NEUROSCIENCE AND
BIOBEHAVIORAL
REVIEWS
PERGAMON
Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
www.elsevier.com/locate/neubiorev
Review
Hypothalamic neuropeptide mechanisms for regulating energy balance:
from rodent models to human obesity
Julian G. Mercer a,*, John R. Speakman a,b
a
Rowett Research Institute, Aberdeen Centre for Energy Regulation and Obesity (ACERO), Bucksburn, Aberdeen AB21 9SB, UK
b
Department of Zoology, University of Aberdeen, Aberdeen AB24 2TZ, UK
Received 20 October 2000; accepted 1 December 2000
Abstract
In small rodents there is compelling evidence of a lipostatic system of body mass regulation in which peripheral signals of energy storage
are decoded in the hypothalamus. The ability of small mammals to defend an appropriate mass against imposed energy imbalance has
implicated hypothalamic neuroendocrine systems in body mass regulation. The effect of the neuropeptide systems involved in this regulation
is primarily compensatory. However, small mammals can also effect changes in the level of body mass that they will defend, as exempli®ed
by seasonal species. Regulatory control over fat mass may be relatively loose in humans; the sizes of long-term storage depots may not
themselves be regulated, but rather may be a consequence of temporal variations in the matching of supply and demand. Whether food intake
is regulated to match energy demand, or to match demand and to regulate storage, it is clear that physiological defects or genetic variation in
hypothalamic and peripheral feedback systems will have profound implications for fat storage. Study of mechanisms implicated in energy
homeostasis in laboratory rodents is likely to continue to identify targets for pharmacological manipulation in the management of human
obesity. q 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Body mass; Body weight; Body weight set point; Siberian hamster; Phodopus; Photoperiod; Hypothalamic neuropeptides; Leptin; Melanocortin
Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2. An evolutionary perspective on the need to regulate fat storage in small mammals . . . . . . . . . . . . . . . . . . . . . . . .
3. Hypothalamic involvement in body mass regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4. Hypothalamic neuropeptides in body mass defence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5. Programmed body mass change in mammals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6. Body massÐthe sliding `set point' . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7. Dietary manipulation of defended body mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8. Seasonal body mass regulation in the Siberian hamster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9. An evolutionary perspective on fat storage regulation in humans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10. The human hypothalamus in control of food intake and adiposity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction
All animals eat food to satisfy their needs for energy and
nutrients. These requirements are not in a ®xed ratio because
* Corresponding author. Tel.: 144-1224-716662; fax: 144-1224716653.
E-mail address: [email protected] (J.G. Mercer).
101
102
103
104
106
107
107
108
110
111
112
113
113
needs vary according to what the individual is doing at any
particular time, i.e. growing, reproducing, migrating etc.
Moreover the problem of meeting these demands is exacerbated by the fact that food is extremely heterogeneous in its
composition. The task is therefore to pick from the available
foods a suitable combination of food types and quantities to
satisfy diverse and temporally variable requirements. Due to
alternative behavioural necessities, food intake must be
0149-7634/01/$ - see front matter q 2001 Elsevier Science Ltd. All rights reserved.
PII: S 0149-763 4(00)00053-1
102
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
Fig. 1. A feedback system matching multidimensional nutrient supply and
demand (here represented by two dimensions±energy and nitrogen). Flows
of materials (energy and nutrients) are illustrated by heavy solid lines.
Peripheral signals to the brain indicating levels of the relevant parameters
are indicated by solid lines. Efferent control signals from the brain are
illustrated by heavy dashed lines. Important factors in¯uencing levels of
pertinent phenomena are illustrated by dashed lines. In a more complex
regulatory model (model 2), feedback is also transmitted to the brain about
levels of long term storage of nutrients and energy (dotted lines).
discontinuous in nature, yet the requirements for resources
are continuous. Consequently there is a need for the shortterm storage of energy and nutrients, to smooth out the
supply so that it meets demand. Because animals are feeding
to satisfy a variety of different requirements, these shortterm storage mechanisms must often be overwhelmed by the
¯ux of any particular type of nutrient. Faced with this
mismatch of supply and demand animals must do one of
two things: store the excess in a more long-term storage, or
dispose of it.
For most mammals, the majority of excess energy is
deposited into adipose tissue stores as fat. However, some
mammals appear able to cope with excess energy by burning it off. Frugivorous bats, for example, consume a food
that is high in energy but low in protein [1]. To meet daily
protein demands, fruit bats must take in far more energy
than they require. Rather than store the excess as fat they
burn it off by ¯ying [2]. It has been suggested that humans
may also burn off excess energy intake during dietary
induced thermogenesis [3] and that individual differences
in this capacity contribute to differences in long-term
storage. The recent implication that there may also be
other mechanisms for `burning off' excess energy ®ts into
this framework [4].
The matching of supply and demand over relatively long
time periods is very good, implying the existence of a
sophisticated regulatory system. The level of fat accumulated over a typical decade by a human suggests that supply
and demand must have been matched to a precision of
around 0.2% [5]. Since we do not accumulate large stores
of protein, calcium or other nutrients it can be presumed that
all these other systems must also exhibit the same degree of
precise regulation. All mammals vary over time in the
amount of energy that they maintain in long-term storage.
These changes can occur over both protracted (months and
years) and relatively short periods (days and weeks). An
important question is whether the magnitudes of the longterm storage depots are themselves a regulated reserve, or
whether the levels of storage are simply an epiphenomenon
of temporal variations in the matching of supply and
demand (Fig. 1). In one simple (unregulated) model, individuals match energy expenditure and energy intake without
reference to the level of fat storage. When food intake
exceeds demand animals get fat, and when expenditure
exceeds intake they get thin. In the alternative model, the
fat (energy) depots, and also presumably the levels of other
nutrient depots, provide signals to the brain about their
current status. These may then be compared with the desirable upper and lower limits of storage, and food intake and
expenditure modulated to effect adjustments to the level of
long term storage. In energy terms this second model is the
familiar lipostatic model originally formulated by Kennedy
[6]. It is important to distinguish between these two alternative systems because they have extremely important
consequences for the manner in which we interpret phenomena connected with regulation of energy and nutrient
balance. A common point, however, is that both systems
involve regulation of food intake either to match demands
(model 1), or to match demands and regulate storage (model
2). Physiological defects or genetic variation in either
system will have profound implications for the levels of
fat storage.
In this review we aim to do several things. We ®rst
consider the question of the need for a lipostatic system in
small rodents in an evolutionary context of the adaptive
value of such a system. We then explore the nature of the
signalling within this system and most particularly the
hypothalamic neuropeptides which form the mechanism
by which peripheral signals are decoded and efferent signals
controlling food intake and energy utilisation are produced.
We will use as examples several well-studied rodent
models. We then turn our attention to an evolutionary
context for the adaptive need for a lipostatic system in
humans, and review the evidence concerning the roles of
hypothalamic neuropeptides in this system.
2. An evolutionary perspective on the need to regulate fat
storage in small mammals
One assumption implicit in the models presented in the
introduction was that food is always available. The problem
facing an animal is therefore only to select from the available resources what and how much to eat. However, in the
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
real world the food supply is not guaranteed. Hence to overcome the uncertainty in food supply, animals need to maintain fat stores that are larger than are immediately required
to get them from meal to meal. Due to the scaling effects of
size on daily energy demands, the importance of fat storage
for survival is greatest in small animals. Studies of daily
energy requirements of free-living small mammals [7],
measured using the doubly-labelled water technique [8],
have revealed that on average the energy requirements of
a 30 g small mammal amount to about 63 kJ/day. Even by
storing 10% of its body mass as fat such a small mammal
would have the capacity to survive for less than 2 days in the
complete absence of food supplies (39 kJ/g £ 3 g ˆ 117 kJ
of fat stored/63 kJ/day ˆ 1.86 days survival). There must be
strong selective pressures therefore for small animals to
store fat, and these pressures are likely to be greater, resulting in greater levels of storage, as the stochasticity in food
supplies increases.
Despite the strong pressures to store greater quantities of
fat, animals in the wild are seldom recovered with a body
condition equivalent to morbid obesity. This is because
there is a counterbalancing selective pressure. Animals storing large amounts of body fat will be slower and less
manoeuvrable, increasing the risk of predation. Body fat
storage is therefore likely to be a trait on which there are
strong selective pressures both at the upper and lower
margins. Under increasing unpredictability in food supply,
animals might be predicted to increase their fat storage, and
conversely when the risks of predation are high, animals
would be predicted to reduce their levels of fat storage
[9±11]. Several experimental tests have con®rmed these
predictions in wild animals, most notably in small birds
[12±17]. Small mammals and birds therefore need to regulate their body fatness within relatively narrow margins that
are themselves sensitive to changes in the environment in
which the animals ®nd themselves.
3. Hypothalamic involvement in body mass regulation
To maintain a relatively stable body mass within such
narrow margins, accurate regulatory systems must exist to
match energy intake to energy expenditure. Indeed such
sensitivity is essential if a reasonable degree of body mass
control is to be effected. In a variable environment characterised by periodic food shortage there will inevitably be
times when animals are forced to draw on their energy
reserves. The behaviour of many mammals upon refeeding
following such challenges supports the notion that there is a
target body mass or body mass range. The restoration of
normal levels of body mass, adiposity and food intake is
now known to involve the interaction of a number of neural,
endocrine and neurochemical signals. The critical feature of
this regulatory system is the feedback of signals from
adipose tissue, as well as from other peripheral sites, to
the hypothalamus, the latter forming the major integratory
103
centre for afferent signals of energetic status. However,
beyond the interaction of hypothalamic neuropeptides
with their receptors, the mechanisms that determine energy
balance and body mass/composition are largely unde®ned.
