Plasma concentration of leptin is related to food addiction in gambling disorder: Clinical and neuropsychological implications Journal of Behavioral MIKEL ETXANDI1,2,3 , ISABEL BAENAS1,3,4,5 , Addictions BERNAT MORA-MALTAS1,3,5 , ROSER GRANERO4,5,6 , 12 (2023) 4, 1019–1031 FERNANDO FERNÁNDEZ-ARANDA1,4,5,7 , SULAY TOVAR4,8 , NEUS SOLÉ-MORATA1 , DOI: 10.1556/2006.2023.00051 IGNACIO LUCAS1,4,5 , SABELA CASADO4,8 , © 2023 The Author(s) MÓNICA GÓMEZ-PEÑA1,5 , LAURA MORAGAS1,5 , AMPARO DEL PINO-GUTIÉRREZ4,5,9 , JAVIER TAPIA1,3,5,10 , EDUARDO VALENCIANO-MENDOZA1 , MARC N. POTENZA11,12,13,14,15 , ASHLEY N. GEARHARDT16 , CARLOS DIÉGUEZ4,8 and SUSANA JIMÉNEZ-MURCIA1,4,5,7p FULL-LENGTH REPORT 1 Clinical Psychology Unit, Bellvitge University Hospital, Barcelona, Spain 2 Department of Psychiatry, Hospital Universitari Germans Trias i Pujol, IGTP Campus Can Ruti, Badalona, Spain 3 Doctoral Program in Medicine and Translational Research, University of Barcelona (UB), Barcelona, Spain 4 Ciber Physiopathology of Obesity and Nutrition (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain 5 Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Programme, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain 6 Department of Psychobiology and Methodology, Autonomous University of Barcelona, Barcelona, Spain 7 Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain 8 Department of Physiology, CIMUS, University of Santiago de Compostela, Instituto de Investigación Sanitaria, Santiago de Compostela, Spain 9 Department of Public Health, Mental Health and Perinatal Nursing, School of Nursing, University of Barcelona, Barcelona, Spain 10 Medical Direction of Ambulatory Processes, South Metropolitan Territorial Management, Bellvitge University Hospital, Barcelona, Spain 11 Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA 12 Child Study Center, Yale University School of Medicine, New Haven, CT, USA 13 Connecticut Mental Health Center, New Haven, CT, USA 14 Connecticut Council on Problem Gambling, Wethersfield, CT, USA 15 Department of Neuroscience, Yale University, New Haven, CT, USA 16 Department of Psychology, University of Michigan, Ann Arbor, USA Received: May 2, 2022 • Revised manuscript received: July 25, 2023 • Accepted: September 3, 2023 Published online: October 17, 2023 p Corresponding author. E-mail: sjimenez@bellvitgehospital.cat ABSTRACT Background: Data implicate overlaps in neurobiological pathways involved in appetite regulation and addictive disorders. Despite different neuroendocrine measures having been associated with both Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1020 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 gambling disorder (GD) and food addiction (FA), how appetite- (Hebebranda et al., 2014), while others propose a substance- regulating hormones may relate to the co-occurrence of both en- based addiction model (Fernandez-Aranda, Karwautz, & tities remain incompletely understood. Aims: To compare plasma Treasure, 2018; Schulte, Avena, & Gearhardt, 2015). The concentrations of ghrelin, leptin, adiponectin, and liver-expressed latter model suggests that some foods, especially palatable antimicrobial peptide 2 (LEAP-2) between patients with GD, with ones with large amounts of processed sugars and fats, may and without FA, and to explore the association between circulating lead to overeating and addictive-like behaviors by activating hormonal concentrations and neuropsychological and clinical fea- tures in individuals with GD and FA. Methods: The sample brain reward pathways, in a similar way to what occurs in included 297 patients diagnosed with GD (93.6% males). None of SUDs (Gearhardt, Phil, & Corbin, 2011; Schulte et al., 2015). the patients with GD had lifetime diagnosis of an eating disorder. Moreover, many clinical and neurobiological similarities FA was evaluated with the Yale Food Addiction Scale 2.0. All pa- have been identified between FA and addictive disorders, tients were assessed through a semi-structured clinical interview such as an excessive preoccupation and desire for rewarding and a psychometric battery including neuropsychological tasks. consumption, the development of tolerance and abstinence, Blood samples to measure hormonal variables and anthropometric and difficulties decreasing consumption despite negative variables were also collected. Results: From the total sample, FA was consequences (Fletcher & Kenny, 2018; Gearhardt, Phil, & observed in 23 participants (FAþ) (7.7% of the sample, 87% males). Corbin, 2011; Pursey, Contreras-Rodriguez, Collins, Stan- When compared participants with and without FA, those with FAþ well, & Burrows, 2019; Volkow, Wang, Fowler, Tomasi, & presented both higher body mass index (BMI) (p < 0.001) and leptin Baler, 2012). Some authors have raised concerns regarding concentrations, after adjusting for BMI (p 5 0.013). In patients with FA, leptin concentrations positively correlated with impulsivity, the diagnostic overlap between binge eating disorder (BED), poorer cognitive flexibility, and poorer inhibitory control. Other an eating disorder (ED) characterized by recurrent episodes endocrine measures did not differ between groups. Discussion and of bingeing in the absence of compensatory behaviors and conclusions: The present study implicates leptin in co-occurring FA, although recent studies provide evidence supporting GD and FA. Among these patients, leptin concentration has been that they are separate entities, which reflect different clinical associated with clinical and neuropsychological features, such as situations (di Giacomo et al., 2022). impulsivity and cognitive performance in certain domains. Along these lines, previous work has suggested a po- tential association between FA and GD (Etxandi et al., 2021; Jiménez-Murcia et al., 2017). The prevalence of FA in pa- KEYWORDS tients with GD has been estimated at around 7.8% (Granero gambling disorder, food addiction, leptin, impulsivity, addictive behaviors et al., 2018), and co-occurrence between GD and FA has been related to specific clinical features in individuals with GD, such as higher body mass index (BMI), more psycho- pathology, and elevated harm avoidance (Etxandi et al., INTRODUCTION 2021). Moreover, some works hypothesized that the co- morbidity with FA could be associated with gambling pat- Gambling disorder (GD) is classified as a behavioral terns indicative of more protracted or severe GD, which addiction in the Diagnostic and Statistical Manual of Mental makes its study of special interest to identify possible pre- Disorders, Fifth Edition (DSM-5) (APA, 2013). It is char- ventive and early detection strategies (Etxandi et al., 2021). acterized by a recurrent and maladaptive gambling behavior, Interestingly, one area of recent attention when studying impaired control and increasing priority given to gambling, the neurobiology of addictive disorders involves neurohor- as well as continuation or escalation of gambling despite the monal systems implicated in appetite regulation, with such occurrence of negative consequences in different domains of systems linked to brain reward pathways (Etxandi et al., patients’ daily lives (Potenza et al., 2019). GD shares clinical 2022; Iovino et al., 2022). Among endocrine factors involved and etiological aspects with substance use disorders (SUDs), in the reward circuit, ghrelin (an appetite stimulating hor- including neurobiological features (Griffiths, 2017; Linnet, mone) has been shown to be a neural reinforcer for both 2020; Solé-Morata et al., 2022). natural (e.g., food) and non-natural (e.g., money) rewards, Although food addiction (FA) is not currently recog- which influences dopamine signaling in brain areas related nized as a formal diagnostic entity, the concept has been to reward processing (e.g., mesolimbic regions) (Farokhnia supported through clinical and biological studies (Gear- et al., 2018; Vengeliene, 2013). The liver-expressed antimi- hardt, Davis, Kuschner, & Brownell, 2011). This construct crobial peptide 2 (LEAP-2) is a recently described endocrine may in part explain high and rising rates of obesity in factor involved in appetite regulation that antagonizes the contemporary society that might relate to addictive prop- effects of ghrelin (Ge et al., 2018; Lugilde et al., 2022). erties of food promoting the consumption of densely caloric, Although there is currently less evidence of its involvement hyperpalatable, inexpensive, processed foods (Gearhardt, in addictive disorders, it has been related to impulsivity Grilo, Dileone, Brownell, & Potenza, 2011). However, there (Voigt et al., 2021), which has been linked to addictions is a lack of consensus regarding some aspects of this including GD (Brewer & Potenza, 2008). Other endocrine construct, such as the most appropriate conceptual factors such as adipocytokines (i.e., leptin and adiponectin) framework to explain FA (Gearhardt & Hebebrand, 2021; produced by adipose tissue have also been studied in relation Treasure, Leslie, Chami, & Fernández-Aranda, 2018). to addictive disorders (Escobar et al., 2018; Housová et al., There are authors who define FA as addictive-like eating 2005; Novelle & Diéguez, 2018). Leptin is an important Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1021 peripheral signal regulating food intake, with appetite-sup- METHODS pressing functions and circulating concentrations related to BMI (Hellström et al., 2004). Both leptin and adiponectin Participants have also been linked to impulsivity (Sutin et al., 2013) and craving in SUDs (Hillemacher et al., 2009; Martinotti et al., The sample consisted of n 5 297 seeking-treatment outpa- 2017). Noticeably, these endocrine factors linked to SUDs tient adults with GD. Participants were mostly male (n 5 have prompted investigations in behavioral addictions 278, 93.6%) and with a mean age of 39.58 years (SD 5 such as GD (Geisel, Hellweg, Wiedemann, & Müller, 2018). 