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 nonstimulated, obese nonstimulated, and obese stimulated). Twelve weeks after surgery, glucose uptake and insulin sensitivity were measured using positron emission tomography during an isoglycemic clamp. Mean whole-body insulin sensitivity was lower by 34% (P < 0.01) and the hepatic glucose uptake rate was lower by 33% (P < 0.01) in obese-nonstimulated mini-pigs but was no different in obese-stimulated compared with lean mini-pigs. An improvement in skeletal glucose uptake rate was also observed in obese-stimulated compared with obese-nonstimulated groups (P < 0.01). Vagal stimulation was associated with increased glucose metabolism in the cingulate and prefrontal brain areas. We conclude that chronic vagal stimulation improves insulin sensitivity substantially in diet-induced obesity by both peripheral and central mechanisms.

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 that 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 (4) in Zucker rats suggested that chronic vagal stimulation may up-regulate insulin receptor expression in the brain, liver, and skeletal muscle. 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 (6) investigated changes in glucose metabolism during vagal stimulation and found an increase in energy expenditure and a decrease in muscle and hepatic glucose uptake (HGU). These observations must, however, be interpreted circumspectly because 1) glucose uptake was extrapolated from standard uptake values without the required arterial input function measurement (7) and 2) the time frame scrutinized was the short-term interruption of the stimulation that was otherwise turned on. Although 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 standardized uptake value) after 1 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 the following: impaired skeletal muscle glucose utilization (9), diminished HGU (10), and altered brain metabolism and glucose transport (11). 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 PET Center (12) to quantify glucose uptake rate and insulin sensitivity has been already successfully used in the pig. It also has been used in our experimental paradigm to quantify both organ insulin sensitivity and 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 used the Yucatan mini-pig, 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 1) through changes in the rate of HGU by an efferent mechanism, 2) by modifying several key brain networks involved in energy intake and glucose metabolism via an afferent mechanism, and 3) 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 positron emission tomography (PET) and computed tomography (CT) imaging during an isoglycemic hyperinsulinemic clamp. Furthermore, nonoxidative glucose metabolism was quantified using indirect calorimetry, and the impact of the stimulation on the cardiac autonomic function was assessed using heart rate variability.

Animals and Diets

A total of 15 adult Yucatan mini-pigs, matched for age and sex, were used. Ten animals were made obese using a high-fat, high-sucrose diet (4,024 kcal/kg feed) supplied at 150% of the recommended caloric intake (288 kcal/kg body wt0.75) (14), while the remaining 5 animals were maintained on a low-fat, low-sucrose diet (2,275 kcal/kg feed) to limit the amount of body fat and ensure that total body weight was <40 kg. This feeding scheme was maintained during the entire experiment. The experiment was conducted in accordance with the current ethical standards of European legislation after validation by an ethics committee (R-2011-MO-01).

Protocol

The animals were divided into the following 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 Supplementary Data. 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; and the obese-stimulated group was maintained on a high-fat, high-sucrose diet, and the stimulator was turned on.

The animals were weighed weekly from 0 to 12 weeks after the surgery and then imaged using CT scanning 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 h to evaluate autonomic balance. Dynamic PET imaging was performed with arterial in-line and off-line function measurements during an isoglycemic-hyperinsulinemic clamp. Brain, liver, and muscle glucose uptake rates were evaluated from PET images, and whole-body insulin sensitivity was calculated from the glucose infusion rate during the clamp. Basal metabolic rate was measured during and before the clamp condition using indirect calorimetry.

Measurements

Fat mass repartition and lean mass were quantified by semiautomatic 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 three-dimensional (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 region of interest (ROI) was adjusted manually subsequently. Electrode impedance, energy expenditure, carbohydrate oxidation rate, and ghrelin/leptin/insulin concentrations were measured, as described in the Supplementary Data.

