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What are the odds: Picking winners in the race to identify genetic components of gambling disorders

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Gambling can have large negative consequences on the social, personal and financial lives of people. Disordered gambling (DB) is a term used to describe people with clinically diagnosed gambling addiction and those with gambling tendencies which trend towards—but don’t yet meet—the clinical threshold for diagnosis. Diagnoses of DG are on the rise, increasing the need for scientists to develop validated animal gambling models for use in identifying root genetic components underlying this behavioral addiction.

In experiments by investigators at the University of Toronto and University of Calgary, the researchers identified genetic single nucleotide polymorphisms (SNPs) in humans with DG that are absent in control (non-DG) humans. Researchers genotyped the SNPs of 38 addiction-related genes in a large sample population: 400 DG and 345 non-DG subjects. Of the starting 38 addiction-related genes, two SNPs in two genes were significantly associated with the human disorder, DRD3 (rs167771) and CAMK2D (rs3815072). While it is possible that age and sex may impact the CAMK2D association with DG, the DRD3 association was robust regardless of other factors.

Next, the researchers ran a set of rats on a rat gambling task (rGT), and looked for correlations of impulsive and perseverative (continually choosing a bad option even after receiving negative feedback) behavior with the SNPs identified in the DG humans. The rGT is based on the Iowa Gambling Task, where subjects choose cards from one of four decks. The decks are stacked where some ‘bad’ decks offer big wins and bigger losses which lead to long term losses, while other ‘good’ decks offer small wins and smaller losses, leading to gains in the long run.1 Patients with different psychiatric illness including addiction, typically choose from the high reward yet ‘bad’ decks longer than normal controls. In the rGT, rats pick from four options and, rather than money, they receive food or sucrose rewards of variable amounts.  Instead of a monetary loss, rats receive a ‘time-out’, which increases the time between choices and cuts down on the overall number of rewards which can be earned.2 In the animal arm of these experiments, impulsive gambling as measured by the rGT was correlated with Drd3 expression, which remained significant even after Bonferroni correction. In situ hybridization demonstrated decreased Drd3 expression in the Islands of Calleja, and decreased amygdalar Camk2a while also illuminating increased Htr2a expression (serotonin receptor) in the cingulate and piriform cortex.

This study supports the content validity of the rGT and confirms the association findings in the human DG population. This research represents a major step forward in the field of addiction research by validating a pre-clinical animal model using human gene expression patterns. Aside from DG research, the cross-translational approach presented in this paper might be used to accelerate treatment development in other forms of addiction.


  1. Lobo DS et al. (2015) Addiction-related genes in gambling disorders: new insights from parallel human and pre-clinical models. Molecular Psychiatry 20:1002-1010. doi: 10.1038/mp.2014.113
  1. 1. Anderson SW et al. (1994) Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50:7-15. doi: 10.1016/0010-0277(94)90018-3
  2. 2. Winstanley CA (2011) Gambling rats: insight into impulsive and addictive behavior. Neuropsychopharmacology 36:359. doi: 10.1038/npp.2010.136