obesity-associated alterations in glucose metabolism...

Malbert et al 1

Obesity-associated alterations in glucose metabolism are

reversed by chronic bilateral stimulation of the

abdominal vagus nerve

Charles-Henri Malbert1, Chloé Picq

2, Jean-Louis Divoux

2, Christine Henry

3 and Michael

Horowitz4.

1 AniScans, INRA, dept of Nutrition (Saint-Gilles, France); 2 Axonic, (Vallauris Cedex, France); 3

LivaNova, Sorin CRM SAS (Clamart, France); 4444 Discipline of Medicine, University of Adelaide,

Royal Adelaide Hospital, (Adelaide, Australia).

Corresponding author’s contact information

Charles-Henri Malbert

Aniscan Unit, Dept of Human nutrition, INRA

Aniscan, INRA, 35590 Saint-Gilles, France

Tel : +33 2 23 48 50 71

Mobile : +33 6 08 91 89 89

Fax : + 33 2 23 48 50 80

Email: [email protected]

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Diabetes Publish Ahead of Print, published online January 12, 2017

Malbert et al 2

Abstract

Acute vagal stimulation modifies glucose and insulin metabolism, but the effect of chronic bilateral

vagal stimulation is not known. Our aim was to quantify the changes in whole body and organ-

specific insulin sensitivities, 12 weeks after permanent, bilateral, vagal stimulation performed at the

abdominal level in adult mini-pigs. In 15 adult mini-pigs, stimulating electrodes were placed around

the dorsal and ventral vagi using laparoscopy and connected to a dual channel stimulator placed

subcutaneously. Animals were divided into three groups based on stimulation and body weight i.e.

lean non-stimulated, obese non-stimulated and obese-stimulated. Twelve weeks after surgery,

glucose uptake and insulin sensitivity were measured using PET during an isoglycemic clamp.

Mean whole body insulin sensitivity was lower by 34% (P<0.01) and hepatic glucose uptake rate by

33% (P<0.01) in obese non-stimulated, but was no different in obese-stimulated compared to lean.

An improvement in skeletal glucose uptake rate was also observed in obese-stimulated compared to

obese non-stimulated groups (P<0.01). Vagal stimulation was associated with increased glucose

metabolism in the cingular and prefrontal brain areas. We conclude that chronic vagal stimulation

improves insulin sensitivity substantially in diet-induced obesity by both peripheral and central

mechanisms.

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Malbert et al 3

Obesity is an international public health issue that affects quality of life, increases the risk of

illness, and raises health-care costs. Bariatric surgery remains the most effective treatment

option for obese patients (1). However, these procedures may be irreversible and are

associated with major adverse-effects, some of which may be life threatening (2). There is an

urgent need for alternative therapeutic options which are effective and safe. Animal studies

provide persuasive evidence that acute vagal stimulation increases fasting insulin release

from the pancreas (3). In contrast, the effect of chronic vagal stimulation on insulin sensitivity

has received much less attention. One recent study in Zucker rats suggested that chronic vagal

stimulation may up-regulate insulin receptor expression in the brain, liver and skeletal muscle

(4). However, the functional impact of this change in receptor density has not been studied.

Several studies in obese depressive and epileptic patients suggest that chronic vagal

stimulation alters eating behavior and reduces body weight (5), but there is a paucity of

information about its impact on metabolism. One human study investigated changes in

glucose metabolism during vagal stimulation and found an increase in energy expenditure

and a decrease in muscle and hepatic glucose uptake (6). These observations must, however,

be interpreted circumspectly because (i) glucose uptake was extrapolated from standard

uptake values without the required arterial input function measurement (7) and (ii) the time

frame scrutinized was the short-term interruption of the stimulation that was otherwise

turned on. While overall brain metabolism seems unchanged by unilateral chronic vagal

stimulation in humans (6), ventromedial prefrontal glucose metabolism has been reported to

be decreased (relative to the whole brain SUV) after one year of stimulation in treatment

resistant depressive patients (8). To date, there has not been any true quantitative

measurement of the glucose uptake rate during chronic bilateral vagal stimulation.

Several factors play a critical role in the regulation of glucose homeostasis and, more specifically,

whole-body insulin resistance including; impaired skeletal muscle glucose utilization (9),

diminished hepatic glucose uptake (10) and altered brain metabolism and glucose transport (11).

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Malbert et al 4

Insulin resistance is known to be tissue-dependent and the effects of chronic vagal nerve stimulation

may vary between tissues. The ‘gold standard’ method introduced by the Turku team to quantify

glucose uptake rate and insulin sensitivity has been already successfully used in the pig (12). It has

also been utilized in our experimental paradigm to quantify both organ insulin sensitivity vs whole

body insulin sensitivity.

The aim of our study was to characterize comprehensively the effect of prolonged (12 weeks) vagal

stimulation on whole body, and organ specific, insulin sensitivities in an animal model of insulin

resistance due to obesity. We utilized the Yucatan minipig, an animal model known to rapidly

develop obesity and insulin resistance in response to a high fat /sucrose diet (13) and to have a

relatively large brain with well-defined cerebral circumvolutions. We hypothesized that chronic

vagal stimulation would restore whole-body insulin resistance (i) through changes in the rate of

hepatic glucose uptake by an efferent mechanism, (ii) by modifying several key brain networks

involved in energy intake and glucose metabolism via an afferent mechanism and (iii) as a

consequence of an increase in glucose uptake at the skeletal muscle level, through an indirect

(humoral) mechanism. Accordingly, we determined the effects of chronic vagal stimulation on

whole body, brain, liver and skeletal muscle insulin sensitivities using PET CT imaging during a

isoglycemic hyperinsulinemic clamp. Furthermore, non-oxidative glucose metabolism was

quantified using indirect calorimetry and the impact of the stimulation on the cardiac autonomic

function was assessed using heart rate variability.