14.16). They were voluntarily recruited from April 2018 to A recent case-control study described an increase in ghrelin September 2021 at the Behavioral Addictions Unit within concentrations, but a decrease in LEAP-2 and adiponectin the Clinical Psychology Unit of Bellvitge University Hospital in individuals with versus without GD, after adjusting for (Barcelona, Spain). All patients had a diagnosis of GD ac- BMI (Etxandi et al., 2022). cording to DSM-5 criteria (APA, 2013). None of them Regarding neurobiological correlates of FA, prior efforts presented a lifetime ED, which constituted an exclusion have explored possible endocrine alterations (Leigh & criteria together with the presence of an organic mental Morris, 2018). Both ghrelin and leptin may play a significant disorder, an intellectual disability, a neurodegenerative dis- role in FA (Piccinni et al., 2021). On the one hand, ghrelin order (such as Parkinson’s disease), or an active psychotic signaling has been suggested as a key regulator of obesity, disorder. and higher concentrations have been associated with increased food craving and consumption (Lopez-Aguilar, Measures Ibarra-Reynoso, & Malacara, 2018). It has also been hy- pothesized that higher fasting leptin concentrations may Hormonal assays. Peripheral blood samples were collected underlie excessive food intake (Miller et al., 2014). FA has by venous aspiration with ethylenediamine tetraacetic acid been associated with lower leptin concentrations in adoles- (EDTA) (25 mM final concentration), obtained at 9 am cents with normal weight whereas with higher leptin con- after at least 8 h of overnight fasting. Blood was centrifuged centrations in individuals with overweight (Peters et al., at 1,700 g in a refrigerated (48C) centrifuge for 20 min. The 2018). The authors hypothesized that the negative associa- plasma was immediately separated from the serum and tion between leptin concentrations and FA under normal- stored at 808C until analysis. Parameter determinations weight conditions could be explained by a stronger sense of were conducted using commercial kits according to the hunger and a greater propensity for overeating in these in- manufacturer’s instructions and in a single analysis to dividuals, which could have led to greater FA severity. In reduce inter-assay variability. Quantitative plasma LEAP-2 individuals with overweight, high circulating leptin con- measurement was performed using a commercial enzyme- centrations may reflect leptin resistance, in which the failure linked immunosorbent assay (ELISA) kit (Human LEAP-2 of leptin-level-induced feeding suppression may lead to the ELISA kit, Phoenix Pharmaceuticals, Inc), previously vali- development of FA (Peters et al., 2018; Yu, Fernandez, dated (Barja-Fernández et al., 2021; Mani et al., 2019). Meng, Zhao, & Groth, 2021). Intraassay and interassay coefficients of variation were To the best of our knowledge, no previous studies have <10% and <15%, respectively. The sensitivity limit of the investigated hormonal factors in the co-occurrence of FA and assay was 0.15 ng/mL. Total ghrelin (pg/mL) was measured a behavioral addiction such as GD. The main aim of the using an ELISA kit (Invitrogen-Thermofisher scientific) for present study was to explore whether there were differences in the detection of human ghrelin, with a specificity of 100%. plasma concentrations of hormones involved in appetite The intra-assay variation coefficient was <6%, and the regulation (namely ghrelin, LEAP-2, adiponectin, and leptin) inter-assay variation coefficient <8.5%. The sensitivity in a sample of patients diagnosed with GD, with and without limit of the assay was 11.8 pg/mL (Pena-Bello et al., 2015). FA. Moreover, we aimed to explore correlates between con- Plasma adiponectin (ng/mL) and leptin (ng/mL) were centrations of any implicated hormones and clinical and measured using a solid-phase sandwich ELISA kit (Invi- neuropsychological variables in the subgroup with FA. These trogen-Thermofisher scientific) with a specificity of 100%. included measures of cognitive domains described as core The intraassay and interassay coefficients of variation were features in well-known neuroscientific models of addiction <4% and <5%, respectively, and the assay sensitivity limit was and especially related to impulse control, that we hypothe- 100 pg/mL for adiponectin and <3.5 pg/mL for leptin. sized to co-occur in GD and FA, such as prefrontally medi- Each sample’s absorbance was measured in duplicate using ated executive functions (i.e., cognitive flexibility, inhibitory a microplate spectrophotometric reader at a wavelength of control, decision making, working memory, attention, and 450 nm (Epoch 2 microplate reader, Biotek Instruments, Inc). set-shifting) (Bechara & Van Der Linden, 2005; Blaszczynski & Nower, 2002; Mallorquí-Bagué et al., 2018; van Timmeren, Neuropsychological variables. Vocabulary subtest of the Daams, van Holst, & Goudriaan, 2018). We hypothesized that Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III) circulating concentrations of appetite-regulating hormones (Wechsler, 1999): The WAIS-III involves defining words of would differ between GD patients with and without FA, with increasing difficulty presented orally. It was used to assess levels of implicated hormones correlating with impulsivity vocabulary expression, as a measure of estimated intelligence measures in the FA subgroup. (De Oliveira, Nitrini, Yassuda, & Brucki, 2014). Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1022 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 Iowa Gambling Task (IGT) (Bechara, Damasio, Damasio, does not match the written name. Three final scores are & Anderson, 1994, 2000): The IGT is a computerized task for obtained based on the number of items the participant can evaluating risk-/reward-based and punishment-influenced read on each of the three lists within 45 seconds. The SCWT decision-making. Participants must select 100 cards from assesses cognitive interference, which occurs when the pro- four decks of cards (i.e., A, B, C, and D) and, after each card cessing of one stimulus feature affects the simultaneous selection, either a monetary gain or a loss is obtained. The processing of another attribute. participants are told that the ultimate goal of the task is to win as much money as possible. The test is scored by sub- Clinical variables. Yale Food addiction Scale 2.0 (YFAS 2.0) tracting the number of cards selected from decks A and B (Gearhardt, Corbin, & Brownell, 2016): The YFAS 2.0 from the number of cards selected from decks C and D. consists of a self-report scale for assessing FA based on 11 Whereas decks A and B are not advantageous, since the final symptoms related to SUDs that are adapted to the context of loss is greater than the final gain, decks C and D are ad- food consumption. The YFAS 2.0 consists of 35 items and vantageous since the penalties are smaller (as are the re- produces two measurements: (1) a continuous symptom wards). Higher scores indicate better performance, while count score that reflects the number of diagnostic criteria negative scores reflect more choices from disadvantageous met (from 0 to 11), and (2) a binary measure (present vs. decks. The test score for each block (IGT-1, 2, 3, 4, and 5) is absent) that is based on the number of symptoms (at least 2) calculated by subtracting the number of choices from and self-reported clinical distress or impairment. In addi- disadvantageous decks to the number of choices from ad- tion, it also provides severity thresholds: mild (2-3 symp- vantageous decks draws. The total task score (IGT-Total) is toms), moderate (4-5 symptoms) and severe (6-11 obatined by adding the scores of the five blocks. The learning symptoms). The Spanish validation of the YFAS-2 (Granero score (IGT-Learning) measures the differences between the et al., 2018) generated an internal consistency of Cronbach’s two first blocks (where the