Non-Δ9tetrahydrocannabinol phytocannabinoids stimulate feeding in rats
Farrimond, Jonathan A.a,b; Whalley, Benjamin J.a; Williams, Claire M.b
aSchools of Pharmacy
bPsychology and Clinical Language Sciences, University of Reading, Whiteknights, Reading, Berkshire, UK
Correspondence to Claire M. Williams, PhD, School of Psychology and Clinical Language Sciences, University of Reading, Whiteknights, Reading, Berkshire, RG6 6AL, UK E-mail: firstname.lastname@example.org
Received June 9, 2011
Accepted October 6, 2011
Cannabinoid type 1 receptor-mediated appetite stimulation by Δ9tetrahydrocannabinol (Δ9THC) is well understood. Recently, it has become apparent that non-Δ9THC phytocannabinoids could also alter feeding patterns. Here, we show definitively that non-Δ9THC phytocannabinoids stimulate feeding. Twelve male, Lister-Hooded rats were prefed to satiety prior to administration of a standardized cannabis extract or to either of two mixtures of pure phytocannabinoids (extract analogues) comprising the phytocannabinoids present in the same proportions as the standardized extract (one with and one without Δ9THC). Hourly intake and meal pattern data were recorded and analysed using two-way analysis of variance followed by one-way analysis of variance and Bonferroni post-hoc tests. Administration of both extract analogues significantly increased feeding behaviours over the period of the test. All three agents increased hour-one intake and meal-one size and decreased the latency to feed, although the zero-Δ9THC extract analogue did so to a lesser degree than the high-Δ9THC analogue. Furthermore, only the analogue containing Δ9THC significantly increased meal duration. The data confirm that at least one non-Δ9THC phytocannabinoid induces feeding pattern changes in rats, although further trials using individual phytocannabinoids are required to fully understand the observed effects.
The scientific study of Cannabis sativa has largely focussed on the main psychoactive ingredient, Δ9tetrahydrocannabinol (Δ9THC; Gaoni and Mechoulam, 1964), and its interaction/s with the endocannabinoid system (ECS). The ECS comprises two cannabinoid receptors (the CBR; CB1R and CB2R; Devane et al., 1988; Matsuda et al., 1990; Munro et al., 1993), the endocannabinoids [anandamide (Devane et al., 1992) and 2-arachidonyl glycerol (Mechoulam et al., 1995; Sugiura et al., 1995)] and the enzymes responsible for their synthesis and degradation (Di Marzo et al., 2005). Modulation of the ECS has many physiological effects (Martin et al., 1981), including those on appetite control (Farrimond et al., 2011). Recently, however, research has begun to focus on the other phytocannabinoids (pCBs; for a full pharmacological review of these data see Pertwee, 2008; Izzo et al., 2009); and their initial characterization suggests that they exert their pharmacological effects through a range of mechanisms not limited to binding at CBR (e.g. through ion channels; Lozovaya et al., 2009). As these mechanisms and their behavioural effects have yet to be fully investigated, possible non-Δ9THC pCB effects on feeding patterns remain undetermined (for a recent in-depth review of the literature, see Farrimond et al., 2011).
Δ9THC-induced hyperphagia is characterized as CB1R-mediated increases in the hour-one food intake, the duration and size of meals and a reduction in feeding latency (Williams et al., 1998; Williams and Kirkham, 1999, 2002a, 2002b). Previously, we described the effects of two standardized pCB-rich C. sativa extracts. The first extract contained 67% Δ9THC (alongside other pCBs, in a ratio comparable with ground Sinsemilla; Potter et al., 2008) and produced a significant hyperphagic effect that was significantly smaller than that induced by purified Δ9THC (Farrimond et al., 2010a). The second extract contained only 6.9% Δ9THC, yet still increased appetitive feeding behaviours by significantly reducing the latency to feed and therefore shifting more consumption into hour-one of testing, although the quantity of food consumed during the test was unaltered (Farrimond et al., 2010b). At first sight, these data could be considered contradictory, as in the first instance the presence of non-Δ9THC pCBs reduced Δ9THC-mediated hyperphagia while in the second the presence of these non-Δ9THC pCBs induced hyperphagia. However, pCB concentrations varied between the extracts with the most notable differences in Δ9THC (67.0–6.9%), CBN (cannabinol: 1.5–6.5%) and CBD (cannabidiol: 0.3–1.0%) content. As such, we hypothesized that these differences in pCB proportions were responsible for the differences in observed effects and that one or more non-Δ9THC pCBs altered feeding patterns and/or modulated Δ9THC-mediated hyperphagia.
