Glucagon-like peptide 1 agonist and effects on reward behaviour: A systematic review

: GLP-1RAs show promise in addressing reward dysfunction linked to food stimuli, obesity, and T2DM. They normalize insulin resistance, and might also modulate dopaminergic signalling and reduce anhedonia. Their effects on glycemic variability and cravings suggest potential applications in addiction disorders.


Introduction:
The roles of metabolic signals, including Glucagon-like peptide 1 (GLP-1), have been implicated in multiple domains outside metabolic regulation.There is a growing interest in repurposing Glucagon-like peptide 1 receptor agonists (GLP-1RAs) as therapeutics for motivation and reward-related behavioural disturbances.Herein, we aim to systematically review the extant evidence on the potential effects of GLP-1RAs on the reward system.Methods: The study followed PRISMA guidelines using databases such as OVID, PubMed, Scopus, and Google Scholar.The search focused on "Reward Behavior" and "Glucagon Like Peptide 1 Receptor Agonists" and was restricted to human studies.Quality assessment achieved by the NIH's Quality Assessment of Controlled Intervention Studies Results: GLP-1RAs consistently reduced energy intake and influenced reward-related behaviour.These agents have been associated with decreased neurocortical activation in response to higher rewards and food cues, particularly high-calorie foods, and lowered caloric intake and hunger levels.Discussion: GLP-1RAs show promise in addressing reward dysfunction linked to food stimuli, obesity, and T2DM.They normalize insulin resistance, and might also modulate dopaminergic signalling and reduce anhedonia.Their effects on glycemic variability and cravings suggest potential applications in addiction disorders.
Glucagon-like peptide 1 receptor agonists (GLP-1RA) are drugs mimicking the GLP-1 incretin hormone [1].These drugs have been approved to be used as a treatment method for type 2 diabetes (T2DM) and for weight management.GLP-1RAs regulate insulin and glucagon secretion in a glucose-dependent manner, slowing gastric emptying and consequently increasing satiety [2][3][4][5].Moreover, GLP-1 receptors are expressed in various body systems and tissues, including the digestive, cardiopulmonary (which helps reduce oxidative stress and prevent cardiomyocyte apoptosis), respiratory (enhancing lung function, improving airway remodelling, and reducing mucus secretion), and nervous systems (both central and peripheral, with expression in the Vagus nerve and key brain areas) [6][7][8][9].Consequently, the role of the GLP-1 has been implicated in multiple domains outside of metabolic regulation.Accumulating evidence has indicated that metabolic signals modulate reward behaviour and its underlying neural circuits.As a result, there is a growing interest in repurposing GLP-1RAs as a therapeutic for motivation and reward-related disturbances.
Reward behaviour facilitates the homeostatic urges necessary for survival.Moreover, reward behaviours can be divided into primary and secondary rewards.Primary rewards focus predominantly on the reward behaviours intrinsic to human nature and do not need to be learned (e.g.food-driven behaviour) [10].Natural rewards are those that are learned and further the drive to achieve hedonistic rewards [11].Secondary rewards can also be associated with the motivational driving forces behind achieving primary reward behaviours; the reward of money drives the primary reward of having sufficient food [12].
Furthermore, reward behaviour has a cognitive (associating the reward stimuli with a specific task), emotional (the implicit pleasure related to a behaviour), and subsequent motivational aspect (the salience of the pleasurable behaviour and the association with a particular task corresponds to a motivational drive to re-achieve the pleasurable state) [13][14][15].Several brain regions have been associated with reward behaviours-namely, cortical areas related to the mesocorticolimbic system [16].GLP-1 receptors (GLP-1Rs) are localized in these areas and have often been implicated in the modulation of reward behaviour [17].Preclinical evidence indicates that the strength of hippocampus-nucleus accumbens synapses regulates reward behaviour [18].Consequently, GLP-1Rs in hippocampal areas play critical roles in enhancing neurogenesis, and improving memory and learning (which are intrinsically linked to motivational drives), among other roles [19][20][21][22].Similarly, the nucleus accumbens is associated with several feeding areas, and GLP-1R stimulation suppresses food intake and reward behaviours [20,23,24].GLP1-RAs have been associated with the modulation of dopaminergic neurotransmission, one of the key molecular mediators of reward processes [25], either directly or indirectly via enhancement of insulin sensitivity and inhibition of pro-inflammatory cytokines [26][27][28][29][30].
Psychiatric and metabolic disorders are associated with dysfunctions in reward behavior.Anhedonia, i.e. the inability to experience pleasure, is a defining feature of mood disorder, such as major depressive disorder (MDD), but are also frequently reported by individuals with obesity, T2DM and insulin resistance [31][32][33][34][35].There is an urgent need to develop further treatment options for reward behavior dysfunctions in these transdiagnostic populations.Herein, we aim to systematically review the extant evidence on the potential effects of GLP-1RAs on the reward neural circuits and behaviors.

