European Psychiatry Anandamide and 2-arachidonoylglycerol www.cambridge.org/epa baseline plasma concentrations and their clinical correlate in gambling disorder Isabel Baenas1,2,3,4 , Neus Solé-Morata1,3 , Roser Granero2,3,5 , Research Article 1,2,3,6 Fernando Fernández-Aranda , Mitona Pujadas , Bernat Mora-Maltas1,3,4 7 , Cite this article: Baenas I, Solé-Morata N, 1,2,3 1,3 1,3 Granero R, Fernández-Aranda F, Pujadas M, Ignacio Lucas , Mónica Gómez-Peña , Laura Moragas , Mora-Maltas B, Lucas I, Gómez-Peña M, 2,3,8 Moragas L, del Pino-Gutiérrez A, Tapia J, de la Amparo del Pino-Gutiérrez , Javier Tapia3,4 , Rafael de la Torre2,7,9 , Torre R, Potenza MN, Jiménez-Murcia S (2023). 10,11,12,13,14 1,2,3,6 Anandamide and 2-arachidonoylglycerol Marc N. Potenza and Susana Jiménez-Murcia baseline plasma concentrations and their 1 clinical correlate in gambling disorder. Department of Clinical Psychology, Bellvitge University Hospital, Barcelona, Spain; 2CIBER Physiopathology of Obesity European Psychiatry, 66(1), e97, 1–9 and Nutrition (CIBEROBN), Instituto de Salud Carlos III, Barcelona Spain; 3Psychoneurobiology of Eating and Addictive https://doi.org/10.1192/j.eurpsy.2023.2460 Behaviors Group, Neuroscience Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain; 4Doctoral Program in Medicine and Translational Research, University of Barcelona, Barcelona, Spain; 5 Received: 23 June 2023 Department of Psychobiology and Methodology, Autonomous University of Barcelona, Barcelona, Spain; 6Department of Revised: 08 September 2023 Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain; 7Integrative Accepted: 26 September 2023 Pharmacology and Systems Neuroscience Research Group, Hospital del Mar Research Institute (IMIM), Barcelona, Spain; 8Department of Public Health, Mental Health and Perinatal Nursing, School of Nursing, University of Barcelona, Keywords: 2-arachidonoylglycerol; addictive behaviors; Barcelona, Spain; 9Department of Experimental and Health Sciences, Universitat Pompeu Fabra (CEXS-UPF), Barcelona, anandamide; gambling disorder; impulsive Spain; 10Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; 11Child Study Center, Yale behaviors University School of Medicine, New Haven, CT, USA; 12Connecticut Mental Health Center, New Haven, CT, USA; 13 Connecticut Council on Problem Gambling, Wethersfield, CT, USA and 14Department of Neuroscience, Yale University, Corresponding author: New Haven, CT, USA Susana Jiménez-Murcia; Email: sjimenez@bellvitgehospital.cat Abstract Introduction. Different components of the endocannabinoid (eCB) system such as their most well-known endogenous ligands, anandamide (AEA) and 2-arachidonoylglycerol (2-AG), have been implicated in brain reward pathways. While shared neurobiological substrates have been described among addiction-related disorders, information regarding the role of this system in behavioral addictions such as gambling disorder (GD) is scarce. Aims. Fasting plasma concentrations of AEA and 2-AG were analyzed in individuals with GD at baseline, compared with healthy control subjects (HC). Through structural equation modeling, we evaluated associations between endocannabinoids and GD severity, exploring the potentially mediating role of clinical and neuropsychological variables. Methods. The sample included 166 adult outpatients with GD (95.8% male, mean age 39 years old) and 41 HC. Peripheral blood samples were collected after overnight fasting to assess AEA and 2-AG concentrations (ng/ml). Clinical (i.e., general psychopathology, emotion regulation, impulsivity, personality) and neuropsychological variables were evaluated through a semi- structured clinical interview and psychometric assessments. Results. Plasma AEA concentrations were higher in patients with GD compared with HC (p = .002), without differences in 2-AG. AEA and 2-AG concentrations were related to GD severity, with novelty-seeking mediating relationships. Conclusions. This study points to differences in fasting plasma concentrations of endocanna- binoids between individuals with GD and HC. In the clinical group, the pathway defined by the association between the concentrations of endocannabinoids and novelty-seeking predicted GD severity. Although exploratory, these results could contribute to the identification of potential endophenotypic features that help optimize personalized approaches to prevent and treat GD. © The Author(s), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:// creativecommons.org/licenses/by/4.0), which Introduction permits unrestricted re-use, distribution and Gambling disorder (GD) is a psychiatric disorder characterized by a recurrent betting behavior reproduction, provided the original article is properly cited. despite negative consequences [1]. It has been classified within the “substance-related and addiction disorders” category in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which recognizes the disorder as a behavioral addiction [1]. The estimated lifetime prevalence of GD varied between 0.2 and 10.6% worldwide, being around 1% in Spain [2–4]. It is considered as a complex disorder with a multifactorial etiology, involving psychosocial and biological factors [4, 5]. In this line, some studies have pointed to the role of different https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press 2 Baenas et al. neuroendocrine systems in the pathogenesis of GD, which modu- emotion regulation has suggested a role in the pathogenesis of late neurobiological responses associated with reward and gratifi- mood disturbances [32, 33]. That said, it is worth mentioning that cation [6–9]. impulsivity, poor cognitive processing, a dysfunctional personality Over the past few decades, the study of the endocannabinoid structure (e.g., high novelty-seeking), and emotion dysregulation (eCB) system has garnered closed attention in the field of represent core features related to the pathogenesis of GD [4, 34–36]. psychiatry due to its involvement in several brain functions Altogether, dysfunctions on the eCB system seem to be involved such as cognition, emotion, impulsivity, and motivation in several processes related to addiction [13, 25]. However, there is [10]. Indeed, the eCB system has been directly implicated in the still controversy whether eCB system dysfunctions may be associ- regulation of reward homeostasis in both animal and human ated with causes and/or consequences of exposure to potentially studies [11–13]. This system includes endogenous ligands addictive rewards. In fact, exposure to