Finally, in these studies, the extracts contained residual plant matter (RPM) and, while better representing the chemical composition of medicinal cannabis, cannabis-based medicines (e.g. Sativex) and/or recreationally abused cannabis, it was impossible to exclude a contribution from RPM in the observed effects. Evidence that pCB combinations can induce alterations in feeding patterns would be valuable for drug development as alternatives to existing Δ9THC-based treatments (e.g. nabilone) would be preferable given the nonspecific and psychotropic side-effects of Δ9THC. Interestingly, no evidence currently exists to link non-Δ9THC pCBs to such adverse effects. Therefore, given previous encouraging results (Farrimond et al., 2010a, 2010b), we investigated whether two synthetic mixtures of pCBs intended to model the pCB composition of our previously studied plant extracts (one with and one without Δ9THC), but without RPM or other unknown material, could increase feeding in rats. The data confirm that pCB combinations can induce alterations in feeding patterns and demonstrate that Δ9THC is not necessary for the effects observed.
Twelve male, Lister-Hooded rats (postnatal day>40, at the start of testing, Harlan UK Ltd., England) were maintained in a temperature controlled environment (21–22°C) on a reversed 12 : 12 h white : red light cycle (red lights on at 10.00 h). Standard lab chow (PCD Mod C, Special Diet Services, England) was freely available except for a 3-h period on experimental days. Fresh water was available at all times. All procedures were performed in compliance with the United Kingdom Animals (Scientific Procedures) Act, 1986.
All tests were performed during the dark phase under low intensity red light (approximately 4 lx). Testing was carried out in standard plastic cages, each fitted with a modified food hopper connected, through a strain gauge weighing device, to a computer running data acquisition and analysis software (The Feeding and Drinking Monitor v 2.16, TSE Systems GmbH, Bad Homburg, Germany), which permitted continuous monitoring of food intake. Food intake data were analysed to provide information on hourly food intakes as well as critical meal parameters such as latency to onset of meals, individual meal size and duration and intermeal intervals. For the purposes of this study, a meal was defined as any feeding episode causing a change in food weight of 0.1 g or more, lasting for at least 1 min and separated by at least 15 min from any subsequent episode. Consecutive feeding events separated by intervals of less than 15 min were considered to be part of a single meal. These criteria have been previously used to facilitate the visualization and interpretation of drug effects on feeding behaviour and to distinguish prolonged eating episodes from more transient, exploratory contacts with food (Williams and Kirkham, 2002a; Farrimond et al., 2010a, 2010b).
Two synthetic mixtures of purified pCBs were used, one with (high-Δ9THC analogue) and one without (zero-Δ9THC analogue) Δ9THC [Δ9THC: 0.0% or 67.0%; CBD: 0.3%; cannabigerol: 1.7%; cannabichromene: 1.6%; tetrahydrocannabivarin: 0.9%; tetrahydrocannabinolic acid: 0.3%; CBN: 1.5%; and sesame oil vehicle; total mixture dose range: 0.5–4.0 mg/kg), matched to the proportions present in a positive control compound (high-Δ9THC botanical drug substance (BDS): 4.0 mg/kg]. The mixtures were prepared in advance and defrosted immediately before use on test days. Drugs were administered orally through a syringe placed into the cheek pouch of the rat. Each group of animals received their drug treatments according to a Latin Square design, with at least 48 h between successive treatments. A single treatment of pure sesame oil was used as the vehicle-control in this study. Drug administration began only after animals had been habituated to housing conditions, oral dosing and subsequent test procedures.
Animals in individual cages were prefed a palatable mash (10.00–12.00 h), followed by drug administration and assimilation (12.00–13.00 h; during which time food was unavailable). The palatable mash comprised 1 part Rat and Mouse Expanded Ground Diet (Special Diet Services, Witham, England), 1.25 parts fresh tap water and 0.25 parts sucrose (Tate and Lyle, London, England) by weight. Any remaining palatable mash and spillage was recovered after 120 min and weighed. After removal of the prefeed at 12.00 h, drugs were orally administered to the rats according to a randomized counterbalanced design. Rats were then deprived of food until 13.00 h to allow for drug assimilation. At 13.00 h, 30 g of normal laboratory chow were placed into the food hoppers and testing began (13.00–15.00 h). The procedure is identical to that presented in the study by Farrimond et al. (2010a).