Search string
This systematic review followed the 2020 Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines [36].Articles were searched for on OVID (MedLine, Embase, AMED, Psy-chINFO, JBI EBP Database), PubMed, and Scopus, and selected articles were searched for on Google Scholar.The search string for this systematic review included: (Reward Behavio* AND Glucagon Like Peptide 1 Receptor Agonists) AND (Peptide OR Hypoglycemic Agents, OR Insulin, OR Diabetes Mellitus, Type 2) AND ("Primary article" OR "Randomized Controlled Trial").On OVID, it was also limited to only human studies, and the publication type was set to clinical trials, with English-only articles being assessed.

Study screening
The Covidence platform for systematic review management was used to select and assess the quality of the study.Two reviewers (S.B. and A. T.) independently screened titles and abstracts.Once a consensus was reached on the title/abstract screenings, the same two individuals (S.B. and A.T.) conducted a full-text review of the selected texts.Data extraction included the following information: Study Title, sample size, population description, study aims, method synopsis, outcome characteristics, discussion synopsis, and significance of findings.Outcomes of interest were reward-related behaviours or reward-related dysfunctions.Specifically, the effects of the GLP-1RA on overall reward behaviour modulation were of primary importance, regardless of the reward behaviour type.

Quality assessment and conflict resolution
The Quality Assessment of Controlled Intervention Studies, adapted from the National Institute of Health (NIH), was used to assess the risk of bias [37].The same two independent reviewers (S.B. and A.T.) conducted the risk of bias.Discrepancies were discussed at all stages of the systematic review process, and a consensus was reached through discussion with the other reviewer.

Search results
The search yielded 600 studies; 19 additional articles were found through a manual search of Google Scholar.After removing 206 duplicate references, the remaining 403 were screened based on their titles and abstracts, and 333 studies were removed.The remaining 70 articles underwent full-text screening and were then analyzed according to predefined eligibility criteria (Table 1).Of those, 55 studies were excluded for various reasons detailed in Fig. 1.Ultimately, 15 studies were included in this systematic review, with their specific results and experimental designs outlined in Table 2.

Risk of bias
Broadly, most of the studies assessed presently did not have any significant concerns regarding risks of bias.Most of the studies that scored high for risk of bias in the individual categories were due to insufficient descriptions regarding those domains; hence, the overall score for three of the studies analyzed had a medium risk of bias.Specifically, one of the studies was single-blinded (Bae et al. 2019).Whereas the other two were conducted such that minimal steps were taken to minimize functional unblinding because of differences in drug/placebo volume or procedure for either the placebo or GLP-1RA conditions (Ten Kluve et al. 2023, and Hanssen et al. 2021) (Fig. 2) [38][39][40].

Functional activation in obese individuals
Bae et al. ( 2019) assessed (among other outcomes of interest) obese subjects (BMI > 26 kg/m 2 ) observing high-calorie food images in fMRI scans [38].They found an increased activation of the hypothalamus, pineal gland, and parietal cortex.The change in regional brain activation was negligible in conditions of low-calorie food images.Furthermore, Bae et al. (2019) also noted an increase in the orbitofrontal cortex when exposed to high-calorie images compared to non-food images.More broadly, the visual cortex was activated when food images were compared to non-food images (p < 0.05).This study highlights how high-calorie food images can significantly influence brain activation in obese individuals.
Likewise, Van Bloemendaal et al. (2014) presented images showing food vs non-food conditions and comparisons between high and lowcalorie food conditions to obese, lean, and T2DM individuals under GLP-1RA pharmacological intervention conditions [41].In the placebo condition, obese individuals exhibited heightened bilateral activation in the insula and the right amygdala, unlike lean and T2DM individuals, particularly when exposed to images of food and high-calorie food (p <

Table 1
Inclusion and exclusion criteria.

