UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl) UvA-DARE (Digital Academic Repository) Neurobiological aspects of obesity: dopamine, serotonin, and imaging van de Giessen, E.M. Link to publication Citation for published version (APA): van de Giessen, E. M. (2012). Neurobiological aspects of obesity: dopamine, serotonin, and imaging. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date: 10 Jul 2020
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UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl)
UvA-DARE (Digital Academic Repository)
Neurobiological aspects of obesity: dopamine, serotonin, and imaging
van de Giessen, E.M.
Link to publication
Citation for published version (APA):van de Giessen, E. M. (2012). Neurobiological aspects of obesity: dopamine, serotonin, and imaging.
General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, statingyour reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Askthe Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,The Netherlands. You will be contacted as soon as possible.
maps of their cerebral grey matter volumes. their main finding was that those participants
who carried a specific variant of the fto gene (fat mass and obesity-associated gene) had, on
average, an 8% smaller total grey matter volume than the non-carriers. this fto gene variant
is carried by ~ 48% of the western/central europeans population and is associated with an
increased risk for developing obesity (142).
cazettes et al. (143) investigated a different possible cause for the grey matter volume
reduction in obesity. they noted that an overweight or obese state is associated with subtle,
but chronic, systemic inflammation and they hypothesized that this inflammation might impact
on the structural integrity of the brain, in particular in some reward and feeding related areas.
to test their idea they measured fibrinogen levels, a marker of inflammation, and collected mri
data from 44 overweight/obese and 19 lean controls to calculate diffusion tensor imaging (dti)
maps. the main findings of the study were that in obese subjects, the volume of the bilateral
ofc was negatively associated with the inflammation marker, and that fibrinogen levels
correlated positively with diffusion in the amygdala and the right parietal cortex. by contrast,
in healthy lean subjects there was a negative correlation between ofc volume and diffusion in
the left prefrontal, right parietal and left occipital lobe.
contrary to the frequently observed volume decrease of grey matter, there are indications
that the white matter volume is increased in obesity. Haltia et al. (140) report an expansion
of the total white matter volume in their obese sample compared to the controls. Walther et
al. (133) describe bmi associated increases in white matter volumes in frontal, temporal, and
parietal lobes. pannacciulli et al. (135) found greater white matter density in the vicinity of the
striatum of obese subjects and gazdzinsky et al. (132) describe a positive association between
bmi and frontal white matter volume in obese participants. in contrast to this, raji et al. (137)
found a negative correlation between bmi and subcortical white matter. However, the subject
sample in raji’s study differed from that the other studies as the mean age was above 77 years,
and hence the reported white matter reduction might be age-related. an interesting addition
comes from Haltia et al., who scanned their obese subjects again after a 6-week period with a
very low-caloric diet (2.3 mJ per day) (140). it turned out that at this post-diet measurement
the white matter volume was reduced and approached the volume measured in normal weight
subjects. one may wonder whether this is not an acute effect of the diet, but it is nevertheless
an indication that the reported difference in white matter volume between obese and lean
subjects is reversible. No changes in grey matter volume following the diet were reported. in
sum, the data support the conclusion agree that the white matter volume tends to be increased
during obesity and might be adaptable to diet and current weight.
interestingly, the increase in white matter volume does not seem to provide increased
functionality of the white matter tracts. in contrast, the integrity of both white and grey matter
appears to be compromised in obesity. results of research using several different imaging
techniques agree that integrity of several brain structures is affected by a high bmi. by use of
proton magnetic resonance spectroscopy, gazdzinsky et al. (132) showed that bmi negatively
correlated with N-acetylaspartate levels in frontal, parietal, and temporal white matter
and in frontal gray matter. this is an indication that the integrity and amount of neurons is
negatively affected in these brain regions at a higher bmi. furthermore, the choline-containing
metabolite level, a measure of cell membrane turnover, negatively correlated with bmi in the
frontal white matter. altogether, these findings show that especially in the frontal brain regions
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the neuronal integrity in obese people is compromised, which may be a sign of accelerated
cognitive decline. alkan et al. (144) performed diffusion weighted imaging in obese subjects
and controls. increased diffusion is thought to reflect microstructural damage to the brain.