Research design and Methods

Animals and diets

A total of 15 adult Yucatan mini-pigs, age and sex matched, were used. Ten animals were made

obese using a high fat, high sucrose diet (4024 kcal/kg of feed) supplied at 150% of the

recommended caloric intake (288 kcal/kg BW0.75

(14)), while the remaining 5 animals were

maintained on a low fat, low sucrose diet (2275 kcal/kg of feed) to limit the amount of body fat and

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ensure that total body weight was less than 40 kg. This feeding scheme was maintained during the

entire experiment. The experiment was conducted in accordance with the current ethical standards

of the European legislation after validation by an ethics Committee (R-2011-MO-01).

Protocol

The animals were divided into three groups (n=5 each): lean, obese and obese-stimulated. The same

surgical procedure was performed in all three groups. Surgical placement of the stimulator and the

electrodes and pulse parameter settings, are described in the online supplemental material. The lean

group was maintained on a low fat, low carbohydrate diet and the stimulator was turned off; the

obese group was maintained on a high fat high sucrose diet and the stimulator was turned off; the

obese-stimulated group was maintained on a high fat high sucrose diet and the stimulator was

turned on.

The animals were weighted weekly from 0 to 12 weeks after the surgery and then imaged using CT

scan to evaluate fat deposition and fat free mass (15). Together with body weight these data were

used to quantify energy expenditure and leptin. Heart rate was recorded for 24 hours to evaluate

autonomic balance. A dynamic PET imaging was performed with arterial in-line and off-line

function measurements during a isoglycemic hyperinsulinemic clamp. Brain, liver and muscle

glucose uptake rates were evaluated from PET images, whole body insulin sensitivity was

calculated from the glucose infusion rate during the clamp. Basal metabolic rate was measured

during, and before, clamp condition using indirect calorimetry.

Measurements

Fat mass repartition and lean mass were quantified by semi-automatic segmentation of CT-based

images of the abdomen obtained at the levels of S1 and S3 (15). The volume of the liver was also

quantified from whole body 3D acquisition using level set based segmentation with MIA Lite

software. The volume of the brain was quantified using the vicinity algorithm of Osirix software

and the ROI adjusted manually subsequently. Electrode impedance, energy expenditure,

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carbohydrate oxidation rate and ghrelin/leptin/insulin concentrations were measured, as described in

the online supplemental material.

PET protocol and data analyses

PET images were acquired during a isoglycemic hyperinsulinemic clamp

(120 mU.kg-1

.hr-1

), as described in the online supplemental material. Glucose uptake rates were

obtained for each organ through model analysis of regions of interest (ROI) data and arterial input

function using PMod software (Switzerland). ROI’s, including either the liver, or the most

voluminous muscles of the leg (i.e. vastus lateralis, gastrocnemus, semimembranosus and

semitendinosus), were drawn manually, while avoiding large blood vessels on the respective PET

images using PMod. ROI’s at the brain level were obtained automatically by co-registration of the

PET brain image with a dynamic PET template co-registered with our 3D brain atlas (16). The

following Lumped Constants (LC) were used to take into account the differences in affinity

between FDG and native glucose: 0.45 for the brain (17), 1 for the liver (12) and 1.2 for the skeletal

muscle (18). A classical 3K model was used for the brain and the liver ROI analysis, while a 5K

model was used for skeletal muscle measurement (9). Glucose uptake rate was averaged over the

two thighs.

To identify changes in brain glucose metabolism that did not extend to large brain areas, a pixel-

wise modeled brain volume was reconstructed from the raw PET images and arterial input function

using PXMod software. Because of the intrinsic noise of such processing, the image was

reconstructed using a Patlak plot instead of a model based approach. The synthetic image was co-

registered in our 3D atlas space.

Statistical analyses

Data are presented as means± SE. Data were compared using one and two ways analysis of variance

using Prism 6 (Graphad, USA). Time dependent analysis (changes in body weight) were corrected

for multiple comparison using the Sidak test. Differences were regarded as statistically significant if

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P < 0.05. Body weight and resting energy expenditure were analyzed by Ancova with final weight

as the dependent variable and pre-operative weight as the covariable and energy expenditure as the

dependent variables and fat free mass as the covariable. T values were obtained from Tukey

pairwise comparison tests performed in Stata 14 (StataCorp, USA). Statistical analysis of brain

uptake rate was performed using SPM8 using a Full Monthy statistical mode with significance level

set as P ≤ 0.001 FDR corrected to exclude random brain activation.

Results

All animals recovered from surgery within a day e.g. their eating behavior was apparently no

different to that observed before surgery. No significant problems were observed during the 12

weeks of the experiment. Electrode impedance measurements obtained on the obese-stimulated

group after 12 weeks of stimulation established that there was no breakage in electrode continuity;

impedance was 828 ± 23 to 958 ± 75 Ohms for the dorsal and ventral vagal trunks, respectively.

Body weight, fat mass, energy expenditure, hormonal status and autonomic balance

In both obese non-stimulated and obese-stimulated groups there was an increase in body weight

compared to the pre-operative weight, whereas there was no change in the lean group. The increase

in body weight was substantially less in the obese-stimulated group compared to obese non-

stimulated group (Figure 1), a difference that was significant at 10 and 12 weeks after surgery

(Table 1).

Total fat mass obtained from abdominal CT measurements was about three times greater in the

obese than the lean group. Vagal stimulation was associated with a reduction in total fat mass

(P<0.05) reflecting a reduction in subcutaneous fat (P<0.05) without any difference in visceral fat.