participant has not learned which alpha (α) 5 0.94. The internal consistency of our sample was decks are advantageous and disadvantageous) and the two α 5 0.97. last blocks (where the participant could have already detected South Oaks Gambling Screen (SOGS) (Lesieur & Blume, which decks involve a risky choice and then, the experience 1987): The SOGS includes 20 items for the identification of gained through the trial can produce changes in choice problem gambling and associated negative consequences. patterns). Additionally, the risk score (IGT-Risk) is measured Total scores obtained as the summation of the items have considering the scores from the two last blocks. been used as a measure of problem-gambling severity, with a Wisconsin Card Sorting Test (WCST) (Grant & Berg, score of five or more reflecting “probable pathological 1948): The WCST evaluates cognitive flexibility. It is gambling." The Spanish validation of the scale showed very comprised of four types of stimulus cards and 128 response good psychometric results in the adaptation study (test- cards that show different shapes, colors, and numbers of fig- retest reliability R 5 0.98, internal consistency α 5 0.94 and ures on each one. Participants must match the response cards convergent validity R 5 0.92) (Echeburúa, Baez, Fernández- to the stimulus cards in a way that seems justifiable to them Montalvo, & Páez, 1994). The internal consistency for this before they receive feedback (i.e., correct or incorrect). After scale in the study sample was α 5 0.74. ten correct consecutive responses, the categorization criteria Diagnostic Questionnaire for Pathological Gambling Ac- change. Total trials, total errors, perseverative errors and cording to DSM criteria (Stinchfield, 2003): Spanish adap- non‐perseverative errors, the number of complete categories, tation (Jiménez-Murcia et al., 2009). This instrument is a conceptual, and trials to complete first category are recorded. self-report questionnaire containing 19 items coded on a Trail Making Test (TMT) (Reitan, 1958): TMT part A binary scale (yes-no), which is used for the diagnosis of GD consists of 25 circles on a piece of paper with the numbers 1 according to the DSM-IV-TR (APA, 2000). This question- to 25 written randomly in each. The person is tasked naire has been updated according to DSM-5 (APA, 2013) with drawing a line from one circle to the next in ascending criteria. The internal consistency of this scale in the study numerical order, from 1 to 25, as quickly as possible. The sample was α 5 0.80. lines between the circles are referred to as the “trail.” For part Symptom Checklist-90-Revised (SCL-90-R) (Derogatis, B, the dots go from 1 to 13 and include letters from A to L. As 1994): The SCL-90-R is a self-report questionnaire of 90 in the first part, the person must connect the dots in order items that assesses a broad range of psychological problems while alternating letters and numbers, as in 1-A-2-B-3-C…, and psychopathology, based on nine primary symptom di- in the shortest time possible without lifting the pen from the mensions (Somatization, Obsessive-Compulsion, Interper- paper. The task assesses visual conceptual and visual-motor sonal Sensitivity, Depression, Anxiety, Hostility, Phobic tracking, entailing motor speed, attention, and the capacity to Anxiety, Paranoid Ideation, and Psychoticism). Three global alternate between cognitive categories (set‐shifting). Each part indexes are included (global severity index, positive symp- is scored according to the time spent to complete the task. tom distress index and total positive symptom). The vali- Stroop Color and Word Test (SCWT) (Golden, 1978): dation of the scale in the Spanish population (Derogatis, The SCWT consists of three separate lists. First, a word list 2002) showed a mean internal consistency of α 5 0.75. The contains the names of colors in black ink. Then, a color list internal consistency in the study was α 5 0.98. includes the letter "X" printed in different colors. Lastly, a Temperament and Character Inventory-Revised (TCI-R) color word list consisting of color names in a color ink that (Cloninger, 1999): The TCI-R is a 240-item questionnaire Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1023 scored on a 5-point Likert scale that measures personality Spain). Finally, in a third session, the psychological assess- features derived from three character dimensions (Self- ment was performed by an experienced neuropsychologist Directedness, Cooperativeness, and Self-Transcendence) and for 60 min. We also administered the WAIS-III (Wechsler four temperament dimensions (Harm Avoidance, Novelty et al., 1999) vocabulary subtest as a measure of estimated Seeking, Reward Dependence and Persistence). Evaluation intelligence (Lezak et al., 2004). All measures used in this of the Spanish revised version (Gutiérrez-Zotes et al., 2004) study correspond to the evaluation done prior to the had an internal consistency of α 5 0.87. This questionnaire beginning of specialized treatment in our Unit. was administered in its Spanish adaptation, in which the original author participated (Gutiérrez-Zotes et al., 2004). Statistical analysis The internal consistency in the study was between α 5 0.70 Statistical analysis was performed with Stata17 for Windows (Novelty Seeking) and α 5 0.88 (Persistence). (Stata-Corp, 2021). Comparison of socio-demographic and Impulsive Behavior (UPPS-P) (Whiteside, Lynam, Miller, gambling-related problems between the YFAS 2.0 positive & Reynolds, 2005). Through 59 self-report items, the UPPS- versus negative screening groups was done with chi-square P assesses five aspects of impulsive behavior: negative ur- tests (χ2) for categorical data and T-tests for quantitative gency; positive urgency; lack of premeditation; lack of data. For these models, effect sizes of relationships were perseverance; and sensation-seeking. The Spanish validation measured with Cohen’s-h and Cohen’s-d coefficients, of the UPPS-P demonstrated good reliability (Cronbach’s α interpreting mild-moderate effect sizes for values above 0.50 between 0.79 and 0.93) and external validity (Verdejo-Gar- and less than 0.80 and high-large effect size for values above cía, Lozano, Moya, Alcázar, & Pérez-García, 2010). The 0.80 (Kelley & Preacher, 2012). internal consistency in the study varied between α 5 0.80 Comparisons of hormonal measures between groups were (lack of perseverance) and α 5 0.93 (positive urgency). performed with analysis of covariance (ANCOVA), adjusting Difficulties in Emotion Regulation Strategies (DERS) for sex, age, and BMI. The association between leptin con- (Gratz & Roemer, 2004). The DERS is a self-reported centrations and clinical and neuropsychological variables was 36-item scale that assesses emotion dysregulation. The scale assessed through partial correlation coefficients, adjusted for is divided into six subscales (non-acceptance of emotional sex, age, BMI, and WAIS-vocabulary scores, the latter used to responses, difficulties in performing goal-directed behaviors adjust the between-group comparisons for estimated intelli- when experiencing strong emotions, difficulties in control- gence. Given the relationship between the significance of ling impulses, lack of emotional awareness, limited access to correlations with sample sizes (small coefficients can achieve emotion regulation strategies, and lack of emotional clarity). highly significant p-values in large samples, and vice versa), The participants are asked to answer each item using a five- correlation values with size |R|>0.24 (medium-moderate point Likert scale ranging from 1 (almost never) to 5 (almost effect size) or |R| (large-high effect size) were considered always). Higher scores suggest greater problems in emotion relevant in this study (Rosnow, 1996). regulation. The instrument has been validated in the Spanish This study used Finner’s procedure for controlling the population (Hervás & Jódar, 2008). The internal consistency increase in the Type-I error due to the use of multiple sta- of the DERS total score in our sample was α 5 0.92. tistical comparisons. This procedure is sustained by the Other variables. Additional data (e.g., socio-demographic, familywise error rate stepwise multiple method, and it is and socio-economic, anthropometric variables, and GD- aimed to adjust significance levels (p-values) by controlling related characteristics) were collected in a semi-structured for the probability that the statistical tests make at least k face-to-face clinical interview, as described elsewhere false rejections (Finner & Roters, 2001). (Jiménez-Murcia, Aymamí-Sanromà, Gómez-Pena, Álvarez- Ethics Moya, & Vallejo, 2006). The latest version of the Declaration of Helsinki guided Procedure conduct in the present study. The Clinical Research Ethics Committee of Bellvitge University Hospital approved this The participants were assessed at the Behavioral Addictions study (ref. PR329/19 and PR338/17), as part of the scientific Unit of the Clinical Psychology Unit of Bellvitge University production within national and competitive research pro- Hospital (Barcelona, Spain). A multidisciplinary team jects developed by our research group (RTI2018-101837-B- (psychology, psychiatry, and nursing) with more than 15 I00; 2019I47). Signed informed consent was obtained from years of experience in the field of GD and other behavioral all participants. addictions conducted the evaluation and data collection. In a first session, a comprehensive semi-structured clinical interview was performed, focusing on gambling behaviors. RESULTS Moreover, lifetime ED was also assessed. In a second session, the psychometric evaluation and the extraction of biological Descriptive for the sample samples took place. The biological samples were subse- quently analyzed at the Singular Center for Research in Most participants in the study were single (53.2%), men Molecular Medicine and Chronic Diseases (CIMUS), Uni- (93.6%), with low education levels (52.9%), and of low social versity of Santiago de Compostela (Santiago de Compostela, status (44.8%). The mean age was 39.6 years old (SD 5 Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1024 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 14.2), mean age of onset of the gambling problems 29.1 years The results of the ANCOVA comparing ghrelin, LEAP-2, old (SD 5 12.4), and mean duration of gambling problems leptin, and, adiponectin concentrations between patients 5.23 years (SD 5 6.0). The percentage of patients who re- with and without FA evidenced differences for the leptin ported non-strategic gambling preference was 49.8%, while values (higher mean concentrations among the FA þ group) 31.0% reported strategic, and 19.2% both non-strategic and (see Table 2 and Fig. 1, with the radar chart). strategic gambling. The prevalence of patients with The ANCOVA procedure with the comparison of the gambling-related debts was 58.9%. clinical profiles between patients with and without FA is showed in Table S1 (supplementary material). Differences between groups were found for the psychopathological Comparison of the measures between FA groups state (higher SCL-90R mean scores in the FA þ group), A small percentage (7.7%) of the sample met criteria for FA. and the emotion regulation capacity (higher scores in Table 1 presents sociodemographic and GD variables strat- DERS among the FAþ group, showing concretely diffi- ified by FA status, with significant differences in the SOGS culties engaging in goal-directed behaviors, limited access total score and the BMI levels (higher means among patients to emotion regulation strategies, lack of emotional clarity, with FA þ group). and higher total score). Table 1. Comparison between the groups for the sociodemographic and the GD profiles Total (n 5 297) FA (n 5 274) FAþ (n 5 23) n % n % n % p |h| Sex Women 19 6.4% 16 5.8% 3 13.0% 0.175 0.25 Men 278 93.6% 258 94.2% 20 87.0% Education Primary 157 52.9% 143 52.2% 14 60.9% 0.160 0.18 Secondary 112 37.7% 107 39.1% 5 21.7% 0.38 University 28 9.4% 24 8.8% 4 17.4% 0.26 Marital Single 158 53.2% 146 53.3% 12 52.2% 0.074 0.02 Married 103 34.7% 98 35.8% 5 21.7% 0.31 Divorced 36 12.1% 30 1.9% 6 26.1% 0.40 Social index High 8 2.7% 7 2.6% 1 4.3% 0.875 0.10 Mean-high 19 6.4% 18 6.6% 1 4.3% 0.10 Mean 24 8.1% 23 8.4% 1 4.3% 0.17 Mean-low 113 38.0% 105 38.3% 8 34.8% 0.07 Low 133 44.8% 121 44.2% 12 52.2% 0.16 Mean SD Mean SD Mean SD p |d| Age (years-old) 39.58 14.16 39.44 14.15 41.26 14.45 0.554 0.13 Age of onset of GD (years) 29.10 12.42 28.80 12.37 32.74 12.69 0.144 0.31 Duration of GD (years) 5.23 6.02 5.24 6.11 5.04 4.88 0.880 0.04 DSM-5 criteria 7.13 1.80 7.09 1.82 7.70 1.40 0.119 0.37 SOGS total 10.85 3.23 10.74 3.17 12.13 3.73 0.048p 0.40 n % n % n % p |h| Preference Non-strategic 148 49.8% 139 5.7% 9 39.1% 0.551 0.23 Strategic 92 31.0% 83 3.3% 9 39.1% 0.19 Mixed 57 19.2% 52 19.0% 5 21.7% 0.07 Debts due to the GD No 122 41.1% 113 41.2% 9 39.1% 0.843 0.04 Yes 175 58.9% 161 58.8% 14 60.9% Mean SD Mean SD Mean SD p |d| Body mass index (Kg/m ) 2 26.48 5.04 25.99 4.37 32.34 8.15 <0.001 p 0.97† Note. GD: gambling disorder. SD: standard deviation. FA: food addiction negative screening group. FAþ: food addiction positive screening group. p Bold: significant comparison. †Bold: effect size into the ranges mild-moderate to high-large. Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1025 Table 2. Comparison of hormonal measures: ANCOVA (adjusted by sex, age, and BMI) Total (n 5 297) FA (n 5 274) FAþ (n 5 23) YFAS-total Mean SD Mean SD Mean SD p |d| R Ghrelin (pg/mL) 941.59 753.26 945.03 758.78 938.15 643.10 0.967 0.01 0.006 LEAP-2 (ng/mL) 5.26 2.88 5.31 2.87 5.21 3.09 0.661 0.03 0.007 Leptin (ng/mL) 10.05 7.85 7.88 7.42 12.23 10.47 0.013p 0.52† 0.106 Adiponectin (ng/mL) 8,678.79 4,374.29 8,374.86 4,429.37 8,982.71 3,710.43 0.543 0.15 0.022 Note. SD: standard deviation. R: Partial correlation. FA: food addiction negative screening group. FAþ: food addiction positive screening group. p Bold: significant comparison. †Bold: effect size into the ranges mild-moderate to high-large. Correlational analysis Table 3 includes the partial correlation matrix assessing the relationship between leptin concentrations and clinical measures, separately for patients with and without FA, and adjusted for sex, age, BMI, and WAIS-vocabulary scores. All correlation coefficients involving the FA group were into the low effect-size range, suggesting no relationships between leptin and psychological performance, GD severity, psychological state, impulsivity, and emotion regulation capacity among these patients. Within the FAþ group, higher leptin concentrations were related to worse performance on neuropsychological measures (including the WCST, TMT, and SCWT), greater problem-gambling severity (reflected in the number of DSM-5 GD criteria and SOGS scores), higher scores on the SCL-90R obsessive- Fig. 1. Radar chart with the hormonal profile (z-standardized means are plotted). compulsive and phobic anxiety scales, higher impulsivity Note. Z-standardized means are plotted in the graph. Total sample levels (UPPS-P: lack of premeditation, sensation-seeking, (N 5 297). positive urgency, and total score), and more emotion- Table 3. Partial correlation with the leptin level (adjusted by sex, age, BMI and WAIS-vocabulary) FA (n 5 274) FAþ (n 5 23) FA (n 5 274) FAþ (n 5 23) IGT: block 1 0.026 0.055 SCL-90R Somatization 0.024 0.129 IGT: block 2 0.023 0.092 SCL-90R Obsessive/compulsive 0.020 0.322† IGT: block 3 0.030 0.071 SCL-90R Interpersonal sensitivity 0.081 0.019 IGT: block 4 0.030 −0.334† SCL-90R Depressive 0.004 0.134 IGT: block 5 0.013 0.071 SCL-90R Anxiety 0.002 0.009 IGT: total 0.006 0.141 SCL-90R Hostility 0.073 0.138 IGT: learning 0.012 0.076 SCL-90R Phobic anxiety 0.061 0.300† IGT: risk 0.008 0.143 SCL-90R Paranoid Ideation 0.069 0.153 WCST: trials 0.035 0.375† SCL-90R Psychotic 0.041 0.140 WCST: errors 0.034 0.244† SCL-90R GSI score 0.023 0.042 WCST: errors perseverant 0.031 0.278† SCL-90R PST score 0.041 0.110 WCST: conceptual 0.071 0.222 SCL-90R PSDI score 0.007 0.002 WCST: categories completed 0.045 0.023 UPPS-P Lack premeditation 0.056 0.285† WCST: trials for the 1st-categ. 0.029 0.182 UPPS-P Lack perseverance 0.019 0.029 TMT: A 0.043 0.109 UPPS-P Sensation seeking 0.145 0.318† TMT: B 0.052 0.326† UPPS-P Positive urgency 0.155 0.435† TMT: Diff 0.046 0.324† UPPS-P Negative urgency 0.077 0.226 Stroop: words 0.062 0.174 UPPS-P Total 0.142 0.348† Stroop: colors 0.002 0.064 DERS Non acceptance emotions 0.056 0.068 Stroop: words-colors 0.018 −0.289† DERS Difficulties directed behav. 0.007 0.282† Stroop: estimated 0.029 0.116 DERS Impulse control difficult. 0.025 0.139 Stroop: interference 0.042 −0.353† DERS Lack emotional aware. 0.043 −0.234† DSM-5 criteria 0.049 0.240† DERS Limited access emotions 0.045 0.163 SOGS total 0.038 0.406† DERS Lack emotional clarity 0.047 0.085 DERS Total 0.022 0.135 Note. †Bold: effect size into the range mild-moderate (|R|>0.24) to high-large (|R|>0.37). Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1026 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 regulation difficulties (DERS) related to goal-directed be- increased impulsivity. However, increased impulsivity may haviors and lack of emotional clarity. underlie FA-related eating behaviors leading to increased leptin concentrations, or other possibilities (relating to synergism) may also exist. Elevated impulsivity has been DISCUSSION previously reported in both GD and FA (Mestre-Bach et al., 2020; Schulte & Gearhardt, 2021). In patients with GD and The present work studied differences in plasma concentra- co-occurring FA, the dysfunction of circuits linked to tions of appetite-regulating hormones between individuals impulsivity and leptin signaling may underlie not only the with and without FA in a sample of patients diagnosed with incursion into behaviors related to excessive food intake, but GD. Likewise, neuropsychological and clinical features were also some common clinical and psychological features assessed. The results suggested that subjects with FA pre- related to both GD and FA. sented higher BMI, more severe GD measured by the SOGS, Poor cognitive performance, such as low cognitive flex- greater emotion dysregulation, worse general psychopatho- ibility and disadvantageous decision-making, has been logical state, and an altered endocrine profile characterized implicated in both GD and FA (Etxandi et al., 2022; Lacroix by an elevation of leptin concentrations (after adjusting for & von Ranson, 2021; Steward et al., 2018). To our knowl- BMI), without differences in the other analyzed endocrine edge, this is the first study to evaluate the association be- factors. Moreover, correlations between leptin concentra- tween leptin concentrations and cognitive performance in tions and certain psychological and clinical features were people with GD and FA. Interestingly, our results showed a observed in the FAþ group. Higher concentrations of leptin positive correlation between leptin concentrations and were associated with phobic anxiety and obsessive-compul- poorer cognitive flexibility, as measured by WCST and TMT sive dimensions (SCL-90R), impulsivity, emotion dysregu- performance, in GD patients with FA. Some studies focusing lation, and poorer cognitive flexibility and inhibitory on populations of lean body mass have suggested a possible control. Furthermore, in the FAþ group, leptin concentra- protective factor of this adiponectin (Holden et al., 2017; tions were also associated with more severe GD. Lieb et al., 2009), while poorer cognitive performance The prevalence of FA in the sample (7.7%) was similar to (specifically in cognitive flexibility and other executive that described in the literature (Granero et al., 2018). As functions) has been related to elevated circulating leptin expected, considering both the nature of the studied co- concentrations in individuals with overweight (Labad et al., morbidity and results from previous studies, patients with 2012). Considering that leptin has an influence on hippo- FA presented higher SOGS scores and BMI, supporting the campus-dependent learning and memory (Harvey, Solo- notion of more severe GD and a worse metabolic profile in vyova, & Irving, 2006) and that the hippocampus has been this subgroup of patients (Etxandi et al., 2021; Jiménez- related to cognitive flexibility (Leirer et al., 2010), these re- Murcia et al., 2017). This finding reinforces the idea that sults as a whole may suggest that leptin resistance could be individuals with GD and FA may benefit from specific involved in the impairment of cognitive flexibility in GD therapeutic strategies (e.g., improving healthy eating habits, patients with FA (Gunstad et al., 2008). increasing physical exercise) and that screening for FA in Recent studies have reported a potential association be- patients with GD may help optimize preventive and thera- tween leptin concentrations and neuropsychological per- peutic approaches (Etxandi et al., 2021). No other significant formance, particularly involving measures of inhibitory differences were found between sociodemographic profiles control (Wollenhaupt et al., 2019). Interestingly, the results nor gambling preferences between both groups, which has of the present study also demonstrate a positive correlation also been reported in a prior publication from our group of leptin concentrations with deficits in inhibitory control, as (Etxandi et al., 2021). measured by the SCWT, in patients with FA. Taking all the Elevated adjusted plasma leptin concentrations in pa- above into account, the relationship between adjusted leptin tients with FA, who presented a higher BMI, is consistent concentrations and measures related to impulsivity is highly with previous studies (Peters et al., 2018) and support the suggestive, especially when observed in the FAþ group (with notion that elevated concentrations of this adipocytokine higher BMI) and not in the FA-group. Although future may represent leptin resistance in patients with overweight. studies are warranted to further clarify its role, the results According to this hypothesis, leptin would not adequately would be in line with the hypothesis that leptin signaling exert its appetite-suppressing function and could underlie could underlie impulsivity-related dysfunctions in patients the development of addictive-like eating in these individuals with GD and co-occurring FA. Moreover, these results may (Peters et al., 2018). Moreover, leptin concentrations showed also contribute to the ongoing debate on the theory and a positive correlation with trait impulsivity, which is in line classification of FA. In this regard, the potential involvement with previous studies (Sutin et al., 2013). Leptin can of neurobiological factors in the development of impair- modulate mesolimbic activity both through receptors ments in dopaminergic pathways that regulate neural sys- expressed on dopaminergic cells in the midbrain, and indi- tems associated with reward sensitivity and incentive rectly via its actions in upstream hypothalamic circuits motivation in FA can reinforce its conceptualization as an (Adams et al., 2018). Our findings suggest that patients with addictive disorder. GD and FA may have leptin resistance that might contribute Individuals with GD, with versus without FA, had higher to dysfunctions in this signaling system and lead to an scores in general psychopathology and emotion dysregulation, Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1027 consistent with previous studies (Etxandi et al., 2021; Jiménez- Some strengths of the present study include a sizable Murcia et al., 2017). FA-related behaviors have been proposed sample, the well-characterized clinical and neuropsychological as maladaptive responses to emotional distress, with serious assessments, and the adjustment of analyses for potential metabolic and clinical implications (Etxandi et al., 2021). confounding factors. Also, we used several measurement Bearing in mind the involvement of leptin signaling in tools, including global scales and subscales, which provide a the potential development of anxiety-related behaviors (Liu, broad visualization of the psychopathological and functional Guo, & Lu, 2016), the positive correlation between leptin profile for the patients. concentrations and emotion dysregulation and phobic anxiety results resonate with prior findings. Although preliminary, these findings suggest that leptin could be a biological CONCLUSIONS mechanism related to the higher emotion dysregulation found in patients with GD and FA. The present study provides insight into possible underlying Noticeably, in the present study no significant alterations endocrine dysfunctions related to reward processing in FA in other endocrine factors concentrations (i.e., ghrelin, among patients with GD. Despite its cross-sectional design, LEAP-2, and adiponectin) were identified between GD pa- this study suggests that leptin signaling may underlie clinical tients with and without FA. It is very suggestive that in a and neuropsychological aspects, especially in terms of previous study of our group comparing the same hormones impulsivity, cognitive flexibility, and GD severity in the between patients with GD and healthy subjects, differences subgroup with FA, with potential therapeutic implications. were observed in ghrelin and adiponectin signaling, but not Future research in this area may contribute to a better un- in leptin concentrations, adjusted for BMI (Etxandi et al., derstanding of the biology of GD and FA, as well as to the 2022). This finding leads us to hypothesize that leptin could development of more specific psychological and biological play a specific role in FA, independent of GD, that involves treatment strategies in this clinical population. specific neuropsychological and psychopathological do- mains, including impulsivity, cognitive flexibility, and inhibitory control. Funding sources: We thank CERCA Programme/Generalitat In sum, our results suggest that leptin is linked to FA in de Catalunya for guarante institutional support. This work patients with GD, underlying clinical and neuropsycholog- was supported by a grant from the Delegación del Gobierno ical characteristics that exist when adjusting for BMI and para el Plan Nacional sobre Drogas (2021I031) and Plan other potential confounders. Leptin appears linked to more Nacional sobre Drogas Convocatoria de subvenciones para severe GD symptomatology in the FAþ group. Although proyectos de investigación financiados con fondos europeos promising, these preliminary exploratory results would 2022 (EXP2022/008847), Ministerio de Ciencia e Innovación benefit from more investigation into leptin signaling dis- (PDI2021-124887OB-I00), Instituto de