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      High fat-fed GPR55 null mice display impaired glucose tolerance without concomitant changes in energy balance or insulin sensitivity but are less responsive to the effects of the cannabinoids rimonabant or Δ(9)-tetrahydrocannabivarin on weight gain

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          Abstract

          Background

          The insulin-sensitizing phytocannabinoid, Δ(9)-tetrahydrocannabivarin (THCV) can signal partly via G-protein coupled receptor-55 (GPR55 behaving as either an agonist or an antagonist depending on the assay). The cannabinoid receptor type 1 (CB1R) inverse agonist rimonabant is also a GPR55 agonist under some conditions. Previous studies have shown varied effects of deletion of GPR55 on energy balance and glucose homeostasis in mice. The contribution of signalling via GPR55 to the metabolic effects of THCV and rimonabant has been little studied.

          Methods

          In a preliminary experiment, energy balance and glucose homeostasis were studied in GPR55 knockout and wild-type mice fed on both standard chow (to 20 weeks of age) and high fat diets (from 6 to 15 weeks of age). In the main experiment, all mice were fed on the high fat diet (from 6 to 14 weeks of age). In addition to replicating the preliminary experiment, the effects of once daily administration of THCV (15 mg kg −1 po) and rimonabant (10 mg kg −1 po) were compared in the two genotypes.

          Results

          There was no effect of genotype on absolute body weight or weight gain, body composition measured by either dual-energy X-ray absorptiometry or Nuclear Magnetic Resonance (NMR), fat pad weights, food intake, energy expenditure, locomotor activity, glucose tolerance or insulin tolerance in mice fed on chow. When the mice were fed a high fat diet, there was again no effect of genotype on these various aspects of energy balance. However, in both experiments, glucose tolerance was worse in the knockout than the wild-type mice. Genotype did not affect insulin tolerance in either experiment. Weight loss in rimonabant- and THCV-treated mice was lower in knockout than in wild-type mice, but surprisingly there was no detectable effect of genotype on the effects of the drugs on any aspect of glucose homeostasis after taking into account the effect of genotype in vehicle-treated mice.

          Conclusions

          Our two experiments differ from those reported by others in finding impaired glucose tolerance in GPR55 knockout mice in the absence of any effect on body weight, body composition, locomotor activity or energy expenditure. Nor could we detect any effect of genotype on insulin tolerance, so the possibility that GPR55 regulates glucose-stimulated insulin secretion merits further investigation. By contrast with the genotype effect in untreated mice, we found that THCV and rimonabant reduced weight gain, and this effect was in part mediated by GPR55.

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          Most cited references22

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          Guidelines for the Design and Statistical Analysis of Experiments Using Laboratory Animals

          For ethical and economic reasons, it is important to design animal experiments well, to analyze the data correctly, and to use the minimum number of animals necessary to achieve the scientific objectives---but not so few as to miss biologically important effects or require unnecessary repetition of experiments. Investigators are urged to consult a statistician at the design stage and are reminded that no experiment should ever be started without a clear idea of how the resulting data are to be analyzed. These guidelines are provided to help biomedical research workers perform their experiments efficiently and analyze their results so that they can extract all useful information from the resulting data. Among the topics discussed are the varying purposes of experiments (e.g., exploratory vs. confirmatory); the experimental unit; the necessity of recording full experimental details (e.g., species, sex, age, microbiological status, strain and source of animals, and husbandry conditions); assigning experimental units to treatments using randomization; other aspects of the experiment (e.g., timing of measurements); using formal experimental designs (e.g., completely randomized and randomized block); estimating the size of the experiment using power and sample size calculations; screening raw data for obvious errors; using the t-test or analysis of variance for parametric analysis; and effective design of graphical data.
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            The putative cannabinoid receptor GPR55 affects osteoclast function in vitro and bone mass in vivo.