Lesioning and electrical stimulation studies conducted in
the 1950s provided the ®rst evidence that the hypothalamus
was a major centre in the control of food intake and body
mass [18]. `Hunger' and `satiety' centres were proposed in
the lateral hypothalamic area (LHA) and the ventromedial
hypothalamic nucleus (VMN), respectively, in the light of
the consumatory and body mass consequences of these
manipulations. These broad regional designations have
now been replaced by a more detailed knowledge of the
anabolic and catabolic molecular substrates involved in
energy balance, the neuronal populations involved, and
their regulation and integration [19±22].
Prior to the landmark cloning of the ob or leptin gene
[23], the existence of a circulating hormone conveying
information about the size of adipose tissue reserves had
been predicted from parabiosis studies [24], and was a
central tenet of the lipostatic theory of food intake and
body mass regulation [6]. It was also predicted that the
mouse diabetic (db) mutation induced obesity by functional
lesion of a receptor for this adiposity signal [24]. While
there is strong evidence that the pancreatic hormone, insulin, is involved in the CNS control of food intake [19,20], the
molecular genetic explanation for the parabiosis data was
provided by the cloning of the leptin [23] and leptin receptor
[25] genes. Leptin is primarily a product of white adipose
tissue. In laboratory rodents, with the notable exception of
the ob/ob mice, serum leptin re¯ects the overall level of
adiposity of the animal and its energy balance state, being
elevated in obesity and lowered following acute manipulations such as food deprivation [26]. Serum leptin concentrations in humans also correlate positively with body
adiposity indices such as body mass index (BMI) [27].
Recombinant leptin protein reverses the hyperphagia and
obese phenotype of the ob/ob mouse and also reduces
food intake and body mass in normal lean rodents [28±30].
Exogenous leptin is more potent when administered
directly into the cerebroventricular system of the brain,
particularly in normal rodents. This route of delivery
would allow a higher concentration of injected hormone
to access hypothalamic structures. Sites of action within
the brain were quickly con®rmed by the mapping of
neurones activated following leptin injection (early
response gene activation; [31,32]), and by the description
of leptin receptor expression in a number of brain regions,
including hypothalamic nuclei with an established regulatory function in energy homeostasis [33]. It is now clear that
leptin interacts via its receptors with hypothalamic neurones
with a number of different neurochemical phenotypes,
thereby providing feedback on peripheral energetic status
to regulatory systems in the brain [34,35]. Leptin provides
two distinct forms of feedback. First, there are profound
diurnal changes in leptin gene expression, which re¯ect
104
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
Table 1
Neuropeptides involved in the control of energy balance
Peptide
Anabolic/orexigenic
Neuropeptide Y
Agouti-related protein
Melanin-concentrating hormone
Orexins (hypocretins)
Galanin
Catabolic/anorexigenic
Alpha-melanocyte-stimulating hormone
Cocaine- and amphetamine-regulated transcript
Corticotrophin-releasing factor
Glucagon-like peptide-1
Glucagon-like peptide-2
Prolactin-releasing peptide
Acronym
Relevant site(s) of synthesis
NPY
AGRP
MCH
±
±
Arcuate nucleus (ARC)
ARC
Lateral hypothalamus (LHA)
LHA
Paraventricular nucleus (PVN)
alpha-MSH
CART
CRF
GLP-1
GLP-2
PrRP
ARC
ARC, other hypothalamic sites?
PVN
Nucleus tractus solitarius (NTS)
NTS
Dorsomedial nucleus (DMH),
NTS
the diurnal pattern of food intake. Leptin rises 4±6 h out of
phase with food intake and therefore peaks in humans
during the early night, and in rodents during the later part
of the night [36±38]. Changes in feeding patterns can alter
the diurnal pattern of leptin expression [39] demonstrating
that it is food intake rather than an endogenous pattern
triggered by the light:dark cycle that controls the expression. This daily leptin surge appears to encode a signal
re¯ecting daily food intake, and its absence is a potent signal
of starvation [40±42]. Second, basal levels of leptin during
the daily nadir encode for the levels of body fat storage. This
second role may indeed be secondary in importance to the
role of leptin as a food intake/starvation signal [41],
although commonly it is this second role that is emphasised
[43±45]. In small mammals, the regulatory loops formed by
leptin and its downstream signalling systems permits
`sensing' of both daily food intake and body fat stores by
the hypothalamus, and thus expression of the behavioural
and metabolic adjustments required to regulate energy
balance.
4. Hypothalamic neuropeptides in body mass defence
As might be anticipated from the evolutionary scenario
presented above small mammals appear to possess regulatory mechanisms for `defending' their body mass/composition within certain limits. Much of the available evidence
suggests that animals attempt to maintain a stable or appropriate body fat content. While fat mass may be the primary
regulated variable, signals from other nutrient stores (such
as lean body tissue) may also be important in long-term
mass recovery. In laboratory rodents the recovery response
following experimentally-induced mass change can be readily demonstrated. Animals habitually return to a body mass
that is appropriate for their age, stage of development and/or
environment after an imposed perturbation. For example,
rats subjected to a period of food deprivation or restriction,
or to imposed overfeeding (i.e. gavage or tube feeding),
express a compensatory hyper- or hypophagia upon return
to ad libitum feeding until they return to a body mass that is
similar to that of freely-feeding controls [46].
A range of compensatory responses is evoked following
imposed energetic manipulations that challenge normal
body mass. These compensatory changes may also be
induced in physiological states with similar effects on
energy balance. In either case, regulatory pathways act in
concert to defend body mass at its existing level or to restore
it to that level once conditions allow. During food deprivation, for example, blood concentrations of leptin and insulin,
which re¯ect body adiposity and energy ¯ux, are reduced
and are accompanied by appropriate changes in the activity
of a number of neuropeptide systems in the hypothalamus
which evoke anabolic and catabolic responses. These
hypothalamic events in turn drive the compensatory adjustments in caloric intake and energy expenditure necessary to
restore body mass and body composition to an appropriate
level.
In general, the behaviour of endogenous hypothalamic
neuropeptide systems during imposed energy imbalance
can be predicted from consideration of the in vivo effects
of these peptides upon exogenous administration directly
into the brain. The energy balance-related peptides can be
divided on the basis of in vivo activity into those that
increase food intake and simultaneously reduce energy
expenditure, and thus have an overall anabolic effect, and
those with the opposite effects contributing to a net catabolic
outcome (Table 1). The generic categorisation of anabolic
(orexigenic) and catabolic (anorexigenic) effector pathways
has been outlined in a number of recent major reviews
[19,20]. From this perspective, it might be anticipated that
in negative energy balance, such as following food deprivation or food restriction, the activity of anabolic systems
would be increased, while that of catabolic systems would
be reduced. Conversely, in imposed positive energy
balance, the opposite responses would be expected. These
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
complementary changes would act to restore body mass to
an appropriate level. A key attribute for a neuropeptide with
primary involvement in body mass regulation might be that
the activity of such a system should remain appropriately
elevated/lowered until normal body mass is attained, rather
than re¯ecting normalisation of energy intake or the period
of ad libitum feeding.
Complete food deprivation (FD) is the best-characterised
paradigm for examining the defence of body mass in laboratory rodents. Similarly, neuropeptide Y (NPY) is the beststudied hypothalamic neuropeptide system [47]. Food deprivation-induced peripheral feedback reaches the rat hypothalamus quite rapidly; recent evidence suggests that FD
beginning 2 h before lights out results in elevated NPY
gene expression within 6 h of the withdrawal of food [48].
Within the hypothalamic arcuate nucleus (ARC), the
expression of anabolic peptide systems such as NPY and
agouti-related protein (AGRP; [49]) is increased by FD, as
is VGF mRNA [50]. Conversely, expression of pro-opiomelanocortin (POMC; [51]) mRNA, the precursor for alphamelanocyte stimulating hormone (alpha-MSH), and of
cocaine- and amphetamine-regulated transcript (CART;
[52]), both catabolic systems, is reduced. These changes
in neuropeptide activity are probably mediated directly by
leptin since these ARC populations of peptidergic neurones
also express leptin receptors [34,35]. The mRNAs for the
anabolic neuropeptides, melanin-concentrating hormone
(MCH) and the orexins (expressed in the LHA and zona
incerta (ZI)), are also elevated during FD [53,54], whereas
corticotrophin-releasing factor (CRF) mRNA in the paraventricular nucleus (PVN) is reduced [55]. The normalisation of neuropeptide gene expression following FD may
indeed be primarily determined by the speed of return to a
normal (appropriate) body mass; preventing the expression
of hyperphagia during refeeding following FD (food intake
held at pre-fast levels), such that body mass remains below
normal, also maintained elevated NPY gene expression
[56].
It would perhaps be surprising if there were not robust
regulatory systems to minimise the risk of starving to death
and to accelerate recovery from severe negative energy
balance. According to the evolutionary perspective
discussed earlier, the response to overfeeding and to attendant increases in adiposity may be of similar importance,
although this aspect of the energy balance regulatory
process has received much less attention. This probably
re¯ects the relative dif®culty in setting up such studies.
Involuntary overfeeding via an implanted gastrostomy
tube at a level that produced a 5% mass increase in 9 days
(up to 125% of normal caloric intake) reduced voluntary
intake of pellet diet to less than 10% of controls. Rats
remained hypophagic for 3 days after tube feeding was
discontinued [57]. Overfeeding increased CRF gene expression in the PVN by approximately 50% [57], and POMC
mRNA levels in the ARC by 80% [58], increases in negative
feedback activity that could be causally linked to the volun-
105
tary hypophagia. The likely involvement of the melanocortin system in this defence of a lower body mass and/or
restoration of energy balance was supported by the ability
of a melanocortin receptor antagonist to reverse regulatory
hypophagia [58]. NPY gene expression was not affected by
the voluntary hypophagia, suggesting again that the state of
energy balance, rather than the absolute level of food intake,
is the critical parameter in determining the activity of this
system [57].
In addition to analysis of the effects of exogenous
peptides in vivo and the responses of endogenous systems
to energetic challenge, the study of transgenic and mutant
mice has been particularly useful in identifying those
hypothalamic signalling systems that are critical to normal
body mass control [59]. As already discussed, a functional
leptin signalling pathway is essential for maintenance of
normal body mass, with mutations of either the hormone
itself or of its receptor giving rise to profound obesity
[23,25]. A competent melanocortin system is also required.