Inclusion and exclusion criteria Inclusion criteria
• A primary or secondary study  (2015) reported that under placebo conditions, there was a positive correlation between BMI and the activation of the bilateral caudate nucleus (Rightp = 0.009, Leftp = 0.036) and putamen (Rightp = 0.041, Leftp = 0.041), as well as the right insula (p = 0.048) when participants anticipated receiving chocolate milk over a tasteless solution [42].These findings indicate a baseline difference in brain activation regarding reward behaviour due to increased BMI, independent of the effects of GLP-1RAs.

Energy intake and postprandial effects
Van Can et al. (2014) reported a decrease in overall levels of appetite and satiety in both the 1.8 and the 3.0 mg doses of subcutaneous liraglutide [43].The aforementioned changes were correlated with an approximate 16 % decrease in overall energy intake compared to placebo.Moreover, Van Can et al. (2014) reported that doses above 1.8 mg of liraglutide would reduce energy expenditure (p = 0.001) and the initial postprandial glycemia (p < 0.0001) and increase fat substrate oxidation (p value not reported); the finding of delayed gastric emptying was correlated with a decrease in appetite, and increased satiety (p = 0.03).These findings were consistent with Da Silva et al. (2011), and Farr et al. (2016), who reported participants had an increased sense of fullness after an infusion of GLP-17-36 amides and liraglutide, respectively [44,45].These results underline the effectiveness of liraglutide in managing appetite and energy intake.2011), who reported that GLP-1 RAs were superior to PYY3-36 amide subcutaneous administration in reducing overall energy intake, with a reduction in energy intake of 15.7 % ± 7.5 % and 12.3 % ± 11.2 %, respectively.A synergistic effect was observed with the co-administration of GLP-1RA and PYY3-36 amides, resulting in a 27.0 % reduction in energy intake [44].

Higher effort for higher rewards and task performance
Hanssen et al. (2021) saw that participants were more likely to exert higher effort for a higher reward, and resulted in liking the resultant reward (β = 0.016, t = 2.35, p = 0.02) [40].Namely, they reported that   Whether liraglutide administration affects neural responses to food cues in diabetic individuals fMRI scans were conducted to observe brain responses to images of highly desirable and less desirable foods and non-food items.Participants reported their liking for each image, and their hunger, fullness, and pleasantness ratings were measured.
• Brain Activation: Liraglutide reduced activation in the inferior parietal cortex, insula, and putamen in response to highly desirable food images.The impact of treatment within specified regions of the central nervous system (CNS), recognized for their significance in regulating feeding, stems from their involvement in CNS reward circuits.
Various doses of liraglutide and insulin glargine administered daily.fMRI scans assessed brain responses to food images.Blood glucose levels and energy intake were measured via a Librium buffet.

