Gene-Environment Interplay in Alcoholism (and other substance use disorders): Presentation to Yale CTNA April 24, 2006

1. Gene-Environment Interplay in Alcoholism (and other substance use disorders): Presentation to Yale CTNA April 24, 2006 Do Not Copy Slides Without Permission From Dr. Heath Andrew C. Heath, D.Phil. Midwest Alcoholism Research CenterDepartment of Psychiatry Washington University School of Medicine

2. Presenter’s Disclosure of Interest • Sources of Research Support as PI • 1. HD049024 (R01) • 2. AA07728 (R37) • 3. AA13321 (R01) • 4. AA11998 (P50) • 5. AA07580 (T32) • 6. AA015210 (R01) • 7. AA09022 (R01) from the National Institute of Child Health and Human Development and the National Institute on Alcohol Abuse and Alcoholism. Name & Presentation Date: Andrew C. Heath, D.Phil., April 24, 2006 • Consulting Relationships • -- Palo Alto VA (Jacob) • Stock Equity (> $10,000) • -- NONE • Speaker’s Bureau(s) • -- NONE

3. Genetic Epidemiology of Alcoholism Understanding, in the general population, the complex interplay of genetic and environmental risk-factors in determining (a) differences in alcoholism risk, (b) the comorbidity of alcoholism with other disorders, and (c) differences in the course of alcohol problems and associated outcomes through time.

4. AUSTRALIA: OZ '81 • AUSTRALIAN 1981 (‘Older’) TWIN COHORT(Heath, Martin, Bucholz, Madden et al.) • Recruited from volunteer twin panel • Mostly born 1940-1964 (N=5,995 interviews) • Spouses also interviewed (N=3,814 interviews); now interviewing the offspring generation. • Subsample underwent alcohol challenge testing (N=412) • Also used to identify informative sibships for gene-mapping efforts (Madden NAG; Heath/Todd/ Martin/Whitfield Alcohol IRPG).

5. AUSTRALIA – OZ '89 • AUSTRALIAN 1989 TWIN COHORT(Heath, Martin, Bucholz, Madden, et al.) • Born 1964-1971 (N=6,250 interviews) • Recruited from volunteer twin panel, enrolled when children • Heavy drinking cohort, with high rates of alcohol problems in women as well as men! • Just starting to interview the offspring generation. • Also used to identify informative sibships for gene-mapping efforts.

6. U.S.A.: VETS • VIETNAM-ERA TWIN PANEL (VETS) (Tsuang, Eisen, True, Jacob, Bucholz, et al.) • Identified through military service in the Vietnam Era • All male twin panel (N=6712 interviews in Harvard Drug Study) • Follow-up assessments of offspring of alcohol dependent and control pairs (Jacob, True) and of drug dependent and control pairs (Bucholz)

7. U.S.A.: MOAFTS MISSOURI ADOLESCENT FEMALE TWIN STUDY (MOAFTS)(Heath, Madden, Bucholz, et al.) • Ascertainment from birth records • Parent intake interviews with cohorts of twins aged 11, 13, 15, 17, 19 (n=3666 parents, 2190 families) • Twin intake interviews at 13, 15, 17, 19 (N=3702 twins, 1799 complete pairs) • Continued follow up of twin birth cohort through age 25 (N=3780 – including new participants) • New NICHD-funded follow up focused on mating, reproducing & parenting.

8. WHY STUDY ALCOHOLISM? • “Ideal phenotype” for studying the complex interplay of genetic factors, environmental risk mechanisms. • Important clinical & public health problem.

9. WHY EMPHASIZE ALCOHOL PROBLEMSIN WOMEN? • Early studies relatively uninformative about genetic influences on risk of alcohol problems in women; • Increasing rates of female alcohol use, problems, drinking to intoxication in recent cohorts; • Women are usually custodial parents – importance of female alcohol abuse/dependence for GxE interaction? Implications for risk to offspring in next generation?

10. WHY AUSTRALIA?: AUSTRALIAN 1989 COHORT (“90/70” COHORT) • 90% of men have consumed 9 or more standard drinks in a day • 70% of women have consumed 7 or more standard drinks in a day • <1% of men, even fewer women, lifetime abstainers

11. HISTORY OF INTOXICATION:AUSTRALIAN FEMALE TWINS

12. HISTORY OF HEAVY DRINKING (5+ in day)AUSTRALIAN FEMALE TWINS

13. PART ONE CRITICAL PERSPECTIVES ON THE BEHAVIORAL GENETIC LITERATURE ON ALCOHOLISM

14. A “Medical Genetic” model of alcoholism a) Threshold model b) Multiple-threshold model UNAFFECTED UNAFFECTED AFFECTED MILD SEVERE CASES CASES Alcoholism Risk Alcoholism Risk

15. Assumptions of Strong “Medical Genetic” Model • To understand the familial transmission of alcoholism, it is sufficient to understand the underlying GENETIC mechanisms. • We can ignore environmental influences as we investigate genes that contribute to risk. REALLY?