The complex nature of this hypothalamic system is still
emerging (Fig. 2). Leptin inputs directly into the melanocortin system via its receptors on POMC neurones and
AGRP neurones in the ARC [34,35,60]. Alpha-MSH, one
of the cleavage products of the POMC precursor, is the main
agonist of the melanocortin-4 receptor (MC4-R), where it
promotes negative energy balance. Perhaps the ®rst hint of
the importance and complexity of this system came from the
positional cloning of the gene responsible for obesity in the
agouti (A y/a) mouse [61,62]. The protein product of this
gene, agouti, is an antagonist at the melanocortin-1 receptor
and is normally expressed in hair follicles. However, in the
agouti mouse, ectopic expression of agouti protein in the
brain results in antagonism at the MC4-R, and obesity.
AGRP is the natural homologue of agouti, and is an endogenous antagonist at MC4-R, promoting positive energy
balance [63]. Transgenic over-expression of AGRP also
gives rise to obesity [64], presumably through the same
mechanism as ectopic expression of agouti. POMC knockout mice, which lack all the peptides that are generated by
processing of the POMC precursor including alpha-MSH,
are obese, with impaired adrenal development and altered
pigmentation [65]. Administration of an alpha-MSH agonist
causes mass loss in the obese POMC knockout model. Data
obtained from the MC4-R knockout mouse, which is hyperphagic and obese [66], is consistent with a critical role for
this receptor in limiting food intake and the accumulation of
fat mass.
Another melanocortin receptor subtype, MC3-R, is also
expressed in hypothalamic areas known to be involved in
energy balance [67], but until recently the role of this receptor was unknown. Alpha-MSH and AGRP also act as
agonist and antagonist, respectively, at the MC3-R. An indication of the function of this receptor came from recent
descriptions of the phenotype of the MC3-R knockout
[68,69]. Inactivation of the MC3-R gives rise to mice with
a relatively normal body mass, but with increased fat mass
106
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
Fig. 2. The hypothalamic melanocortin system and its involvement in the control of body weight through regulation of food intake and feed ef®ciency. The
activity of MC3-R and MC4-R is likely to be regulated by melanocortin peptide agonists, such as alpha-MSH, and the antagonist AGRP. Gamma-MSH shows
selectivity to MC3-R. AGRP is a high af®nity antagonist of MC3-R and MC4-R, while agouti protein has highest af®nity for MC1-R and MC4-R, but relatively
high concentrations are required for antagonism at MC3-R. The following perturbations to the signalling pathways illustrated result in obesity in rodents: loss
of function mutation of leptin or leptin receptor, transgenic knockout of POMC or MC4-R, transgenic over-expression of AGRP, ectopic expression of agouti
protein.
and reduced lean mass. The mice are hypophagic relative to
wild-type littermates and have a higher feed ef®ciency (ratio
of mass gain to food intake). Analysis of mice lacking both
MC3 and MC4 receptor subtypes reveals an even more rapid
rate of mass gain than that observed in MC4-R knockouts.
This suggests that these two receptor subtypes have different, non-redundant, roles in the regulation of energy
balance, thereby emphasising the importance of the melanocortin system overall.
The MCH-de®cient mouse is lean, with reduced body
mass and hypophagia and an increased metabolic rate.
These observations and others suggest that MCH is a critical
regulator of feeding and energy balance which probably acts
downstream of leptin and the melanocortin system [70].
Similarly, a signi®cant role for VGF in energy homeostasis
is indicated from the phenotype of VGF knockout mice,
which are small and thin, with elevated energy expenditure
and altered gene expression for NPY, AGRP and POMC
[71]. However, the outcome of such transgenic studies has
not always been so clear-cut. Mice lacking NPY feed
normally and have a normal body mass phenotype [72],
suggesting that compensatory or redundant systems have
been recruited to make up for this de®ciency. However,
when viewed on the ob/ob background, the NPY knockout
reduces the hyperphagic response to leptin de®ciency and
obesity is attenuated [73]. The phenotype of the orexin
knockout mouse highlights the likely involvement of this
gene in the physiological regulation of arousal and sleep
processes, rather than in body mass regulation [74].
5. Programmed body mass change in mammals
The ability to defend body mass or composition against
energetic challenge by induction of compensatory mechanisms is clear evidence of regulatory capability, and the
pieces of this jigsaw are beginning to fall into place.
However, mammals also provide examples of anticipatory
or programmed adjustments to body mass and body composition. The cycles of body mass and composition exhibited
by seasonal mammals are a particularly good example of
this [75]. These cycles, often cued from a single environmental variable, photoperiod, have evolved as part of a
pro®le of adaptations that enhance survival at temperate
latitudes. The ability to programme changes in body mass
and composition is therefore superimposed on the capacity
to defend an appropriate body mass against de®cit or excess
using the neuroendocrine systems already described. The
relationship between these two levels of regulation has
received little attention at a mechanistic level. It is not
clear at present whether the same downstream signalling
systems will be involved both in the defence of appropriate
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
Fig. 3. The ªsliding set pointº of body weight regulation in Siberian
hamsters. Effect of food restriction, followed by refeeding (SD/R), on
body weight in hamsters undergoing short day (SD) weight loss.
body mass (i.e. shorter-term regulation of energy balance)
and in adjustments to the level of body mass that will be
defended. A major goal is the description of how an `appropriate' body mass is encoded in the brain and how its regulation is effected.
Seasonal body mass regulation may or may not involve the
hypothalamic systems that are implicated in energetic
compensation (Table 1). These `homeostatic' systems may
not exhibit any perturbation from baseline as long as actual
body mass is able to accurately track the seasonally appropriate optimum [75]. Alternatively, discrete changes in activity of neuropeptide systems may lead to a gradual
programmed state of mass loss or mass gain, or abrupt activity changes may be involved in priming the animal for seasonal body mass change. In addition to the resetting of
appropriate body mass, changes are likely in the way in
which feedback signals such as leptin are integrated into
hypothalamic regulatory systems. Such change is probably
necessary in view of the paradoxical nature of the leptin
signal in seasonal animals undergoing programmed mass
change where plasma leptin will vary in parallel with seasonal body adiposity changes. This raises the question of
how the leptin signal is integrated into hypothalamic pathways without acting to reverse the programmed body mass
cycle [75].
6. Body massÐthe sliding `set point'
The Siberian hamster provides some of the most compelling evidence available in support of a `target' or optimum
body mass. These animals are apparently able to continually
adjust the body mass that will be defended according to their
photoperiodic history. This is the so-called `sliding set
point' of body mass regulation. Adjustments are apparently
made to this encoded `appropriate' body mass even when
actual body mass is perturbed by imposed negative energy
107
balance. In such experiments [76], food restriction is superimposed on short photoperiod-induced mass loss (Fig. 3),
accelerating the rate of mass loss. When restriction is lifted
and hamsters are again allowed to feed ad libitum, body
mass increases, but only to the point where it approximates
to the declining mass of control animals fed ad libitum
throughout. Thus the seasonal timekeeping mechanism
continues to operate even when the animals are prevented
from maintaining their desired body mass [77]. The animals
are subsequently able to `defend' an appropriate body
mass irrespective of their recent imposed body mass
manipulation.
In the case of the Siberian hamster, seasonal mass changes
are driven exclusively by photoperiod, and are therefore
likely to involve melatonin feedback onto energy balance
pathways. Although the precise interaction between the
pineal hormone, melatonin, and the body mass regulatory
circuitry remains to be established, there is clearly some
reprogramming of appropriate body mass by the accumulating melatonin signal. This interaction is likely to take place
somewhere within the hypothalamus or thalamus, where the
majority of CNS melatonin receptors are located [78].
7. Dietary manipulation of defended body mass
Although effectively illustrated by the seasonal rodent,
central encoding of appropriate body mass is certainly not
unique to these animals. Similar regulatory systems are
evident from studies of non-seasonal rodents. Whereas
compensatory regulation of body mass is probably effected
through changes in neuroendocrine signals in the energy
homeostasis centres of the hypothalamus, the fact that
these systems act to restore an appropriate body mass
implies that there is retained information encoding this parameter. Experimental evidence demonstrates that other
environmental manipulations are capable of inducing
substantial changes in defended body mass in non-seasonal
rodents. This is illustrated by experiments in outbred Sprague±Dawley rats [79±81]. Rats fed on a normal stock diet
regulate their body mass normally. When transferred to a
moderately high fat/energy diet, a range of responses is
observed, and from this normal distribution rats have been
arbitrarily divided into groups that develop obesity (DIO)
and those that are apparently resistant to excessive mass
gain (diet resistant; DR). DR rats can be made comparably
obese if also supplied with a highly palatable, high carbohydrate, liquid diet. When both groups are transferred back
to a normal diet, the DIO rats defend their elevated (obese)
body mass through hyperphagia, whereas the DR rats do
not. The DR animals that developed obesity by feeding on
the liquid supplement expressed a relative hypophagia on
the pellet diet until their body mass falls to the level of
control animals [79,81]. The DIO rats also defend their
obese body mass against an imposed food restriction.
Thus although both groups of rats expressed a similar
108
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
regain truly represents the body attempting to default to its
former mass, or whether this outcome merely re¯ects the
return to relative hyperphagia and/or hypoactivity.
8. Seasonal body mass regulation in the Siberian hamster
Fig. 4. Photoperiodic regulation of body mass in (a) adult male (from [85]),
and (b) juvenile female Siberian hamsters (from [87]). LD, long days (16 h
light:8 h dark); SD, short days (8 h light:16 h dark).
level of obesity following manipulation of diet, these
manipulations may or may not alter (or reset) the level of
body mass that the animals will defend.
Whereas some form of `set-point' determining defended
body mass is consistent with the characteristics of body
mass regulation in rodents, it is far from clear whether
equivalent control is present in humans. Several aspects of
the DIO rat model ®nd parallel in the human population.