rewards has been proposed (i.e., eCBs), G-protein coupled cannabinoid receptors (CBRs), to induce, in turn, changes in the eCB system functioning [27]. In and enzymes to metabolize eCBs. Anandamide (AEA) and this sense, additional studies are needed to better understand the 2-arachidonoylglycerol (2-AG) are arguably the two most studied link between the eCB system and the pathogenesis of addiction. eCBs [14]. They are produced post-synaptically on demand to act Nonetheless, preclinical and clinical evidence has led to the eCB on presynaptic CBRs, mainly types 1 and 2 (CB1R, CB2R). AEA system being proposed as a potential therapeutic target in psych- and 2-AG do not seem fully interchangeable [15, 16], and even iatry. In this line, CBR blockade or eCBs synthesis inhibition (e.g., when interacting, they display specific functionality and/or act on enzyme inhibitors) seem to reduce reward consumption and crav- different pathways regarding similar functions [15, 17]. AEA ing, as well as subsequent relapse [14, 24, 37, 38]. binds with slightly higher affinity to CB1R than CB2R, whereas To the best of our knowledge, this is the first study to assess eCBs 2-AG exhibits greater general agonist efficacy than AEA [14]. in GD. Then, this study aimed to measure baseline AEA and 2-AG Although both types of receptors are located in the brain and plasma concentrations in fasting among patients with GD, com- peripheral tissues [18], CB1R has been predominantly found in the pared with healthy controls (HC). Moreover, through a path ana- brain [19]. This receptor is widely distributed in mesolimbic struc- lysis model, associations between eCBs concentrations and GD tures integrated in the reward system (e.g., nucleus accumbens and severity were analyzed, considering the mediating role of clinical ventral tegmental area) and other brain regions (e.g., prefrontal and neuropsychological variables. Based on previous data, we cortex, hippocampus, amygdala, insula, and hypothalamus) impli- expected to find differences in eCBs concentrations between cated in cue-elicited craving, relapse-like behaviors, and condition- groups. Besides, we hypothesized a distinctive association between ing processes [14, 20, 21]. Through their union to CB1R, eCBs act as AEA and 2-AG with GD severity. retrograde inhibitors of neurotransmitter release (both inhibitory, gamma-aminobutyric acid (GABA), and excitatory, glutamate (GLU)), with a modulatory role of other neurotransmission sys- Methods tems also involved in reward processing and addiction (e.g., dopa- Participants minergic, serotonergic, opioid systems) [22, 23]. The eCB system seems to enhance motivation for different The final sample consisted of n = 166 treatment-seeking adult natural and learned rewards (e.g., palatable food, sex, money, or outpatients with a diagnosis of GD according to DSM-5 criteria drugs) by stimulating dopaminergic signaling [24, 25]. Indeed, the [1], mostly men (n = 159, 95.8%) with a mean age of 39.13 years old action of eCBs on CB1R regulates short- and long-term synaptic (SD = 13.73). They were voluntarily recruited between April 2018 plasticity in areas related to reward processing, being dysfunctional and September 2021 at the Behavioral Addictions Unit of Bellvitge changes in neuroplasticity linked to addiction [25]. Then, it is not University Hospital (Barcelona, Spain). A total of 41 HC were surprising that the dysregulation of the eCB system signaling has recruited via advertisement from the same catchment area. Exclu- been linked to substance and nonsubstance addictive behaviors sion criteria in both groups were the presence of an organic mental (e.g., food, drugs, sex) [13, 14, 25]. disorder, an intellectual disability, a neurodegenerative disorder, or In this context, eCBs have been proposed to influence an active psychotic disorder. Although a valid blood sample was dopamine-related positive reinforcement that mediates craving available in all cases, 11 patients and 1 HC were excluded from the and impulsive reward-seeking behaviors [26]. Likewise, the eCB initial sample (n = 177 patients with GD and n = 42 HC) due to system seems to participate in negative-reinforcement-driven seek- incomplete clinical data. ing behaviors through their involvement in learning and memory processes [25]. A dysfunctional eCB system signaling between the Assessments limbic system and areas such as the prefrontal cortex and amygdala may result in emotional processing and sensory perceptions under- Biological measures lying addiction. Such processes influence the acquisition of habit Blood samples were obtained after an overnight fasting of at least learning and conditioned responses relevant to progressive impair- 8 hours. Blood was centrifuged at 1700 g in a refrigerated centrifuge ments in control that characterize addiction [23, 27]. (4°C) for over 20 minutes. Plasma was immediately separated and Moreover, the eCB system has been linked to impulsivity and stored at 80°C until the analysis was carried out. AEA and 2-AG executive functioning albeit in different ways [28–30]. For example, were analyzed by liquid chromatography-mass spectrometry circulating AEA concentrations have been related to advantageous (LC/MS–MS) using a previously validated method [39]. decision-making and better cognitive flexibility while 2-AG con- centrations have been linked to impaired cognitive flexibility and Clinical and neuropsychological measures inhibitory response tendencies in a nonclinical population Clinical and neuropsychological variables were collected using [31]. Likewise, the association of the eCB system with personality standardized instruments, which are properly described in the traits, such as novelty-seeking, has also been noted in previous Supplementary Material. Briefly, clinical variables were measured research [28]. Additionally, the involvement of this system in using the Spanish adaptation of the following questionnaires: South https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press European Psychiatry 3 Oaks Gambling Screen (SOGS) [40, 41]; Diagnostic Questionnaire measures obtained in each cognition test (WCST nonperseverative for Pathological Gambling According to DSM criteria [42, 43], errors, WCST conceptual, TMT-A, TMT-B, Stroop interference, Symptom Checklist-90-Revised (SCL-90-R) [44, 45]; Tempera- digits direct, and digits inverse). The goodness-of-fit was evaluated ment and Character Inventory-Revised (TCI-R) [46, 47]; Impulsive with standard criteria [59]: root mean square error of