16. Genotype x Environment Interaction The importance of genetic influences may be greatly increased under some environmental conditions, and decreased under others – beyond what would be predicted from the average effects of genetic, environmental risk-factors in the population. = statistical interaction. Same caveats apply.

17. Risk = Genes + Environment+ Genes x Environment

18. In the beginning …Pioneering Danish Adoption Study • At least in males, risk of alcoholism appeared to be genetically transmitted within families (Goodwin et al, 1973)

19. Swedish (Stockholm) Adoption Study- Temperance Board Registrations (Cloninger et al, 1981, 1988, and reanalyzed in Heath et al, 1997)

20. Stockholm Adoption Study: Unlike-Sex Relative Data Temperance Board Registrations Tetrachoric correlation = 0.17 ± 0.11

21. Genetic and Environmental Variance Estimates in the Stockholm Adoption Study Additive Genetic 95% Confidence Variance Interval % Pooled: 37 19-56 Significance of genotype x gender interaction: X2 = 1.51, d.f. = 3, p = 0.68. NOTE: No significant association of adoptee and adoptive parent temperance board registration(s), suggesting family environment effects unimportant.

22. Adoption Study Findings for Alcoholism Danish; Swedish (Bohman, Cloninger, Sigvardsson); Iowa (Cadoret) • Alcohol outcomes in adopted-away offspring (female as well as male) correlate with alcoholism/antisocial personality disorder in biological parents, NOT (usually) with psychopathology of adoptive parents. • Suggests intergenerational transmission of alcoholism may be determined by genetic transmission, not environmental transmission. • In general, evidence for genotype x environment interaction effects at best equivocal: almost no robust, replicated examples. • No significant evidence for genotype x gender interaction – genetic effects equally important in women and men, but sometimes too few women included, given lower base rate of alcohol problems in women, to allow significant effects to be found.

23. Warning !!! • In the Stockholm Adoption Study, 32% of biological fathers and 4.7% of biological mothers of adoptees had one or more temperance board registrations. • Approximately 14% of Swedish males from the general population had at least one temperance board registration. • Fewer than 4% of adoptive families had one or more parents with at least one temperance board registration. i.e., Adoptees tend to come from high-risk genetic backgrounds, are exposed to low risk rearing environments. Not ‘ideal’ for GxE analyses. • Most of the information from adoption studies is about biological FATHER alcoholism.

24. Example Twin Study: Virginia Twin Study – DSM-IIIR Alcohol Dependence: Female Like-Sex Pairs Lifetime Risk to cotwin of an Recurrence Risk N Prevalencea (%) alcohol-dependent twin (%) Ratio MZ pairs 590 8.1 31.6 3.9 DZ pairs 440 10.2 24.4 2.4 a Proportion of individuals reporting a history of alcohol dependence. (Kendler et al, 1992)

25. Female Like-Sex Twin Correlations for DSM IIIR Alcohol Dependence:Virginia Twin Study (Kendler et al, 1992, reanalyzed)

26. Estimating Parameters of aSimple Genetic Model

27. Genetic and Environmental Variance Components: Alcohol Dependence in Women (Virginia Twin Study)(WITH CONFIDENCE INTERVALS!) (Kendler et al, 1992, reanalyzed)

28. Estimates of Genetic andEnvironmental Variances:(Australian 1981 Cohort, N=5995 twins)(DSM-IIIR Alcohol Dependence) 95% Variance (%) Confidence Interval Additive Genetic 64 32 - 73 Shared Environment 1 0 - 27 Non-Shared Environment 35 27 - 47 NOTE: No genotype x gender interaction: X2 = 0.38, d.f. = 1, p = 0.54 (Heath et al., 1997).

29. Estimates of Genetic andEnvironmental Variances: (Australian 1989 Cohort, N=6250 twins) DSM-IV Alcohol Dependence 95% Variance (%) Confidence Interval Additive Genetic 53 32 - 61 Shared Environment 0 0 - 16 Non-Shared Environment 47 39 - 55 NOTE: No genotype x gender interaction (X2 = 1.61, d.f=3, p=0.66) (Knopik et al., 2004) Controlling for sociodemographic variables and prior psychiatric history reduces heritability minimally.