the team reported that the obese subjects had higher diffusion vectors in the hypothalamus,
hippocampal gyrus, amygdala, insula, cerebellum and midbrain. bmi correlated positively with
diffusion in the amygdala, insula, orbitofrontal and middle temporal cortex, showing that areas
involved in the regulation of food intake are adversely affected by obesity.
stanek et al. (145) suggest that the obesity related reduction in executive function and
memory capacity may be a consequence of impaired white matter integrity, since this leads
to reduced neural transmission speed and slower cognitive processing. stanek and her
colleagues investigated the relationship between fractional anisotropy (fa) and bmi in the
corpus callosum and fornix of lean, overweight and obese humans. they found that greater
diffusion, indicated by lower fa values, was correlated with bmi. obese, but not overweight
participants had significantly lower fa values in both formix and corpus callosum, compared
to lean participants. importantly, all subjects in this study were completely healthy (apart form
the high bmi), which means the observed white matter impairments do not seem to be causally
related to diabetes, depression or other obesity related conditions. also, the results of the
analyses on the role of age in the bmi –fa relationship suggest that normal age-related decline
in white matter integrity may interact with bmi, such that age-related negative effects may
occur at an earlier age in morbidly obese.
discussion of structural changes in obesitythe reviewed studies demonstrate that there are structural alterations in the brain that are
associated with obesity and suggest that these changes may be partly responsible for some of
the functional deficits in obese people. it is shown that obesity is associated with a loss in total
brain volume, which can be attributed to an overall reduced grey matter volume. specifically,
grey matter volume loss was reported (although not always consistently) in a wide network of
cerebral regions including much of the frontal and temporal cortex, acc, parahippocampal
area, and cerebellum and seem to be even smaller with a rising bmi. this is most likely a result
of decreased neuronal integrity or even neuronal loss. this highlights a new and critical point
that has not yet become apparent from the research on neurotransmitter levels and functional
brain activation: obesity may lead to accelerated cognitive decline. indeed, obesity has been
associated with increased risk for dementia, in particular alzheimer’s disease (12;128).
again, the question rises whether the reduced grey matter volume is a cause or a result of the
disease. in how far genetic variances are responsible for reduced grey matter in obesity still has
to be demonstrated, but it seems likely that the fto gene plays an important, predisposing role.
White matter changes in obesity also have been quite clearly established. most studies show
increases in white matter volume in obese subjects, however, no association with cognitive
performance is observed.
part of the structural abnormalities might be reversible by dieting, as Haltia et al. (140) have
shown. the fact that the volume increases can be brought back to normal levels by a diet-
induced weight loss is very promising. However, the diet did not show any effect on grey matter
volumes, so it remains to be seen if the reduced executive control and cognitive function can
be increased by weight loss towards a healthy bmi.
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geNeral discussioN much has been done in neuroimaging to elucidate the role of reward processing in obesity.
studies from the field of imaging in obesity have provided convincing evidence that molecular
processes, functional activations and connectivity, and structure are all affected by an
unhealthy weight status. the most robust findings show that in obesity the striatal drd2
availability is lower, that obese people more highly activate several brain regions in response
to visual food stimuli than normal weight subjects and that obese subjects have smaller brain
volumes, probably due to lower gray matter volumes. brain regions that are repeatedly listed
as affected in the different studies are the striatum (Nac, caudate, putamen), prefrontal cortex,
orbitofrontal cortex, amygdala, hippocampus, somatosensory cortex, and the insula (gustatory
cortex). the list of affected brain regions shows that there is a strong overlap between the
areas affected by a high bmi and the corticolimbic reward systems, which chiefly consists of the
ventral striatum, and orbitofrontal cortex (7;146;147). several studies have focused specifically
on the striatum as the dopaminergic reward center. they show amongst others that the drd2
receptor availability is down regulated in obesity and it seems indicated that this constitutes
a predisposing risk factor, as well as being a consequence of the constant overfeeding that
leads to the obese state. dopaminergic brain areas of the reward system (putamen, caudate,
Nac) also show reduced functional activation levels after food consumption in fmri studies e.g.