Salud Carlos III turbances in patients with GD and FA. (ISCIII) (PI20/00132 co-funded by FEDER funds/European Regional Development Fund, ERDF, a way to build Europe), Agència de Gestió d’Ajust Universitaris i de Recerca Strengths and limitations (AGAUR, 2021 SGR 00824) and European Union’s Horizon Some limitations should be considered when interpreting 2020 research and innovation programme under Grant the results of this study. The cross-sectional nature of the agreement no. 847879 (PRIME/H2020, Prevention and study precludes causal attributions. Future longitudinal Remediation of Insulin Multimorbidity in Europe) and no. research is needed to better characterize a role for leptin in 101080219 (eprObes). CIBERobn is an iniciative of ISCIII. co-occurring GD and FA. The sample was principally IB was supported by the Instituto de Salud Carlos III composed of treatment-seeking males with GD referred to a through the grant CM21/00172 (co-funded by European specialized unit. The extent to which these findings gener- Social Fund. ESF investing in your future). RG is supported alize to other populations, including women with GD, by The Catalan Institution for Research and Advanced warrants direct investigation. However, the percentage of Studies (ICREA-2021 Academia Program). IL was supported women in the study is consistent with those in treatment- by the Ministerio de Ciencia e Innovación (Juan de la seeking GD samples. The last limitation is the lack of Cierva-Formación program, FJC2021-046494-I). The fun- analysis for potential interaction effects (this was not an ders had no role in the study design, data collection and objective of the study). Given the pioneering nature of the analysis, decision to publish or preparation of the work, as well as the large number of variables considered manuscript. (particularly for the neuropsychological area), the number of the potential moderation parameters was too large. We Authors’ contribution: ME, IB, BM-M, and SJ-M contributed considered more appropriate to provide the results of this to the development of the study concept and design. RG first study, aimed to explore and identify the key endocrine performed the statistical analysis. ME, IB, BM-M, MG-P, and neuropsychological variables within the GD profile, and LM, AP-G, EV-M, and SJ-M aided with data collection. IB, to plan future studies with larger samples and a limited AP-G, ST, SC, and, CD carried out the procedures related to number of measures (those selected as the most relevant and neuroendocrine variables extraction and analysis. ME, IB, therefore candidate to analyze the moderation effects). BM-M, IL, NS, and SJ-M aided with interpretation of data Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1028 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 and the writing of the manuscript. MNP, AG, FF-A, JT, and Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. SJ-M revised the manuscript and provided substantial (1994). Insensitivity to future consequences following damage comments. FF-A and SJ-M obtained funding. to human prefrontal cortex. Cognition, 50(1–3), 7–15. https:// doi.org/10.1016/0010-0277(94)90018-3. Conflict of interest: Mikel Etxandi, Isabel Baenas, Bernat Bechara, A., Tranel, D., & Damasio, H. (2000). Characterization of Mora-Maltas, Roser Granero, Sulay Tovar, Neus Solé-Mor- the decision-making deficit of patients with ventromedial pre- ata, Ignacio Lucas, Mónica Gómez-Peña, Laura Moragas, frontal cortex lesions. Brain, 123(11), 2189–2202. https://doi. Amparo del Pino-Gutiérrez, Javier Tapia, Eduardo Valen- org/10.1093/brain/123.11.2189. ciano-Mendoza, Sabela Casado, Ashley N. Gearhardt, and Bechara, A., & Van Der Linden, M. (2005). Decision-making and Carlos Diéguez report no disclosures. Fernando Fernández- impulse control after frontal lobe injuries. Current Opinion in Aranda and Susana Jiménez-Murcia received consultancy Neurology, 18(6), 734–739. https://doi.org/10.1097/01.WCO. honoraria from Novo Nordisk, and Fernando Fernández- 0000194141.56429.3C. Aranda received editorial honoraria from Wiley. Marc N. Blaszczynski, A., & Nower, L. (2002). A pathways model of prob- Potenza has consulted for and advised Opiant Pharmaceu- lem and pathological gambling. In Addiction. (Vol. 97, Issue 5, ticals, Idorsia Pharmaceuticals, Baria-Tek, AXA, Game Day pp. 487–499). John Wiley & Sons, Ltd https://doi.org/10.1046/j. Data and the Addiction Policy Forum; has been involved in 1360-0443.2002.00015.x. a patent application with Yale University and Novartis; has Brewer Ja, P. M. (2008). The neurobiology and genetics of impulse received research support from the Mohegan Sun Casino control disorders: Relationships to drug addictions. Biochemical and Connecticut Council on Problem Gambling; has Pharmacology, 71(1), 63–75. https://doi.org/10.1016/j.bcp.2007. participated in surveys, mailings, or telephone consultations 06.043. related to drug addiction, impulse control disorders, or other Cloninger, C. R. (1999). The temperament and character inventory– health topics; has participated in trainings, medical educa- revised. Center for Psychobiology of Personality, Washington tion and journal editorial work; and has consulted for law University. offices and gambling entities on issues related to impulse De Oliveira, M. O., Nitrini, R., Yassuda, M. S., & Brucki, S. M. D. control or addictive disorders. (2014). Vocabulary is an appropriate measure of premorbid intelligence in a sample with heterogeneous educational level in Acknowledgements: We thank CERCA Programme/Gen- Brazil. Behavioural Neurology, 2014, 875960. https://doi.org/10. eralitat de Catalunya for guarante institutional support. 1155/2014/875960. CIBERobn is an iniciative of ISCIII, FEDER funds/European Derogatis, L. R. (1994). SCL-90-R: Symptom checklist-90-R. Regional Development Fund (ERDF), a way to build Europe, Administration, scoring and procedures manuall—II for the the European Social Fund-ESF investing in your future, revised version. Clinical Psychometric Research. ICREA Academia Program and AGAUR. Derogatis, L. R. (2002). SCL-90-R. Cuestionario de 90 síntomas- Manual. TEA Editorial. Echeburúa, E., Baez, C., Fernández-Montalvo, J., & Páez, D. (1994). SUPPLEMENTARY MATERIAL Cuestionario de Juego Patológico de South Oaks (SOGS): Validación española. Análisis y Modificación de La Conducta, Supplementary data to this article can be found online at 20(74), 769–791. https://doi.org/10.1556/2006.2023.00051. Escobar, M., Scherer, J. N., Ornell, F., Bristot, G., Soares, C. M., Guimarães, L. S. P., … Pechansky, F. (2018). Leptin levels and its correlation with crack-cocaine use severity: A preliminary REFERENCES study. Neuroscience Letters, 671, 56–59. https://doi.org/10.1016/ J.NEULET.2018.02.009. Adams, W. K., D’souza, A. M., Sussman, J. L., Kaur, S., Kieffer, T. J., Etxandi, M., Baenas, I., Mora-maltas, B., Granero, R., Fern, F., & Winstanley, C. A. (2018). Enhanced amphetamine-induced Tovar, S., … Moragas, L. (2022). Are signals regulating energy motor impulsivity and mild attentional impairment in the homeostasis related to neuropsychological and clinical features leptin-deficient rat model of obesity. Physiology and Behavior, of gambling disorder? A case-control study. Nutrients, 14(23), 192, 134–144. https://doi.org/10.1016/j.physbeh.2018.03.027. 5084. https://doi.org/10.3390/nu14235084. APA. (2000). American Psychiatric Association, 2000. Diagnostic Etxandi, M., Baenas, I., Munguía, L., Mestre-Bach, G., Granero, R., and statistical manual of mental disorders (4th ed.). American Gómez-Peña, M., … Jiménez-Murcia, S. (2021). Clinical features Journal of Psychiatry. of gambling disorder patients with and without food addiction: APA (2013). American Psychiatric Association, 2013. Diagnostic Gender-related considerations. Journal of Gambling Studies, and statistical manual of mental disorders (5th ed.). In Amer- 38(3), 843–862. https://doi.org/10.1007/S10899-021-10071-W. ican Journal of Psychiatry. Farokhnia, M., Grodin, E. N., Lee, M. R., Oot, E. N., Barja-Fernández, S., Lugilde, J., Castelao, C., Vázquez-Cobela, R., Blackburn, A. N., Stangl, B. L., … Leggio, L. (2018). Exogenous Seoane, L. M., Diéguez, C., … Tovar, S. (2021). Circulating ghrelin administration increases alcohol self-administration LEAP-2 is associated with puberty in girls. International Jour- and modulates brain functional activity in heavy-drinking nal of Obesity, 45(3), 502–514. https://doi.org/10.1038/S41366- alcohol-dependent individuals. Molecular Psychiatry, 23(10), 020-00703-3. 2029–2038. https://doi.org/10.1038/MP.2017.226. Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1029 Fernandez-Aranda, F., Karwautz, A., & Treasure, J. (2018). Food Grant, D. A., & Berg, E. (1948). A behavioral analysis of degree of addiction: A transdiagnostic construct of increasing interest. reinforcement and ease of shifting to new responses in a Weigl- European Eating Disorders Review: The Journal of the Eating type card-sorting problem. Journal of Experimental Psychology, Disorders Association, 26(6), 536–540. https://doi.org/10.1002/ 38(4), 404–411. https://doi.org/10.1037/H0059831. ERV.2645. Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of Finner, H., & Roters, M. (2001). On the false discovery rate and emotion regulation and dysregulation: Development, factor expected type I errors. Biometrical Journal, 43(8), 985–1005. structure, and initial validation of the difficulties in emotion https://doi.org/10.1002/1521-4036(200112)43:8<985. regulation scale. Journal of Psychopathology and Behavioral Fletcher, P. C., & Kenny, P. J. (2018). Food addiction: A valid Assessment, 26(1), 41–54. concept? Neuropsychopharmacology: Official Publication of Griffiths, M. D. (2017). Behavioural addiction and substance the American College of Neuropsychopharmacology, 43(13), addiction should be defined by their similarities not their dis- 2506–2513. https://doi.org/10.1038/S41386-018-0203-9. similarities. Addiction, 112(10), 1718–1720. https://doi.org/10. Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2016). 1111/add.13828. Development of the Yale food addiction scale version 2.0. Gunstad, J., Spitznagel, M. B., Keary, T. A., Glickman, E., Psychology of Addictive Behaviors: Journal of the Society of Alexander, T., Karrer, J., … Juvancic-Heltzel, J. (2008). Serum Psychologists in Addictive Behaviors, 30(1), 113–121. https://doi. leptin levels are associated with cognitive function in older org/10.1037/ADB0000136. adults. Brain Research, 1230, 233–236. https://doi.org/10.1016/j. Gearhardt, A. N., Davis, C., Kuschner, R., & Brownell, K. D. (2011). brainres.2008.07.045. The addiction potential of hyperpalatable foods. Current Drug Gutiérrez-Zotes, J. A., Bayón, C., Montserrat, C., Valero, J., Abuse Reviews, 4(3), 140–145. https://doi.org/10.2174/18744737 Labad, A., Cloninger, C. R., & Fernández-Aranda, F. (2004). 11104030140. Temperament and Character Inventory Revised (TCI-R). Gearhardt, A. N., Grilo, C. M., Dileone, R. J., Brownell, K. D., & Standardization and normative data in a general population Potenza, M. N. (2011). Can food be addictive? Public health sample. Actas Españolas de Psiquiatría, 32(1), 8–15. and policy implications. Addiction (Abingdon, England), Harvey, J., Solovyova, N., & Irving, A. (2006). Leptin and its 106(7), 1208–1212. https://doi.org/10.1111/J.1360-0443.2010. role in hippocampal synaptic plasticity. Progress in Lipid 03301.X. Research, 45(5), 369–378. https://doi.org/10.1016/j.plipres. Gearhardt, A. N., & Hebebrand, J. (2021). The concept of 2006.03.001. “food addiction” helps inform the understanding of overeating Hebebranda, J., Albayraka, Ö., Adanb, R., Antel, J., Dieguezc, C., and obesity: Debate Consensus. The American Journal of De Jongb, J., … Dickson, S. L. (2014). Eating addiction”, rather Clinical Nutrition, 113(2), 274–276. https://doi.org/10.1093/ than “food addiction”, better captures addictive-like eating AJCN/NQAA345. behavior. Neuroscience and Biobehavioral Reviews, 47, Gearhardt, M. S. A., Phil, M., & Corbin, W. R. (2011). The role of 295–306. Elsevier Ltd. https://doi.org/10.1016/j.neubiorev. food addiction in clinical research. Current Pharmaceutical 2014.08.016. Design, 17(12), 1140– 1142. https://doi.org/10.2174/ Hellström, P. M., Geliebter, A., Näslund, E., Schmidt, P. T., 138161211795656800. Yahav, E. K., Hashim, S. A., & Yeomans, M. R. (2004). Geisel, O., Hellweg, R., Wiedemann, K., & Müller, C. A. (2018). Peripheral and central signals in the control of eating in Plasma levels of leptin in patients with pathological gambling, normal, obese and binge-eating human subjects. British Journal internet gaming disorder and alcohol use disorder. Psychiatry of Nutrition, 92(S1), S47– S57. https://doi.org/10.1079/ Research, 268, 193–197. https://doi.org/10.1016/J.PSYCHRES. bjn20041142. 2018.06.042. Hervás, G., & Jódar, R. (2008). Adaptación al castellano de la Escala Ge, X., Yang, H., Bednarek, M. A., Galon-Tilleman, H., Chen, P., de Dificultades en la Regulación Emocional The Spanish Chen, M., … Kaplan, D. D. (2018). LEAP2 is an endogenous version of the Difficulties in Emotion Regulation Scale. 19(2), antagonist of the ghrelin receptor. Cell Metabolism, 27(2), 461– 139–156. 469.e6. https://doi.org/10.1016/J.CMET.2017.10.016. Hillemacher, T., Weinland, C., Heberlein, A., Gröschl, M., di Giacomo, E., Aliberti, F., Pescatore, F., Santorelli, M., Pessina, R., Schanze, A., Frieling, H., … Bleich, S. (2009). Increased levels of Placenti, V., … Clerici, M. (2022). Disentangling binge eating adiponectin and resistin in alcohol dependence–possible link to disorder and food addiction: A systematic review and meta- craving. Drug and Alcohol Dependence, 99(1–3), 333–337. analysis. Eating and Weight Disorders: EWD, 27(6), 1963–1970. https://doi.org/10.1016/J.DRUGALCDEP.2008.07.019. https://doi.org/10.1007/S40519-021-01354-7. Holden, K. F., Lindquist, K., Tylavsky, F. A., Rosano, C., Tamara, B., Golden, C. J. (1978). Stroop color and word test: A manual for Yaffe, K., … Francisco, S. (2017). Serum leptin level and clinical and experimental uses. Chicago: Stoelting. cognition in the elderly. Neurobiol Aging Neurobiol, 30(9), Granero, R., Jiménez-Murcia, S., Gerhardt, A. N., Agüera, Z., 1483–1489. https://doi.org/10.1016/j.neurobiolaging.2007.11. Aymamí, N., Gómez-Peña, M., … Fernández-Aranda, F. 024.Serum. (2018). Validation of the Spanish version of the Yale food Housová, J., Wilczek, H., Haluzík, M. M., Kremen, J., Krízová, J., & addiction scale 2.0 (YFAS 2.0) and clinical correlates in a Haluzík, M. (2005). Adipocyte-derived hormones in heroin sample of eating disorder, gambling disorder, and healthy addicts: The influence of methadone maintenance treatment. control participants. Frontiers in Psychiatry, 9:321. https://doi. Physiological Research, 54(1), 73–78. https://doi.org/10.33549/ org/10.3389/FPSYT.2018.00208. physiolres.930568. Unauthenticated | Downloaded 01/08/24 11:45 AM UTC 1030 Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 Iovino, M., Messana, T., Lisco, G., Mariano, F., Giagulli, V. A., Journal of Neuropsychopharmacology, 19(2), 1–11. https://doi. Guastamacchia, E., … Triggiani, V. (2022). Neuroendocrine org/10.1093/ijnp/pyv115. modulation of food intake and eating behavior. Endocrine, Lopez-Aguilar, I., Ibarra-Reynoso, L. D. R., & Malacara, J. M. (2018). Metabolic & Immune Disorders Drug Targets, 22. https://doi. Association of Nesfatin-1, acylated ghrelin and cortisol with org/10.2174/1871530322666220127114326. scores of compulsion, food addiction, and binge eating in adults Jiménez-Murcia, S., Aymamí-Sanromà, M., Gómez-Pena, M., with normal weight and with obesity. Annals of Nutrition and Álvarez-Moya, E., & Vallejo, J. (2006). Protocols de tractament Metabolism, 73(1), 54–61. https://doi.org/10.1159/000490357. cognitivoconductual pel joc patològic i d’altres addiccions no Lugilde, J., Casado, S., Beiroa, D., Cuñarro, J., Garcia-Lavandeira, M., tòxiques [Protocols of cognitive-behaviour therapy for patho- Álvarez, C. V., … Tovar, S. (2022). LEAP-2 counteracts ghrelin- logical gambling and other behavioural addictions]. induced food intake in a nutrient growth hormone and age Jiménez-Murcia, S., Granero, R., Wolz, I., Baño, M., Mestre-Bach, G., independent manner. Cells, 11(3), 1–11. https://doi.org/10.3390/ Steward, T., … Fernández-Aranda, F. (2017). Food addiction in cells11030324. gambling disorder: Frequency and clinical outcomes. Frontiers Mallorquí-Bagué, N., Tolosa-Sola, I., Fernández-Aranda, F., in Psychology, 8(MAR), 1–12. https://doi.org/10.3389/fpsyg.2017. Granero, R., Fagundo, A. B., Lozano-Madrid, M., … 00473. Jiménez-Murcia, S. (2018). Cognitive deficits in executive Jiménez-Murcia, S., Stinchfield, R., Álvarez-Moya, E., Jaurrieta, N., functions and decision-making impairments cluster gambling Bueno, B., Granero, R., … Vallejo, J. (2009). Reliability, validity, disorder sub-types. Journal of Gambling Studies, 34(1), and classification accuracy of a Spanish translation of a measure 209–223. https://doi.org/10.1007/S10899-017-9724-0. of DSM-IV diagnostic criteria for pathological gambling. Mani, B. K., Puzziferri, N., He, Z., Rodriguez, J. A., Journal of Gambling Studies, 25(1), 93–104. https://doi.org/10. Osborne-Lawrence, S., Metzger, N. P., … Zigman, J. M. (2019). 1007/s10899-008-9104-x. LEAP2 changes with body mass and food intake in humans and Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological mice. The Journal of Clinical Investigation, 129(9), 3909–3923. Methods, 17(2), 137–152. https://doi.org/10.1037/A0028086. https://doi.org/10.1172/JCI125332. Labad, J., Price, J. F., Strachan, M. W. J., Deary, I. J., Seckl, J. R., Martinotti, G., Montemitro, C., Baroni, G., Andreoli, S., Sattar, N., & Reynolds, R. M. (2012). Serum leptin and cognitive Alimonti, F., Di Nicola, M., … Janiri, L. (2017). Relationship function in people with Type 2 diabetes. Neurobiology of Aging, between craving and plasma leptin concentrations in patients 33(12), 2938–2941.e2. https://doi.org/10.1016/j.neurobiolaging. with cocaine addiction. Psychoneuroendocrinology, 85, 35–41. 