approxima- Behavior Scale (UPPS-P) [48, 49]; and Difficulties in Emotion tion RMSEA < 0.08, Bentler’s Comparative Fit Index CFI > 0.90, Regulation Strategies (DERS) [50, 51]. This last psychometric Tucker–Lewis Index TLI > 0.90, and standardized root mean square assessment was not systematically recorded in the HC group. residual SRMR < 0.10. The global predictive capacity of the model Neuropsychological data has been collected by the following instru- was estimated with the coefficient of determination (CD). ments: Wisconsin Card Sorting Test (WCST) [52]; Stroop Color and Word Test (SCWT) [53]; Trail Making Test (TMT) [54]; and Digits task of the Wechsler Memory Scale-Third Edition (WMS- Results III) [55]. Description of the sample Additionally, body mass index (BMI) and disorder-related vari- ables, such as the age of onset and duration of GD, were collected in In the clinical group, most participants were men (95.8%). The a semi-structured face-to-face clinical interview as described else- mean age was 39.1 years old (SD = 13.7), the mean age of GD onset where [56]. was 27.8 years (SD = 11.9), and mean GD duration was 5.3 years (SD = 6.3). Most HC were men (90.2%), with a mean age of 49.3 years old (SD = 15.2). Table 1 displays the participants char- Procedure acteristics. All participants were evaluated at the Behavioral Addictions Unit of The presence of GD was associated with higher BMI, impulsivity Bellvitge University Hospital (Barcelona, Spain). The data collec- (UPPS-P), general psychopathology (SLC-90R), novelty-seeking, tion was conducted by a trained multidisciplinary team (psycholo- and harm-avoidance (TCI-R), but lower self-directedness (TCI-R). gists, psychiatrists, nurses) with more than 25 years of experience in Table 2 contains results of ANCOVA comparing clinical features the field of GD. A comprehensive semi-structured clinical interview between groups, adjusting for age and sex. was conducted in a first session assessing all aspects related to gambling behavior. The psychometric assessment of clinical vari- Comparison of eCBs concentrations between groups ables and the extraction of blood samples took place in a second session. Blood samples were analyzed at the Integrative Pharma- Broadly, the clinical group displayed higher mean AEA concentra- cology and Systems Neuroscience research group-Hospital del Mar tions while no between-group differences were found in 2-AG Research Institute (IMIM) (Barcelona, Spain). The neuropsycho- concentrations, after adjusting for age, sex, and BMI. Table 3 shows logical evaluation was performed in a third session. All the meas- comparison of eCBs concentrations between groups. Additionally, ures were assessed prior to the beginning of specialized treatment Figure 1 displays a scatterplot with individual data point concen- for GD in our Unit. trations of eCBs. Ethics Path analysis The present study was conducted according to the Declaration of Figure 2 displays the path diagram with the standardized coeffi- Helsinki. The Clinical Research Ethics Committee of Bellvitge cients of the SEM obtained in the GD group. Supplementary Table University Hospital approved this study (ref. PR329/19 and S1 contains the complete SEM results. This final model achieved PR338/17). Signed informed consent was obtained from all parti- adequate goodness-of-fit: RMSEA = 0.065 (95% confidence inter- cipants. val: 0.051 to 0.079), CFI = 0.909, TLI = 0.906 and SRMR = 0.099. The global predictive capacity was 26% (CD = 0.256). All variables used to define the latent variable measuring the Statistical analysis neuropsychological performance level achieved significant results. Statistical analysis was conducted with Stata17 for Windows [57]. The between-group comparison of AEA and 2-AG concen- trations was done with the analysis of covariance (ANCOVA), Table 1. Descriptive features of the sample adjusting for sex, age, and BMI, as well as for sex and age regarding Control (n = 41) GD (n = 166) clinical variables (UPPS-P, SCL-90R, TCI-R, DERS). The stand- ardized Cohen’s d coefficient measured the effect size for the mean n % n % p comparisons (the thresholds of 0.20, 0.50, and 0.80 were considered Sex for low, mild/moderate, and high-large effect sizes) [58]. Path analysis exploring the underlying relationships between Women 4 9.8 7 4.2 .157 variables among the GD subsample was performed through Struc- Men 37 90.2 159 95.8 tural Equation Models (SEM). The rationale for model specification Mean SD Mean SD p was based on the background provided by the cumulated empirical evidence, with the condition of guaranteeing the clinical association Age (years-old) 49.27 15.23 39.13 13.73 <.001* of the relationships. All parameters were free-estimated, and Age of onset of GD – – 27.81 11.95 parameters with no significant tests were deleted with the aim to obtain a final parsimonious model with the highest possible statis- Duration of GD – – 5.30 6.27 tical power. Due to the large number of neuropsychological vari- Abbreviations: GD, gambling disorder; SD, standard deviation. ables in the study, a latent variable was defined for the main *Significant comparison. https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press 4 Baenas et al. Table 2. Comparison of anthropometric, clinical, and neuropsychological variables between groups: ANCOVA Control (n = 41) GD (n = 166) Adjusted for sex and age Mean SD Mean SD p |d| BMI (kg/m2) 24.58 2.60 26.93 5.19 .004* 0.57† UPPS-P: Lack of premeditation 20.84 4.02 24.27 6.11 .001* 0.66† UPPS-P: Positive Urgency 20.26 5.85 31.93 10.39 <.00* 1.38† UPPS-P: Negative Urgency 22.79 5.55 32.11 6.60 <.001* 1.53† SCL-90R: GSI score 0.40 0.34 1.08 0.65 <.001* 1.31† TCI-R: Novelty-seeking 98.42 10.63 111.29 12.23 <.001* 1.12† TCI-R: Harm avoidance 87.69 17.86 99.17 17.15 <.001* 0.66† TCI-R: Self-directedness 148.96 19.03 131.09 20.24 <.001* 0.91† DERS: Total – – 90.68 21.37 – – WCST nonperseverative errors 9.15 10.42 17.46 13.09 <.001* 0.70† WCST conceptual 66.37 8.66 62.40 14.56 .108 0.33 TMT A 27.65 8.10 30.44 9.85 .096 0.31 TMT B 62.12 22.07 79.27 41.47 .013* 0.52† STROOP interference 3.29 7.71 3.02 6.89 .830 0.04 Digits direct 9.39 1.93 9.03 1.95 .311 0.19 Digits inverse 6.94 1.89 6.16 1.65 .013* 0.44 Note: –, Not available for this group. Abbreviations: GD, gambling disorder; SD, standard deviation. *Significant comparison. † Effect size into ranges mild–moderate (|d| > 0.50) to high-large (|d| > 0.80). Table 3. Comparison of endocannabinoids concentrations between groups: ANCOVA Control (n = 41) GD (n = 166) Adjusted for sex, age, and body mass index Mean SD Mean SD p |d| 2-AG (ng/ml) 4.25 1.94 5.71 5.22 .100 0.37 AEA (ng/ml) 0.32 0.14 0.41 0.16 .002* 0.60† Abbreviations: 2-AG, 2-arachidonoylglycerol (ng/ml); AEA, N-arachidonoylethanolamide (anandamide) (ng/ml); GD, gambling disorder; SD, standard deviation. *Significant comparison. † Effect size into ranges mild–moderate (|d| > 0.50) to high-large (|d| > 0.80). Figure 1. Scatterplot with individual data point concentrations of eCBs. 2-AG, 2-arachidonoylglycerol (ng/ml); AEA, anandamide (ng/ml); GD, gambling disorder; HC, healthy control. https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press European Psychiatry 5 Figure 2. Path diagram with the standardized coefficients within the GD subsample. Results adjusted for sex and age. Only significant parameters are retained. Fit statistics: RMSEA = 0.065 (95%CI: 0.051 to 0.079); CFI = 0.909; TLI = 0.906; SRMR = 0.099; CD = 0.256. The signal of the measurement coefficients indicates that the higher between eCBs concentrations and GD severity, with novelty- the level in the latent variable, the higher the cognitive impairment. seeking being a mediating factor. Although it was not a primary Higher GD severity (SOGS) was directly associated with higher objective of this study, the association between clinical and neuro- novelty-seeking (TCI-R) and psychopathological distress psychological variables and GD severity was previously described (SCL-90R, GSI), but lower neuropsychological dysfunction (latent [63–65]. variable). Indirect mediating links that contributed to increase the Bearing in mind that this is a cross-sectional study, differences in likelihood of higher GD severity were identified: (a) higher AEA eCBs concentrations between groups suggest an involvement of the and lower 2-AG concentrations were positively associated with eCB system in the pathogenesis of GD. Precisely, higher AEA higher novelty-seeking; (b) the path characterized by higher scores concentrations in individuals with GD might indicate a dysfunc- in harm avoidance and negative urgency as well as lower self- tional eCB system, which has already been involved with the directedness and lack of premeditation was linked to higher scores reinforcement of rewarding behaviors in other psychiatric condi- in general psychopathology; and (c) worse cognitive performance tions, such as substance use disorders or binge eating disorder [12, was associated with more general psychopathology. 16, 17, 27, 66–72]. In contrast to AEA, we did not observe statis- tically significant differences in 2-AG concentrations between groups. A possible hypothesis may be that 2-AG is highly sensitive Discussion to cue exposure, as previously proposed [69, 72, 73]. Moreover, it is This exploratory study examined circulating AEA and 2-AG con- worth mentioning that a prominent influence of preanalytical centrations in individuals with and without GD. Moreover, rela- conditions on the plasma 2-AG concentrations (e.g., food intake, tionships between those eCBs concentrations and GD severity were collection, and processing of blood samples) could be affecting our assessed through a SEM model that included different clinical and results [74]. Therefore, these aspects should be considered in the neuropsychological features. Broadly, the socio-demographic, clin- design of future studies. ical, and neuropsychological profile that characterized the clinical Alternatively, the existence of compensatory mechanisms of the group was in line with previous works [60–62]. AEA concentrations eCB system in efforts to counterbalance a dysfunctional activity were higher in individuals with GD than in HC after adjusting for could contribute to explain our results [26, 75]. This rationale may sex, age, and BMI. The SEM analysis showed an association be reinforced by 2-AG acting as a full agonist on CB1R in contrast https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press 6 Baenas et al. with the partial agonism of AEA, which gives AEA a higher Finally, some limitations should be highlighted. Individuals with modulatory capacity on CBRs and the eCB system’s activity, includ- GD were treatment-seeking patients from a hospital setting, which ing other eCBs [14, 76]. Indeed, Maccarrone et al. [76] reported that could limit the representativeness and generalizability of the results. elevated AEA concentrations could mediate a reduced biosynthesis Likewise, the cross-sectional nature of this study does not allow for of 2-AG in brain areas related to reward processing in an animal drawing causal inferences. Moreover, the analysis of peripheral model, suggesting efforts to balance the eCB system tone. Further- eCBs concentrations did not allow to infer the central functioning more, genetic studies have suggested that dysfunction of the of the system. Therefore, future longitudinal studies exploring enzymatic machinery could modulate eCBs concentrations. For central correlates are warranted. Some strengths are also worth example, the inhibition of the fatty acid amide hydrolase noting such as the inclusion of a control group, adjusting for (FAAH), an enzyme involved in the degradation of AEA, has been potential confounding factors, and the use of a previously validated related to increased AEA concentrations, but to an absence of procedure to obtain eCBs concentrations. significant changes in 2-AG or even, to decreased concentrations [27, 71, 76–78]. Altogether, these possibilities represent some of many factors that could underlie a dysfunctional eCB system and Conclusions serve as a basis for future studies. This is the first observational study focused on exploring the eCB In the SEM analysis, we observed that higher AEA concentra- system in a clinical sample with GD. We observed significant tions, but lower 2-AG, predicted higher GD severity through its differences in fasting AEA plasma concentrations between individ- association with novelty-seeking. While the relationship between uals with GD and HC, being higher in the clinical group after novelty-seeking and GD severity has been previously established adjusting for sex, age, and BMI. Moreover, the SEM analysis [65, 79–81], interestingly, a previous study reported a link revealed interesting clinical correlates. Specifically, eCBs concen- between the eCB system and novelty-seeking [28]. Physiologically, trations and novelty-seeking defined a pathway associated with a the eCB system has been directly related to the balance between more severe