(100;101), while the bold signal indicates that the same areas respond with hyperactivation to
the presentation of food stimuli (e.g. (82;83). In vivo measurements of extracellular dopamine
levels in rodents have confirmed that there is a reduced dopamine release in the Nac of obese
compared to lean animals (54) and Johnson and Kenney (41) demonstrated that overfeeding
leads to a down regulation of drd2 in the striatum. together, these changes in the normal
balance of the dopamine system are possibly underlying the addiction-like aspects of obesity.
reduced dopamine signaling after food intake promotes further eating to compensate for the
low reward intensity, while the increased striatal activation to food cues may trigger a high
reward expectation and as a motivator to seek food.
further parallels with addiction are the reduced level of striatal drd2 that have been found
in both disorders (20;21) and the particular pattern of activation in response to cues of the
addiction substance (food, drugs). the simple cue exposure can stimulate intense craving and
trigger a strong sensation of “wanting” (as opposed to “liking” in the incentive-sensitization
theory) (148) which is a typical symptom of any kind of addiction. the areas that show increased
responding to food cues in obese subjects are the same as those activated during cue induced
drug craving in addicts. mainly, these regions include the insula, ocf, acc, (dl)pfc, amygdala,
(ventral) striatum, and hippocampus (149).
another parallel that should be highlighted is the impaired inhibitory control that plays a
central role in addiction and possibly also in obesity (122). both disorders are accompanied by
a diminished inability to control behaviour (75), which seems to be reflected in different brain
activation patterns on inhibitory control tasks (114;115). impaired inhibitory control makes it
increasingly difficult to abstain from the addictive substance or consume it in a measured way.
the brain’s capacity for inhibitory control, exerted primarily from the prefrontal cortex, seems
to be a central factor in the aetiology of obesity. research has shown that obese adults tend to
have reduced inhibitory control and already obese children are more impulsive and more reward
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responsive than their lean peers (150;151). children who are less able to inhibit actions are more
likely to develop overweight later in life (152;153). increased impulsivity therefore appears to be
a predisposing risk factor for obesity. the neural mechanisms underlying impulsivity as a risk
factor for future obesity have not been extensively studied with neuroimaging. one fmri study
reviewed above used a food related go/no-go task in obese and lean girls and found that the food
images produced greater reward related bold-signal and lower prefrontal activation in obese
adolescents (114) and another used a stop-signal task in adults. Weight gain to a bmi >30 correlates
with lower volume of cortical frontal grey matter and with reduced executive functioning, which
implies that weight gain can lead to a reduction a person’s inhibitory control capacity and that
impulsivity is thus both a cause and a consequence of the obesity. the ability to resist temptation
can be trained. a recent study in restrained eaters managed to show that by pairing a craved
food stimulus with a fear stimulus, impulsivity towards the desired food can be controlled and
reduced (154). strengthening behavioral control may be a useful strategy to increase the chances
of successful weight loss, and it may even be possible to benefit from existing treatments used in
addiction, if these could be adapted to be suitable for obesity (i.e. food related impulse control
training). the threat of relapsing to old habits (overeating) after a diet is well established and
recent evidence from rodents suggests that dieting can increase stress reactivity by disregulation
of the Hpa-axis, which in turn promotes binge eating and intake of high-fat foods (155). total
abstinence, which is practiced after drug addiction to limit the chance of relapse, is of course
impossible when food is the object of addiction and the daily repeated exposure to food may add
to the difficulty of controlling their eating behavior for obese subjects.