PET Protocol and Data Analyses

PET images were acquired during an isoglycemic-hyperinsulinemic clamp (120 mU ⋅ kg−1 ⋅ h−1), as described in the Supplementary Data. Glucose uptake rates were obtained for each organ through model analysis of ROI data and arterial input function using PMod software (Switzerland). ROIs, including either the liver or the most voluminous muscles of the leg (i.e., vastus lateralis, gastrocnemius, semimembranosus, and semitendinosus), were drawn manually while avoiding large blood vessels on the respective PET images using PMod. ROIs at the brain level were obtained automatically by coregistration of the PET brain image with a dynamic PET template coregistered with our 3D brain atlas (16). The following lumped constants were used to take into account the differences in affinity between fluorodeoxyglucose (FDG) and native glucose: 0.45 for the brain (17), 1 for the liver (12), and 1.2 for the skeletal muscle (18). A classic 3 K model was used for the brain and the liver ROI analyses, whereas 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 coregistered in our 3D atlas space.

Statistical Analyses

Data are presented as the mean ± SE. Data were compared using one-way and two-way ANOVAs using Prism 6 (GraphPad). Time-dependent analysis (changes in body weight) were corrected for multiple comparison using the Sidak test. Differences were regarded as statistically significant at P < 0.05. Body weight and resting energy expenditure were analyzed by ANCOVA with final weight as the dependent variable, preoperative weight as the covariable, energy expenditure as the dependent variable, and fat-free mass as the covariable. The t values were obtained from Tukey pairwise comparison tests performed in Stata 14 (StataCorp). Statistical analysis of the brain uptake rate was performed using SPM8 with a full monthly statistical mode with significance level set at P ≤ 0.001 corrected for false discovery rate (FDR) to exclude random brain activation.

All animals recovered from surgery within a day (e.g., their eating behavior was apparently no different from that observed before surgery). No significant problems were observed during the 12 weeks of the experiment. Electrode impedance measurements obtained from the obese-stimulated group after 12 weeks of stimulation established that there was no breakage in electrode continuity; impedance was 828 ± 23 and 958 ± 75 Ω, respectively, for the dorsal and ventral vagal trunks.

Body Weight, Fat Mass, Energy Expenditure, Hormonal Status, and Autonomic Balance

In both the obese-nonstimulated and obese-stimulated groups, there was an increase in body weight compared with the preoperative weight, whereas there was no change in the lean group. The increase in body weight was substantially less in the obese-stimulated group compared with the obese-nonstimulated group (Fig. 1), a difference that was significant at 10 and 12 weeks after surgery (Table 1).

Figure 1

Changes in weight postsurgery expressed as a percentage of the initial weight. *P < 0.05, difference from the obese-nonstimulated group.

Figure 1

Changes in weight postsurgery expressed as a percentage of the initial weight. *P < 0.05, difference from the obese-nonstimulated group.

Table 1

Phenotypic and metabolic characteristics of the animals, 12 weeks after onset of stimulation and implantation of the stimulation device

LeanObese nonstimulatedObese stimulated
Body weight changes from preoperative (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 1,126 ± 43.6 877 ± 66.3 
Energy expenditure during clamp (kcal/day) 1,118 ± 9.7 1,324 ± 52.3 1,071 ± 104.1* 
Glucose oxidation rate (mg/kg/min) 6.8 ± 0.75 6.2 ± 0.47 6.1 ± 0.37 
Nonoxidative glucose disposal (mg/kg/min) 4.5 ± 0.65 2.7 ± 0.21 4.3 ± 0.24* 
LeanObese nonstimulatedObese stimulated
Body weight changes from preoperative (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 1,126 ± 43.6 877 ± 66.3 
Energy expenditure during clamp (kcal/day) 1,118 ± 9.7 1,324 ± 52.3 1,071 ± 104.1* 
Glucose oxidation rate (mg/kg/min) 6.8 ± 0.75 6.2 ± 0.47 6.1 ± 0.37 
Nonoxidative glucose disposal (mg/kg/min) 4.5 ± 0.65 2.7 ± 0.21 4.3 ± 0.24* 

Data are the mean ± SE.

Obese-stimulated animals received vagal stimulation during this entire period (n = 5 in each group). *Different from obese-nonstimulated group at P < 0.05.