profile among individuals with GD. Although these novelty-seeking and behavioral inhibition due to its regulation of results might preliminarily contribute to shed light on the neuro- GLU and GABA neurotransmission [82]. That is, a reduction in biological mechanisms underlying GD severity, future research is GLU transmission linked to the activation of the eCB system has warranted to further elucidate the role of the eCB system at a central been associated with decreased behavioral inhibition and level, as well as potential causality relationships. increased novelty-seeking [82–84]. AEA has been described as a primary eCB involved in the control of the excitability of striatal Supplementary material. The supplementary material for this article can be neurons through a direct depressant action at GLU synapses, found at https://doi.org/10.1192/j.eurpsy.2023.2460. while it indirectly interferes with GABA inputs regulated by 2-AG [76, 85, 86]. That said, the relationship between the eCB Acknowledgments. We thank CERCA Programme/Generalitat de Catalunya system and novelty-seeking needs to be further explored, as well as for institutional support. We also thank Instituto de Salud Carlos III (ISCIII), its association with impulsivity-related measures and severity FEDER funds/European Regional Development Fund (ERDF, a way to build in GD. Europe), and the European Social Fund (ESF investing in your future). CIBER- OBN is an initiative of ISCIII. Another important aspect to mention is that we assessed peripheral eCBs concentrations. Thus, it is possible that our results Financial support. This research was supported by grants from the Delega- reflected an altered crosstalk between central and peripheral tissues, ción del Gobierno para el Plan Nacional sobre Drogas (2021I031), Plan Nacional involving both top-down (initiated in the central nervous system) sobre Drogas Convocatoria de subvenciones para proyectos de investigación and bottom-up signaling (initiated in peripheral tissues) [87, financiados con fondos europeos 2022 (EXP2022/008847), Ministerio de Cien- 88]. Here, on the one hand, we wonder to what extent peripheral cia e Innovación (PDI2021-124887OB-I00 supported by MCIN/ AEI /10.13039/ eCBs concentrations may be driven by CB1R-dependent signaling 501100011033 and FEDER “Una manera de hacer Europa”), Instituto de Salud originated in the central nervous system and linked to changes in Carlos III (ISCIII) (FIS PI20/00132) and cofounded by FEDER funds/European neuroplasticity. On the other hand, stimuli-mediated disturbances Regional Development Fund (ERDF), a way to build Europe. CIBEROBN is an in peripheral eCBs concentrations could concurrently influence initiative of ISCIII. Additional funding was received by AGAUR-Generalitat de Catalunya (2021 SGR 00824 and 2021 SGR 00253) and European Union’s central hedonic processing. Horizon 2020 research and innovation program under grant agreement While their lipidic nature facilitates crossing the blood–brain no. 847879 (PRIME/H2020, Prevention and Remediation of Insulin Multi- barrier [15], the involvement of peripheral eCBs in the pathophysi- morbidity in Europe) and no. 101080219 (eprObes). This study has also been ology of addiction-related disorders could also be mediated by the funded by Instituto de Salud Carlos III through the grant CM21/00172 (I.B.) existence of a gut–brain–vagal axis [89]. In this respect, the origin of (cofunded by European Social Fund. ESF investing in your future). R.G. is peripheral eCBs is an unresolved issue, although some authors supported by the Catalan Institution for Research and Advanced Studies speculate a predominantly gut origin [68]. Nonetheless, the (ICREA-Academia, 2021-Programme). I.L. is supported by the Ministerio de involvement of peripheral tissues in the eCB system functioning Ciencia e Innovación (MCIN), Agencia Estatal de Investigación (AEI), and by at a central level seems more delineated for processes such as the European Union “NextGenerationEU/Plan de Recuperación, Transforma- ción y Resiliencia (PRTR)” (Juan de la Cierva-Formación program, FJC2021– feeding regulation and energy homeostasis than for reward pro- 046494-I). M.N.P. was supported by the Connecticut Council on Problem cessing beyond food [89–91]. Taking into account that CB1R is Gambling. The funders had no role in the study design, data collection and found in peripheral tissues [18], future studies are needed to analysis, decision to publish, or the preparation of the manuscript. corroborate the implication of peripheral eCBs-CBR interactions in addictive-related behaviors other than food. Moreover, it would Competing interest. F.F.-A. and S.J.-M. received consultancy honoraria from be interesting to examine whether other CBR such as CB2R may Novo Nordisk. M.N.P. has consulted for and advised Opiant Pharmaceuticals, play a role in peripheral eCBs-CBR interactions due to its high Idorsia Pharmaceuticals, Baria-Tek, AXA, Game Day Data, and the Addiction concentrations in peripheral tissues including the hematological Policy Forum; has been involved in a patent application with Yale University system [92]. and Novartis; has received research support from the Mohegan Sun Casino, https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press European Psychiatry 7 Children and Screens and Connecticut Council on Problem Gambling; has concentrations with clinical features and body mass index in eating participated in surveys, mailings, or telephone consultations related to drug disorders and obesity. Eur Psychiatry. 2023;66:1–42. doi:10.1192/j. addiction, impulse control disorders, or other health topics; and has consulted eurpsy.2023.2411. about law offices and gambling entities on issues related to impulse control, [17] Berridge KC, Robinson TE. Liking, wanting, and the incentive- internet use or addictive disorders. The other authors declared no conflicts of sensitization theory of addiction. Am Psychol. 2016;71(8):670–679. doi: interest. It is worth mentioning that none of the authors are associated with 10.1037/amp0000059. companies endeavoring to promote or develop endocannabinoid treatments for [18] Bermudez-Silva FJ, Cardinal P, Cota D. The role of the endocannabinoid mental disorders, including gambling disorder. Additionally, there are no system in the neuroendocrine regulation of energy balance. J Psychophar- patents that pertain to this subject matter, either on an individual or institutional macol. 2012;26(1):114–24. doi:10.1177/0269881111408458. basis. [19] Piomelli D. The molecular logic of endocannabinoid signalling. Nat Rev Neurosci. 