Food Reinforcement, the Dopamine D 2 Receptor Genotype, and Energy Intake in Obese and Nonobese Humans

Department of Pediatrics, University at Buffalo, State University of New York, Buffalo, NY 14214-3000, USA.
Behavioral Neuroscience (Impact Factor: 2.73). 11/2007; 121(5):877-86. DOI: 10.1037/0735-7044.121.5.877
Source: PubMed


The authors measured food reinforcement, polymorphisms of the dopamine D2 receptor (DRD2) and dopamine transporter (DAT1) genes, and laboratory energy intake in 29 obese and 45 nonobese humans 18-40 years old. Food reinforcement was greater in obese than in nonobese individuals, especially in obese individuals with the TaqI A1 allele. Energy intake was greater for individuals high in food reinforcement and greatest in those high in food reinforcement with the TaqI A1 allele. No effect of the DAT1 genotype was observed. These data show that individual differences in food reinforcement may be important for obesity and that the DRD2 genotype may interact with food reinforcement to influence energy intake.

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Available from: Richard W Erbe, Oct 02, 2015
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    • "As those studies did not directly measure the reinforcing effectiveness of food per se, a behavioral economic analysis could possibly resolve apparent inconsistencies. Additionally, using foods high in fat and sugar, one study reported higher rates of food-maintained responding in human subjects with genetic markers associated with lower DA D 2 R number (Epstein et al, 2007). Possibly the role of DA D 2 Rs in the reinforcing effects of food varies with the type of food. "
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    ABSTRACT: Previous studies suggest dopamine (DA) D2-like receptor involvement in the reinforcing effects of food. To determine contributions of the three D2-like receptor subtypes, knockout (KO) mice completely lacking DA receptors (D2R, D3R, or D4R KO mice) and their wild-type littermates were exposed to a series of fixed-ratio (FR) food-reinforcement schedules in two contexts: an open economy with additional food provided outside the experimental setting and a closed economy with all food earned within the experimental setting. A behavioral-economic model was used to quantify reinforcer effectiveness with food pellets obtained as a function of price (FR schedule value) plotted to assess elasticity of demand. Under both economies, as price increased, food pellets obtained decreased more rapidly (i.e., food demand was more elastic) in DA D2R KO mice compared to WT littermates. Extinction of responding was studied in two contexts: by eliminating food deliveries and by delivering food independently of responding. A hyperbolic model quantified rates of extinction. Extinction in DA D2R KO mice occurred less rapidly compared to WT mice in both contexts. Elasticity of food demand was higher in DA D4R KO than WT mice in the open, but not closed, economy. Extinction of responding in DA D4R KO mice was not different from that in WT littermates in either context. No differences in elasticity of food demand or extinction rate were obtained in D3R KO mice and WT littermates. These results indicate that the D2R is the primary DA D2-like receptor subtype mediating the reinforcing effectiveness of food.Neuropsychopharmacology accepted article preview online, 24 July 2015. doi:10.1038/npp.2015.223.
    Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 07/2015; DOI:10.1038/npp.2015.223 · 7.05 Impact Factor
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    • "Relative reinforcing value can be studied using laboratory tasks or selfreport questionnaires (e.g., Amlung & MacKillop, 2014; MacKillop et al., 2008, 2010; Rousseau et al., 2011). Relative reinforcing value of food has mainly been studied using laboratory tasks where participants are placed on a concurrent reinforcement schedule and work for access to food vs. a non-food related activity (e.g., Epstein et al., 2007; Temple, Legierski, Giacomelli, Salvy, & Epstein, 2008). Consistent with behavioral economic theory, experiential craving (e.g., in response to cues) increases RRV of a preferred drug (Amlung, Acker, Stojek, Murphy, & Mackillop, 2011; MacKillop et al., 2008, 2010). "
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    ABSTRACT: Eating patterns that lead to overconsumption of high fat, high sugar (HFHS) foods share similar features with addictive behaviors. Application of addiction paradigms, such as stress inductions, cue reactivity and behavioral economic assessments, to the study of motivation for HFHS food consumption may be a promising means of understanding food consumption. To date, few studies have investigated the interaction of stress and environmental cues on craving, and no study leveraged the state relative reinforcing value of foods (RRVfood) under varying conditions of affective states, the foci of the current study. This study used a mixed factorial design (Mood Induction: Neutral, Stress; Cues: Neutral, Food) with repeated measures on time (Baseline, Post-Mood Induction, Post-Cue Exposure). Participants (N=133) were community adults who endorsed liking of HFHS snacks but denied eating pathology. The primary DVs were subjective craving and RRVfood. Negative and positive affect (NA, PA), the amount of food consumed, and latency to first bite were also examined. Participants in the Stress condition reported no change in craving or RRVfood. Exposure to food cues significantly increased participants' craving and RRVfood, but an interaction of stress and cues was not present. Participants did not differ on how many calories they consumed based on exposure to stress or food cues, but participants in the food cues condition had a shorter latency to the first bite of food. This study highlights the importance of environmental cues in food motivation. It also demonstrates the utility of using RRVfood to further characterize food motivation. Copyright © 2015. Published by Elsevier Ltd.
    Appetite 05/2015; 92. DOI:10.1016/j.appet.2015.05.027 · 2.69 Impact Factor
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    • "Food reinforcement (RRV food ) refers to the motivation to eat, and is cross-sectionally related to increased energy intake in laboratory and usual intake situations [1] [2], body mass index (BMI) and obesity in children and adults [3] [4] and predicts body fat [5] and weight gain [5] [6] in children and adults. The fat mass and obesity-associated (FTO) gene has been related to elevated BMI [7] [8] [9] and increased energy intake [10] [11] [12] [13] in adults and children [14] [15]. "
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    ABSTRACT: Food reinforcement (RRVfood) is related to increased energy intake, cross-sectionally related to obesity, and prospectively related to weight gain. The fat mass and obesity-associated (FTO) gene is related to elevated body mass index and increased energy intake. The primary purpose of the current study was to determine whether any of 68 FTO single nucleotide polymorphisms (SNPs) or a FTO risk score moderate the association between food reinforcement and energy or macronutrient intake. Energy and macronutrient intake was measured using a laboratory ad libitum snack food consumption task in 237 adults of varying BMI. Controlling for BMI, the relative reinforcing value of reading (RRVreading) and proportion of African ancestry, RRVfood predicted 14.2% of the variance of energy intake, as well as predicted carbohydrate, fat, protein and sugar intake. In individual analyses, six FTO SNPs (rs12921970, rs9936768, rs12446047, rs7199716, rs8049933 and rs11076022, spanning approximately 251 K bp) moderated the relationship between RRVfood and energy intake to predict an additional 4.9 – 7.4% of variance in energy intake. We created an FTO risk score based on 5 FTO SNPs (rs9939609, rs8050136, rs3751812, rs1421085, and rs1121980) that are related to BMI in multiple studies. The FTO risk score did not increase variance accounted for beyond individual FTO SNPs. Rs12921970 and rs12446047 served as a moderators of the relationship between RRVfood and carbohydrate, fat, protein, and and sugar intake. This study shows for the first time that the relationship between RRVfood and energy intake is moderated by FTO SNPs. Research is needed to understand how these processes interact to predict energy and macronutrient intake.
    Physiology & Behavior 06/2014; 132. DOI:10.1016/j.physbeh.2014.04.029 · 2.98 Impact Factor
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