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Genetic Studies of Gambling Disorder Marc N. Potenza, M.D., Ph.D. Professor of Psychiatry, Child Study, and Neurobiology Director, Yale Gambling Center of Research Excellence (CORE) Director, Women and Addictions Core, Womens Health Research at Yale Senior Scientist, The National Center on Addiction and Substance Abuse Yale University School of Medicine

Genetic Studies of Gambling Disordereasg.org/media/file/lisbon2016/presentations/14-09...Sep 14, 2016  · Bivariate Biometric Model for PPG & AD A PPG C PPG E PPG E AD C A AD PPG

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  • Genetic Studies of Gambling

    Disorder

    Marc N. Potenza, M.D., Ph.D.

    Professor of Psychiatry, Child Study,

    and Neurobiology

    Director, Yale Gambling Center

    of Research Excellence (CORE)

    Director, Women and Addictions Core,

    Women’s Health Research at Yale

    Senior Scientist, The National Center on

    Addiction and Substance Abuse

    Yale University School of Medicine

  • Disclosures

    • Consultant to Lundbeck, Ironwood, Shire,

    INSYS, Rivermend Health, Lakelight

    Therapeutics/Opiant and Jazz Pharmaceuticals

    • Research Grants from National Center for

    Responsible Gaming

    • Research Gift from Mohegan Sun

    • Consultant to Gambling and Legal Entities on

    Issues Related to Impulse Control Disorders

    EASG, Sept 14, 2016

  • Overview

    • Genetics of Gambling Disorder

    • Heritability & ACE Estimates from Twin Studies

    • Molecular Genetic Studies

    • Allelic Variation and Behavioral and Brain

    Responses (Endophenotypes and

    Transdiagnostic Considerations)

    • Conclusions

    EASG, Sept 14, 2016

  • Heritability: Genetic and

    Environmental Contributions

    • Many Conditions Including Gambling Disorder

    Aggregate within Families

    • Greater Likelihoods of Conditions in Individuals with

    Affected Family Members May Reflect Either

    Environmental or Genetic Factors or Both

    • Twin Studies Offer the Opportunity to Estimate the

    Degree to Which Specific Conditions (and Their Co-

    Occurrences) May Reflect Environmental or Genetic

    Contributions (Shah et al., 2005)

    EASG, Sept 14, 2016

  • Twin Studies

    • Classic Studies Assume Rearing of Twins in Similar

    Environment

    • Equal Environment Assumption and Possible

    Overestimation of Genetic Contributions (Shah et al.,

    2005)

    • Data May be Modeled to Estimate Genetic (A), Shared

    Environmental (C), and Unique Environmental (E)

    Contributions

    • E Also Includes Error Estimation

    EASG, Sept 14, 2016

  • Twin Datasets: VET-R and

    Australian Twin Samples• Several Large Samples of Twins Have Assessed for

    Pathological Gambling Using DSM Criteria

    • Vietnam Era Twin Registry (VET-R; Eisen et al, 1998)

    • Australian Study (Slutske et al, 2010)

    • Each Dataset Has Strengths and Limitations

    • VET-R Comprised of Over 7000 Male Twins Serving

    During Time of Vietnam Era Conflict

    • Australian Sample Smaller But Has Both Men and

    Women and Molecular Genetic Measures

    EASG, Sept 14, 2016

  • Association Between PG and MD

    in VET Sample

    Variable OR (95% CI) p-value

    Alcohol Abuse/Dependence 2.7 (1.5, 4.7) 0.001

    Drug Abuse/Dependence 1.9 (1.0, 3.3) 0.04

    Antisocial Personality D/O 2.5 (1.1, 5.5) 0.02

    Generalized Anxiety D/O 3.0 (1.3, 6.5) 0.007

    Major Depression 2.0 (1.1, 3.4) 0.02

    NS = Age, Income, HS Education, College Education,

    Nicotine Dependence, PTSD, Panic D/O

    Unadjusted OR for MD = 4.1 (2.6-6.5)

    OR for MD Adjusting for Sociodemographics = 4.1 (2.6-6.5)