a difference between obesity and addiction might be the prominent role of metabolic
signals in guiding eating behavior. it is of interest that a few studies report correlations between
metabolic parameters and brain function. a high level of insulin in a fasted state predicts
increased hippocampal activation in response to food images and is associated with a high bmi
(97), which indicates that hippocampal feeding regulation interacts with insulin signaling and
can increase a person’s susceptibility to (over)eat. pannacciulli et al. (110) showed that post
meal peak glp-1 level was positively correlated to rcbf in the dlpfc and hypothalamus in
obese and lean subjects. rosenbaum et al. (94) demonstrated that daily leptin injections were
effective in dampening the hyperactive reward sensitivity state after weight loss and reduced
the rewards system activation to food cues. these studies show that it will be possible to further
elucidate the role of these metabolic signals on the brain. a recent publication reported on
a role of glp-1, describing that activation of the glp-1 receptor may have a protective effect
on cortical and dopaminergic neurons (156), which might be very interesting with regard to
the affected dopamine system in obesity. given the previous comparison to addiction, these
findings in obesity might even lead to advances in the field of addiction. for example, neural
signals from the food regulation center of the hypothalamus also appear to play a role in
addiction, e.g. (157), and understanding the influence of metabolic signals on motivation and
behavior may add important information to our current knowledge of addiction and may offer
a target for new treatment options. it has been been shown that signaling of the hypothalamic
neuropeptides orexin/ hypocretin (Hcrt) affects substance addiction, possibly through a
motivational pathway involving the mesolimbic dopamine system (158). this example shows
that research on obesity and substance addiction can provide mutual benefits and lead to an
improved understanding of both disorders.
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one important question that has not been resolved is whether weight loss can restore or
lead to improvements in the affected obese brain. the evidence from studies until now is dual:
there are signs that this is possible, but definitely not in all aspects. in the case of white matter
changes, it seems that dieting can indeed normalize the increased volume back to a baseline
level (140), but for grey matter this regulation effect has not been demonstrated. if grey matter
normalization could be achieved by weight loss, it would be particularly intriguing if also the
cognitive and executive function could be regained. the loss of these functions in obesity is
believed to be a result of the reduced cortical grey matter and therefore it may be amendable
through dieting as well. studies in patients after bariatric surgery show that these patients loose
a lot of weight very rapidly. two research groups have tested how this strongly reduced weight
affects the drd2 system (23;27). the results of these investigations are not very conclusive,
since they partly contradict each other. it seems that there is a complex interaction between
bmi and the striatal drd2 system and that simple weight loss alone is insufficient to bring the
drd2 system back into balance and the drd2 availability back to baseline. regarding functional
changes, it has been shown that after successful weight loss the reduced pfc activations upon
satiation are gradually increased again (90). therefore, normalizing the post-diet leptin levels
appears to help reverse the obesity induced changes in the brain and may aid the body in
regulating its food intake motivation.
finally, the first studies on the role of genetics mediating brain function or structure in
obesity have been published. the a1 allele of the taqia polymorphism in the dopamine d2
receptor gene (drd2) has previously been implicated in substance addiction and impulsivity
(159), which makes it a likely candidate to be involved in obesity as well. stice et al. found out that
women who carry the drd2 taqia a1 allele or the drd4–7r allele have an increased likelihood of
becoming obese, if their brain response to food cues or food tasting follows a certain activation
pattern (85;101). in addition, fto is associated with lower total grey matter volume (141) and has
come forward as an important gene related to bmi in genome-wide association studies (142).
these studies need replication, but will also be helpful to answer the question whether some
brain changes are the results of the obese state or the other way around.