Consumption of a high fat diet constitutes a behavioural risk
factor for obesity in humans. However, the consumption of a
high fat diet does not necessarily result in the development
of obesity. This is evidenced by description of young men
with a high fat and high-energy diet but with a normal BMI
[82,83]. The problems experienced by obese subjects
attempting to lose weight by dieting are well documented.
If we extrapolate from the rodent literature, it is tempting to
speculate that the phenomenon of weight rebound after dieting in human obesity could represent the outcome of
compensatory neuroendocrine systems attempting to restore
fat stores to their earlier level once caloric restriction is
eased. Thus the mechanism that determines the level at
which body mass is defended, i.e. the functioning of the
hypothetical comparator system, may be a critical factor
in determining the success of weight loss strategies for the
obese [46,80]. Clearly, a key issue here is whether weight
The Siberian hamster (Phodopus sungorus) is the beststudied laboratory model of seasonal body mass regulation,
and a number of studies performed in our laboratory and
others have sought to describe the involvement of known
energy balance-related neuropeptide and receptor systems
in these cycles. Laboratory manipulations of these hamsters
usually involve square wave transfers between long and
short photoperiods, mimicking an abrupt switch between
winter and summer daylength. Transfer of mature male
hamsters from long days (16 h light/8 h dark; LD) to short
days (8 h light/16 h dark; SD) induces a characteristic body
mass response in the SD hamsters (Fig. 4(a)). After a 2±3
week delay, the body mass of SD hamsters begins to fall and
after 16±20 weeks stabilises at approximately 70% of starting mass. This change is physiological and reversible. The
majority of mass loss in SDs is due to mobilisation of
adipose tissue [84], and body mass cycles are accompanied
by changes in food intake, coat colour, reproductive status
and energy expenditure (shallow daytime torpor).
We have examined leptin signalling and hypothalamic
gene expression in adult male Siberian hamsters kept for
18 weeks in LDs or SDs, with or without a ®nal 24 h FD.
SD hamsters had reduced body mass and adiposity, and
lower adipose tissue leptin gene expression [85]. Hypothalamic gene expression was measured by in situ hybridisation. Gene expression in the ARC was lower in SDs for
leptin receptor (OB-Rb) and POMC, but higher for AGRP
(Table 2). There was no effect of photoperiod on ARC NPY
gene expression, orexin or MCH mRNA in the LHA/ZI, or
CRF mRNA in the PVN. An independent study of male
Siberian hamsters exposed to opposite photoperiods for 12
weeks also reported reduced POMC and unaltered NPY and
orexin mRNA abundance in SDs compared to LDs [86]. The
effect of 24 h FD was broadly in line with the rodent data
discussed above, with up-regulation of OB-Rb, AGRP and
NPY (caudal ARC) [85].
We have also studied changes in leptin signalling and
hypothalamic gene expression in growing juvenile female
Siberian hamsters [87]. Hamsters were kept for up to 12
weeks in LDs or SDs from weaning at 3 weeks of age. SD
hamsters had retarded growth, and lower asymptotic body
mass (Fig. 4(b)), adiposity and leptin gene expression in
adipose tissue than LD hamsters [87]. Gene expression in
the ARC for OB-Rb, POMC, and MC3-R was higher in LDs
than SDs; in contrast, gene expression for CART was higher
in SDs than LDs (Table 2). From comparisons with
hamsters at weaning, the differences in OB-Rb, POMC
and MC3-R mRNA levels re¯ected increases in LDs that
were blocked by SDs, whereas CART gene expression was
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
109
Table 2
Summary of the effect of short photoperiod (SD) and food deprivation or restriction (FD/FR) on hypothalamic gene expression in Siberian hamsters. Arrows
indicate levels of gene expression relative to ad libitum-fed LD controls ( $ Ðno change)
v LD ad libitum-fed controls
FD/FR males
Adult SD males
Juvenile SD females
NPY (ARC)
AGRP (ARC)
POMC (ARC)
CART (ARC)
MCH (LHA)
Orexins (LHA)
CRF (PVN)
OB-Rb (ARC)
MC3-R (ARC)
MC4-R (PVN)
"
"
#
$a
$
$
$
"
#a
±
$
"
#
"a
$
$
$
#
#a
±
$
#?
#
"
±
±
±
#
#
$
a
Mercer et al., unpublished.
elevated under SDs. Photoperiod had no effect on NPY gene
expression in the ARC or on MC4-R gene expression in the
PVN. Amounts of AGRP mRNA in the ARC tended to be
higher in LD hamsters. Only the changes in CART mRNA
preceded the divergence of growth trajectories in the opposite photoperiods (2 weeks post-weaning; Fig. 5). These
data provide the ®rst evidence for a primary event in SD
suppression of growth/body mass and may indicate a role
for CART in this regulation.
The accumulated data indicate that chronic low plasma
leptin signals that result from SD mass loss/growth restriction are perceived differently from those acute changes that
are induced by negative energy balance, where low leptin
acts orexigenically. The apparent insensitivity of the body
mass axis to seasonal variation in leptin feedback may be
explained by the associated differences in hypothalamic
OB-Rb gene expression between the opposite photoperiods.
Both juvenile SD females and adult SD males have less
hypothalamic OB-Rb mRNA in the ARC than their respective LD controls, and regulated sensitivity to leptin feedback
may be critical for the maintenance of seasonal bodymass.
Thus, as leptin feedback increases in LDs so does OB-Rb
gene expression. Alternatively, it is possible that leptin may
not be primarily involved in long term body mass regulation, but rather may be important in protecting the body
from acute and harmful mass loss. It is not clear how the
observed changes to the endogenous leptin system, which
might be interpreted as reducing overall sensitivity, can be
rationalised with experimental observations of increased
responsiveness to exogenous leptin in the SD hamster
[88,89].
Interpretation of these simultaneous changes in neuropeptide and receptor gene expression is necessarily speculative,
but a number of conclusions can be drawn. Several of the
changes in hypothalamic mRNA levels induced by SDs
appear counter-intuitive in the context of the functioning of
these systems in energy balance, and their likely regulation
Fig. 5. Dark®eld images of CART gene expression in the hypothalamic arcuate nucleus (ARC) of female Siberian hamsters (from [87]). CART mRNA
levels at 2 weeks post-weaning were higher in hamsters kept in short (SD) as
opposed to long (LD) daylength from weaning. 3V, third ventricle. Scale bar,
180 mm.
110
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
by peripheral feedback signals such as leptin. SDs reduce, or
prevent the normal LD increase in, the circulating leptin
signal but this low level of leptin signalling does not consistently activate anabolic hypothalamic systems and inhibit
catabolic systems. Only POMC mRNA ®tted the predicted
pattern in both of the photoperiod models (Table 2), when it
might have been anticipated that the lower circulating leptin
signal in SDs would also give rise to decreased ARC POMC
and CART mRNA, and increased gene expression for OBRb, AGRP and NPY. The consequence of low POMC gene
expression in SDs would be likely to be reduced catabolic
(alpha-MSH-mediated) drive through the MC4-R in the
PVN. This change would tend to oppose SD mass loss, an
effect that would be reinforced in male hamsters by increased
AGRP activity, an antagonist at the MC4-R. With the recent
characterization of the MC3-R knockout mouse [68,69],
differences in POMC, AGRP and MC3-R gene expression
with photoperiod may have consequences for feed ef®ciency
at a time when animals are anticipating food shortages. The
modulation of CART gene expression in SDs, which is
elevated in both juvenile female hamsters [87] and in adult
males (unpublished), is consistent with a role in the induction
of mass loss. The consistent absence of any photoperiodic
regulation of NPY gene expression, perhaps the archetypal
negative energy balance signal, lends further support to the
notion that ad lib-fed animals perceive themselves to be in
energy homeostasis in both LDs and SDs despite the large
differential in body mass between photoperiods, i.e. they are
at an appropriate body mass/adiposity.
9. An evolutionary perspective on fat storage regulation
in humans
Estimates of the extent to which food intake and expenditure must be balanced in humans clearly indicate that
regulatory systems controlling food intake and utilisation
of energy and nutrients do exist in humans, and that these
systems impact upon body mass and adiposity. It remains to
be determined at what level these controls operate (Fig. 1).
Are body mass and adiposity directly regulated (model 2),
as appears to be the case in small mammals, or is there a
consequential regulation brought about only through matching of energy intake and energy expenditure (model 1)?
Relatively few studies have addressed the evolutionary
context of the regulation of body fatness in humans. At
present the problem of obesity in modern society is considered in the context of one of two alternative evolutionary
scenarios. The ®rst is the `thrifty genotype' model, initially
proposed by Neel in the 1960s [90,91]. Under this hypothesis the capability to ef®ciently store fat is regarded as
having an evolutionary advantage because it allowed early
humans to avoid starvation. In modern environments,
however, where energy is readily available, obesity is
hypothesised to develop in those individuals with the most
ef®cient fat storage mechanisms (those with the thrift
genotype) because there is no regulatory control exerted
over upper limits of fat storage. In the alternative model,
humans are simply regarded as having experienced the same
(generally unstated) selective pressures that pertain to small
mammals, and are assumed therefore to have also evolved a
very tight regulatory system over the levels of fat storage
[19,20,43±45]. Under this scenario the problem of obesity is
regarded as a more pathological problem within the regulatory frameworkÐobese people have defective regulation,
highlighted in an environment where energy supplies are
freely available. Environment is an obvious complicating
factor in this discussion. Provision of a cafeteria-type diet
can effectively overwhelm the normal body mass regulation
of laboratory rodents [92]. If such a challenge can overcome
the comparatively `tight' regulatory systems operating in
small mammals, what will be its consequences be in
humans? Is it necessary to assume that regulation is defective in this scenario?