Hepatic volume was not significantly different between the groups (1397 ± 45.2, 1577 ± 23.4 and

1402 ± 43.3 mL for lean, obese non-stimulated and obese-stimulated respectively) despite an

overall group effect.

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Resting energy expenditure increased during the clamp compared to fasting irrespective of the

experimental group Table 1. Resting energy expenditure was not significantly different in the obese

non-stimulated group compared to lean group during both fasting and the clamp, while vagal

stimulation was associated with a reduction in energy expenditure compared to non-stimulated

obese animals during the clamp only. During the plateau phase of the clamp, the rate of non-

oxidative glucose disposal was reduced (by about 50%) in the obese non-stimulated compared to

lean subjects, while in vagally-stimulated obese animals, non-oxidative carbohydrate metabolism

was no different to the lean group. There was no difference between the groups in the glucose

oxidation rate.

Fasting glycemia and insulinemia were greater in the obese non-stimulated compared to lean group

Table 2, whereas in the obese-stimulated group fasting glycemia and insulinemia were not different

to the lean group. There were no differences between groups in fasting leptin expressed in grams of

fat mass. Ghrelin was lower in the obese non-stimulated group, while in the obese-stimulated group

plasma ghrelin was not different to the lean group.

Autonomic heart balance was not affected by abdominal vagal stimulation, as indicated by an

unchanged LF/HF ratio in obese non-stimulated versus obese-stimulated group (3.1 ± 0.80 versus

3.5 ± 0.31 for obese non-stimulated versus obese-stimulated group, P>0.05). The LF/HF ratio was

lower in the lean group compared to the obese groups (0.5 ± 0.07 for lean group, P<0.05), probably

in part reflecting a lower RR interval in the lean group (607 ± 15.3, 969 ± 52.5 and 930 ± 66.2 msec

for lean, obese non-stimulated and obese-stimulated groups, P<0.05).

Whole body and organ specific insulin sensitivity

Insulin-mediated glucose metabolism was reduced in the obese non-stimulated group compared to

lean and obese-stimulated groups Table 3. Insulin sensitivity and whole body glucose uptake were

reduced by about one third in the obese non-stimulated group compared to obese-stimulated, while

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in the obese-stimulated group insulin sensitivity and whole body glucose uptake were not different

from the lean group.

Hepatic glucose uptake was reduced by more than one third in the obese non-stimulated group

compared to the lean group Table 3. Similarly, skeletal muscle glucose uptake was less in the obese

non-stimulated compared to the lean group, whereas there was no difference between the obese-

stimulated compared to the lean group when skeletal muscle glucose uptake was expressed in grams

of fat free mass. The improvement in skeletal muscle glucose uptake observed in the obese

stimulated group is likely to be the consequence of an improvement in the transport process, as

indicated by significant changes in k3 and k4 kinetic parameters (increased inward k3 and decreased

outward k4) in the obese stimulated compared to non-stimulated group (Table 4).

Brain glucose metabolism and regional brain FDG uptake

Brain glucose metabolism, as assessed by the rate of insulin mediated glucose uptake, was reduced

in the obese non-stimulated compared to the lean group Figure 2, particularly in the frontal and

temporal cortices where the VOI level analysis showed a significant difference at P<0.01. In the

group with vagal stimulation there was no difference in glucose uptake rate compared to the lean

group in any of the brain areas for which a VOI analysis was performed Table 3. Unidirectional

glucose transfer from blood to brain, calculated through the analysis of the K1 parameter, was less

in the obese non-stimulated compared to the lean group and not significantly different from the lean

group to the obese-stimulated group (0.62 ± 0.034, 0.42 ± 0.0051, 0.63 ± 0.029 µmol/min/100g for

lean, obese non-stimulated and obese-stimulated respectively, P<0.05).

Using statistical parameter mapping analysis, four areas were found to be activated differentially

between obese non-stimulated and obese-stimulated groups despite a very conservative approach

e.g. P < 0.001 FDR and cluster level corrected Table 5. The main area, both in terms of size and

with the second largest Z score, was the dorsal anterior cingulate cortex Figure 3. No differences

were observed, using the same conservative approach, between lean and obese-stimulated groups.

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Discussion

Our study demonstrates for the first time that chronic bilateral vagal stimulation has the capacity to

restore fasting glucose metabolism in obese pigs. This effect occurs at the whole body level and in

the brain, the liver and the skeletal muscle and is associated with reductions in fasting glucose and

insulin and an increase in ghrelin concentrations. The observed changes in glucose metabolism in

the brain were area-specific, with particular involvement of a amygdalo-cingulate network; a

network already identified in depressive patients treated with vagal stimulation (8; 19). We also

demonstrated that vagal stimulation increases non oxidative glucose metabolism and reduces fat

mass. Finally, our study confirms the attenuation of weight gain by vagal stimulation observed in

our previous study (20).

The vagus nerve comprises an intricate neuro-endocrine network that maintains body homeostasis

and it is, accordingly, difficult to identify the precise physiological processes modified by vagal

stimulation. Therefore, we believe that the investigation of the impact of vagal stimulation on

glucose metabolism must be comprehensive. We have used a combination of methods, including

quantitative PET imaging that represents the gold- standard, to investigate glucose metabolism at

the systemic and organ level (21). Potential confounding effects related to surgery were minimized

by the development of (i) a laparoscopic surgical approach to insert dedicated electrodes on the

dorsal and ventral vagal trunks and (ii) a purpose-made dual channel stimulator placed under the

skin. Finally, the stimulation lasted 12 weeks, since previous studies have demonstrated that the

effects of vagal stimulation may be dependent on its duration (22). This is distinct from previous

studies that were either of short duration (acute or ≈ 2 weeks) (23) or employed non validated

methods to evaluate insulin sensitivity (6; 24).