2003;4(11):873–84. doi:10.1038/nrn1247. [20] Sagheddu C, Muntoni AL, Pistis M, Melis M. Endocannabinoid signaling References in motivation, reward, and addiction: Influences on mesocorticolimbic dopamine function. Int. Rev. Neurobiol. 2015;125:257–302. doi:10.1016/ [1] American Psychiatric Association (APA). Diagnostic and statistical man- bs.irn.2015.10.004. ual of mental disorders. Washington, DC: APA; 2013. [21] De Vries TJ, Schoffelmeer ANM. Cannabinoid CB1 receptors control [2] Calado F, Griffiths MD. Problem gambling worldwide: an update and conditioned drug seeking. Trends Pharmacol Sci. 2005;26(8):420–6. doi: systematic review of empirical research (2000–2015). J Behav Addict. 10.1016/j.tips.2005.06.002. 2016;5:592–613. doi:10.1556/2006.5.2016.073. [22] Bellocchio L, Lafentre P, Cannich A, Cota D, Puente N, Grandes P, et al. [3] DGOJ. Dirección General de Ordenación del Juego. Memoria Anual 2015. Bimodal control of stimulated food intake by the endocannabinoid system. Madrid: Ministerio de Hacienda y Administraciones Públicas; 2015. Nat Neurosci. 2010;13(3):281–3. doi:10.1038/nn.2494. [4] Potenza MN, Balodis IM, Derevensky J, Grant JE, Petry NM, Verdejo- [23] Moreira FA, Lutz B. The endocannabinoid system: emotion, learning and Garcia A, et al. Gambling disorder. Nat Rev Dis Prim. 2019;5:51. doi: addiction. Addict Biol. 2008;13(2):196–212. doi:10.1111/j.1369- 10.1038/s41572-019-0099-7. 1600.2008.00104.x. [5] Sharman S, Murphy R, Turner J, Roberts A. Psychosocial correlates in [24] Spanagel R. Cannabinoids and the endocannabinoid system in reward treatment seeking gamblers: differences in early age onset gamblers vs later processing and addiction: from mechanisms to interventions. Dialogues age onset gamblers. Addict Behav. 2019;97:20–6. doi:10.1016/j.addbeh.20 Clin Neurosci. 2020;22(3):241–250. doi:10.31887/DCNS.2020.22.3/ 19.05.013. RSPANAGEL. [6] Geisel O, Panneck P, Hellweg R, Wiedemann K, Müller CA. [25] Parsons LH, Hurd YL. Endocannabinoid signalling in reward and addic- Hypothalamic-pituitary-adrenal axis activity in patients with pathological tion. Nat Rev Neurosci. 2015;16(10):579–94. doi:10.1038/nrn4004. gambling and internet use disorder. Psychiatry Res. 2015;226:97–102. doi: [26] Laksmidewi AAAP, Soejitno A. Endocannabinoid and dopaminergic sys- 10.1016/j.psychres.2014.11.078. tem: the pas de deux underlying human motivation and behaviors. J [7] Geisel O, Hellweg R, Wiedemann K, Müller CA. Plasma levels of leptin in Neural Transm. 2021;128(5):615–630. doi:10.1007/s00702-021-02326-y. patients with pathological gambling, internet gaming disorder and alcohol [27] Rodríguez de Fonseca F, del Arco I, Bermudez-Silva FJ, Bilbao A, Cippitelli use disorder. Psychiatry Res. 2018;268:193–197. doi:10.1016/j.psy- A, Navarro M. The endocannabinoid system: physiology and pharmacol- chres.2018.06.042. ogy. Alcohol Alcohol. 2005;40(1):2–14. doi:10.1093/alcalc/agh110. [8] Geisel O, Banas R, Hellweg R, Müller CA. Altered serum levels of brain- [28] Van Laere K, Goffin K, Bormans G, Casteels C, Mortelmans L, De Hoon J, derived neurotrophic factor in patients with pathological gambling. Eur et al. Relationship of type 1 cannabinoid receptor availability in the human Addict Res. 2012;18:297–301. doi:10.1159/000338281. brain to novelty-seeking temperament. Arch Gen Psychiatry. 2009;66(2): [9] Pettorruso M, Zoratto F, Miuli A, De Risio L, Santorelli M, Pierotti A, et al. 196–204. doi:10.1001/archgenpsychiatry.2008.530. Exploring dopaminergic transmission in gambling addiction: A systematic [29] Fagundo AB, de la Torre R, Jiménez-Murcia S, Agüera Z, Granero R, translational review. Neurosci Biobehav Rev. 2020;119:481–511. doi: Tárrega S, et al. Executive functions profile in extreme eating/weight 10.1016/j.neubiorev.2020.09.034. conditions: from anorexia nervosa to obesity. PLoS One. 2012;7(8): [10] Navarrete F, García-Gutiérrez MS, Jurado-Barba R, Rubio G, Gasparyan e43382. doi:10.1371/journal.pone.0043382. A, Austrich-Olivares A, et al. Endocannabinoid system components as [30] Solinas M, Goldberg SR, Piomelli D. The endocannabinoid system in brain potential biomarkers in psychiatry. Front Psych. 2020;11:1–30. doi: reward processes. Br J Pharmacol. 2008;154:369–83. doi:10.1038/bjp.200 10.3389/fpsyt.2020.00315. 8.130. [11] Van Hell HH, Jager G, Bossong MG, Brouwer A, Jansma JM, Zuurman L, [31] Fagundo AB, de la Torre R, Jiménez-Murcia S, Agüera Z, Pastor A, et al. Involvement of the endocannabinoid system in reward processing in Casanueva FF, et al. Modulation of the endocannabinoids N- the human brain. Psychopharmacology (Berl). 2012;219(4):981–90. doi: arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG) 10.1007/s00213-011-2428-8. on executive functions in humans. PLoS One. 2013;8(6):e66387. doi: [12] Solinas M, Yasar S, Goldberg SR. Endocannabinoid system involvement in 10.1371/journal.pone.0066387. brain reward processes related to drug abuse. Pharmacol Res. 2007;56(5): [32] Rademacher DJ, Hillard CJ. Interactions between endocannabinoids and 393–405. doi:10.1016/j.phrs.2007.09.005. stress-induced decreased sensitivity to natural reward. Prog Neuro- [13] Fattore L, Melis M, Fadda P, Pistis M, Fratta W. The endocannabinoid Psychopharmacology Biol Psychiatry. 2007;31(3):633–41. doi:10.1016/j. system and nondrug rewarding behaviours. Exp Neurol. 2010;224(1):23– pnpbp.2006.12.013. 36. doi:10.1016/j.expneurol.2010.03.020. [33] Cota D, Steiner MA, Marsicano G, Cervino C, Herman JP, Grübler Y, et al. [14] D’Addario C, Micioni Di Bonaventura MV, Pucci M, Romano A, Gaetani Requirement of cannabinoid receptor type 1 for the basal modulation of S, Ciccocioppo R, et al. Endocannabinoid signaling and food addiction. hypothalamic-pituitary-adrenal axis function. Endocrinology. 2007;148: Neurosci Biobehav Rev. 2014;47:203–24. doi:10.1016/j.neu- 1574–81. doi:10.1210/en.2005-1649. biorev.2014.08.008. [34] Mallorquí-Bagué N, Fagundo AB, Jimenez-Murcia S, De La Torre R, [15] Luchicchi A, Pistis M. Anandamide and 2-arachidonoylglycerol: pharma- Baños RM, Botella C, et al. Decision making impairment: a shared vul- cological properties, functional features, and emerging specificities of the nerability in obesity, gambling disorder and substance use disorders? PLoS two major endocannabinoids. Mol Neurobiol. 2012;46(2):374–92. doi: One. 2016;11(9):e0163901. doi:10.1371/journal.pone.0163901. 