30. We can elaborate this simple model by jointly modeling (probit) regressions on hypothesized mediating variables of alcoholism risk, estimating residual genetic and environmental effects (and, in principle, G x E interaction effects).

31. Predictors of Alcoholism Risk(1989 Cohort) Gender ↑ risk in males Education ↑ risk in early school leavers Religion ↓ risk with religious involvement Depression ↑ risk Conduct Disorder ↑ risk Childhood sexual abuse ↑ risk (Women only) (Knopik et al, 2004)

32. Unadjusted versus Adjusted Genetic Variance Estimates Unadjusted (95% CI) Adjusted (95% CI) 53% 33-61% 47% 28-55%

33. Shared Environmental Variance Estimates Unadjusted (95% CI) Adjusted (95% CI) 0 0-15 0 0-14

34. BEWARE: SIMPLIFYING ASSUMPTIONS!!

35. Hidden Assumption: 1 • Unless environmental moderators are assessed and included in our models Confounding of genetic effects and genotype x shared environment interaction effects

36. Contributions of Genetic, Shared Environment, Genotype x Shared Environment Interaction Effects to Twin/Sib Resemblance

37. Confounding of GxSE Interaction Applies Equally to Sibling Data with Genetic Marker Information i.e. GxSE can be very helpful – if we can identify the environmental conditions under which genetic effects are especially strongly amplified.

38. Shared Environmental Variance Estimates Unadjusted (95% CI) Adjusted (95% CI) 0 0-15 0 0-14

39. Estimates of Genetic andEnvironmental Variances: (Meta-analysis of U.S. data) “Alcoholism” variously defined 95% Variance (%) Confidence Interval Additive Genetic 58 43 - 67 Shared Environment 2 0 – 16 NOTE: No genotype x gender interaction (X2 = 0.49, d.f=3, p=0.92)

40. Estimating a Model Allowing for Genetic Non-Additivity

41. Hidden Assumption 2 Strong genetic non-additivity could mask shared environmental influences in the classical twin design, producing zero estimates for shared environmental variance across multiple studies. ASSUMED ABSENT.

42. We can conduct a sensitivity analysis, fixing different assumed values of the shared environmental variance, and estimating the dominance ratio, i.e. the ratio of non-additive to additive genetic variance, as a free parameter, to determine whether significant shared environmental variance is plausible.

43. Sensitivity Analysis: Alcohol Dependence

44. PART TWO RECONSIDERING GENE-ENVIRONMENT INTERPLAY IN ALCOHOLISM – A WORK IN PROGRESS

45. What’s wrong with the “medical genetic” model for alcoholism?? • By oversimplifying our model for alcoholism inheritance, it may cause us to overlook complexity, or to infer complexities (e.g., Gene-environment interactions) where none exist. • It tempts us to neglect the importance of environmental influences in alcoholism; • It may cause us to miss opportunities for gene-discovery (by NOT stratifying on environmental exposure).

46. ENVIRONMENTAL INFLUENCES? • GENDER (why have rates of nicotine dependence in men versus women converged, but not rates of alcohol dependence?) • COHORT differences • PRE-NATAL (& PRE-CONCEPTION) influences • EARLY CHILDHOOD TRAUMA (e.g., childhood physical & sexual abuse) • OTHER CHILDHOOD ENVIRONMENTAL influences (e.g. parental divorce) • Etc etc etc

47. SOME SIMPLE QUESTIONS (1) Can genetic factors EVER explain cohort differences in rates of alcoholism? (2) In the general community, do male alcoholics or female alcoholics on average report faster progression from first intoxication to onset of alcohol dependence? (3) … do alcoholics reporting early-onset of alcohol use or alcoholics reporting later onset of alcohol use (e.g. age 13 versus age 18) have faster progression to alcohol dependence? (4) If we match on history of alcohol use (level of consumption), are women more likely to develop alcohol problems or men? (5) Replace gender in (2)-(4) by other hypothesized environmental modifiers of alcoholism risk, e.g. CSA, or psychiatric risk-factors or comorbid conditions (e.g., nicotine dependence).

48. Characterizing Gene-Environment Interplay: Five Routes to Increased Risk • Timing of exposure – age at onset of alcohol use; • Amount of exposure – quantity consumed; • Dependence vulnerability – risk differences, controlling for exposure history; • Delayed desistance – persistence in excessive or problem drinking; • Psychiatric comorbidity, via (1) – (4).