Arguably, the most important observation in our study is that vagal stimulation induces an increase

in whole body glucose uptake that leads to improved insulin sensitivity which itself led to a

reduction in fasting glucose. We further demonstrated that insulin-mediated hepatic glucose uptake

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was impaired by obesity and reversed by vagal stimulation. Such changes in hepatic glucose uptake

(HGU) have been observed in obese subjects both before and after bariatric surgery (10).

Abnormalities in HGU have been implicated in the pathogenesis of liver steatosis, hyper-

triglyceridaemia and type 2 diabetes (21). Accordingly, vagally-induced improvement in HGU

may be of relevance in the context of obesity, despite the limited quantitative impact of HGU

on whole body glucose uptake (about 1% of whole body glucose uptake). Improvement in

hepatic glucose uptake, through activation of glycogen synthetase, has been demonstrated during

acute stimulation of the hepatic vagal branches (25). Since our stimulation scheme employed

relatively similar pulses, it is probable that part of the improvement in hepatic glucose uptake was

the consequence of a peripheral activation of the vagal hepatic branches. Furthermore, as hepatic

vagal section induces insulin resistance (26), it could be suggested that vagally-mediated effects on

hepatic glucose uptake persisted over time, being comparable in both an acute and a chronic set-up.

Aside from the aforementioned improvement in hepatic glucose uptake induced by vagal

stimulation, we also found a vagally-induced improvement in skeletal muscle glucose uptake. Given

the large volume of muscle mass this is probably the major quantitative contributor to whole body

glucose uptake. While the kinetic constants for 18

FDG differed in the porcine model compared to

human and were based on mathematical modelling of kinetic data only, they are within the

boundaries for FDG during clamp defined by Kelley group (27). The substantial improvement in

skeletal muscle glucose uptake observed in the vagal stimulation group is likely to reflect alterations

in the transport mechanism, since k3 and k4 differed between the obese non-stimulated and obese-

stimulated groups. This mechanism, together with glucose delivery, modulates muscle glucose

uptake in diet-induced insulin-resistant rats (28) and, to some extent, in obese subjects (27). This

may potentially relate to the stimulation of ghrelin by VNS since exogenous systemic ghrelin

administration has been reported to facilitate glucose uptake by skeletal muscle and increase

its insulin sensitivity (29). The precise glucose metabolic step targeted by ghrelin is not

known. Alternatively, the increase in muscle glucose uptake may reflect a centrally mediated

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activation of the sympathetic system. Indeed, sympathetic activation improves muscle glucose

uptake (30) and is likely to be a consequence of anterior cingulate cortical activation (31).

Fasting glucose and insulinemia were reduced by vagal stimulation. The reduction in fasting

glucose might relate to an increase in glucose uptake by the liver and the skeletal muscle in obese-

stimulated animals. There are a number of potential explanations for the increase in fasting ghrelin

observed during vagal stimulation. First, ghrelin levels rise in obese individuals after diet-induced

weight loss (32) and the attenuation of weight gain induced by vagal stimulation might be sufficient

to activate this phenomenon. Second, stimulation of the vagus can increase ghrelin secretion

directly. Indeed, in both rats and humans, ghrelin is stimulated by muscarinic agonists and

diminished by muscarinic antagonists (33).

We observed substantial differences in brain activity between obese non-stimulated and obese-

stimulated groups in several brain areas, all of which were either part of the limbic system, or had

access to the former via the amygdala-hippocampus-enthorinal cortex pathway. These brain areas,

with specific reference to the dorsal anterior and dorsal posterior cingulate cortices, have been

identified in patients treated for depression by vagal stimulation (34). The importance of the

cingulate in insulin secretion is of particular interest since electrical stimulation of the dorsal

cingulate cortex in the dog suppresses insulin secretion in response to an intravenous glucose load

(35). Similarly, there is evidence that the cingulate cortices are involved in the brain response to the

GLP1 agonist, exenatide (36) which also improves insulin sensitivity. There is a large body of

evidence that insulin resistance is associated with altered striatal activity and impaired dopamine

function (37). Surprisingly, in our model, we were unable to identify any vagally- induced change

in striatal glucose metabolism. However, in insulin resistant patients, without cognitive impairment,

the anterior and posterior cingulate CMRglu’s were also reduced (38). Unlike the striatum, we

found the metabolism of these structures to be profoundly altered in the obese-stimulated group

compared the obese non-stimulated group. In addition, in insulin resistant humans, the functional

connectivity between the striatum and the cingulate appears to be altered and related to symptoms

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of depressive mood (39). Since vagal stimulation-induced improvement in depressive symptoms

has been linked to modifications in cingulate activity and, conversely, that insulin resistance

triggers alteration in the same brain areas, it can be speculated that vagal stimulation modifies the

consequence of insulin resistance through an action on the cingulate cortices and/or their

connectivity’s to the limbic system. The implication of the amygdala in the network initiated by

vagal stimulation is not surprising given that the outcome of several studies supports a role for the

amygdala in insulin resistance (40). Our compartmental analysis of glucose uptake allowed

identification of the unidirectional glucose transfer from blood to brain as fundamental to these

focal activations. Since PET is insensitive to the effects of flow/metabolism coupling, it is likely

that the effect of vagal stimulation reflected, at least in part, a change in the transport mechanism of

the brain blood barrier to glucose.