10.1007/s12035-012-8299-0. [35] Mallorquí-Bagué N, Vintró-Alcaraz C, Verdejo-García A, Granero R, [16] Baenas I, Miranda-Olivos R, Granero R, Solé-Morata N, Sánchez I, Pastor Fernández-Aranda F, Magaña P, et al. Impulsivity and cognitive distor- A, et al. Association of anandamide and 2-arachidonoylglycerol tions in different clinical phenotypes of gambling disorder: profiles and https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press 8 Baenas et al. longitudinal prediction of treatment outcomes. Eur Psychiatry. 2019;61:9– [55] Wechsler D. Wechsler memory scale. 3rd ed. San Antonio, TX: Psychol 16. doi:10.1016/j.eurpsy.2019.06.006. Corp; 1997. [36] Agüera Z, Lozano-Madrid M, Mallorquí-Bagué N, Jiménez-Murcia S, [56] Jiménez-Murcia S, Aymamí-Sanromà M, Gómez-Pena M, Álvarez-Moya Menchón JM, Fernández-Aranda F. A review of binge eating disorder E, Vallejo J Protocols de tractament cognitivoconductual pel joc patològic i and obesity. Neuropsychiatrie. 2021;35(2):57–67. doi:10.1007/s40211- d’altres addiccions no tòxiques [Protocols of cognitive-behaviour therapy 020-00346-w. for pathological gambling and other behavioural addictions]; 2006. [37] Sloan ME, Gowin JL, Ramchandani VA, Hurd YL, Le Foll B. The endo- [57] Stata Press Publication SL. Stata statistical software: release 17; 2021. cannabinoid system as a target for addiction treatment: trials and tribu- [58] Kelley K, Preacher KJ. On effect size. Psychol Methods. 2012;17:137–52. lations. Neuropharmacology. 2017;124:73–83. doi:10.1016/j. doi:10.1037/a0028086. neuropharm.2017.05.031. [59] Barrett P. Structural equation modelling: adjudging model fit. Pers Individ [38] Cahill K, Ussher MH. Cannabinoid type 1 receptor antagonists for smok- Dif. 2007;42:815–24. doi:10.1016/j.paid.2006.09.018. ing cessation. Cochrane Database Syst Rev. 2011;2011(3):CD005353. doi: [60] Jiménez-Murcia S, Granero R, Fernández-Aranda F, Arcelus J, Aymamí 10.1002/14651858.CD005353.pub4. MN, Gómez-Peña M, et al. Predictors of outcome among pathological [39] Pastor A, Farré M, Fitó M, Fernandez-Aranda F, De La Torre R. Analysis of gamblers receiving cognitive behavioral group therapy. Eur Addict Res. ECs and related compounds in plasma: artifactual isomerization and 2015;21:169–78. doi:10.1159/000369528. ex vivo enzymatic generation of 2-MGs. J Lipid Res. 2014;55:966–77. [61] Jiménez-Murcia S, Granero R, Fernández-Aranda F, Stinchfield R, Trem- doi:10.1194/jlr.D043794. blay J, Steward T, et al. Phenotypes in gambling disorder using socio- [40] Echeburúa E, Báez C, Fernández-Montalvo J, Páez D, Baez C, Fernández- demographic and clinical clustering analysis: an unidentified new subtype? Montalvo J, et al. Cuestionario de Juego Patológico de south oaks (SOGS): Front Psychiatry. 2019;10:173. doi:10.3389/fpsyt.2019.00173. validación española. Análisis y Modif La Conduct. 1994;20:769–91. [62] Etxandi M, Baenas I, Mora-Maltas B, Granero R, Fernández-Aranda F, [41] Lesieur HR, Blume SB. The south oaks gambling screen (SOGS): a new Tovar S, et al. Are signals regulating energy homeostasis related to neuro- instrument for the identification of pathological gamblers. Am J Psych- psychological and clinical features of gambling disorder? A case–control iatry. 1987;144:1184–8. doi:10.1176/ajp.144.9.1184. study. Nutrients. 2022;14:5084. doi:10.3390/nu14235084. [42] Stinchfield R. Reliability, validity, and classification accuracy of a measure [63] Jiménez-Murcia S, Fernández-Aranda F, Mestre-Bach G, Granero R, of DSM-IV diagnostic criteria for pathological gambling. Am J Psychiatry. Tárrega S, Torrubia R, et al. Exploring the relationship between reward 2003;160:180–2. doi:10.1176/appi.ajp.160.1.180. and punishment sensitivity and gambling disorder in a clinical sample: a [43] Jiménez-Murcia S, Stinchfield R, Álvarez-Moya E, Jaurrieta N, Bueno B, path modeling analysis. J Gambl Stud. 2017;33:579–97. doi:10.1007/ Granero R, et al. Reliability, validity, and classification accuracy of a s10899-016-9631-9. Spanish translation of a measure of DSM-IV diagnostic criteria for patho- [64] Mide M, Arvidson E, Gordh AS. Clinical differences of mild, moderate, logical gambling. J Gambl Stud. 2009;25:93–104. doi:10.1007/s10899-008- and severe gambling disorder in a sample of treatment seeking patho- 9104-x. logical gamblers in Sweden. J Gambl Stud. 2023;39(3):1129–1153. doi: [44] Derogatis LR. SCL-90-R. Cuestionario de 90 Síntomas-Manual. Madrid, 10.1007/s10899-022-10183-x. Spain; 2002. [65] Jiménez-Murcia S, Giménez M, Granero R, López-González H, Gómez- [45] Derogatis LR. SCL-90-R: symptom checklist-90-R. administration, scor- Peña M, Moragas L, et al. Psychopathogical status and personality correl- ing and procedures manual—II for the revised version. Towson, MD: ates of problem gambling severity in sports bettors undergoing treatment Clinical Psychometric Research; 1994. for gambling disorder. J Behav Addict. 2022;10(3):422–434. doi: [46] Gutiérrez-Zotes JA, Bayón C, Montserrat C, Valero J, Labad A, Cloninger 10.1556/2006.2020.00101. CR, et al. Temperament and character inventory revised (TCI-R). Stand- [66] Morales I, Berridge KC. ‘Liking’ and ‘wanting’ in eating and food reward: ardization and normative data in a general population sample. Actas Esp brain mechanisms and clinical implications. Physiol Behav. 2020;227: Psiquiatr. 2004;32:8–15. 1–54. doi:10.1016/j.physbeh.2020.113152. [47] Cloninger CR. The temperament and character inventory—revised. St Louis, MO: Center for Psychobiology of Personality, Washington Univer- [67] Pataky Z, Gasteyger C, Ziegler O, Rissanen A, Hanotin C, Golay A. Efficacy sity; 1999. of rimonabant in obese patients with binge eating disorder. Exp Clin Endocrinol Diabetes 2013;121:20–6. doi:10.1055/s-0032-1329957. [48] Verdejo-García A, Lozano Ó, Moya M, Alcázar MÁ, Pérez-García M. Psychometric properties of a Spanish version of the UPPS-P impulsive [68] Gatta-Cherifi B, Cota D. Endocannabinoids and metabolic disorders. behavior scale: reliability, validity and association with trait and cognitive Endocannabinoids 2015;231:367–91. doi:10.1007/978-3-319-20825-1_13. impulsivity. J Pers Assess. 2010;92:70–7. doi:10.1080/0022389090338 [69] Monteleone P, Matias I, Martiadis V, De Petrocellis L, Maj M, Di Marzo V. 2369. Blood levels of the endocannabinoid anandamide are increased in anorexia [49] Whiteside SP, Lynam DR, Miller JD, Reynolds SK, Whiteside SP, Lynam nervosa and in binge-eating disorder, but not in bulimia nervosa. Neurop- DR, et al. Validation of the UPPS impulsive behaviour scale: a four-factor sychopharmacology. 