2012.02.026. https://doi.org/10.1016/J.PSYNEUEN.2017.08.004. Lacroix, E., & von Ranson, K. M. (2021). Prevalence of social, Mestre-Bach, G., Steward, T., Granero, R., Fernández-Aranda, F., cognitive, and emotional impairment among individuals with Mena-Moreno, T., Vintró-Alcaraz, C., … Jiménez-Murcia, S. food addiction. Eating and Weight Disorders: EWD, 26(4), (2020). Dimensions of impulsivity in gambling disorder. Scien- 1253–1258. https://doi.org/10.1007/S40519-020-01014-2. tific Reports, 10(1). https://doi.org/10.1038/S41598-019-57117-Z. Leigh, S. J., & Morris, M. J. (2018). The role of reward circuitry and Miller, R., Tanofsky-Kraff, M., Shomaker, L. B., Field, S. E., food addiction in the obesity epidemic: An update. Biological Hannallah, L., Reina, S. A., … Yanovski, J. A. (2014). Serum Psychology, 131, 31–42. https://doi.org/10.1016/j.biopsycho. leptin and loss of control eating in children and adolescents. 2016.12.013. International Journal of Obesity, 38(3), 397. https://doi.org/10. Leirer, V. M., Wienbruch, C., Paul-Jordanov, I., Kolassa, S., 1038/IJO.2013.126. Elbert, T., & Kolassa, I. T. (2010). Hippocampal activity during Novelle, M. G., & Diéguez, C. (2018). Unravelling the role and the transverse patterning task declines with cognitive compe- mechanism of adipokine and gastrointestinal signals in animal tence but not with age. BMC Neuroscience, 11. https://doi.org/ models in the nonhomeostatic control of energy homeostasis: 10.1186/1471-2202-11-113. Implications for binge eating disorder. European Eating Lesieur, H. R., & Blume, S. B. (1987). The South Oaks gambling Disorders Review, 26(6), 551–568. https://doi.org/10.1002/erv. screen (SOGS): A new instrument for the identification of 2641. pathological gamblers. The American Journal of Psychiatry, Pena-Bello, L., Pertega-Diaz, S., Outeiriño-Blanco, E., Garcia-Buela, J., 144(9), 1184–1188. https://doi.org/10.1176/AJP.144.9.1184. Tovar, S., Sangiao-Alvarellos, S., … Cordido, F. (2015). Effect Lezak, M. D., & Howieson Db, L. D. (2004). Neuropsychological of oral glucose administration on rebound growth hormone assessment (4th ed.). New York: Oxford University Press. release in normal and obese women: The role of adiposity, Lieb, W., Beiser, A. S., Vasan, R. S., Tan, Z. S., Au, R., Harris, T. B., … insulin sensitivity and ghrelin. Plos One, 10(3). https://doi.org/ Seshadri, S. (2009). Association of plasma leptin levels with inci- 10.1371/JOURNAL.PONE.0121087. dent Alzheimer disease and MRI measures of brain aging. Jama, Peters, T., Antel, J., Föcker, M., Esber, S., Hinney, A., Schéle, E., … 302(23), 2565–2572. https://doi.org/10.1001/jama.2009.1836. Hebebrand, J. (2018). The association of serum leptin levels Linnet, J. (2020). The anticipatory dopamine response in addiction: with food addiction is moderated by weight status in adolescent A common neurobiological underpinning of gambling disorder psychiatric inpatients. European Eating Disorders Review: The and substance use disorder? Progress in Neuro-Psychopharma- Journal of the Eating Disorders Association, 26(6), 618–628. cology & Biological Psychiatry, 98. https://doi.org/10.1016/J. https://doi.org/10.1002/ERV.2637. PNPBP.2019.109802. Piccinni, A., Bucchi, R., Fini, C., Vanelli, F., Mauri, M., Stallone, T., Liu, J., Guo, M., & Lu, X. Y. (2016). Leptin/LepRb in the ventral … Claudio, C. (2021). Food addiction and psychiatric comor- tegmental area mediates anxiety-related behaviors. International bidities: A review of current evidence. Eating and Weight Unauthenticated | Downloaded 01/08/24 11:45 AM UTC Journal of Behavioral Addictions 12 (2023) 4, 1019–1031 1031 Disorders: EWD, 26(4), 1049–1056. https://doi.org/10.1007/ Treasure, J., Leslie, M., Chami, R., & Fernández-Aranda, F. (2018). S40519-020-01021-3. Are trans diagnostic models of eating disorders fit for purpose? Potenza, M. N., Balodis, I. M., Derevensky, J., Grant, J. E., A consideration of the evidence for food addiction. European Petry, N. M., Verdejo-Garcia, A., & Yip, S. W. (2019). Eating Disorders Review, 26(2), 83–91. https://doi.org/10.1002/ Gambling disorder. Nature Reviews Disease Primers, 5(1), 51. erv.2578. https://doi.org/10.1038/s41572-019-0099-7. van Timmeren, T., Daams, J. G., van Holst, R. J., & Pursey, K. M., Contreras-Rodriguez, O., Collins, C. E., Stanwell, P., Goudriaan, A. E. (2018). Compulsivity-related neurocognitive & Burrows, T. L. (2019). Food addiction symptoms and performance deficits in gambling disorder: A systematic review amygdala response in fasted and fed states. Nutrients, 11(6). and meta-analysis. Neuroscience and Biobehavioral Reviews, 84, https://doi.org/10.3390/NU11061285. 204–217. https://doi.org/10.1016/J.NEUBIOREV.2017.11.022. Reitan, R. M. (1958). Validity of the trail making test as an indicator Vengeliene, V. (2013). The role of ghrelin in drug and natural of organic brain damage perceptual and motor skills. https://doi. reward. Addiction Biology, 18(6), 897–900. https://doi.org/10. org/10.2466/pms.1958.8.3.271. 1111/adb.12114. Rosnow, R. L. R. R. (1996). Computing contrasts, effect sizes and Verdejo-García, A., Lozano, Ó., Moya, M., Alcázar, M. Á., & counternulls on other people’s published data: General pro- Pérez-García, M. (2010). Psychometric properties of a Spanish cedures for research consumers. Psychological Methods, 1, 331– version of the UPPS-P impulsive behavior scale: Reliability, 340. https://doi.org/10.1037/1082-989X.1.4.331. validity and association with trait and cognitive impulsivity. Schulte, E. M., Avena, N. M., & Gearhardt, A. N. (2015). Which Journal of Personality Assessment, 92(1), 70–77. https://doi.org/ foods may be addictive? The roles of processing, fat content, 10.1080/00223890903382369. and glycemic load. Plos One, 10(2). https://doi.org/10.1371/ Voigt, K., Giddens, E., Stark, R., Frisch, E., Moskovsky, N., journal.pone.0117959. Kakoschke, N., … Verdejo-Garcia, A. (2021). The hunger Schulte, E. M., & Gearhardt, A. N. (2021). Attributes of the food games: Homeostatic state-dependent fluctuations in disinhibi- addiction phenotype within overweight and obesity. Eating and tion measured with a novel gamified test battery. Nutrients, Weight Disorders: EWD, 26(6), 2043–2049. https://doi.org/10. 13(6), 2001. https://doi.org/10.3390/nu13062001. 1007/S40519-020-01055-7. Volkow, N. D., Wang, G. J., Fowler, J. S., Tomasi, D., & Baler, R. Solé-Morata, N., Baenas, I., Etxandi, M., Granero, R., Forcales, S. V., (2012). Food and drug reward: Overlapping circuits in human Gené, M., … Jiménez-Murcia, S. (2022). The role of neurotrophin obesity and addiction. Current Topics in Behavioral Neurosci- genes involved in the vulnerability to gambling disorder. Scientific ences, 11, 1–24. https://doi.org/10.1007/7854_2011_169. Reports, 12(1), 1–11. https://doi.org/10.1038/s41598-022-10391-w. Wechsler, D. K. A. (1999). WAIS-III: Wechsler adult intelligence Stata-Corp (2021). Stata statistical software: Release 17. College scale, 3rd edition [Book in Spanish]. Madrid: TEA Ediciones station, Texas: Stata Press Publication (StataCorp LLC). SA. Steward, T., Mestre-Bach, G., Vintró-Alcaraz, C., Lozano-Madrid, M., Whiteside, S. P., Lynam, D. R., Miller, J. D., & Reynolds, S. K. Agüera, Z., Fernández-Formoso, J. A., … Fernández-Aranda, F. (2005). Validation of the UPPS impulsive behaviour scale: A (2018). Food addiction and impaired executive functions in four-factor model of impulsivity. European Journal of Person- women with obesity. European Eating Disorders Review: The ality, 19(7), 559–574. Journal of the Eating Disorders Association, 26(6), 574–584. Wollenhaupt, C., Wilke, L., Erim, Y., Rauh, M., Steins-Loeber, S., & https://doi.org/10.1002/ERV.2636. Paslakis, G. (2019). The association of leptin secretion with Stinchfield, R. (2003). Reliability, validity, and classification accu- cognitive performance in patients with eating disorders. Psy- racy of a measure of DSM-IV diagnostic criteria for patholog- chiatry Research, 276, 269–277. https://doi.org/10.1016/j. ical gambling. The American Journal of Psychiatry, 160(1), psychres.2019.05.001. 180–182. https://doi.org/10.1176/APPI.AJP.160.1.180. Yu, Y., Fernandez, I. D., Meng, Y., Zhao, W., & Groth, S. W. (2021). Sutin, A. R., Zonderman, A. B., Uda, M., Deiana, B., Taub, D. D., Gut hormones, adipokines, and pro- and anti-inflammatory Longo, D. L., … Terracciano, A. (2013). Personality traits and cytokines/markers in loss of control eating: A scoping review. leptin. Psychosomatic Medicine, 75(5), 505–509. https://doi.org/ Appetite, 166, 105442. https://doi.org/10.1016/j.appet.2021. 10.1097/PSY.0B013E3182919FF4. 105442. Open Access statement. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated. Unauthenticated | Downloaded 01/08/24 11:45 AM UTC