            GPR55 is a G protein-coupled receptor recently shown to be activated by certain cannabinoids and by lysophosphatidylinositol (LPI). However, the physiological role of GPR55 remains unknown. Given the recent finding that the cannabinoid receptors CB(1) and CB(2) affect bone metabolism, we examined the role of GPR55 in bone biology. GPR55 was expressed in human and mouse osteoclasts and osteoblasts; expression was higher in human osteoclasts than in macrophage progenitors. Although the GPR55 agonists O-1602 and LPI inhibited mouse osteoclast formation in vitro, these ligands stimulated mouse and human osteoclast polarization and resorption in vitro and caused activation of Rho and ERK1/2. These stimulatory effects on osteoclast function were attenuated in osteoclasts generated from GPR55(-/-) macrophages and by the GPR55 antagonist cannabidiol (CBD). Furthermore, treatment of mice with this non-psychoactive constituent of cannabis significantly reduced bone resorption in vivo. Consistent with the ability of GPR55 to suppress osteoclast formation but stimulate osteoclast function, histomorphometric and microcomputed tomographic analysis of the long bones from male GPR55(-/-) mice revealed increased numbers of morphologically inactive osteoclasts but a significant increase in the volume and thickness of trabecular bone and the presence of unresorbed cartilage. These data reveal a role of GPR55 in bone physiology by regulating osteoclast number and function. In addition, this study also brings to light an effect of both the endogenous ligand, LPI, on osteoclasts and of the cannabis constituent, CBD, on osteoclasts and bone turnover in vivo.
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              Some mathematical and technical issues in the measurement and interpretation of open-circuit indirect calorimetry in small animals.

              Indirect calorimetry is increasingly used to investigate why compounds or genetic manipulations affect body weight or composition in small animals. This review introduces the principles of indirect (primarily open-circuit) calorimetry and explains some common misunderstandings. It is not widely understood that in open-circuit systems in which carbon dioxide (CO2) is not removed from the air leaving the respiratory chamber, measurement of airflow out of the chamber and its oxygen (O2) content paradoxically allows a more reliable estimate of energy expenditure (EE) than of O2 consumption. If the CO2 content of the exiting air is also measured, both O2 consumption and CO2 production, and hence respiratory quotient (RQ), can be calculated. Respiratory quotient coupled with nitrogen excretion allows the calculation of the relative combustion of the macronutrients only if measurements are over a period where interconversions of macronutrients that alter their pool sizes can be ignored. Changes in rates of O2 consumption and CO2 production are not instantly reflected in changes in the concentrations of O2 and CO2 in the air leaving the respiratory chamber. Consequently, unless air-flow is high and chamber size is small, or rates of change of O2 and CO2 concentrations are included in the calculations, maxima and minima are underestimated and will appear later than their real times. It is widely appreciated that bigger animals with more body tissue will expend more energy than smaller animals. A major issue is how to compare animals correcting for such differences in body size. Comparison of the EE or O2 consumption per gram body weight of lean and obese animals is misleading because tissues vary in their energy requirements or in how they influence EE in other ways. Moreover, the contribution of fat to EE is lower than that of lean tissue. Use of metabolic mass for normalisation, based on interspecific scaling exponents (0.75 or 0.66), is similarly flawed. It is best to use analysis of covariance to determine the relationship of EE to body mass or fat-free mass within each group, and then test whether this relationship differs between groups.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                24 August 2020
                2020
                : 8
                : e9811
                Affiliations
                [1 ]Institute of Translational Medicine, University of Buckingham , Buckingham, United Kingdom
                [2 ]Medical School, University of Buckingham , Buckingham, United Kingdom
                Article
                9811
                10.7717/peerj.9811
                7451014
                b6cfb796-96f0-4451-8e4f-630daabe7e68
                ©2020 Wargent et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 17 April 2020
                : 4 August 2020
                Funding
                Funded by: GW Research Ltd
                Funding for this study was provided by GW Research Ltd. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biochemistry
                Diabetes and Endocrinology
                Nutrition

                gpr55,thcv,rimonabant,diabetes,obesity,glucose tolerance,body composition,energy balance

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