Energy expenditure was not altered in the fasting state, or during the clamp, unlike previous studies

using either unilateral short lasting vagal stimulation in rats (41), or rapid on/off stimulating pattern

in humans (6). Rather, we found a reduction in energy expenditure that was less than that observed

in the lean group. An explanation to account for this discrepancy is that energy expenditure may be

controlled by low threshold B/A fibers only. Indeed, as these fibers were not present at the

abdominal level, abdominal vagal stimulation had no effect on energy expenditure either in our

study or that of Sobocki et al (42). Conversely, Vijgen et al (6) activated low threshold B/A fibers

by selecting a cervical stimulation and observed an increased energy expenditure. The absence of

changes in heart rate variability in our experimental design is consistent with this hypothesis since

HRV relies, for its vagal component, on the activity of low threshold B/A fibers innervating the

heart.

Vagal stimulation reduced weight gain of our animals so that in stimulated animals weight gain was

about 25% less than non-stimulated ones. Similar changes were observed for total fat mass, which

was reduced by 24%, but not visceral fat, which was not altered by vagal stimulation. The absence

of a vagally-induced reduction of visceral fat was surprising, since in humans central/visceral

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obesity is closely related to insulin resistance and other metabolic consequences of obesity (43). We

do not have a clear explanation for this finding, but it is possible that porcine visceral fat

metabolism responds differently to weight reduction than that in humans (44), or that the

relationship between visceral fat and metabolic outcome is weak, or non-existent below a set degree

of obesity.

It should be recognized that our study has limitations. We were unable to stabilize the body weight

of obese animals irrespective of the group i.e. in both the obese groups weight gain was progressive

after surgery. This was often observed in several animal models of obesity. For example, even after

Roux en Y bypass, super obese mini pigs continue to gain weight (45). In rodents, sham operated

obese animals gained about 20% of their body weight, 100 days after surgery (46). Nevertheless,

there was a clear difference in weight gain at 12 weeks between the stimulated and the non-

stimulated groups. We did not measure insulin production. Although this can be performed easily in

an IVGTT/OGTT set-up with C-peptide dosage in pigs, the porcine C-peptide antibodies were

discontinued by Novus and the new Mercodia test was under evaluation. Finally, our results refer to

fasting insulin-mediated changes, since whole body and organ specific glucose uptake rates were

measured during the clamp. An additional measurement without a clamp might have provided

additional insights and would have allowed hepatic glucose production to be calculated. While post-

prandial glucose metabolism might modulate the effect of vagal stimulation, its major contributor

i.e. gastric emptying of liquids or solids, was not affected after five days of chronic vagal

stimulation (47).

Our observations relating to the restoration of whole body and organ specific insulin sensitivities

have potential implications. Bilateral abdominal vagal stimulation was able to reduce weight and to

restore insulin sensitivity. In contrast, unilateral cervical vagal stimulation has minimal effect on

body weight (41) and does not affect fasting glycaemia (48). Therefore, the technical challenge of

inserting two electrodes around the abdominal vagal trunks needs to be weighed against the positive

impact on insulin sensitivity, which is a key player in obesity-associated comorbidities. Recently, in

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an uncontrolled study, the opposite to vagal stimulation e.g. vagal blockade by high frequency high

amplitude biphasic pulses on both abdominal vagal trunks for 12 months has been reported to

reduce HbA1c by 1% and it was suggested that the improvement of HbA1c was related to the

associated weight loss (49). Nevertheless, a previous study from the same group using the same

device failed to demonstrate any weight loss (50).

In conclusion, we have demonstrated that chronic bilateral stimulation of the vagus at the

abdominal level improves whole body insulin sensitivity reflecting substantial improvements in

brain, hepatic and skeletal muscle glucose uptake rate. While this was associated with attenuation in

the gains in weight and body fat, we were unable to establish a causal relationship between the two

phenomena. The observed changes are likely to be the consequence of both efferent hepatic

stimulation and afferent brain stimulation with specific involvement of the cingulate cortex.

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Acknowledgements

The study was conducted within the Aniscan imaging center (Aniscan, INRA, 35590 Saint-

Gilles, France) and the animal facilities of Pegase unit (UMR Pegase, INRA, 35590 Saint-Gilles,

France) at Saint-Gilles. It was supported by BPIFrance within the “Investments for the Future”

program in France. No potential conflicts of interest relevant to this article were reported by

C.H.M., C.P., J.L.D, C.H. and M.H.

C-H.M. and C.P. planned the experiments, conducted the studies, analyzed the data and wrote

the manuscript. J-L.D. designed the stimulating electrodes and the specifications of the

stimulator. C.H. was responsible of the stimulator. M.H. made a major contribution to writing

including data interpretation. C-H.M. is the guarantor of this work and, as such, had full access

to all the data in the study and takes responsibility for the integrity of the data and the

accuracy of the data analysis. The authors thank the staff of the animal facilities of Pegase unit

for animal care: Mickael Genissel, Julien Georges, Alain Chauvin, Francis Le Gouevec and

Vincent Piedvache. The authors thank Christine Trefeu (Pegase unit) for leptin and ghrelin

measurements and Raphael Comte (Pegase unit) for insulin measurement. The authors also

thank Eric Bobillier, of Aniscan imaging center, for the development of the electronic in-line

radiation detector. The authors also thank the members of Aniscan imaging center for data

collection.

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Malbert et al 21

Table 1 - Phenotypic and metabolic characteristics of the animals, 12 weeks after onset of

stimulation and implantation of the stimulation device. Obese-stimulated animals received vagal

stimulation during this entire period (n=5 in each group).

