, most of what has been studied in the rubric of the
lipostatic model is consistent with this function.
We suggest that a second and equally important function for ingesting calories is to provide readily available
fuel to meet current cellular functions. This assertion
assumes that it is preferable for an animal not to have to
dip into its fuel stores, and therefore to adopt a pattern of
ingestion of calories that allows their continued and regulated absorption from the gastrointestinal tract to obviate
the need to release stored fuel. Some might label this regulation as glucostatic, but that would be misleading as it
relates to fuel sensors in the CNS and other tissues that
read out fuel status, not just glucose availability.
Although this conjecture might seem simple and even
axiomatic, it does represent a departure from the previous
debate between the lipostatic and glucostatic hypotheses.
It follows that energy balance is not maintained because
the animal relies solely on either lipostatic or glucostatic
signals. Rather, energy balance is maintained because
organisms can simultaneously monitor the amounts of
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a
CNS
Adiposity
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Energy balance
Figure 4 | Diagrams depicting how signals of stored and available fuel could be
integrated. a | Adiposity signals act on a separate set of target neurons to those that receive
signals from peripheral fuel sensors and those that contain neuronal fuel sensors. Output from
each of these populations must act on common targets to regulate food intake and energy
expenditure and maintain energy balance. CNS, central nervous system. b | Sensors that detect
adiposity signals and neuronal fuel are in the same population of neurons. These influences are
integrated by common intracellular signalling systems that can ultimately influence both neuronal
firing rate and transcription of important effector molecules. c | Adiposity signals act through
intracellular signalling cascades to alter neuronal metabolic status. Changes in metabolic status
are sensed by neuronal fuel sensors that ultimately change neuronal firing and transcription to
influence food intake and energy expenditure.
stored and immediately available fuels at the intracellular
level. So, from our perspective, there is no ‘debate’
between the lipostatic and glucostatic models. Rather,
both mechanisms are necessarily ongoing at all times,
and each is likely to influence the activity of the other.
This perspective is not uniquely ours, but has also been
proposed by other investigators6,96. However, it is our
belief that most perspectives have favoured one or other
NATURE REVIEWS | NEUROSCIENCE
side of this equation, and the question of how the
two mechanisms operate simultaneously has not really
been addressed.
Let’s take an example. In the absence of leptin, the
brains of ob/ob mice [Au: homozygous mutants? Ob–/–]
receive an inappropriately low adiposity signal, and this is
interpreted as if there is inadequate stored fuel. From our
conjecture, this gives the animal not one but two reasons
to over-consume calories. First and most obvious, the
animal eats to raise the level of stored fuel. Second,
because it perceives fuel stores to be inadequate, the
animal is overly responsive to maintain adequate fuel for
immediate use, as it perceives that it cannot draw on
energy stores to bridge any immediate fuel gaps.
Consistent with this, rats and mice with genetic mutations of either leptin or its receptor not only have
increased food consumption, but they also distribute that
consumption much more evenly throughout the
24-hour period than do normal controls103. To turn this
example around, an animal that perceives its current fuel
needs as not being met must also be simultaneously more
concerned about its fuel stores. After all, it must now
draw on fuel stores to meet its ongoing energy demands,
and it cannot begin to replenish stored energy until it can
consume calories in excess of its ongoing demand. What
these examples highlight are that the two sides of this
conjecture — stored fuel and current fuel availability —
are necessarily linked, making it difficult to study one side
of the system without perturbing the other.
If the organism uses separate signals for monitoring
stored fuel and ongoing fuel availability, the key question is not which is more important, but rather how
these distinct signals are integrated to influence food
intake and energy expenditure, and thereby maintain
energy balance. One possibility is that adiposity signals
act on one population of neurons, whereas cellular fuel
sensors exist in a separate population. It might be
assumed that these populations reside entirely within
the hypothalamus, although leptin and insulin receptors, as well as glucose responsive neurons, are also
found within the caudal brainstem9,104,105. Consequently,
it is possible that extrahypothalamic neurons contribute
to these signals. In this case, the crucial question would
be whether these two populations of neurons communicate through direct inputs on one another, or whether
they have a common set of target neurons that integrate
their inputs. A second model might posit that the same
neurons that are direct targets of adiposity signals also
have intracellular fuel sensors. The crucial question is:
how are the inputs from membrane bound receptors
and intracellular metabolic pathways integrated?
There are several non-exclusive possibilities for
this integration. One is that both adiposity signals and
cellular fuel sensors influence membrane potentials
directly (potentially through ATP-sensitive K+ channels), such that their influences are integrated into the
ongoing firing patterns of these neurons. Consistent
with this is the finding that glucose can influence the
firing rate of neurons in the region of the arcuate
nucleus where leptin can increase spike frequency106,
and that both leptin and insulin act in part by
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stimulating ATP-sensitive K+ channels107,108 that are also
sensitive to local fluctuations of glucose. A second possibility is that both adiposity signals and metabolizable
fuels act on common intracellular signalling cascades to
alter several specific proteins. This possibility is supported
by preliminary findings that C75 alters the expression of
some of the same genes as leptin and insulin101. An
intriguing third possibility is that adiposity signals act by
altering the sensitivity of the neuronal fuel sensors, and
that these in turn impact on neuronal firing and/or
protein production. This possibility is plausible, as both
leptin and insulin have important metabolic effects on
peripheral cell types, and recent data have indicated
that leptin alters the levels of the putative cellular fuel
sensor AMP kinase in both peripheral tissues and the
hypothalamus109.