GLP-1 receptor and neurocortical activation and food cues
When obese individuals were injected with lixisenatide, Bae et al. (2019) reported a reduction in the frontal activation of the fusiform gyrus and the lateral ventricle when the participants were shown food cues that were of high-calorie food items, especially compared to images that were of non-food items (p < 0.05) [38].When van Bloemendaal et al. (2014) used exenatide to assess neurocortical responses to food cues in obese subjects [43], a decrease in the right amygdala and insula in all food vs non-food conditions was seen; these results were based on a placebo comparator in the same obese sample (amygdala: t(16) = 3.21, p = 0.007; insula: t(16) = 3.06, p = 0.0.025).When performing the same analysis comparing high-calorie foods to non-foods, they found a decrease in activation of the right insula (t(16) = 3.66, p = 0.007) and the left orbitofrontal cortex (t(16) = 3.10, p = 0.032).When considering obese patients with T2DM, there was a similar decreased activation in the bilateral insula (left: t = 2.64, p = 0.010; right: t = 3.19, p = 0.026; left: t = 3.54, p = 0.010; right: t = 3.74, p = 0.005), left putamen (t = 2.92, p = 0.032; t = 3.38, p = 0.015), and the right orbitofrontal cortex (t = 3.43, p = 0.009; t = 3.51, p = 0.011) in both the all-food and the high-calorie food conditions, respectively.These findings suggest consistent alterations in brain activation patterns across different food conditions and highlight the potential role of these brain regions in the pathophysiology of obesity and T2DM.
In healthy participants, De Silva et al. ( 2011) reported fasting responses to food images were reduced in the right insula when treated with a GLP-17-36 amides [44].Farr et al. (2016) found that liraglutide administration in persons with T2DM decreased activation in the inferior parietal cortex, insula, and putamen when shown highly desirable foods [45].However, these changes were not seen in the hypothalamus.
Overweight and T2DM patients were assessed by Ten Kuluve et al. (2016) on their response to high-calorie food pictures in insulin and Liraglutide conditions [39].In a fasted state, liraglutide showed significant reductions in the bilateral insula activation compared to the insulin condition (right p = 0.003, left p = 0.02).In a postprandial state, liraglutide showed a significant decrease in right putamen activation when patients were shown both food and high-calorie food images (food pictures; p = 0.02, high-calorie food pictures; p = 0.01).After ten days of treatment, postprandial liraglutide effects showed a decrease in the left putamen ((p = 0.05) and left amygdala (p = 0.01).Similarly, van

GLP-1 receptor and neurocortical activation and food intake and hunger
Regarding the effects of GLP-1RAs on food intake and hunger, most of the papers assessed presently analyzed the effects of this class of drugs.
Bae et al. ( 2019) reported that Lixisenatide reduced caloric intake in 59 % of lean and obese participants [38].Of those with reduced caloric intake, after Lixisenatide injection, activation of the posterior cingulate and medial frontal cortex was associated with baseline craving (r = 0.38, P = 0.02) and post-fMRI hunger (r = 0.31, P = 0.04) in the high versus low-calorie food contrast [38].Blundell et al. (2017) saw these changes partly contributed to the decrease in the appetite of the patients on Semaglutide (p = 0.0023), as well as better eating control and reduced cravings, as reported on the Control of Eating Questionnaire (COEQ) [46].COEQ scores also indicated these results were particularly prevalent for savoury foods; these foods were considered less pleasant when on Semaglutide.Moreover, the Leeds Food Preference Task (LFPT) highlighted participants decreased liking and wanting for high-fat and non-sweet foods (p = 0.0016; p = 0.0203, respectively), and a higher desire for low-fat and sweet foods (p = 0.0401).
Furthermore, based on findings by Lin et al. (2022), GLP-1RAs could normalize the glycemic variability brought by different food components such as fat, cholesterol, or protein [48], which affects the weight of food as a reward factor.The normalization was exemplified through the continuous overlapping net glycemic action at the 2 h (p = 0.049) and 4-hour rate (p = 0.020).Likewise, Da Porto et al. (2020) found decreased Binge Eating Scores (BES) when patients diagnosed with Binge Eating Disorder were treated with Dulaglutide compared to Gliclazide, a sulfonylurea (p < 0.0001) [49].Moreover, these findings directly correlated with reduced insulin resistance, as evidenced by both independent HbA1c values (p = 0.009) and a significant direct correlation between HbA1c and BES scores (p = 0.033).The reduction in hunger can also influence the motivational process, particularly evident in lean individuals, as illustrated by Hanssen et al. (2021), who reported that incentive motivation rose with higher levels of hunger (F (1, 42)= 5.31, p = 0.026, β = 0.19) [40].
Moreover, in T2DM patients, alterations in caloric intake were positively correlated with attenuation of the bilateral insula (left: p = 0.039; right: p = 0.011) right caudate (p = 0.046), bilateral insula (left: p = 0.035; right: p = 0.026), orbitofrontal cortex (left: p = 0.006; right: p = 0.040), and in the right caudate (p = 0.046) [42].Similarly, Farr et al. (2016) reported that hunger and appetite correlate with activation in the parietal and occipital cortex and the precuneus and the cuneus [45].In contrast, the pleasantness of food was correlated predominantly with the parietal cortex (p < 0.024).Interestingly, Ten Kluve et al. (2016) did not show any statistically significant correlation between brain activation and food intake from an ad liberum lunch buffet, nor did they show any significant correlation between hunger scores [39], even though these values were lower in the GLP-1RA condition.
Van Bloemendaal et al. ( 2015) reported placebo conditions resulted in a negative correlation between BMI and the right putamen upon receipt of a reward-such as chocolate milk-(p = 0.025) [42].Moreover,