‡Different from the lean group at P < 0.05.

**Final weight as the dependent variable and preoperative weight as the covariable.

†Energy expenditure as the dependent variable and fat-free mass as the covariable.

Total fat mass obtained from abdominal CT scan measurements was about three times greater in the obese group than in 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 (1,397 ± 45.2, 1,577 ± 23.4, and 1,402 ± 43.3 mL, respectively, for the lean, obese-nonstimulated, and obese-stimulated groups) despite an overall group effect.

Resting energy expenditure increased during the clamp compared with fasting irrespective of the experimental group (Table 1). Resting energy expenditure was not significantly different in the obese-nonstimulated group compared with the lean group during both fasting and the clamp, while vagal stimulation was associated with a reduction in energy expenditure compared with nonstimulated obese animals during the clamp only. During the plateau phase of the clamp, the rate of nonoxidative glucose disposal was reduced (by ∼50%) in the obese-nonstimulated compared with the lean subjects, while in vagally stimulated obese animals, nonoxidative carbohydrate metabolism was no different from that in the lean group. There was no difference between the groups in the glucose oxidation rate.

Fasting glycemia and insulinemia were greater in the obese-nonstimulated group compared with the lean group (Table 2), whereas in the obese-stimulated group fasting glycemia and insulinemia were not different from the lean group. There were no differences between groups in fasting leptin expressed in grams of fat mass. The ghrelin level was lower in the obese-nonstimulated group, whereas in the obese-stimulated group the plasma ghrelin level was not different from that in the lean group.

Table 2

Biochemical characteristics of the animals, 12 weeks after implantation surgery

LeanObese nonstimulatedObese stimulated
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 (mmol/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* 
LeanObese nonstimulatedObese stimulated
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 (mmol/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 the mean ± SE. Obese-stimulated animals received vagal stimulation during this entire period (n = 5 in each group).

*Different from the obese-nonstimulated group at P < 0.05.

‡Different from the lean group at P < 0.05.

**Values at clamp plateau ≠ 120 min after onset of insulin infusion.

Autonomic heart balance was not affected by abdominal vagal stimulation, as indicated by an unchanged low frequency/high frequency ratio in obese-nonstimulated versus obese-stimulated group (3.1 ± 0.80 vs. 3.5 ± 0.31, respectively, for the obese-nonstimulated group vs. the obese-stimulated group, P > 0.05). The low frequency/high frequency ratio was lower in the lean group compared with the obese groups (0.5 ± 0.07 for the 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 ms, respectively, for the lean, obese-nonstimulated, and obese-stimulated groups, P < 0.05).

Whole-Body and Organ-Specific Insulin Sensitivity

Insulin-mediated glucose metabolism was reduced in the obese-nonstimulated group compared with the lean and obese-stimulated groups (Table 3). Insulin sensitivity and whole-body glucose uptake were reduced by about one-third in the obese-nonstimulated group compared with the obese-stimulated group, whereas in the obese-stimulated group insulin sensitivity and whole-body glucose uptake were not different from those in the lean group.

Table 3

Whole-body, brain, liver, and skeletal muscle glucose metabolism during the clamp in the three groups (n = 5 in each group)