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Conclusions
Our conjecture implies that the underlying aetiology of
the current obesity epidemic could be the result of
environmental factors that alter the sensing of stored
fuel, the sensing of ongoing fuel availability, or the
integration of these two types of signal. Treatment
strategies could focus on either mechanism independently, or on the mechanisms by which these two types
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Acknowledgements [Au: any acknowledgements?]
Online links
DATABASES
The following terms in this article are linked online to:
LocusLink: http://www.ncbi.nlm.nih.gov/LocusLink/
AGRP | ASP | insulin | insulin receptor | leptin | MC1 | MC3 | MC4 |
NPY | ob | POMC
FURTHER INFORMATION
Encyclopedia of Life Sciences: http://www.els.net/
obesity
Access to this interactive links box is free online.
VOLUME 4 | NOVEMBER 2003 | 9
ONLINE
Online Links
Obesity:
http://www.els.net/els/FDA/default.asp?id=09A45CDB-819F-4049A346-5B55B4B37B7F
Locuslink:
AGRP: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=181
ASP: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=434
insulin: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=3630
insulin
receptor:
http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=3643
leptin: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=3952
MC1: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=4157
MC3: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=4159
MC4: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=4160
NPY: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=4157
ob: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=16846
POMC: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=5443
At a glance
• Attempts to understand the neural underpinnings of eating have taken
on an unfortunate urgency over the last decade owing to the exponential increase in obesity in both the developed and developing world.
However, although our growing waistlines might indicate otherwise,
the system that matches caloric intake to caloric expenditure is
remarkably accurate.
• Research on the neural control of energy balance began with the
observation that lesions of specific nuclei in the hypothalamus produce profound increases or decreases in food intake and body weight.
Recent work has shown that ingestive behaviour is influenced by a distributed neural network, which includes caudal brainstem, limbic and
cortical structures.
• Lipostatic theories propose that the hypothalamus monitors the storage and metabolism of fat, whereas glucostatic theories postulate that
it monitors the storage and use of carbohydrate. Rather than choosing
between these two theories, it might be more pertinent to ask how the
signals from the two systems are integrated to control ingestive behaviour.
• How does the central nervous system (CNS) monitor the collective
status of adipocytes that are dispersed throughout the body? An ‘adiposity’ signal must circulate in proportion to the total amount of
stored fat and should interact with the brain directly, and changes in its
level or activity should alter food intake and energy expenditure. The
hormones leptin and insulin both fulfil these criteria.
• The primary tenet of the glucostatic hypothesis is that fluctuations of
glucose-derived energy drive the initiation and cessation of most
meals. However, most neurons are buffered from fluctuations in circulating glucose, and most meals occur when blood glucose is well
within the normal range. So, fluctuations in glucose use by the CNS
probably contribute minimally to normal adjustments in food uptake.
• Recently, there has been a renewed interest in how metabolic-sensing
neurons detect and respond to their ongoing metabolic status, and
how this is related to energy homeostasis. This work challenges the
idea that all neurons use glucose exclusively, and it raises the possibility
that some neurons monitor and respond to a more global and integrated pool of intracellular fuel availability.
• It is suggested that the ingestion of calories serves two functions — to
maintain adequate stores of fuel and to provide readily available fuel to
meet current cellular needs. This represents a departure from the
debate between the lipostatic and glucostatic hypotheses, and it
implies that energy balance is maintained by the simultaneous monitoring of stored and immediately available fuels.
Biographies
Randy Seeley is a professor of psychiatry at the University of Cincinnati
College of Medicine. He received his Ph.D. from the department of psychology at the University of Pennsylvania in 1993 working under H.
Grill and J. Kaplan. He then spent four years at the University of
Washington working with S. Woods, D. Porte and M. Schwartz before
moving to the University of Cincinnati. His work focuses on neuroendocrine regulation of energy balance and therapeutic strategies to treat
obesity. He is the 2003 recipient of the Lilly Scientific Achievement
Award from the North American Association for the Study of Obesity.
Stephen Woods is Professor of Psychiatry and Director of the Obesity
Research Center at the University of Cincinnati. He received his Ph.D. in
physiology and biophysics as well as in psychology from the University
of Washington, and was on the faculty of Columbia University and the
University of Washington before joining University of Cincinnati. He
initially investigated the control of insulin secretion by the brain and in
the 1970s, along with D. Porte, he hypothesized that insulin is an adiposity signal to the brain. He has published hundreds of reports on the control of energy homeostasis and has been President of the Society for the
Study of Ingestive Behavior and the International Congress for the
Physiology of Food and Fluid Intake.