Elsevier

Physiology & Behavior

Volume 118, 13 June 2013, Pages 63-69
Physiology & Behavior

‘Food addiction’ and its association with a dopaminergic multilocus genetic profile

https://doi.org/10.1016/j.physbeh.2013.05.014Get rights and content

Highlights

  • Food addiction (FA) is associate with enhanced dopamine signaling.

  • Overeating facilitates relationship between FA and dopamine genetic markers.

  • FA appears to be a reward-responsive phenotype of obesity.

Abstract

Background

Our objective was to employ a novel genetic methodology – whereby functional variants of the dopamine pathway were aggregated to reflect a polygenic liability – in the study of food addiction. We anticipated that the composite index of elevated dopamine signaling (a multilocus genetic profile score [MLGP]) would distinguish those with a designation of food addiction (according to the Yale Food Addiction Scale [YFAS] criteria), and age and weight equivalent controls. Our second aim was to assess whether this index was positively associated with eating-related sub-phenotypes of food addiction (e.g. binge eating and food cravings).

Methods

Adults (n = 120) recruited from the community were solicited for an overeating/overweight study. Eating-behavior questionnaires were completed and a blood sample was taken for genotyping.

Results and conclusions

The YFAS identified 21 participants with food addiction. As predicted, the MLGP score was higher in those with YFAS-diagnosed food addiction, and it correlated positively with binge eating, food cravings, and emotional overeating. We then tested a multiple-mediation model proposing that reward-driven overeating facilitates the relationship between the MLGP score and food addiction. The model was statistically significant, supporting the view that the relationship between a composite genetic index of dopamine signaling and food addiction is mediated by certain aspects of reward-responsive overeating.

Introduction

While “behavioral addictions” have been recognized by scientists and clinicians for many years [1], they have only recently been endorsed by the American Psychiatric Association with the proposed classification of Addiction and Related Disorders in the new Diagnostic and Statistical Manual [DSM]-5 [2]. The DSM diagnostic shift is timely in light of growing evidence that excessive consumption of hyper-palatable food is an identifiable clinical entity with striking biobehavioral parallels to drug abuse [3], [4], [5]. Unfortunately, some discussions on this topic conflate obesity and overeating with ‘food addiction’, which tends to cloud its distinctiveness and muddle validation efforts.

Research has shown clearly that repeated consumption of high sugar/fat food can produce dopamine signaling changes in the brain which result in abnormally sustained stimulation of the reward system [6]. As we have seen from preclinical studies [7], over time, and when combined with intermittent periods of food restriction, a sugar-enhanced diet can lead to the same excessive pattern of intake, and the same behavioral symptoms, observable when animals are exposed to addictive drugs like heroin. A recent case–control study has also provided good human evidence that food addiction is a distinguishable syndrome with psychiatric co-morbidities and a psycho-behavioral profile remarkably similar to conventional drug-abuse disorders [8]. For example, two studies have shown that about half the obese adults who met criteria for food addiction according to the Yale Food Addiction Scale (YFAS) [9] were co-morbid for binge eating disorder (BED) [8], [10]. While there has been little study of the neurobiological similarities between YFAS-diagnosed food addiction and other drug-addiction disorders, supporting evidence can be found in related functional neuroimaging research. For instance, very tasty and attractive-looking food has shown reinforcing characteristics in the brain similar to those found from drugs of abuse, and the same brain changes reported for hedonic overeating are also seen in various types of addictions [11], [12], [13].

One of the striking features of addiction is that most individuals who take psychoactive substances do not develop dependence. This recognition has prompted efforts to identify a vulnerable phenotype whose predisposing traits determine the neuroplasticity induced by addictive behaviors [14]. Addiction is a dynamic and multistage process. Indeed, the transition from casual drug use to dependence has been described as a shift to the “dark side” — that is, from initial pleasure, to a need for the behavior to relieve the anhedonia that ensues from abstinence [15]. Therefore, it is highly unlikely that a homogeneous set of risk factors pertains to all phases of its development.

Variation in the sensitivity of brain reward circuitry has been the focus of many vulnerability studies. Some research indicates that a high responsiveness to the prospect or delivery of reward is a high-risk endophenotype for addiction because these individuals are novelty seekers and easily pleased by rewarding stimuli in their environment [16]. Other evidence supports the opposite view — that natural rewards inadequately activate hedonic tone in certain individuals because brain reward circuitry has diminished signaling strength [17]. It is further argued that since potent pharmacologic rewards provide a pleasing dopamine ‘boost’, the tendency to use these behaviors is increased. Efforts to reconcile the two perspectives have proposed that high reward sensitivity may be a risk during the initiation and escalation stages of addiction, but that the consequent dopamine-system down-regulation contributes to its maintenance and the proneness to relapse [15], [18].

Neuroimaging studies, which simply illustrate the current state of brain-circuitry activation, have mostly used case–control designs in addiction-risk research, constraining the ability to separate causal traits from consequences of the behavior [16]. Self-report measures of reward sensitivity are also limited by the incapacity to distinguish antecedents from outcomes in those with addiction disorders. By contrast, the study of genetic variation underlying addictions is able to address causality, and is grounded on the premise that exposure to various environmental influences – in combination with one's inherent biology – determines the initial response to drugs as well as the neuro-adaptations that contribute to the transition from casual use to the addicted state [19].