LeanObese nonstimulatedObese stimulated
Whole-body insulin sensitivity (dL/kg ⋅ min/µU/mL * 1E−36.4 ± 0.25 4.2 ± 0.37 5.8 ± 0.20* 
Whole-body glucose uptake (µmol ⋅ min−1 ⋅ kg−166.0 ± 5.08 47.3 ± 1.58 62.5 ± 2.72* 
Brain glucose uptake (µmol ⋅ min−1 ⋅ 100 g−127.6 ± 2.47 (0.75%) 17.9 ± 3.98 (0.47%) 28.1 ± 3.27* (0.61%) 
HGU (µmol ⋅ min−1 ⋅ 100 g−13.7 ± 0.31 (2.41%) 2.5 ± 0.27 (1.67%) 3.9 ± 0.32* (1.85%) 
Skeletal muscle glucose uptake (µmol ⋅ min−1 ⋅ kg−166.7 ± 11.34 56.4 ± 3.32 72.5 ± 8.67* 
LeanObese nonstimulatedObese stimulated
Whole-body insulin sensitivity (dL/kg ⋅ min/µU/mL * 1E−36.4 ± 0.25 4.2 ± 0.37 5.8 ± 0.20* 
Whole-body glucose uptake (µmol ⋅ min−1 ⋅ kg−166.0 ± 5.08 47.3 ± 1.58 62.5 ± 2.72* 
Brain glucose uptake (µmol ⋅ min−1 ⋅ 100 g−127.6 ± 2.47 (0.75%) 17.9 ± 3.98 (0.47%) 28.1 ± 3.27* (0.61%) 
HGU (µmol ⋅ min−1 ⋅ 100 g−13.7 ± 0.31 (2.41%) 2.5 ± 0.27 (1.67%) 3.9 ± 0.32* (1.85%) 
Skeletal muscle glucose uptake (µmol ⋅ min−1 ⋅ kg−166.7 ± 11.34 56.4 ± 3.32 72.5 ± 8.67* 

Data are the mean ± SE. Whole-body data are expressed in kilograms of body weight. Brain, liver, and muscle glucose uptake are expressed in tissue weight. Values in parentheses are the percentage 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 scanning.

*Different from the obese-nonstimulated group at P < 0.01.

‡Different from the lean group at P < 0.01.

HGU was reduced by more than one-third in the obese-nonstimulated group compared with the lean group (Table 3). Similarly, skeletal muscle glucose uptake was less in the obese-nonstimulated compared with the lean group, whereas there was no difference between the obese-stimulated compared with the lean group, with skeletal muscle glucose uptake 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 group compared with the nonstimulated group (Table 4).

Table 4

Kinetic constants for 18FDG in the skeletal muscle using a 5K model in the three groups (n = 5 in each group)

LeanObese nonstimulatedObese stimulated
k1 (mL ⋅ mL−1 ⋅ min−10.0764 ± 0.03839 (3 ± 0.5%) 0.1106 ± 0.02139 (5 ± 0.4%) 0.1355 ± 0.04305 (3 ± 0.2%) 
k2 (min−10.0996 ± 0.03785 (12 ± 0.9%) 0.1138 ± 0.02480 (23 ± 12.2%) 0.1022 ± 0.02320 (6 ± 2.6%) 
k3 (min−10.0247 ± 0.0067 (22 ± 4.1%) 0.0136 ± 0.00391 (8 ± 2%) 0.0240 ± 0.00473* (31 ± 13.9%) 
k4 (min−10.0053 ± 0.00236 (6 ± 0.7%) 0.0125 ± 0.00619 (40 ± 21%) 0.0078 ± 0.00303* (36 ± 14%) 
k5 (min−10.0276 ± 0.00969 (38 ± 21.4%) 0.1092 ± 0.03728 (53 ± 44.1%) 0.0572 ± 0.03968* (75 ± 30.7%) 
LeanObese nonstimulatedObese stimulated
k1 (mL ⋅ mL−1 ⋅ min−10.0764 ± 0.03839 (3 ± 0.5%) 0.1106 ± 0.02139 (5 ± 0.4%) 0.1355 ± 0.04305 (3 ± 0.2%) 
k2 (min−10.0996 ± 0.03785 (12 ± 0.9%) 0.1138 ± 0.02480 (23 ± 12.2%) 0.1022 ± 0.02320 (6 ± 2.6%) 
k3 (min−10.0247 ± 0.0067 (22 ± 4.1%) 0.0136 ± 0.00391 (8 ± 2%) 0.0240 ± 0.00473* (31 ± 13.9%) 
k4 (min−10.0053 ± 0.00236 (6 ± 0.7%) 0.0125 ± 0.00619 (40 ± 21%) 0.0078 ± 0.00303* (36 ± 14%) 
k5 (min−10.0276 ± 0.00969 (38 ± 21.4%) 0.1092 ± 0.03728 (53 ± 44.1%) 0.0572 ± 0.03968* (75 ± 30.7%) 

Data are the mean ± SE. Kinetics constants were obtained after the iterative fitting using a 5K model where VB is fixed at 5%. Values in parentheses are the errors for parameter estimation.

