1. Neurogenetics Section, Problem Gambling Service Centre for Addiction and Mental Health - University of Toronto Functional variants in the dopamine D2-like receptors are associated with lower risk for gambling behaviour in healthy Caucasian subjects Daniela S. S. Lobo M.D., Ph.D, Renan P. Souza Ph.D., Ryan P. Tong B.Sc., David M. Casey Ph.D., David C. Hodgins Ph.D., Garry J. Smith Ph.D., Rob J. Williams Ph.D., Don P. Schopflocher Ph.D., Rob T. Wood Ph.D., Nady el-Guebaly M.D., James L. Kennedy M.D.

2. Pathological Gambling - Phenotype behavioural addiction (Marks, 1990) behavioural addiction (Marks, 1990) high impulsive traits high impulsive traits high comorbidity rates high comorbidity rates degrees of severity – continuum (Eisen et al., 1998, 2001) degrees of severity – continuum (Eisen et al., 1998, 2001) 3-4 DSM criteria = Problem Gambling (~6%) 3-4 DSM criteria = Problem Gambling (~6%)  5 DSM criteria = Pathological Gambling (~2%)  5 DSM criteria = Pathological Gambling (~2%)

3. Why Dopamine Receptor Genes?

4. Dopamine Receptors and Reward Mechanisms Two types of Dopamine (DA) receptors Two types of Dopamine (DA) receptors D1- like: DRD1 and DRD5 D1- like: DRD1 and DRD5 D2-like: DRD2, DRD3, DRD4 D2-like: DRD2, DRD3, DRD4 DA is the main neurotransmitter involved in substance and behavioural addictions DA is the main neurotransmitter involved in substance and behavioural addictions Changes in DA receptors in the brain have been observed through imaging techniques in individuals who have addictive disorders. Changes in DA receptors in the brain have been observed through imaging techniques in individuals who have addictive disorders.

5. To evaluate whether genetic variants in the dopaminergic receptors could be used as susceptibility markers of gambling behaviour in healthy subjects using the Problem Gambling Severity Index (PGSI) derived from the Canadian Problem Gambling Index (CPGI). To evaluate whether genetic variants in the dopaminergic receptors could be used as susceptibility markers of gambling behaviour in healthy subjects using the Problem Gambling Severity Index (PGSI) derived from the Canadian Problem Gambling Index (CPGI). Objectives

6. Methods Sample Lifestyle, and Lifecycle Project Lifestyle, and Lifecycle Project First wave of data collection: 1,372 adult subjects were assessed, with 325 subjects providing consent to participate in the genetic arm of the study First wave of data collection: 1,372 adult subjects were assessed, with 325 subjects providing consent to participate in the genetic arm of the study Only Caucasians included (242 subjects) Only Caucasians included (242 subjects) Assessment (instruments used in this study) Assessment (instruments used in this study) CIDI CIDI CPGI CPGI Demographic data Demographic data

7. Methods Genotyping: The TaqIA/rs1800497 alters D2 receptor density (Jonsson et al., 1999;Neville et al., 2004).The TaqIA/rs1800497 alters D2 receptor density (Jonsson et al., 1999;Neville et al., 2004). Located in the ankyrin repeat and kinase domain containing 1 gene (ANKK1) (Neville et al., 2004). Located in the ankyrin repeat and kinase domain containing 1 gene (ANKK1) (Neville et al., 2004). Two other functional variants in the DRD2 gene (BstNI/ rs1799732 and C957T/ rs6277) have been reported to affect D2 receptor availability (Hirvonen et al., 2009a; Hirvonen et al., 2009b; Jonsson et al., 1999). Two other functional variants in the DRD2 gene (BstNI/ rs1799732 and C957T/ rs6277) have been reported to affect D2 receptor availability (Hirvonen et al., 2009a; Hirvonen et al., 2009b; Jonsson et al., 1999). The DRD3 rs6280 (Ser9Gly). The Gly9 variant presents increased dopamine affinity – “gain-of function effect”The DRD3 rs6280 (Ser9Gly). The Gly9 variant presents increased dopamine affinity – “gain-of function effect”

