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Cannabis exposure associated with weight reduction and [beta]-cell protection in an obese rat model.

ARTICLE INFO

Keywords:

Cafeteria diet

Cannabis

THC

Obesity

Cannabinoids

ABSTRACT

The aim of this study was to investigate the effect of an organic cannabis extract on 13-cell secretory function in an in vivo diet-induced obese rat model and determine the associated molecular changes within pancreatic tissue. Diet-induced obese Wistar rats and rats fed on standard pellets were subcutaneously injected with an organic cannabis extract or the vehicle over a 28-day period. The effect of diet and treatment was evaluated using the intraperitoneal glucose tolerance tests (IPGTTs) and qPCR analysis on rat pancreata harvested upon termination of the experiment.

The cafeteria diet induced an average weight difference of 32 g and an overall increase in body weight in the experimental groups occurred at a

significantly slower rate than the control groups, irrespective of diet. Area under the curve for glucose (AU[C.sub.g]) in the obese group was significantly lower compared to the lean group (p < 0.001), with cannabis treatment significantly reducing the AU[C.sub.g] in the lean group (p <0.05), and remained unchanged in the obese group, relative to the obese control group. qPCR analysis showed that the cafeteria diet induced down-regulation of the following genes in the obese control group, relative to lean controls: UCP2, c-MYC and FLIP. Cannabis treatment in the obese group resulted in up-regulation of CB1, GLUT2, UCP2 and PKB, relative to the obese control group, while c-MYC levels were down-regulated, relative to the lean control group. Treatment did not significantly change gene expression in the lean group. These results suggest that the cannabis extract protects pancreatic islets against the negative effects of obesity.

[c] 2012 Elsevier GmbH. All rights reserved.

Introduction

Most drugs have been derived either directly or indirectly from plants. While the medicinal use of Cannabis sativa L., commonly referred to as marijuana, goes back several thousands of years, the isolation and characterization of the phytocannabinoid tetrahydrocannabinol (THC) in the 1960s and with the cloning of the two distinct cannabinoid subtypes in the early 1990s, has prompted renewed interest in cannabinoid compounds (Munro et al. 1993). There are numerous cannabinoids with the most common natural plant cannabinoids being cannabidiol (CBD), cannabinol (CBN), cannabichromene (DC) and cannabigerol (CBG) (El-Alfy et al. 2010). THC is the best characterized of the cannabinoids. World-wide, where cannabis usage has increased both for medicinal and recreational purposes, research is required to understand the individual roles of each of the cannabinoids and the synergistic effect that exists between them. Understanding of plant cannabinoid effects will also contribute to unravelling the role of the endogenous cannabionoids.

Cannabis extracts have been used in the treatment of various ailments including inflammation, bronchitis, pain and diabetes (van Wyk and Gericke 2000). In rats THC mediates its physiological effects via cannabinoid receptor type 1 (CB1) and type 2 (CB2) binding, activating intracellular G-proteins which provide signals to a variety of effectors such as ion channels, the mitogen-activated protein kinase (MAPK) cascade and induce myelocytomatosis oncogene (c-MYC) expression (Howlett et al. 2002). CB1 receptors are mainly associated with the central nervous system (CNS), however, lower levels of CB1 mRNA has been detected in several peripheral tissues including the rat pituitary gland, adrenal glands, skeletal muscle, liver, gastrointestinal tract and pancreas. CB2 receptors are mainly associated with tissues involved in immune cell production and regulation (DiPatrizo et al. 2011; Howlett et al. 2004). CB1 and CB2 receptors form part of the endocannabinoid system, together with their endogenous ligands. Studies have shown cannabinoid receptor expression within the endocrine pancreas, however, no consensus has been reached on which cannabinoid receptor subtype is associated with each type of islet endocrine cell (Li et al. 2010a). CBI and CB2 receptors and the novel cannabinoid receptor GPR55 has been found to be expressed in the [beta]-cells in murine islets and MINE cell line (Li et al. 2010b,c), while Vilches-Flores et al. (2010) found peripheral localization of CB1 receptors in rat islets and Bermudez-Silva et al. (2007) found co-expression of CB1 and CB2 receptors in both insulin positive and non-insulin-expressing rat dissociated islet cells. Other studies have shown the co-localization of CB1 receptors on [alpha]-and [delta]-cells in rats and humans (Bermudez-Silva et al. 2009; Juan-Pico et al. 2006).

