Genetics of Disordered Gambling
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1 Overview of talk Genetics of Disordered Gambling Wendy Slutske, Ph.D. Professor of Psychology University of Missouri Presented at the lberta Gaming Research Institute 11 th nnual Conference pril 13, 2012, Banff Canada definitions of terms evidence for genetic variation in susceptibility parsing the genetic variation in susceptibility psychopathology involvement searching for specific susceptibility genes Concept of liability distribution There are more sub-clinical (4.6%) than clinical (0.4%) cases of no pathological problems T1 T2 liability for subclinical pathological pathological disorder ents % of respond n=2,001 PG n=185 tx n= DSM-IV pathological : at least 5 of 10 symptoms Disordered : at least 1 of 10 symptoms Number of pathological symptoms Continuum of pathology susceptibility + availability =? liability for fewer risk factors more risk factors fewer consequences more consequences 1
2 ustralian Twin Gambling Study the twin study monozygotic twins dizygotic twins national sample of male and female pairs from the ustralian Twin Registry 4,764 individuals completed a structured diagnostic interview in ,355 (91%) completed a self-report questionnaire 1,312 (28%) provided blood/dn sample twins were years old at the time of the interview lifetime prevalence of DSM-IV PG = 2.2% (3.4%/1.2%) past-year prevalence of DSM-IV PG = 0.59% (0.98%/0.29%) lifetime prevalence of = 12.5% (18.2%/8.3%) 100% shared genes shared family environment compare similarity 50% shared genes shared family environment Sources of trait variation that can be estimated from twin data Genetic and environmental influences and risk () additive genetic influences: cumulative effect of genetic risk factors (C) shared family environment: environmental factors that twins share equally, such as childhood social class and religion, neighborhoods, characteristics of parents () nonshared (individual-specific) environment: environmental factors that are unique to a twin, such as the influence of different peers, spouses, traumatic events r retest r MZ r DZ C United States Men ustralia Men ustralia Women From: Slutske et al., 2001; Slutske et al., 2010 summary of genetic and environmental influences on parsing the genetic susceptibility for multivariate twin studies molecular genetic studies 50%? 50% availability?? 2
3 Parsing the genetic variation in risk Parsing the genetic variation in risk common with SB From: Slutske et al., 2000 common with alcohol dependence From: Slutske et al., 2001 common with D and SB Parsing the genetic variation in risk common with major depression susceptibility individual differences in involvement individual differences in non D D Data from Potenza et al., 2005 susceptibility stages in the career individual differences in involvement ever gambled/ abstinence participation in specific activities participation in types of activities versatility of frequency of (time spent) quantity of ($ spent) age of initiation of initiation occasional regular frequent 1 C
4 lifetime initiation of involvement susceptibility r retest r MZ r DZ C any initiation specific activity (four most common in ustralia) lottery pokies/slot machines horse or dog races casino table games individual differences in involvement ever gambled/ abstinence participation in specific activities participation in types of activities versatility of frequency of (time spent) quantity of ($ spent) age of initiation of From: Slutske et al., 2009 latent classes of involvement Twin concordance for class assignment past yea (pr ar involvement roportion) Gambling activity Kappa = 0.26 Kappa = 0.09 From: Savage et al., in preparation From: Savage et al., in preparation age first gambled Genetic and environmental influences and age of initiation 100 % Men (mean = 17.2) Women (mean = 18.3) r retest r MZ r DZ C Full sample Men Women ge first gambled Slutske et al., in preparation From: Honn et al., in preparation 4
5 Next steps susceptibility Develop and test models that better capture the stage-sequential unfolding of the genetic susceptibility for Wish list: Prospective longitudinal twin studies of? individual differences in involvement individual differences in Big Three dimensions of : Positive motionality Negative motionality Constraint and their lower-order components Positive motionality Individuals high in P have a lower threshold for the experience of positive emotions and for positive engagement in their social and work environments, and tend to view life as being essentially a pleasurable experience. Positive motionality Individuals high in P have a lower threshold for the experience of positive emotions and for positive engagement in their social and work environments, and tend to view life as being essentially a pleasurable experience. Primary scales: Well-being Social Potency Social Closeness chievement extraversion Negative motionality Negative motionality Individuals high in N have a low general threshold for the experience of negative emotions such as anxiety and anger, and tend to break down under stress. Individuals high in N have a low general threshold for the experience of negative emotions such as anxiety and anger, and tend to break down under stress. Primary scales: Stress Reaction lienation ggression neuroticism 5