  • Bivariate Biometric Model for PG & MD

    Potenza et al, 2005, Arch Gen Psychiatry

  • Bivariate Biometric Model for PG & GAD

    Giddens et al, 2011, J Affect Dis

    APG

    CPG

    EPG

    EGAD

    AGAD

    CGAD

    PG GAD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.53*

    PG 0.65* 0.0 0.35* rC=0.0

    GAD 0.38* 0.0 0.62* rE=0.0

    EASG, Sept 14, 2016

  • Bivariate Biometric Model for PG & PD

    Giddens et al, 2011, J Affect Dis

    APG

    CPG

    EPG

    EPD

    APD

    CPD

    PG PD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.34*

    PG 0.64* 0.0 0.36* rC=0.0

    PD 0.43* 0.0 0.57* rE=0.31*

    EASG, Sept 14, 2016

  • Bivariate Biometric Model for PG & AD

    Slutske et al, 2000, Arch Gen Psychiatry

    APG

    CPG

    EPG

    EAD

    AAD

    CAD

    PG AD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.35*

    PG 0.64* 0.0 0.36* rC=0.0

    AD 0.55* 0.0 0.45* rE=0.26*

    EASG, Sept 14, 2016

  • Bivariate Biometric Model for PPG & AD

    APPG

    CPPG

    EPPG

    EAD

    AAD

    CAD

    PPG AD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.45*

    PPG 0.49* 0.0 0.51* rC=0.0

    AD 0.55* 0.0 0.45* rE=0.16*

    Slutske et al, 2000, Arch Gen PsychiatryEASG, Sept 14, 2016

  • Bivariate Biometric Model for PPG & ND

    Xian et al, 2014, Addiction

    APPG

    CPPG

    EPPG

    END

    AND

    CND

    PPG ND

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.22*

    PPG 0.49* 0.0 0.51* rC=0.0

    ND 0.61* 0.0 0.39* rE=0.24*

    EASG, Sept 14, 2016

  • Bivariate Biometric Model for PPG & CAD

    Xian et al, 2014, Addiction

    APPG

    CPPG

    EPPG

    ECAD

    ACAD

    CCAD

    PPG CAD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.32*

    PPG 0.48* 0.0 0.52* rC=0.0

    CAD 0.28* 0.34 0.39* rE=0.36*

    EASG, Sept 14, 2016

  • Bivariate Biometric Model for PPG & SAD

    Xian et al, 2014, Addiction

    APPG

    CPPG

    EPPG

    ESAD

    ASAD

    CSAD

    PPG SAD

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.32*

    PPG 0.50* 0.0 0.50* rC=0.0

    SAD 0.54* 0.0 0.46* rE=0.0

    EASG, Sept 14, 2016

  • OC Latent Classes

    • PG and PPG Typically Co-Occur at Elevated Odds with

    Multiple Forms of Psychopathology (Consistent with

    VET-R Findings)

    • Population-Based Studies Do Not Support Increased

    Odds Between PPG and OCD (Cunningham-Williams et

    al, 1998)

    • Transdiagnostic Measure of Compulsivity Linked to

    PPG / Addictive Disorders (Fineberg et al, 2014)

    • Latent Classes of OC Features Differing Qualitatively

    and Quantitatively Identified in Follow-up Survey of

    VET-R Participants and Linked to PPG (Scherrer et al,

    2015)

    EASG, Sept 14, 2016

  • OC Latent Classes

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    rituals

    compulsions

    repeang

    everordering

    hoarding

    violentimages

    concerngerms

    luckynumbers

    symmetrical

    fearillness-contaminaon

    endorsementprobab

    ility

    Class1(64.1%)

    Class2(20.8%)

    Class3(7.9%)

    Class4(7.2%)