Lean

Obese non-

stimulated Obese-stimulated

Body weight changes from pre-

operative (kg) - 0.4 ± 0.60 18.6 ± 1.06✝ 13.8 ± 0.99*✝

Body weight (kg) 32.5 ± 1.10 50.3 ± 1.03 47.7 ± 1.24

Total Fat mass (kg) ◊ 3.3 ± 0.74 8.0 ± 0.68✝ 6.1 ± 0.30*✝

Visceral Fat mass (kg) 1.0 ± 0.26 2.3 ± 0.32✝ 2.7 ± 0.30✝

Fat free mass (kg) 29.1 ± 1.32 42.3 ± 0.97 ✝ 41.7 ± 0.64✝

Fasting energy expenditure

(kcal/day) ‡ 942 ± 23.9 1126 ± 43.6 877 ± 66.3

Energy expenditure during clamp

(kcal/day) ‡ 1118 ± 9.7 1324 ± 52.3 1071 ± 104.1*

Glucose oxidation rate (mg/kg/min) 6.8 ± 0.75 6.2 ± 0.47 6.1 ± 0.37

Non-oxidative glucose disposal

(mg/kg/min) 4.5 ± 0.65 2.7 ± 0.21✝ 4.3 ± 0.24*

Data are mean ± SE. * different from obese non-stimulated at P<0.05. ✝ different from lean at

P<0.05. ◊ final weight as the dependent variable and pre-operative weight as the covariable. ‡

energy expenditure as the dependent variable and fat free mass as the covariable.

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Malbert et al 22

Table 2 - Biochemical characteristics of the animals, 12 weeks after implantation surgery. Obese-

stimulated animals received vagal stimulation during this entire period (n=5 in each group).

Lean

Obese non-


Fasting blood glucose (mmol/L) 3.9 ± 0.22 4.7 ± 0.24✝ 3.6 ± 0.21*

Fasting plasma insulin (µU/mL) 0.7 ± 0.10 2.1 ± 0.31✝ 0.8 ± 0.21*

Fasting plasma leptin (ng/mL/kg fat

mass) 1.2 ± 0.02 1.3 ± 0.22 1.0 ± 0.12

Fasting plasma ghrelin (pg/mL) 503 ± 9.19 303 ± 61.5✝ 484 ± 45.6*

Mean blood glucose during clamp

(mmoles/L)◊

3.9 ± 0.36 4.7 ± 0.20✝ 3.6 ± 0.33

Clamp plasma insulin (µU/mL) ◊

181.1 ± 6.75 305.0 ± 13.87 ✝ 224.0 ± 8.08*

Data are mean ± SE. * different from obese non-stimulated P<0.05. ✝ different from lean at

P<0.05. ◊

indicates values at clamp plateau ≠ 120 minutes after onset of insulin infusion.

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Malbert et al 23

Table 3 - Whole body, brain, liver and skeletal muscle glucose metabolism during the clamp in the

three groups (n=5 in each group)

Lean

Obese non-


Whole body Insulin

sensitivity

(dL/kg.min/µU/mL*1E-3)

6.4 ± 0.25 4.2 ± 0.37✝ 5.8 ± 0.20*

Whole body glucose uptake

(µmoles.min-1

.kg-1

) 66.0 ± 5.08 47.3 ± 1.58✝ 62.5 ± 2.72*

Brain glucose uptake

(µmoles.min-1

.100g-1

)

27.6 ± 2.47

(0.75%)

17.9 ± 3.98✝

(0.47%)

28.1 ± 3.27*

(0.61%)

Hepatic glucose uptake

(µmoles.min-1

.100g-1

)

3.7 ± 0.31

(2.41%)

2.5 ± 0.27✝

(1.67%)

3.9 ± 0.32*

(1.85%)

Skeletal muscle glucose

uptake (µmoles.min-1

.kg-1

) 66.7 ± 11.34 56.4 ± 3.32✝ 72.5 ± 8.67*

Data are mean ± SE. Whole body data are expressed in kg of body weight. Brain, liver and muscle

glucose uptake are expressed in tissue weight. * Different from obese non-stimulated at P<0.01. ✝

Different from lean at P<0.01. Values in brackets are % of brain or hepatic uptakes relative to

whole body glucose uptake. Data are not shown for skeletal muscle because of the imprecise

quantification of muscle mass using CT.

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Malbert et al 24

Table 4 - Kinetic constants for 18FDG in the skeletal muscle using a 5K model in the three

groups (n=5 in each group)

Lean

Obese non-


K1 (ml.ml-1.min-1) 0.0764 ± 0.03839

(3 ± 0.5 %)

0.1106 ± 0.02139

(5 ± 0.4 %)

0.1355 ± 0.04305

(3 ± 0.2 %)

k2 (min-1) 0.0996 ± 0.03785

(12 ± 0.9 %)

0.1138 ± 0.02480

(23 ± 12.2 %)

0.1022 ± 0.02320

(6 ± 2.6 %)

k3 (min-1) 0.0247 ± 0.0067

(22 ± 4.1 %)

0.0136 ±

0.00391‡

(8 ± 2 %)

0.0240 ±

0.00473*

(31 ± 13.9 %)

k4 (min-1) 0.0053 ± 0.00236

(6 ± 0.7 %)

0.0125 ±

0.00619‡

(40 ± 21 %)

0.0078 ±

0.00303*

(36 ± 14 %)

k5 (min-1) 0.0276 ± 0.00969

(38 ± 21.4 %)

0.1092 ±

0.03728‡

(53 ± 44.1 %)

0.0572 ±

0.03968*

(75 ± 30.7 %)

Data are mean ± SE. kinetics constants were obtained after the iterative fitting using a 5K model

with VB is fixed at 5%. Values in brackets are the errors for parameter estimation. * Different from

obese non-stimulated at P<0.05. ‡ Different from lean at P<0.05.

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Malbert et al 25

Table 5 - Statistical parameter mapping analysis of activation patterns (local maxima) in obese

stimulated animals relative to obese non stimulated ones.