The increasing recognition that complex traits and behaviors are influenced by multiple genes has fostered the view that risk for common disorders is best considered in quantitative terms whereby relevant genetic variants can be aggregated to reflect a polygenic liability [20]. Nikolova et al. [21] were the first to use a biologically informed “multilocus genetic profile score” (MLGP) — a composite genetic index reflecting the influence of multiple functional polymorphic dopamine markers, which individually have been associated with variation in striatal dopamine signaling. They found that the MLGP score accounted for a greater proportion of variance in ventral striatum reactivity than did each locus considered independently.

Our first objective was to employ this novel genetic methodology to the study of food addiction by investigating whether functional genetic markers associated with elevated dopamine signaling distinguished those with YFAS-diagnosed food addiction from controls. Based on prior evidence that the former group have a greater hedonic responsiveness to food [8], we anticipated they would also have a higher MLGP score than their control counterparts. Our second aim was to assess whether the MLGP score was also positively associated with eating-related sub-phenotypes of food addiction, such as binge eating and food cravings, which have been identified in other research [8]. To test this hypothesis, we included an assessment of the five eating behaviors (viz. hedonically-driven eating, binge eating, emotional eating, food cravings, and snacking on sweets) that differentiated YFAS cases from controls in our recent study of food addiction [8].

Section snippets

Participants

One hundred and twenty adults (women: 82; men: 38) between the ages of 25 and 47 years took part in the study. Participants were recruited from posters placed at public institutions soliciting volunteers for an overeating/overweight study. Advertisements were also placed in local newspapers and online sites like CraigsList. Participants were required to have lived in North America for at least five years prior to their enrolment. Women were also required to be pre-menopausal as identified by the

Food addiction diagnosis

According to the YFAS diagnostic scoring procedure, 21 adults (female = 16; male = 5) were classified with food addiction.

Descriptive statistics and group differences

Prior to analysis, all data were screened for potential outliers and normality. None of the variables deviated significantly from normal, nor were there any univariate or multivariate outliers. Means and standard deviations for all quantitative variables are displayed in Table 2, listed separately by YFAS-diagnostic status.

As shown in Table 2, and as we predicted, the MLGP score

Discussion

This study is the first to investigate genetic differences between those with YFAS-food addiction and non-affected controls. As such, it offers fresh and supportive evidence that reward responsiveness is a high-risk endophenotype for this condition. The mediation model we tested demonstrated that enhanced dopamine-signaling, as implied by the proxy MLGP score, was significantly stronger in the food-addiction group than in controls, and that this relationship was mediated by greater food

Acknowledgments

This study was funded by a grant (MOP- 84257) from the Canadian Institute of Health Research.

Declaration of interests

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

References (56)

  • A. Meule et al.

    Women with elevated food addiction symptoms show accelerated reactions, but no impaired inhibitory control in response to pictures of high-calorie food-cues

    Eat Behav

    (2012)
  • J. Voisey et al.

    A DRD2 and ANKK1 haplotype is associated with nicotine dependence

    Psychiatry Res

    (2012)
  • J. Chen et al.

    Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain

    Am J Hum Genet

    (2004)
  • L.M. Williams et al.

    COMT Val108/158Met polymorphism effects on emotional brain function and negativity bias

    Neuroimage

    (2010)
  • A. Cepeda-Benito et al.

    The development and validation of the state and trait food-cravings questionnaires

    Behav Ther

    (2000)
  • D.G. Schlundt et al.

    The Eating Behavior Questionnaire predicts dietary fat intake in African American women

    J Am Diet Assoc

    (2003)
  • A. Meule

    Food addiction and body mass index: a non-linear relationship

    Med Hypotheses

    (2012)
  • J.M. Burmeister et al.

    Food addiction in adults seeking weight loss treatment. Implications for psychosocial health and weight loss

    Appetite

    (2013)
  • B.P. Bradley

    Behavioral addictions — common features and treatment implications

    Br J Addict

    (1990)
  • C. Holden

    Behavioral addiction debut in proposed DSM-5

    Science

    (2010)
  • Ő. Albayrak et al.

    Does food addiction exist? A phenomenological discussion based on the psychiatric classification of substance-related disorders and addiction

    Obes Facts

    (2012)
  • A.N. Gearhardt et al.

    An examination of the food addiction construct in obese patients with binge eating disorder

    Int J Eat Disord

    (2012)
  • Y. Zhang et al.

    Food addiction and neuroimaging

    Curr Pharm Des

    (2011)
  • J. Swendsen et al.

    Individual vulnerability to addiction

    Ann N Y Acad Sci

    (2011)
  • G.F. Koob et al.

    Plasticity of reward neurocircuitry and the ‘dark side’ of drug addiction

    Nat Neurosci

    (2005)
  • D.W. Hommer et al.

    Imaging brain response to reward in addictive behaviors

    Ann N Y Acad Sci

    (2011)
  • I. Maze et al.

    The epigenetic landscape of addiction

    Ann N Y Acad Sci

    (2011)
  • R. Plomin et al.

    Common disorders are quantitative traits

    Nat Rev Genet

    (2009)
  • Cited by (130)

    • Why haven't we solved the addiction crisis?

      2022, Journal of the Neurological Sciences
    View all citing articles on Scopus
    View full text