    Class 1 – Low OC Class 2 – Symmetry / Order / Rituals

    Class 3 – Germs / Contamination / Rituals Class 4 – High OC

    Scherrer et al, 2015, JAMA PsychiatryEASG, Sept 14, 2016

  • Odds Ratios Reflecting

    OC Class / GD Relationships

    C2 v C1 C3 v C1 C4 v C1

    No Criteria 1 1 1

    1+ Criteria 2.2* 1.6* 3.4*

    0-3 Criteria 1 1 1

    4+ Criteria 2.0* 2.0# 3.1*

    Scherrer et al, 2015, JAMA PsychiatryEASG, Sept 14, 2016

  • Bivariate Biometric Model for GD & OC

    Scherrer et al, 2015, JAMA Psychiatry

    AGD

    CGD

    EGD

    EOC

    AOC

    COC

    GD OC

    rE

    rC

    rA

    Parameter Estimates from Best Fitting Models

    a2 c2 e2 rA=0.44*

    GD 0.64* 0.0 0.36* rC=0.0

    OC 0.37* 0.0 0.63* rE=0.0

    EASG, Sept 14, 2016

  • Summary of VET-R Findings

    • Greater Genetic Contributions to More Stringently

    Thresholded Levels of Problem/Pathological Gambling

    in Men (Eisen et al, 1998)

    • Co-occurrences Between (P)PG and MD, GAD, SAD and

    OC Classes Appear Linked to Predominantly Genetic

    Factors

    • Co-occurrences Between (P)PG and PD, AD, ND and

    CUD Appear Linked to Both Environmental and Genetic

    Factors

    EASG, Sept 14, 2016

  • Australian Twin Findings

    • Similar Genetic and Environmental Contributions to

    PPG in Men and Women (Slutske et al, 2010)

    • Genetic Contributions to Gambling Age of Onset

    Greater in Men than in Women; Shared Environmental

    Factors Greater in Women (Richmond-Rakert et al,2013)

    • Genetic Factors Linked to Temperament and ODD May

    Explain Link Between Gambling Age of Onset and

    Gambling Problems (Slutske et al, 2014)

    • Local Area Disadvantage May Increase Likelihood of

    Genetic Expression of Propensity to Gamble and

    Develop Gambling Problems (Slutske et al, 2015)

    EASG, Sept 14, 2016

  • Molecular Genetic Studies• Most Studies Small or Not Well Characterized or Both

    (Leeman and Potenza, 2013)

    • 2 GWAS (for GD) Published to Date With No Findings

    Surviving Genome-Wide Significance Thresholding for

    Individual Sites (Lind et al, 2013; Lang et al, 2016)

    • Suggestive Significance for Non-Exonic Regions Close

    to MT1X, ATXN1, and VLDLR (Lind et al, 2013)

    • Significant Findings for Polygenic Risk Score for

    Alcohol Dependence and For Pathways Relating to

    Huntington’s Disease, AMPK Signalling, and Apoptosis

    (Lang et al., 2016)

    EASG, Sept 14, 2016

  • Allelic Variants with Known

    Functional Correlates: COMT

    • COMT Val-158-Met Allelic Functional Variation with

    Met Allele Associated with 40% Less Enzymatic

    Activity, Higher Dopamine Levels in the PFC and in

    Some Cases Better Cognitive Functioning (Grant et al,

    2013)

    • In Proof of Concept Study, Treatment Outcome to

    Tolcapone (A COMT Inhibitor) was Found to Be

    Associated with Val-158-Met Status and Linked

    Preliminarily to Fronto-parietal Circuitry Function

    (Grant et al, 2013)

    EASG, Sept 14, 2016

  • Yale Department of Psychiatry Grand Rounds - March 21, 2003

    Tolcapone Treatment

    Outcome by COMT Genotype

    Grant et al, 2013, Eur NeuropsychopharmEASG, Sept 14, 2016

  • Yale Department of Psychiatry Grand Rounds - March 21, 2003

    Changes In Fronto-Parietal

    Activation With Tolcapone Tx

    Grant et al, 2013, Eur NeuropsychopharmEASG, Sept 14, 2016

  • Allelic Variants with Known

    Functional Correlates: DBH• DBH, a Gene Whose Enzymatic Product is Involved in

    Dopamine / Norepinephrine Conversion, Has a Functional

    Allelic Variant rs1611115 Associated with 35%-52% of

    Enzymatic Activity (Cubells et al, 2000)

    • TT Individuals Have Lowest Enzymatic Activity and CC

    Highest, With CT Individuals Showing Intermediate Levels

    (Zabetian et al, 2001)