Do the evolutionary arguments outlined above stand up to
logical scrutiny? The most abundant size class of mammal is
around 100 g [93,94]. Humans are about three orders of
magnitude heavier. This difference is likely to have played a
major role in the pattern of selective pressures acting on early
humans when compared with small mammals, a difference
that is completely ignored in the evolutionary scenarios played
out to date. In particular, because of their larger size, humans
would be expected to be far less sensitive to the risks of starvation. We can estimate the levels of energy expenditure of early
hominids from the scaling relationships established for
modern wild mammals [7,95] since estimates for primates
do not deviate signi®cantly from the allometric means
[96,97]. On this basis an early 70 kg human would expend
energy at a rate of about 14 MJ each day [95]. If such a
human were to store 10% of its body mass as fat
(7 kg ˆ 273 MJ of fat), this would be suf®cient to allow it to
survive for around 20 days without feeding (about 7.5 times
longer than the survival time of a 30 g mammal storing the
same relative amount). Consequently there is likely to have
been less intense selection on the lower margin of fat storage
than one would expect to occur in small mammals, simply
because of the body size difference.
Two things, unique to the evolutionary history of humans,
however, are likely to have exacerbated the difference
between small mammals and us. First, early hunter-gatherers were extremely ¯exible in their diet choice exploiting
plants and animals with variable frequency as well as foods
from marine sources [98±100]. This ¯exibility in their diets
would enable early humans to ride out periods of shortage in
one particular food type, not only by withdrawing stored fat,
but also by switching their diets to other items. This option
would be unavailable to most small mammals that are more
rigid in their diet choice. An insectivorous shrew, for example, would starve to death on a mountain of hazelnuts that
would keep a bank vole alive for weeks, whereas the bank
vole would die rapidly in a cage full of beetles that would
provide adequate sustenance for the shrew. The selective
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
pressures on lower margins for fat storage were likely therefore to have been less intense. This pressure would have
been further relaxed as humans developed agriculture and
the capacity to store energy outside their own bodies, further
diluting the need to store fat as a mechanism for riding out
periods of food unavailability. It is dif®cult to imagine in
this scenario how a `thrifty genotype' predisposing one to
ef®ciently deposit fat stores would evolve, or be maintained,
within the human population.
On the other hand, early humans were still probably under
considerable risk of predation. Selection to limit fat storage
would probably therefore still be present, but in the absence
of any pressure driving humans to deposit large quantities of
fat it seems unlikely that this selective pressure on the upper
margins of fat storage would be intense. Moreover, as with
the lower margin of fat storage, two aspects of human evolutionary history were probably signi®cant. First, humans live
in social groupings. It is well established that groups derive
bene®ts in terms of their ability to detect, escape from and
deter predators [101,102]. Indeed it has been suggested that
primate sociality may have evolved because of the bene®ts
linked to reducing predation risk [103]. Animals in groups
also increase the amount of time spent in low cost behaviours (i.e. resting) compared with more expensive activities [104]. The evolution of sociality would be expected to
not only reduce predation risk but also reduce energy
demands and therefore contribute to further lowering the
risk of starvation. Second, humans developed tools, and
harnessed ®re, both of which would be potent weapons
(literally) to defend against predation. By 6±10,000 years
ago, humans were probably already effectively immune
from both predation and starvation risks as signi®cant forces
moulding the evolution of body fatness regulatory systems.
Over the 300 generations since this time there has been
ample opportunity for whatever regulation did exist to
become less intense.
The dominant thread then is that the selective pressures
which we know have resulted in a very tight regulatory
system within small mammals over levels of body fat
storage are unlikely to have been as potent within the evolutionary history of early humans. We might then expect that
regulation of body fatness in humans is at best going to be a
sloppy version of model 2 and may in fact conform to model
1. Extrapolating uncritically from small rodents to humans
is therefore fraught with as many problems as the `thrifty
genotype' model. This novel evolutionary scenario sheds an
entirely different light on the patterns of obesity that we
observe in modern western societies. Most critically it
suggests that obesity is unlikely to be a consequence of a
selective ef®ciency to store fat (a thrifty genotype), nor a
malfunctioning lipostatic regulatory system. Rather it might
be a consequence of the absence of strong selective pressures for regulatory control over a morphological parameter
that probably was not of key importance in early hominid
evolution. Nevertheless, it is clear that even if humans
conform to model 1, many of the components of the endo-
111
crine and neuroendocrine regulatory system characterised in
small mammals will also have consequences for the maintenance of normal body mass in humans, although there may
be implications for the ef®cacy of potential therapies such as
administering leptin to obese humans [105].
Consequently, the above hypothesis still ®ts without dif®culty into the emerging picture that susceptibility to obesity
may be controlled largely by genetic factors, with environment determining phenotypic expression, and that there may
be a large pool of genes that impact upon energy intake,
energy expenditure or nutrient partitioning, and that ultimately in¯uence body mass. Although body fatness in
humans may not be a regulated parameter itself in the
same way that it is in small mammals, it will nevertheless
be an epiphenomenon of the regulatory systems that control
food intake and energy expenditure. These systems are
likely to show parallels in regulatory control to those
found in small mammals, and their functional impairment
is likely to lead to problems in body mass control. Speci®c
genes and gene products will be critical to the maintenance
of energy balance, and studies seeking the nature of regulatory control over body energy balance in rodents form a
critical initial step in understanding these processes in
humans. The insight gained from the characterisation of
obesity mutations in mice bears testament to the value of
this approach. Understanding the processes that control food
intake and expenditure may lead to a greater understanding
of the development of obesity without the need to consider
the small mammal system as an identical model to the
human system.
10. The human hypothalamus in control of food intake
and adiposity
There is only limited direct evidence that hypothalamic
neuropeptide and receptor systems are involved in the control
of body mass in humans, whether it be through a putative adipostat or via the interaction of energy intake and energy expenditure.Indeed,asidefromtherarecasesofobesitythatareinduced
byspeci®cgenemutations,mostevidenceiscircumstantial.The
identi®cation of rare human obesity mutations does at least
con®rm the existence of signalling pathways within the human
hypothalamus that are essential for normal body mass control,
andthathaveaconservedfunctioninmammalianspeciesstudied
todate.Unsurprisingly,researchershavedrawnupontherodent
literature and adopted a candidate gene approach in identifying
these mutations within the obese human population [59]. The
following monogenic mutations have been identi®ed in the
human population as having important effects on fat storage:
leptin [106,107], leptin receptor [108,109], POMC [110],
MC4-R[111±113]andprohormoneconvertase1(apolypeptide
processing enzyme) [114]. A detailed description of the phenotypes of patients harbouring these mutations can be found elsewhere [59]. The fact that these genes are all components the
leptin-melanocortin signalling pathway serves to emphasise
112
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
the importance of this system in the maintenance of energy
balance. Indeed, between 3 and 5% of extremely obese individuals may have MC4-R mutations [115], although this
frequency is made up of a range of defects in MC4-R function.
Thus, as discussed earlier, if complete loss offunction of a particulargeneproductresultsinobesity,itislikely thatallelicvariation may induce partial loss of function and generate a
predisposition to obesity subject to the remaining genetic background (where several hundred genes may contribute) and to
environmental factors. By contrast, sequence variants in the
MC3-R gene were not associated with obese phenotypes [116].
Comparative neuroanatomical and neurochemical
evidence indicates that the substrates and structures
involved in the maintenance of energy homeostasis are
well conserved between mammalian species. However,
there are few detailed protein or gene expression studies
of the post-mortem human brain. One exception to this is
the leptin receptor. The leptin receptor is widely distributed
in human brain, with a broadly similar pattern of expression
to laboratory rodents, and with the strongest expression in
the cerebellum and hypothalamus, including the ARC and
PVN [117,118]. No differences were observed between the
levels of leptin receptor gene expression of obese, lean and
diabetic subjects. Another approach to assessing the applicability of in vivo rodent data to the human situation is the
measurement of concentrations of neuropeptides and monoamines in human CSF. These procedures address the rate of
release of neurochemicals by regulatory centres within the
brain, they cannot determine whether effects are primary or
secondary to the accompanying pathological state. Results
have been contradictory. Lower than normal CSF concentrations of CRF, b-endorphin and NPY have been recorded
in obese women [119]. However, in a group of massively
obese patients, CSF concentrations of somatostatin were
reduced whereas b-endorphin levels were elevated [120],
and no differences were observed in levels of CRF, NPY
or growth hormone releasing hormone (GHRH). The neurobiology of eating disorders has been investigated using the
same approach. Patients with bulimia nervosa had elevated
CSF levels of peptide YY, an anabolic peptide in the NPY
family [121]. Underweight anorexia nervosa patients had
elevated CSF levels of NPY, CRF and vasopressin, and
reduced b-endorphin and oxytocin [122,123]. Most of
these alterations were normalised after weight recovery. It
is not possible to draw any ®rm conclusions from these data
about the role of the hypothalamic peptides in these pathophysiological conditions.
An approach to the human hypothalamus that could have
potential in obesity and eating disorder research is photon
emission computed tomography (PET scanning) either in
the measurement of regional cerebral blood ¯ow (rCBF),
thereby revealing brain circuits in which activity is changed,
or in areas such as receptor imaging in the living human
brain. For example, a recent study of obese and normal
weight women during exposure to food observed an inverse
association between leptin and hypothalamic rCBF only in
the former group [124]. This suggests that high leptin
concentrations in obese patients depress the activity of
hypothalamic neurones during exposure to food. Bingeeating obese subjects have different rCBFs to non-bingeing
obese or normal weight controls [125]. The potential for in
vivo study of receptor concentrations and mechanisms of
action in the hypothalamus of obese individuals has yet to
be realised.