The endocannabinoid system has been implicated in the regulation the body's energy balance (Bermudez-Silva et al. 2009; Juan-Pico et al. 2006). The majority of studies conducted on the effect of cannabis and/or various cannabinoid administrations on food intake in animals, have either failed to find an effect on eating behaviour, or found that cannabinoids induced an anorectic or hyperphagic effect (Pagotto et al. 2006; Kirkham and Williams 2001). Past studies have focused on endocannabionoid signaling in the brain. Past studies have focused on endocannabionoid signaling in the brain. Most recently DiPatrizo et al. (2011) have shown that a fat-rich diet alters intestinal endocannabinoid levels, which upregulate the CB1 receptors in nervous and vagal fibres. This surprising result indicates a potential role of the endocannabinoids to regulate dietary fat intake which is one of the main contributors to obesity. The prevalence of diet induced obesity (1310) continues to increase, resulting in associated life style diseases such as hypertension, cardiovascular disease and diabetes (WHO, 2008). The progression of diabetes is characterized by a concomitant change in metabolic parameters, loss in [beta]-cell mass as well as [beta]-cell function. Therefore our study was to investigate the effect of an organic cannabis extract (with a quantified THC, CBD and CBN content) and their role on [beta]-cell function in an obese rat model to evaluate the molecular changes induced in the pancreatic tissue.

Materials and methods

Cannabis extraction and quantification

The cannabinoid extraction and quantification was performed as described by Gallant et al. (2009). Cannabis plant material was obtained from the South African Police Services. Briefly, an organic extraction was obtained using chloroform, and evaporated using nitrogen, and the remaining resin was redissolved in methanol. The THC, CBN and CBD contents of the extract were quantified against a commercial THC, CBN and CBD standards (Industrial Analytical, Johannesburg, South Africa), using reverse-phase high performance liquid chromatography (RP-HPLC) on a [C.sub.18] Grace Vydac analytical column (4.6 min x 250 mm, 5 [micro]m), previously described by Coetzee et al. (2007).

Animals

Experimental procedures were approved by the Nelson Mandela Metropolitan University Animal Ethics Committee. Rats were treated as reported by Coetzee et al. (2007). Briefly, the rats were housed in an air-conditioned room (22 [+ or -] 3 [degrees] C) with a 12 h light/dark cycle, and randomly assigned to four groups: untreated lean control (LNC); cannabis-treated lean experimental (LNE); untreated obese control (OBC) and cannabis-treated obese experimental (OBE). Rats assigned to the obese groups were fed on a cafeteria diet (15% protein, 68% carbohydrates and 17% fat) over a period of eight weeks to effect DIO, while lean rats were fed on standard chow (Epol, Pretoria, South Africa) (18% protein, 41.4% carbohydrates and 4.5% fat) over the same period and maintained throughout the experiment. Food consumption was monitored daily. Rats were injected subcutaneously with cannabis extract every alternate day for 28 days, with the first five treatments containing an equivalence of 5 mg THC/kg body weight, and the remaining treatments, an equivalence of 2.5 mg THC/kg body weight. The control groups were treated with an equivalent volume of the vehicle (1% Tween 80 in saline). Water was available ad libitum.

Intraperitoneal glucose tolerance test (IPGTT)

To determine the effect of treatment on insulin sensitivity, rats were given a glucose bolus of 2 g/kg body weight via intraperitoneal injection. Blood samples were obtained from the tail vein, and the glucose concentration was measured using a Glucometer (Accutrend GC, Roche, South Africa). Area under the curve for glucose (AU[C.sub.g]) was calculated over the standard 2-h period, using the following formula: AU[C.sub.g] = ([concentration.sub.0] + [concentration.sub.1])/2 x [Times.sub.1-0] (Chiou 1978).

Insulin quantification using radioimmunoassay (R1A)

The Linco rat insulin RIA (Linco Research, USA) was used to quantify plasma insulin levels of post-experimental plasma samples, according to the manufacturer's specifications, using the Packard-Perkin Elmer Tri-Carb 2300TR liquid scintillation analyzer (Life and Analytical Science (Pty) Ltd, South Africa).

Cytokine assay

Plasma levels of interleukin (IL)-1[alpha], interleukin (IL)-1[beta], interleukin (IL)-6, interferon (IFN)-[gamma] and tumor necrosis factor (TNF)-[alpha] were measured using Luminex Lincoplex kits (Labodia, Preiverenges, Switzerland), according to the manufacturer's specifications. Analytes were quantified using the [Luminexlm.sup.100] system (Luminex Corp., USA).