Data were separately analysed using two-way analysis of variance (ANOVA) for repeated measures with two drugs (Δ9THC-free analogue and high-Δ9THC analogue) and five doses (0.0–4.0 mg/kg). In the case of significant drug differences, one-way ANOVAs were used for each drug followed by Bonferroni post-hoc tests when appropriate. As this trial randomized the administration of drug and dose using a Latin Square design, only one vehicle-treatment was used. Thus, in our statistical analyses this vehicle-treatment has been used as the control for both analogues. High-Δ9THC BDS data were compared with vehicle administration using Student’s t-tests. All tests were run using PASW18 (SPSS Inc., Chicago, USA). Data presented for all meal-two parameters could not be analysed statistically due to the small number of second meals which were observed, but are included for completeness.
Prior to testing, a stable prefeed intake was established and continued during testing [F(14,165)=1.0, not significant]; animals consumed 20.1±0.3 g daily.
Both the zero-Δ9THC and high-Δ9THC analogues significantly increased hour-one intake and decreased the latency to feed, despite the differences in Δ9THC concentration (0% vs. 67% respectively). Indeed, both analogues induced significant dose-dependent increases in hour-one intake [F(4,72)=11.59, P<0.001; by factors of approximately 7 and 9 at 4.0 mg/kg vs. vehicle-treatments] and doses 2.0 mg/kg or more significantly increased feeding alone in post-hoc tests versus vehicle-treatments (P≤0.005; Fig. 1a). Furthermore, during hour-two, both analogues significantly decreased intake [F(4,72)=5.31, P<0.001; Fig. 1b]. The zero-Δ9THC and high-Δ9THC analogues also caused significant reductions in the latency to feed [F(4,72)=4.96, P<0.001; Fig. 2] from approximately 50 min to approximately 10 min (vehicle-treatments vs. 4.0 mg/kg of both analogues).
Interestingly, significant differences between some behavioural changes induced by the analogues were also observed. While both analogues significantly increased meal-one size in a dose-dependent manner [F(4,72)=5.08, P<0.001; Fig. 1c], there was also a marginally significant difference between the drugs [F(1,18)=3.21, P=0.09] whereby the zero-Δ9THC analogue increased meal-one size less than the high-Δ9THC analogue. Moreover, significant differences were present between the mixtures in terms of meal duration [F(1,18)=8.96, P<0.01] and further analysis revealed this to be due to a lack of effect of the zero-Δ9THC analogue upon meal-one duration [F(4,49)=2.13, not significant], while the high-Δ9THC analogue significantly increased meal-one duration [F(4,49)=4.81, P<0.005] with a significant post-hoc effect at 4.0 mg/kg versus vehicle-treatments (P<0.005). There was no significant difference between the rates of meal-one intake between the two analogues [F(2.28,41.04)=1.81, not significant; 0.90 versus 0.32 g/min at a dose of 4.0 mg/kg]. Thus, our high-Δ9THC analogue produced a significant increase in both meal-one size and duration, while the zero-Δ9THC analogue produced only weakly significant effects on meal-one size.
The positive control compound (high-Δ9THC BDS) behaved as previously described (Farrimond et al., 2010a); at a dose of 4.0 mg/kg, it significantly increased hour-one intake (P<0.002; Fig. 1a), decreased hour-two intake (P<0.05; Fig. 1b) and reduced the latency to feed (P<0.01; Fig. 2) when compared with vehicle-treated animals.
Here, we compared the effects of three pCB combinations: a high-Δ9THC BDS extract containing RPM and two mixtures of purified pCBs (extract analogues; one with and one without Δ9THC). Neither analogue contained RPM, allowing us to specifically examine if we could attribute any hyperphagic effects of these mixtures to the presence of non-Δ9THC pCBs.
Both analogues significantly increased hour-one and meal-one intakes, in addition to reducing the latency to feed and inducing a compensatory reduction in hour-two intake. Importantly, these effects were seen even in the mixture that did not contain any Δ9THC, clearly indicating that non-Δ9THC pCBs can themselves induce hyperphagic actions comparable with those seen with Δ9THC. Further study is required to discover which pCB, or combination of pCBs, may be responsible for this pattern of effects.