cliNical implicatioNsmedical treatment options for obesity are unfortunately only limited in their success. the
main options are the traditional methods of (supervised) dieting and exercise, medication and
surgery. the results of medication have been disappointing, since to date, no drug has been
able to induce lasting and substantial weight loss in a range of patients or drugs have been
withdrawn from the market due to their side effects. because of the more reliable and enduring
success, surgery (e.g. gastric bypass) has been the principal choice option and the number of
surgical interventions has largely increased over the past 10 years. However, most operations
are very drastic and lead to lifelong, serious restrictions on eating behaviour with side-effects
such as vitamin deficits. Neuroimaging studies have the potential to provide important new
findings to improve out knowledge about the aetiology of obesity and can possibly point
towards new targets for intervention.
the similarity between obesity and addiction discussed previously makes it conceivable
that treatments that are effective in cases of addiction may also benefit obese patients once the
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treatments have been tailored to address the specific object of addiction. further treatments
may be developed based on theories of cognitive therapy, possibly targeting impulsive
behaviour (e.g. binge-eating) by strengthening cognitive control capacities, or aiming to
improve weight-loss outcomes and life-style by reducing anxiety and body-dissatisfaction
through guided exposure therapy (160). pharmacologic treatments for obesity can possibly
benefit from medication research concerning addiction, because similar underlying
neurochemical pathways are affected in both disorders that can be influenced through drugs.
in treating obesity, medications that target just one mechanism produce relatively little
weight loss (decrease of 5%-10% body weight) and the associated risk factors diminish their
practical usefulness (161). New combinations of pharmacotherapy are currently being tested
(e.g. phentermine with the serotonin precursor l-5-hydroxytryptophan and the peripheral
decarboxylase initiator carbidopa) (162). Neuroimaging studies could to support these kind
of processes by screening the effect of anti-obesity drugs in lean, but also in obese people
and evaluating the functional changes of brain activation to different in response to different
cues, and at baseline. for example, treatment with the cannabinoid-1 receptor antagonist
rimonabant, which is an anti-obesity drug, reduces the neural response to visual food stimuli
in reward related brain regions (163). as we now know that these brain regions are affected in
obesity, these paradigms could be used in the development of new drugs.
deep brain stimulation (dbs) is a method that is used in neurologic disorders (parkinson’s
disease) and sometimes for the treatment of psychiatric disorders such as severe depression
or obsessive compulsive disorder (ocd). given the role of the nucleus accumbens in reward
from food, which has been indicated by the neuroimaging studies, one can imagine that Nac
dbs could be a potential treatment in morbid obesity. there is one case report showing that
dbs of the Nac can lead to remission of the obsessive compulsive symptoms, accompanied
by successful weight loss (-44 kg, from bmi 37 to bmi 25) and lasting cessation from smoking
without any cravings or withdrawal symptoms (164). in this case, as a side effect, the ocd
treatment intervention facilitated both weight loss and quitting of smoking. in view of the
remarkable success, it seems promising to continue the investigation of dbs in obesity since
it could develop into a powerful tool to aid morbidly obese patients. it is likely that among
obese patients there is a spectrum of varied underlying causes, but the role of diagnostics to
differentiate subtypes of obesity is very limited until now. Neuroimaging studies could in future
help to predict cases in which dbs may be successful, based on neuroimaging data of Nac
activation in response to food stimuli and food consumption.
in the same way, neuroimaging data could potentially inform the decision of what type
of treatment should be applied in individual cases of obesity. for instance, one can imagine
that medication with the glp-1 like analogues (exenatide, liraglutide) may be more effective
in cases where very low levels of glp-1 correlate with reduced regional cerebral blood flow
(rcbf, measured with pet) in the prefrontal cortex and hypothalamus (see e.g. (110)). a role for
neuroimaging in these kind of decisions needs a high sensitivity and specificity to detect the
right category of patients. thus, this will not be implicated in short-term.