    • T Carriers Have Been Found to Demonstrate Less Empathy,

    Lower Conscientiousness, Higher Neuroticism, More

    Novelty-Seeking and Greater Drug-Use Severity (See Yang

    et al, in press)

    EASG, Sept 14, 2016

  • DBH Allelic Variation and Emotional

    and Motivational Responses• We Investigated in 43 Individuals (18 PG – 9 T Carrier, 9 CC;

    25 HC – 14 T Carrier, 11 CC) Subjective and Brain

    Responses to Films of Sad, Gambling and Cocaine Content

    (Yang et al, in press)

    • We Hypothesized and Observed A Main Effect of DBH

    Genotype on Subjective Responses to the Sad Tapes

    (Greater in CC: 6.88(1.7) Vs. T Carrier: 5.22(2.3); p=.035),

    Suggestive of A Transdiagnostic/Endophenotypic Feature

    (Yang et al, in press)

    • We Hypothesized and Observed Main Effects of DBH and

    Interactive DBH-by-Condition Effects on Cortico-limbic-

    Striatal Brain Activations

    EASG, Sept 14, 2016

  • Yale Department of Psychiatry Grand Rounds - March 21, 2003

    A

    Main Effect of DBH

    z = -8z = -11 z = -4 z = -1

    mOFC vmPFC

    F-value

    4.09

    16.54

    Amygdala

    VentralStriatum

    R

    Main Effect of DBH

    CC Individuals Show Greater Activation Than Do T Carriers

    Yang et al, in press, J Behav AddictionEASG, Sept 14, 2016

  • Yale Department of Psychiatry Grand Rounds - March 21, 2003

    ADBH x Condition

    z = - 4 z = 5

    Hippocampus

    Putamen

    R L

    F-value

    3.12

    11.14

    DBH-by-Condition Effect

    CC Individuals Relative to T Carriers Show Greater

    Recruitment of Thalamus, Putamen, Insula, Hippocampus,

    dlPFC, ACC and PCC During Sad Tapes

    (No Differences in Responses to Other Tapes)

    Yang et al, in press, J Behav AddictionEASG, Sept 14, 2016

  • Conclusions & Future Directions• Significant Progress Has Been Made in

    Understanding the Genetics of Pathological Gambling / Gambling Disorder

    • Gene-by-Environment Studies Providing Insight

    • More GWAS Studies Are Needed to Identify Genetic Regions Linked to Gambling Disorder

    • Understanding the Molecular Genetic Contributions to Gambling Disorder and Clinical Features That May Represent Therapeutic Targets May Help Prevention and Treatment Strategies

    • Similar Studies in Other Behavioral Addictions Are Needed

    EASG, Sept 14, 2016

  • AcknowledgmentsDiv Substance Abuse

    Bruce Rounsaville

    Kathleen Carroll

    Suchitra Krishnan-Sarin

    Stephanie O’MalleyEt al

    Gambling Center

    Of Excellence

    Iris Balodis

    Corey Pilver

    Sarah Yip

    Justin Wareham

    Scott Bullock

    Shane Kraus

    Monica Solorzano

    Ardeshir Rahman

    Yvonne Yau

    And Many Others!

    Women & Addictions

    Carolyn Mazure

    Rani Desai

    Et al

    NIH (NIDA, NIAAA, ORWH) VA CASAColumbia WHR DMHAS NCRG Moh Sun

    Imaging

    Todd Constable

    Godfrey Pearlson

    Rajita Sinha

    Bruce Wexler

    Robert Fulbright

    Cheryl Lacadie

    Patrick Worhunsky

    Jiansong Xu

    Judson Brewer

    Hedy Kober

    Elise DeVito

    Michael Stevens

    Bao-Zhu Yang et al

    Translational

    Jane Taylor

    R. A. Chambers

    Genetics

    Joel Gelernter

    Seth Eisen

    Hong Xian

    Jeff Scherrer

    Justine Giddens

    Wendy Slutske

    Kamini Shah et al

    RCTs

    Jon Grant

    SW Kim et al

    CT Partnerships

    Marvin Steinberg & CCPG

    Loreen Rugle & PGS