Coordinate of local maximum (x, y, z in mm)

Pcorrected

(voxel level)

T-Value

(voxel level)

Tentative anatomic

localization

-16, 4, 1 0.002 4.14 Amygdala R

-0, 22, 11 0.003 3.63 Dorsal anterior

cingulate cortex R

-6, 46, 1 0.004 3.5 Anterior prefrontal

cortex L

6, 5, 12 0.005 3.31 Dorsal posterior

cingulate cortex R

Analysis was performed with cluster size of 100 voxels each of the cluster representing 1mm3.

Values of P were presented using FDR correction. Tentative anatomic localization is given based

on interpretation of the projection of the activation pattern on the pig brain anatomic atlas

published by our group [23].

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Malbert et al 1

Figure 1: Changes in weight post-surgery expressed as a percentage of the initial weight. * indicates

difference (P<0.05) from obese non-stimulated group.

Figure 2: Brain glucose uptake per 100g of brain tissue. Left histogram - the brain areas from which

the VOI were obtained were calculated as the 3D sum of individual smaller regions defined in the

3D digital pig brain atlas published by our group. Right histogram - Whole brain VOI was

calculated as the sum of the 178 individual brain structures. Mean brain glucose uptake was less in

all structures in the obese non-stimulated group compared to the lean group, but this difference was

only significant for the frontal and the temporal cortices. Vagal stimulation was associated with an

increase in the glucose uptake rate in the obese-stimulated versus obese non-stimulated group, so

that there was no difference from the lean group. * indicates a difference from lean group at P<0.01.

All others bars in the obese non stimulated group were different from lean at P<0.05.

Figure 3: Results from voxel-based statistical parametric mapping analysis showing the differences

in glucose metabolism between the obese non-stimulated and obese-stimulated groups. A - The

cross-hair was centered on the largest region that differed between the stimulated and non-

stimulated obese groups e.g. the dorsal anterior cingular cortex. B - Tridimensional projection of the

brain areas for which statistical differences in glucose metabolism between obese non stimulated

and obese stimulated groups were evident. For right and left planes - P ≤ 0.005 cluster level FDR

corrected.

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0 2 4 6 8 10 12-20

0

20

40

60

80

Weeks after surgery

% B

ody

wei

ght r

elat

ive

to p

re-s

urge

ry c

ondi

tion Lean

*

*

Obese StimulatedObese non stimulated

**

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Frontal

corte

xTem

poral co

rtex

Parieta

l corte

x

Occipita

l corte

x

Insula

Striatu

m

Cerebell

um

Thalamus

0

5

10

15

20

25

Brain CMRgluµm

ol/m

in/1

00g

LeanObese non stimulatedObese stimulated

* *

Whole brai

n

*

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0

4.5 Z

A

B

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Malbert et al Supplementary material p 1

Online supplemental material

Vagal stimulation and surgery

Two sets of cuff electrodes were fixed on the dorsal and ventral trunks using laparoscopy.

This was achieved using a left lateral approach with 5 laparoscopic ports while the pig was

placed in right decubitus position to expose the crus and the gastro-esophageal junction.

Under general anesthesia and artificial ventilation (isoflurane MAC = 2.0 and Fentanyl IV

500 µg in toto) both vagal trunks were freed from their connective tissue attachments at the

level of the esophagogastric junction. After placement around the nerve, the electrode cuff

was secured in position using two surgical clips (Acuclip OMSA8, Covidien) to allow it to

move longitudinally independently from the oesophagus. Particular care was taken during this

procedure to minimize nervous tissue damage and the vagal trunk was not grasped directly at

any time. Once in position, a stitch (SILS Stich, Covidien) was placed between the left and

right crus to close the esophageal groove. The electrode leads were then placed between the

liver and the diaphragm and exited using the most distal laparoscopic port. The stimulating

electrodes consisted of in cuff electrodes for a nerve diameter target of about 3.0 mm and

comprised two pairs of Pt-Ir 10% half circular contacts (4 in total), short-circuited together to

form a bipolar configuration. Pairs of contacts were located on both sides of a tube, forming a

circumference, 10 mm distal from the other pair of contacts. The overall dimension of the cuff

was 25 ± 0.1 mm.

The electrode leads were connected to a neurostimulator that was implanted in a subcutaneous

pocket immediately behind the last rib on the left flank. The neurostimulator was derived

from a cardiac pacemaker and was able to deliver a current-controlled pulse to the two set of

electrodes in an independent manner. The device included an impedance measuring

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subroutine that allowed the maximum and minimum impedance values to be evaluated daily.

Bidirectional data transfer was performed transcutaneously with an inductive wand placed

temporarily over the skin within the vicinity of the stimulator. Stimulation was performed as

bipolar pulse trains. The frequency of the pulses within the train was 30 Hz for a 500 ms

pulse. The duration of each pulse train was 30 s and the interval between pulse trains was 5

min [1, 2]. The amplitude of the pulse was initially set to 1 mA, one day after surgery to

progressively reach 5 mA one week afterwards. This value was maintained until the end of

the experiment.

Isoglycemic hyperinsulinemic clamp

Insulin (Actrapid, Novo Nordisk, Denmark) and glucose 20% were infused using a catheter

placed extemporaneously in the saphenous vein. Insulin was diluted in 50 ml saline plus 0.5%

homologous blood and infused at 120mU.kg-1

.hr-1

. This rate was selected based on

Christoffersen et al [3]. Arterial blood samples were obtained every 5 minutes from a

Sledinger type catheter (RS+A50K10SQ, Terumo, France) placed extemporaneously under

echo guidance (M Turbo, Sonosite, France) in the femoral artery [4]. Measurements of blood

glucose from the arterial blood sample were obtained using a OneTouch Verio+ reader

(Lifescan France). The clamp was computer-controlled with custom software written by one

of the author (CHM, AniMate) running an algorithm derived from Furler et al [5], which

includes a filter to remove glucose measurement noise, as suggested by Bequette [6]. Whole

body insulin sensitivity (M) was calculated according to Defronzo et al [7] and Bastard et al

[8] (IS) to take into account differences in insulinemia both before and during the clamp.