qPCR analysis using Relative Expression Software Tool

Total RNA was extracted using the QIAGEN RNeasy mini kit and reverse transcription was performed using QIAGEN QuantiTech Reverse Transcription kit (Southern Cross Biotechnology, RSA). Primers were developed using Beacon Designer[R] 3 Software (Biorad), and included two reference genes, viz. [beta]-tubulin (5'-3': AACCCAGCCCAGTTCTAAG; 3'-5': GATTCCCGTGTCTAAATG) and cyclophilin A (5'-3': CGTGGTCAAGACTGAGTGG; 3'-5': GTGCTTCCCACCAGACC), and the genes of interest included CB1 (5'-3': CTGGTTCTGATCCTGGTGGT; 3'-5': TGTCTCAGGTCCTTGCTCCT), c-MYC (5'-3': AGGAAGGACTATCCAGC; 3'-5': CCTCTTGTCGTTTTCCTC), FLIP (5'-3': GGGACCTCCTGGATTGTTTAAG; 3'-5': ACGGCTGCTTTATCTGTCTTC), GLUT2 (5'-3': ATGACATCAATGGCACAGACAC; 3'-5': GACACAGACAGAGACCAGAG), insulin (5'-3': CTGCCCAGGCTTTTGTCAAA; 3'-5': TCCACTTCACGACGGGACTT), pancreatic duodenal homeobox-1 (PDX-1) (5'-3': CTGCCTCTCGTGCCATGTGAAC; 3'-5': GGCTGTTATGGGACCGCTCAAG), phosphoenolpyruvate carboxykinase 1 (PEPCK) (5'-3': TCGATGCCTTCCCAGTAAAC; 3'-5': GTGATGACATTGCCTGGATG), protein kinase B (PKB) (5'-3': CAACTGGCAGGATGTGGTAC; 3'-5': AGGCTGTCATATCGGTCTGG), uncoupling protein 2 (UCP2) (5'-3': TGGCGGTGGTCGGAGATAC; GGGCAACATTGGGAGAGGTC). All qPCR reactions were conducted on the 'Cycler iQ Multicolour Real-Time Detection System (Biorad), V3.1, using iQ SYBR Green Supermix (Biorad). Quantitative real-time polymerase chain reaction (qPCR) analysis of 5 pancreatic samples per experimental group was conducted using Relative Expression Software Tool (REST) 2009 V2.0.13 (QIAGEN) (Pfaffl 2001).

Statistical analysis

Data analysis using MANOVA, followed by two-tailed student's t-tests (where applicable) were conducted to determine the significance of diet and treatment on various physiological parameters. Multiple regression analysis was performed to determine the effect of the interactions between time, diet and/or treatment on blood glucose and body weight. Data is represented as the mean [+ or -] SEM, unless otherwise stated, p [less than equal to] 0.05.

Results

The cannabinoid quantification revealed the ratio of the quantified THC:CBN:CBD was 1.0:1.2:0.4 as shown in a typical HPLC chromatogram (Fig. 1). CBN was the predominant cannabinoid quantified in the extract. The average weight difference prior to cannabis treatment was 26.8 g between lean and obese rats (p < 0.01) (Table 1). Cannabis extract exposure significantly increased food consumption in the LNE rats to 50.03 [+ or -] 0.54 g per day, relative to the respective control rats (45.37 [+ or -] 0.12 g). Food consumption in the obese group was significantly higher compared to the lean group (p < 0.0001), however, the effect of cannabis exposure significantly reduced food intake (57.42 [+ or -] 0.44 g) relative to the respective OBC rats (64.61 [+ or -] 1.18 g). Cannabis exposure induced a reduction in weight gain over time, in both LNE (5.8%) and OBE (3.8%) rats, relative to the respective LNC (12.4%) and OBC (14.3%) rats (p < 0.001).

Table 1 Effect of diet and cannabis extract on body weight of
lean and obese Wistar rats.

Croups  Body weight (g)                   Food intake per  Weight
                                              day (g)       gain
                                                             (%)
        Pre                     Post

LNC     395.85 [+ or -]  445.08 [+ or -]  45.37 [+ or -]  12.44%
                  10.01        14.93 (c)            0.12

LNE     401.12 [+ or -]  424.51 [+ or -]  50.03 [+ or -]   5.83%
                   9.18         8.63 (c)        0.54 (c)     (b)

OBC    427.05 [+ or -]   488.24 [+ or -]  64.61 [+ or -]  14.33%
              9.21 (a)     11.68 (a) (c)        1.18 (c)

OBE    423.90 [+ or -]   439.83 [+ or -]  57.42 [+ or -]   3.76%
                 10.62      9.21 (b) (c)        0.44 (c)     (c)

Body weight: (a.) p<0.05, pre-LNC vs pre-OBC; post-LNC vs post-OBC;
(b.) p<0.01, post-OBC vs post-OBE; (c.) p<0.001, preLNC vs
post-LNC; pre-LNE vs post-LNE; pre-OBC vs post-OBC; pre-OBE vs
post-OBE.
Food intake: (c.) p < 0.001, LNC vs LNE; LNC vs OBC; INC vs OBE;
OBC vs OBE.
Weight gain: (b.) p < O.Ol, LNC vs LNE; (c.) p < 0.001, LNC vs OBE;
OBC vs OBE.