*Different from the obese-nonstimulated group at P < 0.05.

‡Different from the lean group at P < 0.05.

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-nonstimulated group compared with the lean group (Fig. 2), particularly in the frontal and temporal cortices where the volume of interest (VOI) level analysis showed a significant difference at P < 0.01. In the group with vagal stimulation, there was no difference in the glucose uptake rate compared with 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 analysis of the K1 parameter, was less in the obese-nonstimulated compared with the lean group and was not significantly different from the lean group to the obese-stimulated group (0.62 ± 0.034, 0.42 ± 0.0051, and 0.63 ± 0.029 µmol/min/100 g, respectively, for the lean, obese-nonstimulated, and obese-stimulated groups, P < 0.05).

Figure 2

Brain glucose uptake per 100 g 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: The whole-brain VOI was calculated as the sum of the 178 individual brain structures. The mean brain glucose uptake was less in all structures in the obese-nonstimulated group compared with the lean group, but this difference was only significant for the frontal and temporal cortices. Vagal stimulation was associated with an increase in the glucose uptake rate in the obese-stimulated vs. the obese-nonstimulated group so that there was no difference from the lean group. *P < 0.01, difference from lean group. All others bars in the obese-nonstimulated group were different from those in the lean group at P < 0.05. CMRglu, cerebral glucose metabolic rate.

Figure 2

Brain glucose uptake per 100 g 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: The whole-brain VOI was calculated as the sum of the 178 individual brain structures. The mean brain glucose uptake was less in all structures in the obese-nonstimulated group compared with the lean group, but this difference was only significant for the frontal and temporal cortices. Vagal stimulation was associated with an increase in the glucose uptake rate in the obese-stimulated vs. the obese-nonstimulated group so that there was no difference from the lean group. *P < 0.01, difference from lean group. All others bars in the obese-nonstimulated group were different from those in the lean group at P < 0.05. CMRglu, cerebral glucose metabolic rate.

Using statistical parameter mapping analysis, four areas were found to be activated differentially between the obese-nonstimulated 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 having the second largest z score, was the dorsal anterior cingulate cortex (Fig. 3). No differences were observed, using the same conservative approach, between lean and obese-stimulated groups.

Table 5

Statistical parameter mapping analysis of activation patterns (local maxima) in obese-stimulated animals relative to obese-nonstimulated animals

Coordinate of local maximum (x, y, z), mmPcorrected
(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 
Coordinate of local maximum (x, y, z), mmPcorrected
(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 a cluster size of 100 voxels each of the cluster representing 1 mm3. P values 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).

Figure 3

Results from a voxel-based statistical parametric mapping analysis showing the differences in glucose metabolism between the obese-nonstimulated and obese-stimulated groups. A: The crosshair was centered on the largest region that differed between the stimulated and nonstimulated obese groups (e.g., the dorsal anterior cingular cortex). B: Tridimensional projection of the brain areas for which statistical differences in glucose metabolism between the obese-nonstimulated and the obese-stimulated groups were evident. For the right and left planes, P ≤ 0.005, with cluster level FDR corrected.

Figure 3

Results from a voxel-based statistical parametric mapping analysis showing the differences in glucose metabolism between the obese-nonstimulated and obese-stimulated groups. A: The crosshair was centered on the largest region that differed between the stimulated and nonstimulated obese groups (e.g., the dorsal anterior cingular cortex). B: Tridimensional projection of the brain areas for which statistical differences in glucose metabolism between the obese-nonstimulated and the obese-stimulated groups were evident. For the right and left planes, P ≤ 0.005, with cluster level FDR corrected.