11. Conclusions
Evolutionary pressures on small mammals have led to
relatively tight control over the upper and lower limits of
body fat stores. Most of our knowledge of the involvement
of hypothalamic systems in body mass regulation is based
on the ability of small mammals to defend an appropriate
body mass from imposed energy imbalance. The neuroendocrine systems involved in this regulation are primarily
compensatory in nature. However, body mass regulation
functions at different levels. The body mass responses
exhibited by seasonal animals to photoperiodic and food
restriction stimuli indicate the existence of a different
level of body mass regulation, through which animals are
able to effect changes in the level of body mass that they will
defend when challenged with energy imbalance. Studies of
hypothalamic gene expression in the Siberian hamster have
begun to tease apart the neuroendocrine pathways involved
in programmed and compensatory regulation of body mass
and adiposity. These studies suggest that the isolated study
of compensatory body mass regulation in non-seasonal
species may only be illuminating part of the picture. The
characteristics of body mass regulation in the Siberian
hamster are indicative of a comparator system whereby
body composition is assessed against encoded target parameters. However the sites and identity of neurochemicals
involved in encoding body mass set point, as opposed to
those involved in energy homeostasis, remain elusive.
It seems likely that regulatory control over fat mass is
loose in humans compared with small mammals, a situation
that can be rationalised from an evolutionary context.
Nevertheless, it is also clear from studies of human obesity
genes that certain regulatory systems, most notably those
focussed on the leptin and melanocortin pathways, are
essential for normal body mass regulation. Even in the
assumed absence of tight direct regulation of body adiposity, this parameter is likely to be controlled as a consequence
of regulated energy intake and expenditure. Study of
mechanisms implicated in energy homeostasis in laboratory
rodents is therefore likely to continue to highlight possible
targets for pharmacological manipulation in the management of human obesity. This will include mechanisms
highlighted in the seasonal model, where the manifestation
of programmed as well as compensatory control over energy
balance may signi®cantly advance our understanding of
body mass regulation across mammalian species, including
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
man. It remains to be determined whether the best potential
targets for pharmacological intervention in human obesity
will be individual components of predominantly short-term
compensatory pathways or as yet unknown components of
the `set-point' system. In large part the answer to this question will be determined by the nature of the regulatory
process in humans, although `silent' mechanisms could
still be amenable to manipulation. Depending on the
strength of any direct adipostatic regulation, targeting the
former, compensatory, systems will carry the risk of weight
regain at the end of the intervention period, whereas the
latter has at least the prospect of lowering defended body
weight [80].
[16]
[17]
[18]
[19]
[20]
[21]
[22]
Acknowledgements
Work in the authors' laboratory was funded by the Scottish Executive Rural Affairs Department and by the BBSRC
(1/S12030). JRS was supported by a Royal Society Leverhulme Senior Research Fellowship.
[23]
[24]
[25]
References
[26]
[1] Thomas DW. Fruit intake and energy budgets of frugivorous bats.
Physiol Zool 1984;57:457±67.
[2] Winter Y, von Helversen O. The energy cost of ¯ight: do small bats
¯y more cheaply than birds?. J Comp Physiol 1998;168:105±11.
[3] Rothwell NJ, Stock MJ. A role for brown adipose tissue in dietinduced thermogenesis. Nature 1979;281:31±35.
[4] Clapham JC, Arch JR, Chapman H, Haynes A, Lister C, Moore GB,
Piercy V, Carter SA, Lehner I, Smith SA, Beeley LJ, Godden RJ,
Herrity N, Skehel M, Changani KK, Hockings PD, Reid DG, Squires
SM, Hatcher J, Trail B, Latcham J, Rastan S, Harper AJ, Cadenas S,
Buckingham JA, Brand MD, Abuin A. Mice overexpressing human
uncoupling protein-3 in skeletal muscle are hyperphagic and lean.
Nature 2000;406:415±8.
[5] Weigle DS. Appetite and the regulation of body composition.
FASEB J 1994;8:302±10.
[6] Kennedy GC. The role of depot fat in the hypothalamic control of
food intake in the rat. Proc Royal Soc Lond B 1953;140:578±92.
[7] Speakman JR. The cost of living: factors in¯uencing the daily energy
demands of small mammals. Adv Ecol Res 2000;30:177±297.
[8] Speakman JR. Doubly-labelled water: theory and practice. London:
Chapman and Hall, 1997.
[9] Lima SL. Predation risk and unpredictable feeding conditions: determinants of body mass in birds. Ecology 1986;67:377±85.
[10] McNamaraJM.Thestarvation-predationtrade-offandsomebehavioural
and ecological consequences. In: Hughes RN, editor. Behavioural
mechanisms offood selection, Berlin: Springer, 1990. p. 39±50.
[11] McNamara JM, Houston AI. The value of fat reserves and the tradeoff between starvation and predation. Acta Biotheoretica
1990;38:37±61.
[12] Bednekoff PA, Krebs JR. Great tit fat reserves: effects of changing
and unpredictable feeding day length. Functional Ecology
1995;9:457±62.
[13] Ekman JB, Hake MK. Monitoring starvation risk: adjustments of
body reserves in green®nches (Carduelis chloris) during periods of
unpredictable foraging success. Behav Ecology 1990;1:62±67.
[14] Gosler AG, Greenwood JJD, Perrins C. Predation risk and the cost of
being fat. Nature 1995;377:621±3.
[15] Hurly AT. Energetic reserves of marsh tits (Parus palustris): food
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
113
and fat storage in response to variable food supply. Behav Ecology
1992;3:181±8.
Rogers CM. Predation risk and fasting capacity: do winter birds
maintain optimal body mass?. Ecology 1987;68:1051±61.
Witter MS, Cuthill IC, Bonser RHC. Experimental investigations of
mass-dependent predation risk in the European Starling, Sturnus
vulgaris. Animal Behav 1994;48:210±22.
Stellar E. The physiology of motivation. Psychol Rev 1954;61:5±22.
Schwartz MW, Woods SC, Porte Jr D, Seeley RJ, Baskin DG.
Central nervous system control of food intake. Nature
2000;404:661±71.
Woods SC, Seeley RJ, Porte D, Schwartz MW. Signals that regulate
food intake and energy homeostasis. Science 1998;280:1378±83.
Kalra SP, Dube MG, Pu S, Xu B, Horvath TL, Kalra PS. Interacting
appetite-regulating pathways in the hypothalamic regulation of body
weight. Endocrine Rev 1999;20:68±100.
Friedman JM, Halaas JL. Leptin and the regulation of body weight in
mammals. Nature 1998;395:763±70.
Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM.
Positional cloning of the mouse obese gene and its human homologue. Nature 1994;372:425±32.
Coleman DL. Obese and diabetes: two mutant genes causing
diabetes-obesity syndromes in mice. Diabetologia 1978;14:141±8.
Tartaglia LA, Dembski M, Weng X, Deng N, Culpepper J, Devos R,
Richards GJ, Camp®eld LA, Clark FT, Deeds J, Muir C, Sanker S,
Moriarty A, Moore KJ, Smutko JS, Mays GG, Woolf EA, Monroe
CA, Tepper RI. Identi®cation and expression cloning of a leptin
receptor. OB-R Cell 1995;83:1263±71.
Trayhurn P, Thomas MEA, Duncan JS, Rayner DV. Effects of fasting and refeeding on ob gene-expression in white adipose-tissue of
lean and obese (ob/ob) mice. Febs Letters 1995;368:488±90.
Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens
TW, Nyce MR, Ohannesian JP, Marco CC, McKee LJ, Bauer TL.
Serum immunoreactive leptin concentrations in normal-weight and
obese humans. New England Journal of Medicine 1996;334:292±5.
Pelleymounter MA, Cullen MJ, Baker MB, Hecht R, Winters D,
Boone T, Collins F. Effects of the obese gene-product on bodyweight regulation in ob/ob mice. Science 1995;269:540±3.
Halaas JL, Gajiwala KS, Maffei M, Cohen SL, Chait BT, Rabinowitz
D, Lallone RL, Burley SK, Friedman JM. Weight-reducing effects of
the plasma-protein encoded by the obese gene. Science
1995;269:543±6.
Camp®eld LA, Smith FJ, Guisez Y, Devos R, Burn P. Recombinant
mouse ob proteinÐevidence for a peripheral signal linking adiposity and central neural networks. Science 1995;269:546±9.
Woods AJ, Stock MJ. Leptin activation in hypothalamus. Nature
1996;381:745.
Van Dijk G, Thiele TE, Donahey JC, Camp®eld LA, Smith FJ, Burn
P, Bernstein IL, Woods SC, Seeley RJ. Central infusions of leptin
and GLP-1-(7-36) amide differentially stimulate c-FLI in the rat
brain. Amer J Physiol 1996;271:R1096±100.
Mercer JG, Hoggard N, Williams LM, Lawrence CB, Hannah LT,
Trayhurn P. Localization of leptin receptor messenger-RNA and the
long form splice variant (Ob-Rb) in mouse hypothalamus and adjacent brain-regions by in-situ hybridization. Febs Letters
1996;387:113±6.
Cheung CC, Clifton DK, Steiner RA. Proopiomelanocortin neurons
are direct targets for leptin in the hypothalamus. Endocrinology
1997;138:4489±92.
Mercer JG, Hoggard N, Williams LM, Lawrence CB, Hannah LT,
Morgan PJ, Trayhurn P. Coexpression of leptin receptor and preproneuropeptide Y mRNA in arcuate nucleus of mouse hypothalamus. J
Neuroendocrinology 1996;8:733±5.
Wolthers OD, Heuck C, Skjaerbaek C. Diurnal rhythm in serum
leptin. J Pediatr Endocrinol Metab 1999;12:153±866.
Xu B, Kalra PS, Farmerie WG, Kalra SP. Daily changes in
hypothalamic gene expression of neuropeptide Y, galanin,
114
[38]
[39]
[40]
[41]
[42]
[43]
[44]
[45]
[46]
[47]
[48]
[49]
[50]
[51]
[52]
[53]
[54]
[55]
[56]
[57]
[58]
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
proopiomelanocortin, and adipocyte leptin gene expression and
secretion: effects of food restriction. Endocrinology 1999;
140:2858±75.
Nagatani S, Guthikonda P, Foster DL. Appearance of a nocturnal
peak of leptin secretion in the pubertal rat. Hormones Behav
2000;37:345±52.
Schoeller DA, Cella LK, Sinha MK, Caro JF. Entrainment of the
diurnal rhythm of plasma leptin to meal timing. J Clin Invest
1997;100:1882±7.