Subtle differences between the drug effects presented here and those we have previously reported were also observed. First, the high-Δ9THC, but not the zero- Δ9THC, analogue increased meal-one duration, as we have previously demonstrated through administration of purified Δ9THC (Farrimond et al., 2010a). This selective action suggests that Δ9THC in the high-Δ9THC analogue was responsible for the appearance of increased meal-one duration. In contrast, given that the zero-Δ9THC analogue did not affect meal-one duration (c.f. significant increases in meal-one duration with the high-Δ9THC analogue) but still resulted in an increase in the size of meal-one, these data are suggestive of an effect of the zero-Δ9THC analogue to increase the speed of chow consumption. Indeed, animals administered the zero-Δ9THC analogue ate chow at a faster rate (albeit nonsignificantly) than those treated with the high-Δ9THC analogue (0.90 vs. 0.32 g/min at a dose of 4.0 mg/kg). Such data strengthen the argument that at least one non-Δ9THC pCB can significantly affect both appetitive and consummatory feeding behaviours, but that they do so in a manner that is subtly different to Δ9THC.
Given the differential effects of pCB administration reported in literature (e.g. Sofia and Knobloch, 1976; Riedel et al., 2009; Ignatowska-Jankowska et al., 2010), the effects of cannabis extracts on appetitive and/or consummatory behaviours that we have previously reported and the data presented here, the evidence supporting non-Δ9THC pCB effects on feeding is growing. Specifically, purified Δ9THC increases appetitive and consummatory behaviours, but removal of Δ9THC or alteration of the non-Δ9THC pCB ratio present in analogues or BDSs (e.g. in the high-Δ9THC analogue and BDS) maintains increases in appetitive behaviours but reduces consummatory behaviours (see results and Farrimond et al., 2010a). Finally, after administration of a low-Δ9THC BDS that contained a different pCB ratio (c.f. high-Δ9THC analogue and BDS), increases in appetitive behaviours alone have been observed (Farrimond et al., 2010b). Hence, we propose that individual pCBs can exert a complex range of effects on feeding behaviours and that at least one non-Δ9THC pCB contained in the analogues or BDSs examined can modulate Δ9THC-mediated hyperphagia. In our view, given this data and the available literature, the most likely pCBs to be inducing the alterations to meal patterns seen here are CBN and CBD. CBN is a potent CB1R agonist with selectivity for the receptor higher than Δ9THC (Felder et al., 1995; Rhee et al., 1997); therefore, CBN may contribute to the observed effects by increasing CB1R activation. On the other hand, CBD has been shown to inhibit anandamide reuptake and effect Ca2+ homeostasis (see Izzo et al., 2009), which could modulate endocannabinergic tone. However, the specific mechanisms by which these pCBs may act to alter feeding remains unknown and it is possible that further study may demonstrate that CBN and CBD alter feeding in different ways. Hence, while further studies are required to fully elucidate the complex feeding effects of, and drug–drug interactions between, individual pCBs, this study importantly demonstrates that Δ9THC is not necessary for pCB-mediated induction of hyperphagia and, as such, could hold therapeutic potential for the treatment of feeding disorders.
The high-Δ9THC analogue and high-Δ9THC BDS produced hyperphagia similar to that previously described (Williams et al., 1998; Williams and Kirkham, 2002a; Farrimond et al., 2010a, 2010b). Importantly, the zero-Δ9THC analogue also induced hyperphagic effects by reducing the latency to feed but without increases in meal-one duration. These data suggest that while non-Δ9THC pCBs can stimulate feeding, their actions on feeding microstructure are distinct from those of Δ9THC.
Given the highly purified pCBs administered during this experiment, these data confirm the assertion that at least one non-Δ9THC pCB/s can increase feeding and reject the possibility that RPM affects feeding (Farrimond et al., 2010a, 2010b).
Further studies using individual non-Δ9THC pCBs are required to fully understand the differential effects observed in this study.
This research was supported in part by the University of Reading Research Endowment Trust Fund (to J.A.F.). The authors thank GW Pharmaceuticals for their kind gift of the purified phytocannabinoids and Dr Andrew Hill for his constructive comments on this manuscript.
Funding was kindly provided by the University of Reading Endowment Trust Fund.
Conflicts of interest
There are no conflicts of interest.
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