Individual parameters were calculated from LOESS-smoothed glucose infusion rate versus

time data [9]. In each clamp the plateau was considered to have been achieved when

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variations of glucose uptake rate and glycemia were less than 5% in three consecutive

samples.

Since the validity of the clamp measurement is dependent on complete suppression of hepatic

glucose production (HGP) by insulin, we have calculated HGP value for all subjects, using

the procedure described by Iozzo et al in pigs [10]. AUCFDG was obtained using 3

exponentials adjustment of the arterial radioactivity curve with Pkin software (Pmod,

Switzerland).

PET study protocol

PET images were acquired during the isoglycemic hyperinsulinemic clamp using an ECAT

EXACT HR CTI/Siemens. A transmission scan of 5 min was performed with three rotating

pin sources containing 68Ge before the emission scan to correct for tissue attenuation. At the

glucose perfusion plateau of the clamp, 18

Fluoro-deoxy-glucose (FDG, about 370 MBq, IBA

France) was injected intravenously over 30 seconds, the amount of 18

FDG injected was

calculated subsequently through measurements of the residuals from the injecting syringe,

extension lines and sampling vial. The PET-Scanning started from the brain (4 x 30 s, 3 x 60

s, 10 x 300 s frames), followed by the liver (5 x 180 s frames), and legs (3 x 300 s frames)

[11]. Concurrently with the PET scanning, arterial blood radioactivity was recorded

continuously for the first 13 minutes after 18

FDG injection using an in line device coupled

with a gamma ray detector (Model 802 Canberra, Areva) according to Bingham et al [12].

Blood was withdrawn at a rate of 4 ml/min through a computer controlled peristaltic pump

coupled with a weighting scale (AniMate software, Labview). Subsequently, arterial blood

and plasma samples were withdrawn once during each time frame and measured using an

automatic gamma counter (Wizard 1470, Perkin Elmer). The in-line blood sampling device

and automatic gamma counter were both cross calibrated daily before the experiment against

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the PET scanner using a 18

F water filled phantom of 5 liters as reference. Composite arterial

input function was built from these measurements using AniMate software (Labview, 2015).

All image data were corrected for dead time, decay and photon attenuation. PET images were

reconstructed by filtered back-projection and smoothed with a Hanning 0.5 Hz filter. This

gave a spatial resolution of 8.5 mm full-width at half maximum transaxially and axially.

Reconstructed images of the brain were displayed in a 128 x 128 x 63 - voxel format, each

voxel measuring 0.64 x 0.64 x 2.42 mm. These values were larger for the liver and the leg

(skeletal muscle) 128 x 128 x 63 voxel format where each voxel measured 2.57 x 2.57 x 2.42

mm. Glucose uptake rates obtained initially in units of volume were converted in units of

weight using the following densities: 1 g/ml for brain tissue, 1.05 g/ml for liver and 1.06 g/ml

for skeletal muscle.

Ancillaries

Energy expenditure and carbohydrate oxidation rate were measured after 12 hours fasting by

indirect calorimetry before and during the isoglycemic hyperinsulinemic clamp. A breath to

breath metabolic analyzer (Quark RMR Cosmed) was attached to a non-rebreathing ventilator

(Siemens SAL 900) to measure the difference between inspired and expired VO2 and VCO2

[13]. The calorimeter was calibrated daily using gas of certified O2 and CO2 composition and

the flowmeter was also calibrated using a 3 L syringe. Determinations of energy expenditure

and carbohydrate oxidation rate were obtained, as described previously from calorimetric

measurements for at least 15 minutes or more, until the reading were stable at ± 10% [14].

Non-oxidative glucose utilization was calculated by subtracting the rate of glucose oxidation

during a given time period from the total rate of glucose uptake obtained with the clamp

during the same period. Plasma glucose was measured using the glucose oxidase method on a

multiparametric analyzer (Konelab 20i, ThermoFisher scientific). Plasma systemic insulin

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concentrations were measured for clamp studies using ST-AIA-Pack IRI reagent kit.

Quantification limit was 0,5 µU.ml-1

and intra-assay coefficient of variation was less than 2%

from 12 to 200 µU.ml-1

. Plasma leptin concentrations were obtained using the multi-species

RIA kit (ref XL-85K, Millipore) according to Berg et al [15]. The linearity is 0.801 for 50

ng/ml. Plasma ghrelin concentrations were also measured by RIA (Phoenix Pharmaceuticals)

according to Salfen et al [16]. Autonomic balance was measured through spectral analysis of

24H ECG recorded using ActiWave (Camntech) recorder. The raw ECG signal was recorded

at 256 Hz and analyzed by Labview Biomedical toolkit (National Instruments) to extract high

and low frequency components of the heart variability as an index of autonomic balance [17].

Hepatic glucose production

Endogenous glucose production equals -5, -12.3 and -10.1 mmoles.min-1 for Lean, Obese

Non-stimulated and Obese-stimulated respectively. The negative values obtained for

EGP establish that the amount of insulin infused in the clamp was sufficient to

completely suppress glucose production by the liver.

of 36Diabetes


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decreased weight gain, food consumption and sweet craving in adult obese minipigs.

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[5] Furler SM, Zelenka GS, Kraegen EW. Development and testing of a simple algorithm

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