8. Methods Statistical Analysis:Statistical Analysis: General Linear Model with and without covariatesGeneral Linear Model with and without covariates Analysis of combined variants of genes (haplotypes)Analysis of combined variants of genes (haplotypes) Estimate of sample power:Estimate of sample power: 94% power to detect PGSI variations as low as 0.45 assuming that genetic variations account for 5% of the variance in PGSI scores94% power to detect PGSI variations as low as 0.45 assuming that genetic variations account for 5% of the variance in PGSI scores

9. Results Final sample: 242 subjects (PGSI 0-7)Final sample: 242 subjects (PGSI 0-7) 90 males + 152 females90 males + 152 females Mean PGSI score = 0.53 ± 1.18Mean PGSI score = 0.53 ± 1.18 Mean Age = 46.6 ± 16 yearsMean Age = 46.6 ± 16 years Gender: PGSI scores not significantly differentGender: PGSI scores not significantly different Younger age associated with higher PGSI scoresYounger age associated with higher PGSI scores

10. Results DRD3 MscI/ rs6280 – Ser9 alleleDRD3 MscI/ rs6280 – Ser9 allele P = 0.03P = 0.03 corrected by age P = 0.01, F = 3.629, R 2 = 0.05corrected by age P = 0.01, F = 3.629, R 2 = 0.05 Subjects with this variant have lower PGSI.

11. Results Association (p= 0.005) of the haplotype with lower PGSI scores in healthy subjects Association (p= 0.005) of the haplotype with lower PGSI scores in healthy subjects rs11604671 – G or A rs4938015 – C or T rs2303380 – A or G

12. Discussion Comings et al. (Comings et al., 1996) reported association of PG with allele T of TaqIA/ rs1800497;Comings et al. (Comings et al., 1996) reported association of PG with allele T of TaqIA/ rs1800497; More recent studies suggest that variants on ANKK1 and NOT the TaqIA are associated with addictive disorders (Gerlernter et al., 2006, Yang et al., 2008)More recent studies suggest that variants on ANKK1 and NOT the TaqIA are associated with addictive disorders (Gerlernter et al., 2006, Yang et al., 2008) Haplotype composed by the opposite alleles in the same three variants (rs11604671-rs4938015-rs2303380) have been associated with increased risk for nicotine dependence in two populations (Gerlernter et al., 2006)Haplotype composed by the opposite alleles in the same three variants (rs11604671-rs4938015-rs2303380) have been associated with increased risk for nicotine dependence in two populations (Gerlernter et al., 2006)

13. Discussion From a clinical standpoint… Symptoms of PG fluctuate over time and several questions remain as to whether individuals with subclinical levels of PG will present a higher rate of progression to PG compared to non-gamblers (LaPlante et al., 2008), which can be influenced by numerous environmental factors such as availability of gambling venues, and significant life-events that could promote behavioural change.Symptoms of PG fluctuate over time and several questions remain as to whether individuals with subclinical levels of PG will present a higher rate of progression to PG compared to non-gamblers (LaPlante et al., 2008), which can be influenced by numerous environmental factors such as availability of gambling venues, and significant life-events that could promote behavioural change.

14. Discussion From a biological standpoint… Subjects who gamble at least 25 times in a year but have never developed any symptoms of PG genetic factors account for 35% of the varianceSubjects who gamble at least 25 times in a year but have never developed any symptoms of PG genetic factors account for 35% of the variance Subjects with 1, 2, or 3 symptoms of PG in their lifetime - contribution of genetic factors is estimated to be 48%, 54%, and 67% respectively (Eisen et al., 1998).Subjects with 1, 2, or 3 symptoms of PG in their lifetime - contribution of genetic factors is estimated to be 48%, 54%, and 67% respectively (Eisen et al., 1998).

15. From a clinical and biological standpoint Genes are not single determinants of human behaviours. Genes can contribute to traits that will influence human behaviour.Genes are not single determinants of human behaviours. Genes can contribute to traits that will influence human behaviour. We only evaluated the genetic risk component of the gene-environment interplayWe only evaluated the genetic risk component of the gene-environment interplay

16. Acknowledgments Natalie Freeman Olga Likhodi Maria Tampakeras Ontario Problem Gambling Research Centre (“Factors influencing the development of responsible gaming”), (“Factors influencing the development of responsible gaming”), Alberta Gaming Research Institute Alberta Gaming Research Institute (“Leisure, Lifestyle, Lifecycle Project”), Canadian Institutes of Health Research (RPS is holder of Postdoctoral Fellowship #93967). (RPS is holder of Postdoctoral Fellowship #93967).