Ahima RS, Prabakaran D, Mantzoros C, Qu D, Lowell B, MaratosFlier E, Flier JS. Role of leptin in the neuroendocrine response to
fasting. Nature 1996;382:250±2.
Ahima RS, Flier JS. Leptin Ann Rev Physiol 2000;25:413±27.
Ahima RS, Saper CB, Flier JS, Elmquist JK. Leptin regulation of
neuroendocrine systems. Front Neuroendocrinol 2000;21:263±307.
Baile CA, Della-Fera MA, Martin RJ. Regulation of metabolism and
body fat mass by leptin. Ann Rev Nut 2000;20:105±27.
Rohner-Jeanrenaud F. Hormonal regulation of energy partitioning.
Int J Obes 2000;24:34±37.
Lu H, Li C. ReviewÐleptin: a multifunctional hormone. Cell
Research 2000;10:81±92.
Keesey RE, Hirvonen MD. Body weight set-points: determination
and adjustment. J Nutr 1997;127:18755±835.
Leibowitz SF. Brain Neuropeptide Y: an integrator of endocrine,
metabolic and behavioral processes. Brain Res Bull 1991;27:333±7.
Dallman MF, Akana SF, Bhatnagar S, Bell ME, Choi S, Chu A,
Horsley C, Levin N, Meijer O, Soriano LR, Strack AM, Viau V.
Starvation: early signals, sensors, and sequelae. Endocrinology
1999;140:4015±23.
Mizuno TM, Mobbs CV. Hypothalamic agouti-related protein
messenger ribonucleic acid is inhibited by leptin and stimulated by
fasting. Endocrinology 1999;140:814±7.
Salton SR, Ferri GL, Hahm S, Snyder SE, Wilson AJ, Possenti R,
Levi A. VGF: a novel role for this neuronal and neuroendocrine
polypeptide in the regulation of energy balance. Front Neuroendocrinol 2000;21:199±219.
Bergendahl M, Wiemann JN, Clifton DK, Huhtaniemi I, Steiner RA.
Short-term starvation decreases POMC mRNA but does not alter
GnRH mRNA in the brain of adult male rats. Neuroendocrinology
1992;56:913±20.
Kristensen P, Judge ME, Thim L, Ribel U, Christjansen KN, Wulff
BS, Clausen JT, Jensen PB, Madsen OD, Vrang N, Larsen PJ,
Hastrup S. Hypothalamic CART is a new anorectic peptide regulated
by leptin. Nature 1998;393:72±76.
Qu D, Ludwig DS, Gammeltoft S, Piper M, Pelleymounter MA,
Cullen MJ, Mathes WF, Przypek J, Kanarek R, Maratos-Flier E. A
role for melanin-concentrating hormone in the central regulation of
feeding behaviour. Nature 1996;380:243±7.
Sakurai T, Amemiya A, Ishii M, Matsuzaki I, Chemelli RM, Tanaka
H, Williams SC, Richardson JA, Kozlowski GP, Wilson S, Arch
JRS, Buckingham RE, Haynes AC, Carr SA, Annan RS, McNulty
DE, Liu W-S, Terrett JA, Elshourbagy NA, Bergsma DJ, Yanagisawa M. Orexins and orexin receptors: a family of hypothalamic
neuropeptides and G protein-coupled receptors that regulate feeding
behavior. Cell 1998;92:575±85.
Brady LS, Smith MA, Gold PW, Herkenham M. Altered expression
of hypothalamic neuropeptide mRNAs in food-restricted and fooddeprived rats. Neuroendocrinology 1990;52:441±7.
Davies L, Marks JL. Role of hypothalamic neuropeptide Y gene
expression in body weight regulation. Amer J Physiol
1994;266:R1687±91.
Seeley RJ, Matson CA, Chavez M, Woods SC, Dallman MF,
Schwartz MW. Behavioral, endocrine, and hypothalamic responses
to involuntary overfeeding. Amer J Physiol 1996;271:R819±23.
Hagan MM, Rushing PA, Schwartz MW, Yagaloff KA, Burn P,
Woods SC, Seeley RJ. Role of the CNS melanocortin system in
the response to overfeeding. J Neurosci 1999;19:2362±23627.
[59] Barsh GS, Farooqi IS, O'Rahilly S. Genetics of body-weight regulation. Nature 2000;404:644±51.
[60] Hahn TM, Breininger JF, Baskin DG, Schwartz MW. Coexpression
of Agrp and NPY in fasting-activated hypothalamic neurons. Nature
Neurosci 1998;1:271±2.
[61] Miller MW, Duhl DM, Vrieling H, Cordes SP, Ollmann MM,
Winkes BM, Barsh GS. Cloning of the mouse agouti gene predicts
a secreted protein ubiquitously expressed in mice carrying the lethal
yellow mutation. Genes Dev 1993;7:454±67.
[62] Bultman SJ, Michaud EJ, Woychik RP. Molecular characterization
of the mouse agouti locus. Cell 1992;71:1195±204.
[63] Ollmann MM, Wilson BD, Yang YK, Kerns JA, Chen Y, Gantz I,
Barsh GS. Antagonism of central melanocortin receptors in vitro and
in vivo by agouti-related protein. Science 1997;278:135±8.
[64] Graham M, Shutter JR, Sarmiento U, Sarosi I, Stark KL. Overexpression of Agrt leads to obesity in transgenic mice. Nat Genet
1997;17:273±4.
[65] Yaswen L, Diehl N, Brennan MB, Hochgeschwender U. Obesity in
the mouse model of pro-opiomelanocortin de®ciency responds to
peripheral melanocortin. Nat Med 1999;5:1066±70.
[66] Huszar D, Lynch C, Fairchild-Huntress V, Dunmore J, Fang Q,
Berkemeier L, Gu W, Kesterson R, Boston B, Cone R, Smith F,
Camp®eld L, Burn P, Lee F. Targeted disruption of the melanocortin-4 receptor results in obesity in mice. Cell 1997;88:131±41.
[67] Roselli-Rehfuss L, Mountjoy KG, Robbins LS, Mortrud MT, Low
MJ, Tatro JB, Entwistle ML, Simerly RB, Cone RD. Identi®cation of
a receptor for gamma melanotropin and other proopiomelanocortin
peptides in the hypothalamus and limbic system. Proc Natl Acad Sci
USA 1993;90:8856±60.
[68] Chen AS, Marsh DJ, Trumbauer ME, Frazier EG, Guan XM, Yu H,
Rosenblum CI, Vongs A, Feng Y, Cao L, Metzger JM, Strack AM,
Camacho RE, Mellin TN, Nunes CN, Min W, Fisher J, Gopal-Truter
S, MacIntyre DE, Chen HY, Van Der Ploeg LH. Inactivation of the
mouse melanocortin-3 receptor results in increased fat mass and
reduced lean body mass. Nat Genet 2000;26:97±102.
[69] Butler AA, Kesterson RA, Khong K, Cullen MJ, Pelleymounter MA,
Dekoning J, Baetscher M, Cone RD. A unique metabolic syndrome
causes obesity in the melanocortin-3 receptor-de®cient mouse.
Endocrinology 2000;141:3518±21.
[70] Shimada M, Tritos NA, Lowell BB, Flier JS, Maratos-Flier E. Mice
lacking melanin-concentrating hormone are hypophagic and lean.
Nature 1998;396:670±4.
[71] Hahm S, Mizuno TM, Wu TJ, Wisor JP, Priest CA, Kozak CA,
Boozer CN, Peng B, McEvoy RC, Good P, Kelley KA, Takahashi
JS, Pintar JE, Roberts JL, Mobbs CV, Salton SR. Targeted deletion
of the Vgf gene indicates that the encoded secretory peptide precursor plays a novel role in the regulation of energy balance. Neuron
1999;23:537±48.
[72] Erickson JC, Clegg KE, Palmiter RD. Sensitivity to leptin and
susceptibility to seizures of mice lacking neuropeptide Y. Nature
1996;381:415±8.
[73] Erickson JC, Hollopeter G, Palmiter RD. Attenuation of the obesity
syndrome of ob/ob mice by the loss of neuropeptide Y. Science
1996;274:1704±7.
[74] Chemelli RM, Willie JT, Sinton CM, Elmquist JK, Scammell T, Lee
C, Richardson JA, Williams SC, Xiong Y, Kisanuki Y, Fitch TE,
Nakazato M, Hammer RE, Saper CB, Yanagisawa M. Narcolepsy in
orexin knockout mice: molecular genetics of sleep regulation. Cell
1999;98:437±51.
[75] Mercer JG. Regulation of appetite and body weight in seasonal
mammals. Comp Biochem Physiol 1998;119C:295±303.
[76] Steinlechner S, Heldmaier G, Becker H. The seasonal cycle of body
weight in the Djungarian hamster: photoperiodic control and in¯uence of starvation and melatonin. Oecologia 1983;60:401±5.
[77] Bartness TJ, Elliot JA, Goldman BD. Control of torpor and body
weight patterns by a seasonal timer in Siberian hamsters. Amer J
Physiol 1989;257:R142±9.
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
[78] Morgan PJ, Barrett P, Howell HE, Helliwell R. Melatonin receptors:
localization, molecular pharmacology and physiological signi®cance. Neurochem Int 1994;24:101±46.
[79] Levin BE. Acurate NPY neurons and energy homeostasis in dietinduced obese and resistant rats. Amer J Physiol 1999;276:R382±7.
[80] Levin BE, Dunn-Meynell AA. Defense of body weight against
chronic caloric restriction in obesity-prone and -resistant rats.
Amer J Physiol 2000;278:R231±7.
[81] Levin BE, Keesey RE. Defense of differing body weight set points in
diet-induced obese and resistant rats. Amer J Physiol
1998;274:R412±9.
[82] Macdiarmid JI, Cade JE, Blundell JE. High and low fat consumers,
their macronutrient intake and body mass index: further analysis of
the National Diet and Nutrition Survey of British Adults. Eur J Clin
Nutr 1996;50:505±12.