6 Constraint Constraint Individuals high on the dimension of Constraint tend to endorse conventional social norms, avoid thrills, and act in a cautious and restrained manner. Individuals high on the dimension of Constraint tend to endorse conventional social norms, avoid thrills, and act in a cautious and restrained manner. Pi Primary scales: Self Control Harm voidance Traditionalism low impulsivity low risk-taking Dunedin Multidisciplinary Health and Development Study Predicting at age 21 from age 18 longitudinal study of a complete birth cohort born in Dunedin, New Zealand between pril, 1972 and March, 1973 N=1,037 96% study retention at age 32 0 birth age 32 birth MPQ profiles at age 18 and at age 21 Personality predictors of High negative emotionality including stress reaction, alienation and aggression Low behavioral control including low self control and harm avoidance These are similar to the predictors of other (substance-related) addictive disorders MPQ Scale MPQ Superfactor From: Slutske et al.,
7 Which came first, the chicken or the egg? Predicting in adulthood from age 3 temperament birth ge 3 temperament ge 3 temperament and adult Behavioral observations of temperament undercontrolled restless short attention span willful impulsive emotionally labile impersistent negativism withdraws from tasks inhibited fearful shy flat affect self-critical negativism requires attention withdraws from tasks impersistent birth From: Slutske et al., in press ge 3 under-control and adult unadjusted adjusted ge 21 and 32 composite ge ge (Cell entries are odds ratios) So, which came first? Ruled out Still possible But what about? X g From: Slutske et al., in press 7
8 multivariate twin studies multivariate twin studies Daniel Sedin Henrik Sedin Daniel Sedin Henrik Sedin univariate (within-trait) twin correlations within-twin (cross-trait) correlations multivariate twin studies Cross-sectional correlates of among adult twins Daniel Sedin Henrik Sedin cross-twin (cross-trait) correlations Slutske et al., under review MPQ lower-order dimensions MPQ higher-order dimensions Cross-sectional correlates of among adult twins Cross-sectional correlates of among adult twins Slutske et al., under review MPQ lower-order dimensions MPQ higher-order dimensions Slutske et al., under review MPQ lower-order order dimensions MPQ higher-order dimensions 8
9 Personality and : new findings in women Personality and : new findings in men CON P N P N CON Slutske et al., under review Slutske et al., under review summary of genetic and environmental influences on Next steps there have not yet been any replicated findings about specific genes Determine the extent to which individual differences in can explain the genetic overlap between and other psychiatric disorders Confirm genetic associations with availability? Overlaps with alcohol dependence, antisocial behavior disorders, major depression, and parsing the genetic susceptibility for multivariate twin studies molecular genetic studies Genome-wide scans might be more powerful if gene hunters deliberately recruit samples selected for known exposure to environmental risks for the disorder they wish to study. From Moffitt,
10 Cross-national comparison of gaming machines xpenditure on gaming machines per adult ($U) Gaming machines per 10,000 adults Maximum average loss per hour ($U) the human genome ~25,000 genes arranged on 23 chromosomes Canada United Kingdom United States New Zealand ustralia From: How ustralia Compares, 2004 approaches to gene identification candidate gene association studies based on a single, or a handful of polymorphisms hypothesis-driven only a handful of previous studies of (see review by Lobo & Kennedy, 2009) ) genome-wide association studies covers the entire genome with ~ 1-2 million polymorphisms (SNPs) exploratory/atheorical only one genome-wide study (Lind et al., in press) genome-wide association study of a quantitative trait Item (top 5 shown) Factor loading Gambling versatility (0-11) SOGS #6 (felt had a problem) DSM #10 (relied on others for money) DSM #3 (unsuccessful efforts to control) DSM #4 (restless/irritable when attempting to control) plus 26 other diagnostic and 3 frequency items From Lind et al., in press Manhattan plot of GWS SNP results gene associations TXN1 VLDLR MT1X closest genes FZD10 only suggestive evidence for several novel gene associations 80% power to detect genes accounting for > 3% of the variation in the g trait genetic susceptibility to is likely due to common variants of small effect found associations with sets of candidate genes or those involved in known biological pathways From Lind et al., in press 10
11 Conclusions susceptibility to has genetic underpinnings in both men and women may be attributable in part to genetic contributions to individual differences in involvement may be attributable in part to genetic contributions to individual differences in normalrange traits or childhood temperament Conclusions, continued the search for specific susceptibility genes is still in its infancy genetic susceptibility to is likely due to many common variants, each of small effect future work will require larger sample sizes, cross-institutional collaborations, and replication acknowledgements QIMR colleagues Nicholas Martin, Ph.D. (Co-I) Gu Zhu, M.D., Ph.D. Penelope Lind, Ph.D. interviewers IT staff Consultants lex Blaszczynski, Ph.D. Rachel Volberg, Ph.D. MU colleagues Madeline Meier, Ph.D. Jarrod llingson, M Leah Richmond-Rakerd, M Jeanne Savage Laura Honn Thomas Piasecki, Ph.D. Funding from United States National Institute of Mental Health grant MH
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