Based on the experimental data (Fig. 2), a validated predictive polynomial model for body weight was generated, within a 95% confidence interval, taking into account the effect of time, treatment, diet and their interaction:

Predicted body weight ([gamma]) = [[beta].sub.0] + [[beta].sub.1] Time + [[beta].sub.2] [Time.sup.2] + [[beta].sub.3] Treatment + [[beta].sub.4] Diet + [[beta].sub.5] Time . Treatment ([r.sup.2] = 0.31),

where [[beta].sub.0] = 400.09 (p < 0.0001); [[beta].sub.1] 6.71 (p = 0.42); [[beta].sub.2] = 8.21 (p=0.001) and [[beta].sub.3] = -7.16 (p =0.40); [[beta].sub.4] = 31.91 (p < 0.0001); [[beta].sub.5] = -11.63 (p <0.01).

Regression analysis shows that body weight increased by an average of 8.21 g over 28 days (p < 0.0001), irrespective of diet or treatment, while the cafeteria diet induced an average weight difference of 31.9 g (p < 0.0001) between lean and obese rats. For the same period, cannabis exposure on its own did not have a significant influence on body weight, contributing an average decrease in body weight of 7.16 g (p = 0.40), while the combined effect of time and cannabis exposure significantly reduced body weight by an average of 11.63 g (p < 0.01) over the experimental period. The predictive body weights are graphically depicted in Fig. 2.

The changes observed in body weight were confirmed by the overall changes in body composition as depicted in Fig. 3. A significant reduction in epididymal fat mass was found in rats exposed to cannabis extract treatment, with LNE rats showing a significant reduction in the average epididymal fat mass (5.58 [+ or -] 0.24 g), relative to LNC rats (6.72 [+ or -] 0.45g) (p < 0.05). Similarly, OBE rats showed a significant reduction (8.86 [+ or -] 0.49g) compared to OBC rats (10.78 [+ or -] 0.65g) (p < 0.05). Skeletal muscle in the obese rats were significantly higher than the lean rats (p < 0.01), with significance increasing due to weight loss associated with rats that received cannabis treatment (Fig. 3). Cannabis treatment significantly increased the weights of pancreata in OBE rats (1.94 [+ or -] 0.10g), relative to OBC rats (1.62 [+ or -] 0.09 g) (p < 0.05), with LNC and OBC pancreata showing no significant differences. The hepatic somatic index (HSI), i.e. the liver:body weight ratio, of obese rats was significantly lower (3.26 [+ or -] 0.05%) relative to the lean rats (3.50 [+ or -] 0.10%) (p < 0.05). Cannabis treatment significantly increased HSI in OBE rats (3.39 [+ or -] 0.06%), relative to the OBC rats (p < 0.01), while LNE rats maintained levels similar to the LNC rats.

Plasma insulin and glucose levels did not differ significantly for all experimental groups, irrespective of diet and treatment (Table 2). The cafeteria diet, surprisingly, induced a reduction in the blood glucose and insulin levels in obese rats, with the average blood glucose levels in obese rats (3.84 [+ or -] 0.18 mmol/l), relative to lean rats (5.48 [+ or -] 0.28 mmol/l) (p < 0.001).

Table 2

A summary of the effect of cannabis extract on post-experimental
blood glucose, insulin and area under the curve for glucose
(AU[C.sub.g]) associated with IPGTT in lean and obese Wistar rats.

Experimental  Glucose (mmol/l)      Insulin         AUCg (IPGTT)
group                               (ng/ml)         (mmol/min/l)

LNC              5.67 [+ or -]   5.70 [+ or -]   769.20 [+ or -]
                          0.46            1.83             14.36

LNE              5.31 [+ or -]   2.55 [+ or -]   707.45 [+ or -]
                           035            0.50         21.87 (d)

OBC              3.60 [+ or -]   3.30 [+ or -]   524.31 [+ or -]
                      0.2l (c)            0.68         13.22 (c)

OBE              4.06 [+ or -]   2.84 [+ or -]   534.75 [+ or -]
                      0.28 (b)            0.54         20.83 (c)

(a.) p <0.05, (b.) p <0.01, (c.) p <0.001, relative to LNC.


Based on the experimental data over 28 days (Fig. 4), a validated predictive polynomial model was generated, within a 95% confidence interval, taking into account the effect of time, treatment, diet and their interaction (Fig. 4):

Predicted blood glucose ([gamma]) = [[beta].sub.0] + [[beta].sub.1] Diet + [[beta].sub.2] Treatment + ([[beta].sub.3] + [[beta].sub.4])Time + [[beta].sub.5] Time2 ([r.sup.2] = 0.36),

where [[beta].sub.0] = 6.36 (p <0.0001); [[beta].sub.1] = 1.05 (p = 0.002); [[beta].sub.2] = -0.15 (p = 0.45); [[beta].sub.3] = -1.51 (p < 0.0001); [[beta].sub.4] = 0.36 (p = 0.05) and [[beta].sub.5] = 0.52 (p < 0.0001).