[83] Cooling J, Blundell J. Differences in energy expenditure and
substrate oxidation between habitual high fat and low fat consumers
(phenotypes). Int J Obesity 1998;22:612±8.
[84] Wade GN, Bartness TJ. Effects of photoperiod and gonadectomy on
food intake, body weight, and body composition in Siberian
hamsters. Amer J Physiol 1984;246:R26±30.
[85] Mercer JG, Moar KM, Ross AW, Hoggard N, Morgan PJ. Photoperiod regulates arcuate nucleus POMC, AGRP, and leptin receptor
mRNA in Siberian hamster hypothalamus. Amer J Physiol
2000;278:R271±81.
[86] Reddy AB, Cronin AS, Ford H, Ebling FJP. Seasonal regulation of
food intake and body weight in the male Siberian hamster: studies of
hypothalamic orexin (hypocretin), neuropeptide Y (NPY) and proopiomelanocortin (POMC). Eur J Neuroscience 1999;11:3255±64.
[87] Adam CL, Moar KM, Logie TJ, Ross AW, Barrett P, Morgan PJ,
Mercer JG. Photoperiod regulates growth, puberty and hypothalamic
neuropeptide and receptor gene expression in female Siberian
hamsters. Endocrinology 2000;141:4349±4356.
[88] Klingenspor M, Niggemann H, Heldmaier G. Modulation of leptin
sensitivity by short photoperiod acclimation in the Djungarian
hamster Phodopus sungorus. J Comp Physiol B 2000;170:37±43.
[89] Mercer JG, Adam CL, Morgan PJ. Towards an understanding of
physiological body weight regulation: seasonal animal models.
Nutr Neurosci 2000;3:307±320.
[90] Neel JV. The ªthrifty genotypeº in 1998. Nut Rev 1999;57:32±39.
[91] Lev-Ran A. Thrifty genotype: how applicable is it to obesity and
type 2 diabetes?. Diabetes Reviews 1999;7:1±22.
[92] Sclafani A, Springer D. Dietary obesity in adult rats: similarities to
hypothalamic and human obesity syndromes. Physiol Behav
1976;17:461±71.
[93] Brown JH, Marquet PA, Taper ML. Evolution of body size: consequences of an energetic de®nition of ®tness. Amer Naturalist
1993;142:573±84.
[94] Lovegrove BG. The zoogeography of mammalian basal metabolic
rate. Amer Naturalist 2000;156:201±19.
[95] Nagy KA, Giraud IA, Brown TK. Energetics of free-ranging
mammals, reptiles and birds. Ann Rev Nutr 1999;19:247±77.
[96] Schmid J, Speakman JR. Daily energy expenditure of the grey
mouse lemur (Microcebus murinus): a small primate that uses
torpor. J Comp Physiol 2000 (in press).
[97] Drack S, Ortmann S, BuÈhrmann N, Schmid J, Warren RD, Ganzhorn
JU. Field metabolic rate and the cost of ranging of the red-tailed
sportive lemur. In: Rakotosamimanana B, Rasaminanana H, Ganzhorn JU, Goodman SM, editors. New directions in lemur studies,
New York and London: Plenum Press, 1999.
[98] Stewart KM. Early hominid utilization of ®sh resources and implications for seasonality and behavior. J Human Evolution
1994;27:229±45.
[99] Mann N. Dietary lean red meat and human evolution. Eur J Nut
2000;39:71±79.
[100] Speth JD. Plant-animal subsistence ratios and macronutrient energy
[101]
[102]
[103]
[104]
[105]
[106]
[107]
[108]
[109]
[110]
[111]
[112]
[113]
[114]
[115]
[116]
[117]
[118]
115
estimations in worldwide hunter-gatherer diets. Amer J Clin Nut
2000;71:682±92.
Slotow R, Coumi N. Vigilance in bronze mannikin groups: the
contributions of predation risk and intra-group competition. Behaviour 2000;14:565±78.
Hilton GM, Cresswell W, Ruxton GD. Intra¯ock variation in the
speed of escape-¯ight response on attack by an avian predator.
Behav Ecol 1999;5:391±5.
Hill RA, Dunbar RIM. An evaluation of the roles of predation rate
and predation risk as selective pressures on primate grouping behaviour. Behaviour 1998;135:411±30.
Blumstein DT, Evans CS, Daniel JC. An experimental study of
behavioural group size effects in tammar wallabies, Macropus eugenii. Ann Behav 1999;58:351±60.
Heyms®eld SB, Greenberg AS, Fujioka K, Dixon RM, Kushner R,
Hunt T, Lubina JA, Patane J, Self B, Hunt P, McCamish M. Recombinant leptin for weight loss in obese and lean adultsÐa randomized, controlled, dose-escalation trial. JAMA 1999;282:1568±75.
Montague CT, Farooqi IS, Whitehead JP, Soos MA, Rau H, Wareham NJ, Sewter CP, Digby JE, Mohammed SN, Hurst JA, Cheetham
CH, Earley AR, Barnett AH, Prins JB, O'Rahilly S. Congenital
leptin de®ciency is associated with severe early-onset obesity in
humans. Nature 1997;387:903±8.
Strobel A, Issad T, Camoin L, Ozata M, Strosberg AD. A leptin
missense mutation associated with hypogonadism and morbid
obesity. Nature Genetics 1998;18:213±5.
Clement K, Vaisse C, Lahlou N, Cabrol S, Pelloux V, Cassuto D,
Gourmelen M, Dina C, Chambaz J, Lacorte JM, Basdevant A,
Bougneres P, Lebouc Y, Froguel P, Guy-Grand B. A mutation in
the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 1998;392:398±401.
Strosberg AD, Issad T. The involvement of leptin in humans
revealed by mutations in leptin and leptin receptor genes. Trends
in Pharmacological Sciences 1999;20:227±30.
Krude H, Biebermann H, Luck W, Horn R, Brabant G, Gruters A.
Severe early-onset obesity, adrenal insuf®ciency and red hair
pigmentation caused by POMC mutations in humans. Nat Genet
1998;19:155±7.
Yeo GS, Farooqi IS, Aminian S, Halsall DJ, Stanhope RG, O'Rahilly S. A frameshift mutation in MC4R associated with dominantly
inherited human obesity. Nat Genet 1998;20:111±2.
Hinney A, Schmidt A, Nottebom K, Heibult O, Becker I, Ziegler A,
Gerber G, Sina M, Gorg T, Mayer H, Siegfried W, Fichter M,
Remschmidt H, Hebebrand J. Several mutations in the melanocortin-4 receptor gene including a nonsense and a frameshift mutation
associated with dominantly inherited obesity in humans. J Clin
Endocrinol Metab 1999;84:1483±6.
Vaisse C, Clement K, Guy-Grand B, Froguel P. A frameshift mutation in human MC4R is associated with a dominant form of obesity.
Nat Genet 1998;20:113±4.
Jackson RS, Creemers JW, Ohagi S, Raf®n-Sanson ML, Sanders L,
Montague CT, Hutton JC, O'Rahilly S. Obesity and impaired
prohormone processing associated with mutations in the human
prohormone convertase 1 gene. Nat Genet 1997;16:303±6.
Vaisse C, Clement K, Durand E, Hercberg S, Guy-Grand B, Froguel
P. Melanocortin-4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest 2000;106:253±62.
Li WD, Joo EJ, Furlong EB, Galvin M, Abel K, Bell CJ, Price RA.
Melanocortin 3 receptor (MC3R) gene variants in extremely obese
women. Int J Obes 2000;24:206±10.
Burguera B, Couce ME, Long J, Lamsam J, Laakso K, Jensen MD,
Parisi JE, Lloyd RV. The long form of the leptin receptor (OB-Rb) is
widely expressed in the human brain. Neuroendocrinology
2000;71:187±95.
Savioz A, Charnay Y, Huguenin C, Graviou C, Greggio B, Bouras C.
Expression of leptin receptor mRNA (long form splice variant) in the
human cerebellum. Neuroreport 1997(29):3123±6.
116
J.G. Mercer, J.R. Speakman / Neuroscience and Biobehavioral Reviews 25 (2001) 101±116
[119] Strombom U, Krotkiewski M, Blennow K, Mansson JE, Ekman R,
Bjorntorp P. The concentrations of monoamine metabolites and
neuropeptides in the cerebrospinal ¯uid of obese women with different body fat distribution. Int J Obes 1996;20:361±8.
[120] Brunani A, Invitti C, Dubini A, Piccoletti R, Bendinelli P, Maroni P,
Pezzoli G, Ramella G, Calogero A, Cavagniini F. Cerebrospinal
¯uid and plasma concentrations of SRIH, beta-endorphin, CRH,
NPY and GHRH in obese and normal weight subjects. Int J Obes
1995;19:17±21.
[121] Kaye WH, Weltzin TE. Neurochemistry of bulimia nervosa. J Clin
Psychiatry 1991;52:21±28.
[122] Krahn DD, Gosnell BA. Corticotropin-releasing hormone: possible
role in eating disorders. Psychiatr Med 1989;7:235±45.
[123] Demitrack MA, Putnam FW, Rubinow DR, Pigott TA, Altemus M,
Krahn DD, Gold PW. Relation of dissociative phenomena to levels
of cerebrospinal ¯uid monoamine metabolites and beta-endorphin in
patients with eating disorders: a pilot study. Psychiatry Res
1993;49:1±10.
[124] Karhunen LJ, Lappalainen RI, Vanninen EJ, Kuikka JT, Uusitupa
MI. Serum leptin and regional cerebral blood ¯ow during exposure
to food in obese and normal-weight women. Neuroendocrinology.
1999;69:154±9.
[125] Karhunen LJ, Lappalainen RI, Vanninen EJ, Kuikka JT, Uusitapa
MI. Serum leptin and regional cerebral blood ¯ow during exposure
to food in obese and normal-weight women. Neuroendocrinology
2000;69:154±9.