Fig. 2. Risk of bias analysis (Cochrane risk of bias version 1).
in Exenatide conditions, exenatide increases brain activation upon receipt of chocolate milk.Specifically, lean subjects had increased activation of the right caudate nucleus (p = 0.05), obese subjects had increased activation of the right orbitofrontal cortex (p = 0.004), and obese subjects with a T2DM comorbidity had increased activation of the bilateral putamen(Left -p = 0.014, Rightp = 0.02), left insula (Anterior -p = 0.027, Posteriorp = 0.016, Anterior/Mid p = 0.004) and left amygdala (p = 0.008).All these changes in brain activation patterns highlight the potential role of these brain regions in the pathophysiology of obesity and T2DM.

Smoking and alcohol consumption
Prediabetic or overweight individuals with smoking habits were assessed by Yammine et al. (2020) [50].They reported that exenatide increased the patient's abstinence rate by 21.5 % in the GLP-1RAs group compared to the placebo group.Moreover, patients in the extended-release Exenatide cohort rated themselves lower on the Questionnaire of Smoking Urges (QSU) assessment, which analyses one's smoking urges and the anticipation of relief (PP= − 1.25; 95 % CI [− 4.34, 2.26] PP= 79.7 %).
Probst et al. ( 2023) secondary analysis on effects of Dulaglutide on alcohol consumption in a smoking sensation reported that Dulaglutide decreased alcohol consumption by 1.4 glasses per week (standard deviation (SD):3.7),and the placebo group reduced alcohol consumption by 0.1 glasses per week (SD: 6.3) [51] This decrease translated to a 29 % decrease in alcohol consumption compared to the placebo group (baseline alcohol intake adjusted relative effect= 0.71, 95 % CI= [0.52, 0.97], p = 0.04).However, a subgroup analysis revealed no significant between-group differences among heavy drinkers (characterized by females who consumed more than seven glasses of alcohol per week and males who drank more than 14 glasses per week).
Likewise, Klausen et al. (2022) found obese patients (BMI > 30) with Alcohol Use Disorder (AUD) had a reduction in heavy drinking by 23.6 % when treated with Exenatide (p = 0.034) [52].Interestingly, lean individuals (BMI < 25) with AUD had an increase in the number of heavy drinking days by 27.5 % (p = 0.024).Furthermore, AUD individuals-independent of BMI-experienced a notable decrease in cue reactivity to alcohol reward substances in the ventral striatum (p = 0.037), dorsal striatum (p = 0.019), and putamen (p = 0.037) after 26 weeks of Exenatide treatment compared to a placebo group (p = 0.025).These changes were also associated with decreased alcohol cravings, correlated with reductions in brain regions, including the left caudate, septal area, right middle frontal gyrus, temporal lobe, hippocampus, and parahippocampus.Moreover, at baseline, there was a significant difference between healthy and AUD patients in terms of cravings (p < 0.001), whereas at the endpoint, this difference became insignificant (p = 0.50).These findings highlight applications for GLP-1RAs regarding dysfunctional behaviours beyond food-related disorders.