Regression analysis shows that the cafeteria diet resulted in an average 1.05 mmol/l (p < 0.01) reduction in blood glucose levels, while cannabis exposure did not significantly affect blood glucose levels, inducing an average decrease of 0.15 mmol/l, over the experimental period. The combined effect of time and diet contributed an average increase of 0.36 mmol/l (p = 0.05) in blood glucose levels, while an average increase of 0.52 mmol/l (p < 0.001) over time was observed, irrespective of diet.

Similar to the average blood glucose being higher in the lean rats, the average IPGTT in lean rats was significantly higher AUCg (736.86 [+ or -] 14.73) compared to obese rats (533.64 [+ or -] 13.01) (p < 0.001). Cannabis treatment significantly reduced the AUCg in the LNE rats (707.45 [+ or -] 21.87), relative to LNC rats (769.20 [+ or -] 14.36), while the OBE rats (534.75 [+ or -] 20.83) remained relatively unchanged, relative to the OBC rats (524.31 [+ or -] 13.22). A notable observation was that 27% of the LNE rats showed no change in blood glucose levels subsequent to glucose bolus administration, compared to 10% of the LNC rats. A similar trend was observed in the obese group, where 29% of the OBE rats showed no change in blood glucose levels, compared to 14% of the OBC rats.

Trends in the plasma cytokine profile (Table 3) show IL-1[alpha], IL-6 and IFN-[gamma] were detectable and IL-1[beta] and TNF-[alpha] levels not (data not shown). In LNE rats cannabis treatment induced increases in IL-1[alpha] (1.1-fold), and IL-6 (1.6-fold) while levels remained unchanged, relative to LNC rats. Diet induced a reduction in IL-1[alpha] (0.8-fold), IL-6 (0.2-fold) and IFN-[gamma] (0.9-fold) levels in OBC rats, relative to LNC rats. Cannabis treatment resulted in an increase in IL-6 (6.4-fold) and IFN-[gamma] (1.2-fold) levels, relative to OBC rats, while IL-1[alpha] levels remained unchanged.

Table 3

Plasma cytokine profile of obese and lean rats treated with
cannabis extract.

Groups    IL-1[alpha]           IL-6 (pg/ml)          IFN-[gamma]
            (pg/ml)                                  (pg/ml)

LNC      90.03 [+ or -]    95.66 [+ or -] 27.42  65.73 [+ or - ]
           5.15 (3) (a)                 (5) (a)     5.58 (4) (a)

LNE      95.73 [+ or -]   152.88 [+ or -] 77.56  65.12 [+ or - ]
          16.65 (3) (a)                 (4) (a)     16.50(5) (a)

OBC      67.96 [+ or -]     19.00 [+ or -] 3.40  56.53 [+ or - ]
          15.74 (5) (a)                 (2) (a)     6.08 (3) (a)

OBE      69.00 [+ or -]   121.46 [+ or -] 46.87  70.23 [+ or - ]
           1.00 (2) (a)                 (5) (a)    17.15 (4) (d)

(a.) Numbers in parentheses reflect the number of rats evaluated.


Changes in gene expression in pancreatic tissue, relative to LNC rats, is summarized in Fig. 5, where OBC expression of c-MYC, FLIP and UCP2 was significantly down-regulated: 0.01- (p < 0.05), 0.18- (p < 0.05) and 0.14-fold (p < 0.01), respectively. OBE pancreatic tissue, relative to LNC rats, showed that diet and cannabis exposure induced a 0.03-fold (p < 0.05) reduction in c-MYC gene expression. No significant changes in expression of the genes of interest were found between the lean groups (data not shown).

Gene     Expression    Std. Error       95% C.I.      * P   Result
                                                     (H1)

INSULIN       0.441   0.088 - 6.152  0.013 - 14.600   0422

CBI           0.333   0.133 - 1.404   0.066 - 4.454  0.116

GLUT2         0.568  0.188 - 11.687  0.166 - 18.120  0.590

UCP2          0.137   0.034 - 0.289   0.018 - 0 466  0.004  DOWN

c-MYC         0.009   0.000 - 0.255   0.000 - 5.876  0.032  DOWN

FLIP          0.177   0.015 - 0.675   0.005 - 1.097  0.038  DOWN

PEPCK         0.357   0.058 - 1.852   0.024 - 3.067  0.247

PKB           0.495   0.248 - 1.024   0.129 - 2 285  0.125

PDX-1         1.479   0.487 - 4.680   0.24 - 12.328  0.502

* P (H)1 refers to the probability that the alternative hypothesis
is true.


Diet and cannabis induced up-regulation of CB1 (2.92-fold, p < 0.01), glucose transporter 2 (GLUT2) (2.77-fold, p < 0.001), UCP2 (3.2-fold, p < 0.001) and PKB (2.6-fold, p < 0.05) gene expression in the OBE rats, relative to OBC rats (Fig. 6).