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future directioNsNeuroimaging in obesity is a relatively young field, which has been developing very quickly
in the last five years. although this study has enabled us to learn much about the key factors,
many questions on the role of the brain in obesity still remain unanswered.
a lot of studies have used neuroimaging techniques to elucidate the role of reward
processing in relation to obesity. future research should also direct its focus towards other
functional processes, such as impulsivity, learning and memory, and executive functions, and
investigate the interaction of all these with reward processing in obese people. interestingly,
the role of emotions in obesity has not received much attention in neuroimaging studies so far,
even though the importance of emotional eating and the impact of emotions on motivation
and action have clearly been demonstrated in lean individuals (165). in normal weight subjects,
the affect state influences brain activation on food pictures (166), so it can be expected that in
obese subjects this also plays a role. Hedonic memories relating to food and feeding probably
play a powerful role in the maintenance of obesity by creating a motivation to consume food
(167). futhermore, women seem to relate cue-induced cravings for sweet food, like chocolate,
with negative emotions like guilt, anxiety, or depression, when on a diet (168). the involvement
of central emotion processing areas like hippocampus and amygdala in the network regulating
food-intake is a definite indication of a key role for emotional memories, current mood state,
and emotion regulation in food related decision-making, clearly warranting the need for more
neuroimaging studies with this focus in future.
the hypothalamus is a central regulator of basic homeostatic food intake, so one would
expect a lot of research concentrating on this structure. However, imaging activation in this
area has been difficult due to technical limitations. advanced imaging protocols and studies
using a 7-tesla mri might be able to fill this gap and provide new insights into the effect of
obesity on hypothalamic functioning.
to date, it remains unclear whether many of the changes observed in brain during obesity
are a cause or a consequence of the disorder. prospective studies are of course very difficult
to execute, but are necessary to definitely answer this question. stice et al. (102) showed the
predictive value of striatal activation for weight gain one year later. this study is a valuable
example of how longitudinal data can inform our understanding of causal relationships, so
studies spanning even longer periods of time would add highly interesting and relevant data.
in the discussion of cause and consequence one persuasive argument is the case of a
predisposition by genetic effects. Nevertheless, even a predisposing gene does not guarantee
the expression of a specific behavioural phenotype with certainty. the human brain is remains
flexible to some extent in adulthood and can adapt itself to the weight status. these adaptational
changes may still be reversible, but future research will need to determine the extent of this
reversibility and more neuroimaging studies should provide follow-up data on weight status to
investigate functional long-term effects of weight gain and weight loss.
regarding structural changes in the brain related to an obese state, there remains some ambiguity
of which areas are most affected and whether weight loss can restore the brain to its normal state.
longitudinal data of structural measurements would be highly relevant for answering this question.
in the same way, not very much is known about the precise effect of obesity on cognitive functioning
(e.g. decline in executive functions, memory) or on the long-term effect of weight loss on cognition
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and neuropsychological functions. the question of reversibility of all of the (negative) consequences
of obesity on the brain is of course of great importance for all those concerned.
finally, one limitation of much of the research to date concerning food related processing
and obesity is that the majority of studies have used mostly women in their sample of participants.
among the obese population in the Western world the distribution is roughly gender balanced
(1), therefore both sexes seem equally prone to develop overweight. it has even been shown
that there is a gender effect on brain activation to food stimuli in lean subjects (169). also, Haltia
et al. (25) showed that there are gender differences in the drd2 levels and that expectations
moderate the dopamine release to a different extent in males and females. the systematic bias
in the gender distribution of study samples should be addressed in future research by focusing
on male subjects and comparing the effects of obesity on the brain between both sexes. there
may be gender specific differences in causes, maintenance mechanisms, and vulnerability of
brain and body to the effects of obesity, so more research is needed that investigates this field.
in conclusion, neuroimaging research in obesity has brought much insight in the etiology
and effects of obesity on the brain. However, many questions remain unanswered and this still
young field will needs further development in future. as the obesity epidemic steadily rises, the
urgency increases for effective, knowledge based interventions to target obesity, and future
neuroimaging research can contribute to their development.
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