Discussion
Herein, the analyses of the current clinical literature relating to GLP-1RAs and reward behaviours indicates that these agents modulate foodrelated reward behaviours, with consistent findings among the studies that GLP-1RAs reduce meal intake and the rewarding aspect of foodrelated stimuli.Preliminary evidence also supports a potential effect on substances of abuse, although mostly on individuals who have metabolic dysfunctions, such as obesity and T2DM.Insulin resistance has been shown to reduce baseline levels of dopamine, as well as dopamine synthesis, reuptake, turnover, and firing frequency [53,54].Consequently, normalizing insulin resistance with GLP-1RAs can remediate this impaired dopaminergic signalling.Specifically, dopaminergic function correlates with reward by enhancing positive emotions, such as enjoyment, thereby boosting motivational drive and subsequent anticipation of rewards upon re-exposure to the stimuli [55,56].This finding is exemplified by the behavioural updating observed in both studies by Hanssen et al.Additionally, prolonged insulin resistance has been shown to induce both anticipatory and consummatory anhedonia, which likewise mitigates the motivational drive of these individuals [57,58].Thus, the effects of GLP-1RAs in enhancing insulin signalling (as seen in the reduced postprandial glycemia levels) can likewise enhance motivational drives in these individuals.
Interestingly, however, while GLP-1RAs can indirectly improve dopaminergic signalling by remediating the deleterious effects of insulin signalling, the direct effects of GLP-1RAs on dopaminergic have contrary effects.Namely, preclinical evidence has shown that GLP-1 decreases excitatory synaptic strength of ventral tegmental area dopaminergic neurons on projections to the medial shell of the nucleus accumbens [59].These findings were correlated to the suppression of the intake of a high-fat diet [59].Both areas play pivotal roles in reward-driven behaviours [60].Similarly, while another pre-clinical study showed that GLP-1 amide increased dopaminergic uptake and expression, the amide was also responsible for increased neurotransmitter clearance [61].These findings highlight the importance of regulating the balance of dopamine both in reward function, and in day-to-day function.
The normalization of glycemic variability seen by Lin et al. (2022) can improve cognitive function, thereby increasing one's ability to interpret motivation-driven behaviours and cost-benefit analysis [62][63][64].This finding is further strengthened by the effects of normalizing glucose variability, which alleviates peripheral insulin resistance and modulates the effect of hunger on incentive motivation [40].Similarly, Blundell's finding of Semaglutide resulting in decreased cravings for high-fat foods and increased cravings for sweet foods can induce a physiological positive feedback loop.High-fat foods reduce the sensitivity of GLP-1 hormone and its signalling to the central nervous system [65].In contrast, sweet-tasting foods were shown to increase the release of GLP-1 [66].Thus, these foods can amplify the effects of GLP-1 in physiological processes.
From a neurobiological perspective, individuals with obesity at baseline showed a propensity to activate cortical regions associated with reward behaviours.Specifically, parietal cortex activation correlates with the ability to associate tasks and rewards and -as is the case with the study participants-process reward stimuli, i.e., the high-calorie images [67].At the same time, insular regions correlate with integrating reward information [68].Similarly, the putamen is responsible for associating the stimuli with the reward [69].Afterwards, the caudate utilizes this learned association and delineates the likelihood of receiving the reward stimuli (error prediction) [70].Thus, these findings highlight the reinforced neural circuits and activations that obese individuals have with food stimuli, resulting in a heightened reward stimuli potential.
Obesity is of particular interest as it is becoming more prevalent and has routinely been shown to be responsible for heightening the risk of developing various comorbidities such as MDD, dementia, or reproductive system dysregulation [71][72][73][74].Moreover, studies have shown that in cases of comorbid obesity and psychiatric diagnosis, there can be an additive effect of reward impairment in cases of monetary reward [75].Furthermore, the differences in activation between obese, lean, and T2DM individuals emphasize the impact insulin resistance and, more broadly, metabolic dysfunction -such as inflammation, has on cortical activation.Nonetheless, the negative correlation between receipt of chocolate milk and BMI and the positive correlation between anticipation and BMI indicates that metabolic dysfunction pertains more to deficits in hedonistic behaviours, including anticipatory hedonismand not learning behaviours.An alternate explanation is that GLP-1RA can normalize the prediction error deficits in the nucleus accumbens and the subcallosal area caused by insulin resistance, thereby minimizing the existing inflated valuation magnitude of the reward stimuli [47].