2005;30:1216–21. doi:10.1038/sj.npp.1300695. model of impulsivity. Eur J Pers. 2005;19:559. doi:10.1002/per.556. [70] Engeli S. Dysregulation of the endocannabinoid system in obesity. J [50] Wolz I, Agüera Z, Granero R, Jiménez-Murcia S, Gratz KL, Menchón JM, Neuroendocrinol. 2008;20:110–5. doi:10.1111/j.1365-2826.2008.01683.x. et al. Emotion regulation in disordered eating: psychometric properties of [71] Ceccarini J, Hompes T, Verhaeghen A, Casteels C, Peuskens H, Bormans the difficulties in emotion regulation scale among Spanish adults and its G, et al. Changes in cerebral CB1 receptor availability after acute and interrelations with personality and clinical severity. Front Psychol. 2015;6: chronic alcohol abuse and monitored abstinence. J Neurosci. 2014;34(8): 907. doi:10.3389/fpsyg.2015.00907. 2822–31. doi:10.1523/JNEUROSCI.0849-13.2014. [51] Gratz KL, Roemer L. Multidimensional assessment of emotion regulation [72] Monteleone AM, Di Marzo V, Monteleone P, Dalle Grave R, Aveta T, El and dysregulation: development, factor structure, and initial validation of Ghoch M, et al. Responses of peripheral endocannabinoids and the difficulties in emotion regulation scale. J Psychopathol Behav Assess. endocannabinoid-related compounds to hedonic eating in obesity. Eur J 2004;26:41–54. doi:10.1023/B:JOBA.0000007455.08539.94. Nutr. 2016;55:1799–805. doi:10.1007/s00394-016-1153-9. [52] Grant DA, Berg E. A behavioral analysis of degree of reinforcement and [73] Gatta-Cherifi B. Neurobiology of food intake. Médecine Des Mal Méta- ease of shifting to new responses in a Weigl-type card-sorting problem. J boliques. 2012. doi:10.1016/S1957-2557(12)70372-3. Exp Psychol. 1948. doi:10.1037/h0059831. [74] Lanz C, Mattsson J, Stickel F, Dufour JF, Brenneisen R. Determination of [53] Golden CJ. Stroop color and word test: a manual for clinical and experi- the endocannabinoids anandamide and 2-arachidonoyl glycerol with gas mental uses. Chicago: Stoelting; 1978. chromatography-mass spectrometry: analytical and preanalytical chal- [54] Reitan RM. Validity of the trail making test as an indicator of organic brain lenges and pitfalls. Med Cannabis Cannabinoids. 2018;1(1):9–18. doi: damage. Percept Mot Skills. 1958. doi:10.2466/pms.1958.8.3.271. 10.1159/000489032. https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press European Psychiatry 9 [75] Matias I, Di Marzo V. Endocannabinoids and the control of energy performance by NMDA receptor in the rat prefrental cortex. Neuropsycho- balance. Trends Endocrinol Metab. 2007;18(1):27–37. doi:10.1016/j. pharmacology. 2004;29:1637–47. doi:10.1038/sj.npp.1300479. tem.2006.11.006. [84] Floresco SB, Tse MTL, Ghods-Sharifi S. Dopaminergic and glutama- [76] Maccarrone M, Rossi S, Bari M, De Chiara V, Fezza F, Musella A, et al. tergic regulation of effort- and delay-based decision making. Neu- Anandamide inhibits metabolism and physiological actions of ropsychopharmacology. 2008;33(8):1966–79. doi:10.1038/sj. 2-arachidonoylglycerol in the striatum. Nat Neurosci. 2008;11(2):152–9. npp.1301565. doi:10.1038/nn2042. [85] Gubellini P, Picconi B, Bari M, Battista N, Calabresi P, Centonze D, et al. [77] Ceccarini J, Casteels C, Koole M, Bormans G, Van Laere K. Transient Experimental parkinsonism alters endocannabinoid degradation: impli- changes in the endocannabinoid system after acute and chronic ethanol cations for striatal glutamatergic transmission. J Neurosci. 2002;22(16): exposure and abstinence in the rat: a combined PET and microdialysis 6900–7. doi:10.1523/jneurosci.22-16-06900.2002. study. Eur J Nucl Med Mol Imaging. 2013;40(10):1582–94. doi:10.1007/ [86] Gerdeman GL, Ronesi J, Lovinger DM. Postsynaptic endocannabinoid s00259-013-2456-1. release is critical to long-term depression in the striatum. Nat Neurosci. [78] Li H, Chen R, Zhou Y, Wang H, Sun L, Yang Z, et al. Endocannabinoids 2002;5(5):446–51. doi:10.1038/nn832. regulate cocaine-associated memory through brain AEA–CB1R signalling [87] Berner LA, Brown TA, Lavender JM, Lopez E, Wierenga CE, Kaye WH. activation. Mol Metab. 2022;65:101597. doi:10.1016/j.molmet.2022. Neuroendocrinology of reward in anorexia nervosa and bulimia nervosa: 101597. beyond leptin and ghrelin. Mol Cell Endocrinol. 2018;497:110320. doi: [79] Granero R, Fernández-Aranda F, Mestre-Bach G, Steward T, García- 10.1016/j.mce.2018.10.018. Caro B, Prever F, et al. Clustering of treatment-seeking women with [88] Kessler RM, Hutson PH, Herman BK, Potenza MN. The neurobiological gambling disorder. J Behav Addict. 2018;7:770–80. doi:10.1556/2006. basis of binge-eating disorder. Neurosci Biobehav Rev. 2016;63:223–38. 7.2018.93. doi:10.1016/j.neubiorev.2016.01.013. [80] Mestre-Bach G, Steward T, Granero R, Fernández-Aranda F, Talón- [89] Berland C, Castel J, Terrasi R, Montalban E, Foppen E, Martin C, et al. Navarro MT, Cuquerella À, et al. Sociodemographic and psychopatho- Identification of an endocannabinoid gut-brain vagal mechanism control- logical predictors of criminal behavior in women with gambling disorder. ling food reward and energy homeostasis. Mol Psychiatry. 2022;27:2340– Addict Behav. 2018;80:124–129. doi:10.1016/j.addbeh.2018.01.022. 54. doi:10.1038/s41380-021-01428-z. [81] Pettorruso M, Testa G, Granero R, Martinotti G, d’Andrea G, di Gian- [90] Osei-Hyiaman D, DePetrillo M, Pacher P, Liu J, Radaeva S, Bátkai S, et al. nantonio M, et al. The transition time to gambling disorder: the roles that Endocannabinoid activation at hepatic CB1 receptors stimulates fatty acid age, gambling preference and personality traits play. Addict Behav. 2021; synthesis and contributes to diet-induced obesity. J Clin Invest 2005;115: 116:106813. doi:10.1016/j.addbeh.2020.106813. 1298–305. doi:10.1172/JCI200523057. [82] Lafenêtre P, Chaouloff F, Marsicano G. Bidirectional regulation of [91] Satta V, Scherma M, Piscitelli F, Usai P, Castelli MP, Bisogno T, et al. novelty-induced behavioral inhibition by the endocannabinoid system. Limited access to a high fat diet alters endocannabinoid tone in female rats. Neuropharmacology. 2009;57(7-8):715–21. doi:10.1016/j.neuro- Front Neurosci. 2018;12:1–12. doi:10.3389/fnins.2018.00040. pharm.2009.07.014. [92] Pagotto U, Marsicano G, Cota D, Lutz B, Pasquali R. The emerging role of [83] Carli M, Baviera M, Invernizzi RW, Balducci C. Erratum: the serotonin the endocannabinoid system in endocrine regulation and energy balance. 5-HT2A receptors antagonist M100907 prevents impairment in attentional Endocr Rev. 2006;27(1):73–100. doi:10.1210/er.2005-0009. https://doi.org/10.1192/j.eurpsy.2023.2460 Published online by Cambridge University Press