Gene     Expression     Std Error     95% C.I.  * P (H1)  Result

INSULIN       1.156       0.091 -     0.028 -    0.882
                            8.089      29.034

CBI           2.923       1.371 -     1.139 -    0.004     UP
                            5.914      10.672

GLUT2         2.765       1.824 -     1.334 -    0.000     UP
                            3.659       6.095

UCP2          3.199       2.121 -     1.521 -    0.000     UP
                            4.823       6.335

c-MYC         2.676       0.108 -     0.004 -    0.619
                           66.466   2.503.173

FlIp          2.053       0.726 -     0.362 -    0.140
                            5.193       9.417

PEPCK         2.110       0.594 -     0.342 -    0.200
                            7.118      12.434

PKB           2.562       1.503 -     0.644 -    0.028     UP
                            5.212       6.343

PDX-1         0.716       0.313 -     0.153 -    0.470
                            1.673       3.227

* P (H)1 refers to the probability that the alternative
hypothesis is true.



Discussion

Since the cloning of the two cannabinoid receptors in the early 1990s, and the subsequent isolation of anandamide (AEA) in 2002, increasing evidence is implicating peripheral and central endocannabinoid pathways in the regulation of feeding behaviour, body weight and glucose metabolism (Bermudez-Silva et al. 2009; DiPatrizo et al. 2011; Juan-Pico et al. 2006). In this study, cannabis exposure showed a varied effect on the feeding behaviour of lean and obese rats. Food consumption in the OBE rats was 15% higher than in LNE rats (p <0.001), which supports the findings of Koch (2001) where a higher volume of high-fat and sweetened high-fat diet was consumed, relative to chow-fed rats. The lag in weight gain observed in the LNE and OBE rats, support the findings that the endocannabinoid system mediates feeding behavior and energy balance. Research findings suggest that THC exerts a biphasic dose response, with appetite stimulation at low doses and inhibition at high doses (Cota et al. 2003). Other factors which have been proposed to contribute to the biphasic effect of THC on food intake include the differential involvement of the [G.sub.s] and [G.sub.i]; proteins, which are activated at high and low doses, respectively, activation of presynaptic cannabinoid receptors by low doses of cannabinoid, and storage of unused cannabinoids in fat deposits (Sulcova et al. 1998). In a study conducted by Kreuz and Axelrod (1973), fat tissue, relative to brain tissue, contained 21-fold higher levels of THC and its metabolites after seven days of consecutive exposure, and 64-fold higher levels after 27 days. It is therefore proposed that the retention of THC and its metabolites in the fat depots partially contributed to the different responses in food consumption of the LNE and OBE rats. The LNE rats, with less fat tissue, consumed significantly more food, relative to the LNC rats, while the OBE rats, with significantly more fat tissue, consumed significantly less food, thus confirming previous observations of the biphasic effect of THC. In addition, in an obese state, leptin, an adipocyte-derived hormone, induces a reduction in food intake, and increased energy expenditure. Acute treatment of normal and ob/ob (leptin-deficient) rats with leptin results in a reduction in anadamide (AEA) and 2-arachidonoylglycerol (2-AG) levels in the hypothalamus, while the ob/ob obese animals were found to have increased levels of AEA and 2-AG, therefore possibly contributing to overeating in the development of obesity (Di Marzo et al. 2000). Currently, not much evidence is available which investigates the role of phytocannabinoids other than THC or synergy of the phytocannabionoids to overeating and energy regulation other than THC.