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 it is associated with reductions in fasting glucose and insulin levels and an increase in ghrelin concentrations. The observed changes in glucose metabolism in the brain were area specific, with particular involvement of an amygdalocingulate network, a network already identified in depressive patients treated with vagal stimulation (8,19). We also demonstrated that vagal stimulation increases nonoxidative 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 neuroendocrine 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, which represents the gold standard, to investigate glucose metabolism at the systemic and organ levels (21). Potential confounding effects related to surgery were minimized by the development of 1) a laparoscopic surgical approach to insert dedicated electrodes on the dorsal and ventral vagal trunks and 2) 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 used nonvalidated 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 level. We further demonstrated that insulin-mediated HGU was impaired by obesity and reversed by vagal stimulation. Such changes in HGU have been observed in obese subjects both before and after undergoing bariatric surgery (10). Abnormalities in HGU have been implicated in the pathogenesis of liver steatosis, hypertriglyceridemia 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 HGU, through activation of glycogen synthetase, has been demonstrated during acute stimulation of the hepatic vagal branches (25). Since our stimulation scheme used relatively similar pulses, it is probable that part of the improvement in HGU 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 HGU persisted over time, being comparable in both an acute and a chronic set-up. Aside from the aforementioned improvement in HGU 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 18FDG differed in the porcine model compared with human and were based on mathematical modeling 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-nonstimulated 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 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-nonstimulated 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-entorhinal 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 glucagon-like peptide 1 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 cerebral glucose metabolic rates were also reduced (38). Unlike the striatum, we found the metabolism of these structures to be profoundly altered in the obese-stimulated group compared with the obese-nonstimulated group. In addition, in insulin-resistant humans, the functional connectivity between the striatum and the cingulate appears to be altered and related to symptoms 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 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 scanning 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 blood-brain barrier to glucose.

Energy expenditure was not altered in the fasting state or during the clamp, unlike in previous studies using either unilateral short lasting vagal stimulation in rats (41) or a 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 in 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 heart rate variability relies, for its vagal component, on the activity of low-threshold B/A fibers innervating the heart.

Vagal stimulation reduced weight gain in our animals so that in stimulated animals weight gain was ∼25% less than in nonstimulated 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 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 the porcine visceral fat metabolism responds differently to weight reduction than visceral fat metabolism in humans (44), or that the relationship between visceral fat and metabolic outcome is weak or nonexistent 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 of 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, superobese mini-pigs continue to gain weight (45). In rodents, sham-operated obese animals had gained ∼20% of their body weight by 100 days after surgery (46). Nevertheless, there was a clear difference in weight gain at 12 weeks between the stimulated and the nonstimulated groups. We did not measure insulin production. Although this can be performed easily in an intravenous glucose tolerance test/oral glucose tolerance test setup with C-peptide dosage in pigs, the manufacture of porcine C-peptide antibodies was 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 postprandial glucose metabolism might modulate the effect of vagal stimulation, its major contributor (i.e., gastric emptying of liquids or solids) was not affected after 5 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 a minimal effect on body weight (41) and does not affect fasting glycemia (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 an uncontrolled study, the opposite of 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 in HbA1c level was related to the associated weight loss (49). Nevertheless, a previous study (50) from the same group using the same device failed to demonstrate any weight loss.

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. Although 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.

Acknowledgments. The authors thank the following staff of the animal facilities of the PEGASE unit for animal care: Mickael Genissel, Julien Georges, Alain Chauvin, Francis Le Gouevec, and Vincent Piedvache. The authors also thank Christine Trefeu (PEGASE unit) for leptin and ghrelin measurements and Raphael Comte (PEGASE unit) for insulin measurements. In addition, the authors thank Eric Bobillier, of the Ani-Scans Imaging Center, for the development of the electronic in-line radiation detector. Finally, the authors thank the members of the Ani-Scans Imaging Center for data collection.

Funding. The study was conducted within the Ani-Scans Imaging Center (Ani-Scans, French National Institute for Agricultural Research) and the animal facilities of PEGASE unit (UMR PEGASE, French National Institute for Agricultural Research) at Saint-Gilles, which were supported by Bpifrance within the Investissements d'Avenir (Initiative Nationale Technologique d'Envergure).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. 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 for the stimulator. M.H. made a major contribution to the writing of the manuscript, 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.

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