Further still, the effects of GLP-1RAs in minimizing brain areas associated with reward in obese and T2DM individuals might underscore the impact of this class of drugs on reducing dopaminergic signalling [59].However, a fuller understanding of the pathophysiological mechanisms of how GLP-1RAs normalize cortical activation in response to rewarding stimuli remains to be elucidated.These cortical findings also manifest behaviourally as these participants had decreased caloric intake and better control over their craving habits.However, it should be noted that these findings can also be attributed to GLP-1RA's effects on delaying gastric emptying, which results in prolonged satiety [76].
Understanding the impact of GLP-1RAs on reward behaviour may inform potential therapeutic avenues for treating motivation and reward-processing disorders, such as anhedonic states.This field of study can thus be widely applicable to the field of psychiatry, where anhedonic states are among the most common and most debilitating symptoms in disorders such as MDD [77][78][79].Moreover, the impact of GLP-1 and insulin resistance on brain function emphasizes the importance of viewing neuropsychiatric disorders from an interdisciplinary perspective that combines these conditions' neurobiological and metabolic perspectives.Consequently, exploring the role of GIP receptor agonists alongside GLP-1RAs presents a potential avenue for future research.GIP agonists have similar metabolic regulatory effects and may result in synergistic effects in conjunction with GLP-1RAs in modulating reward behaviours [80,81].Understanding these interactions could provide new insights into enhancing therapeutic outcomes in complex metabolic and neuropsychiatric disorders associated with reward and motivation dysfunction.
It should be noted that a limitation of this review and the literature, in general, is that a significant portion of this field focuses on food and substance reward behaviours.Nonetheless, as evidenced by the Hansen study, reward behaviours may exhibit common attributes across various stimuli, but these similarities are not entirely uniform.Consequently, different categories of rewards can elicit distinct effects on individuals.These differences can be based on reward valuation and arousal; thus, there will be differing reward behaviours relating to food, money, receiving time off, extracurricular hobbies, and time between decision and reward receipt.Hence, furthering the understanding of differences in motivation based on different reward stimuli and psychiatric states can broaden the potential future therapeutic applications of GLP-1RAs.Specifically, this can drive future research to focus on the implications of GLP-1RAs on regulating immediate reward motivation compared to delayed rewards (such as monetary-based rewards) or highlight more therapeutic potential in gambling disorders compared to obesity-related motivation dysfunction [15,82].Similarly, psychiatric conditions like MDD and Schizophrenia, which are more strongly linked to motivation-related dysfunction, underscore a greater pertinence to investigate the therapeutic potential of GLP-1RAs for these disorders [83].This is in contrast to psychiatric conditions such as Autism Spectrum Disorder or Generalized Anxiety Disorder, where reward and motivation-related dysfunction are less central, though still contribute, to the clinical syndrome and presentation [84,85].Overall, GLP-1RAs demonstrate potential as adjunctive treatments for reward-related dysfunction, highlighting their promise in developing novel therapies for motivation and reward-processing disorders.
RBM has received research grant support from the CIHR, the PSI Foundation, and the Baszucki Brain Research Fund and an Academic Scholars Award, Department of Psychiatry, University of Toronto.
Likewise, both Blundell et al. (2017) and Van Bloemendaal et al. (2014) analyses revealed a 24 % (− 3036 kJ) and 23.6 % decrease in ad libitum energy intake across all meals (p < 0.0001 and p < 0.05, respectively) [41,46].Furthermore, Blundell et al. (2017) observed the most significant decrease at lunch, with a reduction of 34 % energy intake (− 1255 kJ; p < 0.0001) and an average 5 kg reduction in body weight.Furthermore, Blundell et al. (2017) reported that individuals with T2DM had a reduced effect on GLP-1RA.Moreover, implicit liking was lower for high-fat and non-sweet foods (p = 0.0203) and higher for low-fat and sweet foods (p = 0.0401) with semaglutide compared to placebo.These findings accord with Da Silva et al. (

Table 2
Study characteristics.
N = 30 (BMI of 30 to 45 and HbA1c < 6.5 % ) Semaglutide effects on body weight loss, homeostatic levels (ad libitum energy intake, appetite and energy expenditure), gastric emptying, and hedonic ratings (food preference and food cravings) Randomized to subcutaneous injections of semaglutide or placebo weekly.Standardized meals, physical activity, and sleep were controlled.Appetite, food preference, cravings, and energy expenditure were measured.•Semaglutide significantly reduced energy intake across meals by 24 % and led to a 5 kg weight loss over 12 weeks.• Higher overall appetite suppression and increased satiety with semaglutide.• Reduced cravings and better control over eating, with lower liking for high-fat foods.• Correlation: Positive correlation between caloric intake changes and CNS responses.(continued on next page) S. Badulescu et al.