DIO reduce insulin-stimulated glucose utilization, while insulin-stimulated adipogenesis remains unchanged or enhanced, thus increasing the risk of cardiovascular disease and diabetes. Coetzee et al. (2007) found that cannabis treatment in diet-induced obese rats prolonged clotting time, and reduced the atherogenic index, relative to control rats. Megulies and Hammer (1991) showed that intravenous THC administration exerts a dose-dependent dual effect on glucose uptake, stimulating uptake at low THC levels (0.2 mg/kg body weight), and inhibiting uptake at high THC levels (5-10 mg/kg body weight). In the current study, although not significant, this duality was evident with LNE rats showing reduced glucose levels while the OBE rats showed an increase, relative to their respective control groups. In vivo experiments conducted on rats found that acute administration of CB1 agonists impairs glucose uptake, thus retarding plasma glucose clearance, while CB2 agonists elicit an opposite effect (Di Marzo 2008). The OBE rats showed blood glucose levels similar to the LNC rats, and higher AUCg values (not significant), relative to OBC rats. Surprisingly, the lean rats that were fed on normal chow showed significantly higher blood glucose levels than the obese rats fed on cafeteria diet, with LNE (27%) and OBE (29%) rats showing impaired glucose-stimulated insulin secretion. In addition, LNC and LNE rats were found to have 1.47-and 1.44 fold higher AU[C.sub.g], relative to OBC rats, while LNE reduced the AUCg by 8%, relative to LNC rats, thus improving glucose sensitivity in the LNE rats. Despite improving AU[C.sub.g], there were no significant differences in plasma insulin levels, where the insulin gene expression remained relatively unchanged, showing a 0.2-fold reduction in LNE rats and a 1.2-fold increase in OBE rats, relative to their respective controls. Iwasaki et al. (2009) showed increased UCP2 expression impaired GSIS through impaired glucose sensing and insulin secretion in murine [beta]-cells, both in vivo and in vitro. Pi et al. (2009) observed increased oxidative stress and impaired insulin secretion in UCP2 knockout mice, while Produit-Zengaffinen et al. (2007) found that increased UCP2 expression in [beta]-cells did not alter insulin secretion, but enhanced the cellular defense by reducing ROS production. Elevated UCP2 levels possibly contributed to the impaired glucose sensing in LNC rats, while OBC levels were significantly reduced to 0.137-fold, relative to LNC rats, while OBE rats showed a 3.2-fold increase in UCP2 expression, relative to OBC rats, possibly contributed to the impaired glucose sensing observed in LNC rats. A 2.8-fold increase in GLUT2 expression in OBE rats, did not translate into an improved IPGTT, relative to OBC rats, however, the glycemic control was significantly better than that of LNC rats.

Standard chow is composed of agricultural by-products, a protein source, vegetable oil, supplemented with minerals and vitamins, high phytoestrogens, and contains a high proportion of fibre (Warden and Fisler, 2008). Research has shown that high levels of phytoestrogen result in stress-induced corticosteroid levels (Hartley et al. 2003). The elevated blood glucose levels and higher AU[C.sub.g] values associated with the lean group, relative to the obese group, may therefore be due to the effects of the phytoestrogen content in the standard chow.

Obesity has been associated with a chronic state of low-grade inflammation, with pro-inflammatory cytokines such as TNF-[alpha], IL-1 and IL-6 being induced by adipocytes and hepatocytes in severely obese mice (Chida et al. 2006). IL-6 increases energy metabolism in rats (Wallenius et al. 2002) and plays a role in lipolysis and [beta]-oxidation in fat tissue of humans. In the present study the cafeteria diet induced a reduction in IL-1, IL-6 and IFN-[gamma] levels in OBC rats, relative to LNC rats, while cannabis treatment induced increased IL-6 expression in both LNE and OBE, relative to the LNC rats. This increase in IL-6 levels may have contributed to the impaired weight gain observed in the LNE and OBE rats, possibly via increased energy metabolism, as previously observed by Wallenius et al. (2002).

Environmental stimuli affect the degree of gene expression by either inhibitory or stimulatory signals. None of the genes of interest were significantly changed in the LNE rats, relative to LNC rats. Down-regulation of c-MYC in the obese rats, relative to LNC rats, may have contributed to the improved glycemic control by the OBC and OBE rats (Table 2). In a normal adult pancreas, c-MYC levels are low, while hyperglycemia induced increased c-MYC expression in rat pancreatic [beta] cells (Jonas et al. 2001). In diabetics, over-expression of c-MYC induces reduced glucose-stimulated insulin secretion, suppresses insulin gene transcription, induces [beta]-cell apoptosis and loss of differentiation in rodent islets (Kaneto et al. 2002; Pelengaris et al., 2000). Maedler et al. (2002) found that increased FLIP expression level is necessary to switch the Fas signaling, a major regulator of cell death in [beta]-cells, to promote [beta]-cell proliferation. Decreased FLIP expression led to Fas activation, which promoted apoptosis, leading to [beta]-cell loss. The cafeteria diet induced a decrease in FLIP expression in OBC rats, relative to LNC rats, contributing to the reduction in the plasma insulin levels in OBC rats (not significant), while cannabis treatment resulted in a 2.1-fold increase in FLIP expression, relative to OBC rats. In vitro studies on isolated rat pancreatic islets conducted in this laboratory (data not shown) found a 6.9-fold increase in Ki-67-positive [beta]-cells in islets cultured under hyperglycemic conditions and exposed cannabis extract containing an equivalent of 2.5 ng/ml THC, relative to islets cultured under normoglycemic conditions. Diet and cannabis treatment resulted in upregulation of PKB in the OBE rats, relative to OBC rats to levels similar to LNC rats (1.4-fold), which may have contributed to proliferation within the pancreatic tissue. Gomez del Pulgar et al. (2000) have shown that THC induced activation of PKB via CB1 receptors, not CB2 receptors, and stimulates glycolysis and anti-apoptotic cellular activities. DIO resulted in a reduction in CB1 expression to 0.3-fold in OBC rats, relative to LNC rats, while exposure to cannabis extract resulted in upregulation of CB1 expression in OBE (2.9-fold), relative to OBC rats. OBE expression levels were similar to those found in LNC rats (1.0-fold). The combined effects of diet and cannabis exposure on c-MYC, FLIP and PKB expression may collectively have contributed to anti-apoptotic activities in the rat pancreatic tissue investigated.

enlargethispage4pt

The literature on the energy regulation effect of THC often presents varied and conflicting results, with less focus on other phytocannabinoids in this area. Recent findings have indicated that CBD slows down [beta]-cell damage in type 1 diabetes (Di Marzo et al. 2011). The predominant cannabinoid found in the cannabis extract for this study was CBN. It is not clear if CBN plays a significant role in [beta]-cell protection, as has been shown with CBD, this requires further studies. When comparing the chemical structure of THC and CBN, it is noted that CBN has a more rigid conformation than THC, which may be responsible for the subtle differences in the biological effects elicited. This is noted when comparing THC and CBN binding affinities for CB1 and CB2 receptors, where studies have shown equivalent binding affinity (Munro et al. 1993), variable affinity (Rhee et al. 1997) and also highlighting variation in interspecies binding (McPartland et al. 2007). The findings of our study therefore warrant further investigation into the effect of the individual cannabinoids (e.g. CBD, CBN and THC) and their synergistic interactions on energy regulation.

The findings of this research study are not to promote or condone the casual use of cannabis, but to convey the findings of the research to the scientific community to possibly stimulate further research in understanding the effect of phytocannabionoids on energy metabolism in relation to the endocannabinoid system.

Conclusion

Cannabis treatment reduced the deleterious effects of DIO by reducing weight gain, specifically fat depots, maintaining insulin levels, altering cytokine and gene expression levels that induce increased energy expenditure, while protecting pancreatic tissue from apoptosis by promoting proliferation.

Acknowledgements

We would like to acknowledge the Nelson Mandela Metropolitan University and National Research Foundation for the financial support provided for this project, Coos Bothma for his statistical modeling, and Kathrin Maedler and Garetha Siegfried-Kellerberger for their technical assistance.

Abbreviations: 2-AG, 2-arachidonoylglycerol; AEA, arachidonoylethanolamide/anandamide; AM251, 1-(2,4-dichloropheny1)-5-(4-iodophenyl)-4-methyl-N-1-morpholinyl-1H-pyrazole-3-carboxamide; AM630, 6-iodo-2-methyl-1-[2-(4-morpholinypethyl)-1H-indol-yl](4-methoxyphemyl) methanone; AUCg, area under the curve for glucose; Bc1-xL, B-cell lymphomaextra large; CB1, cannabinoid receptor type 1; CB2, cannabinoid receptor type 2; CNS, central nervous system; DIO, diet-induced obesity; FLIP, Fas-associated death-domain-like IL-1[beta]-converting enzyme-like inhibitory protein; Fas, fatty acid synthase; GLUT2, glucose transporter 2; HSI, hepatic somatic index; IL-l [alpha], interleukin-l [alpha]; IL-1 [beta], Interleukin-1 [beta]; IL-6, Interleukin-6; IFN-[gamma], Interferon-[gamma]; IPGTTs, Intraperitoneal glucose tolerance tests; LNC, Lean control; LNE, Lean experimental; MAPK, mitogen-activated protein kinase; c-MYC, myelocytomatosis oncogene; OBC, Obese Control; OBE, Obese Experimental; PDX-1, Pancreatic duodenal homeobox-1; PEPCK1, phosphoenolpyruvate carboxykinase 1; PKB, protein kinase B; qPCR, quantitative real-time polymerase chain reaction; RIA, radioimmunoassay; ROS, reactive oxygen species; RP-HPLC, reverse-phase high performance liquid chromatography; THC, Tetrahydrocannabinol; TNF-a, Tumor necrosis factor-[alpha]; T2DM, Type 2 Diabetes Mellitus; UCP2, uncoupling protein 2; WHO, World Health Organization.

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R-A. Levendal (a), D. Schumann (b), M. Donath (b), C.L. Frost (a), *

(a.) Department of Biochemistry and Microbiology, Nelson Mandela Metropolitan University, PO Box 77000, 6031 Port Elizabeth, South Africa

(b.) Division of Endocrinology, Diabetes and Metabolism, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland

* Corresponding author. Tel.: +27 41 504 4123; fax: +27 41 504 2814.

E-mail address: Carminita.Frost@nmmu.ac.za (C.L. Frost).

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doi:10.1016/j.phymed.2012.02.001
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Author:Levendal, R.-A.; Schumann, D.; Donath, M.; Frost, C.L.
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Date:May 15, 2012
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