GeneEnvironment Interplay in Alcoholism

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 Resea
rch CenterDepartment of Psychiatry
Washington University School of Medicine
2
Presenters Disclosure of Interest
Name Presentation Date Andrew C. Heath,
D.Phil., April 24, 2006

• 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.

• Consulting Relationships
• -- Palo Alto VA (Jacob)
• Stock Equity ( 10,000)
• -- NONE
• Speakers 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 (N5,995 interviews)
• Spouses also interviewed (N3,814 interviews)
  now interviewing the offspring generation.
  
• Subsample underwent alcohol challenge testing
  (N412)
  
• 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 (N6,250 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 (N6712 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 (n3666 parents, 2190
  families)
  
• Twin intake interviews at 13, 15, 17, 19 (N3702
  twins, 1799 complete pairs)
  
• Continued follow up of twin birth cohort through
  age 25 (N3780 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
  

11
HISTORY OF INTOXICATIONAUSTRALIAN 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 DependenceVirginia 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, N5995
twins)(DSM-IIIR Alcohol Dependence)
95 Variance () Confidence Interval Addi
tive 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, N6250
twins)
DSM-IV Alcohol Dependence
95 Variance () Confidence Interval Addi
tive 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.f3, p0.66) (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
Confounding of genetic effects and genotype x
shared environment interaction effects

• Unless environmental moderators are assessed and
  included in our models

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 Addi
tive Genetic 58 43 - 67 Shared Environment 2 0
16
NOTE No genotype x gender interaction
(X2 0.49, d.f3, p0.92)
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

• Whats 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).

49
(No Transcript)
50
(No Transcript)
51
(No Transcript)
52
(No Transcript)
53

• Part A GxE Interaction Psychiatric Comorbidity

54
True for depression?

• Major depression is a familial disorder, and
  its familiality mostly or entirely results from
  genetic influences.
  
• (Sullivan et al., 2000, Am J Psychiatry)

55

• Kendler et al, 1993
• Comorbidity between MD (Major Depression) and
  alcoholism in women is substantial, and appears
  to result largely from genetic factors that
  influence the risk to both disorders.

56
There Are Good Reasons to Anticipate Important
Environment Effects Associated with Parental
Alcoholism

• because parental alcoholism is a major predictor
  of high-risk environmental exposures, from
  conception to young adulthood.
  
• high risk exposures are especially likely if
  biological mother is alcoholic.
  
• fetal alcohol and tobacco exposure
• family socioeconomic disadvantage, divorce
• childhood physical, sexual abuse, other early
  trauma
  
• parent-parent, parent-child conflict
• impaired parental supervision, high-risk peers.

57
Intergenerational Influences on Psychiatric
Comorbidity??
PARENTAL ALCOHOLISM
OFFSPRING GENETIC RISK OF DEPRESSION
OFFSPRING HIGH-RISK ENVIRONMENTAL EXPOSURES
OFFSPRING DEPRESSION
(Simplified from Heath Nelson, 2002)
58
Genetic and Environmental Contributions to Major
Depression RiskMeta-Analysis Results
95 Confidence Interval Genetic Variance 37
31-42 Shared Environmental Variance 0 0-5 Non-S
hared Environmental Variance 63 58-67
(Sullivan et al., 2000, Am J. Psychiat)
59
Major Depression Risk in Australian Women
Australian Adult Twin Surveys
1981 Cohort 1989 Cohort
95 CI 95 CI Genetic Variance 44 29-53 35 1
3-44 Shared Environmental Variance 0 0-12 0 0-17
Non-Shared Environmental Variance 56 47-65 65 56-
74 (Bierut, et al., 1999, Arch Gen Psychiatry
Heath, et al., unpublished)
60
Sensitivity Analysis Australian Twin Study, 1989
Cohort(Female like-sex pairs, Major Depression)
61
A More Direct Approach

• Can we identify indices of family environmental
  risk that are strongly associated with outcomes
  of interest?

62
Early Trauma Exposure in MOAFTS and Depression
Risk
NCS traumatic events experienced by age 13
(European Ancestry)
Polyserial correlation with depression 0.37
(95 CI 0.31-0.42)
63
Association between Maternal Alcoholism (by
Parent Report) and Offspring Early Trauma
Exposure (by Offspring Report)
?2135.27, p?2117.41, p 64
Association between Paternal Alcoholism (by
Parent Report) and Offspring Early Trauma Exposure
?2123.19, p?210.07, p0.9
65
A More Direct TestGenetic and Environmental
Variance Estimates for Early Trauma
CountEuropean Ancestry
i.e., we appear to be indexing environmental risk
(but have not yet completely excluded possibility
of confounding with genetic risk in parents).
66
Genetic and Environmental Variance Estimates for
Early Trauma CountAfrican Americans
67
Genetic Risk-Factors for Alcohol Dependence(in
parents)
Genetic Risk Factorsfor Depression(in parents)
Parental AlcoholDependence
Parental Depression
??
Genetic Risk-Factors for Depression(in children)
High-Risk EnvironmentalExposure of Children
Genetic Risk-Factors forAlcohol Dependence(in
children)
Interactive Effect of GeneticVulnerability to
DepressionHigh-Risk Environmental Exposure
Alcohol Dependence(in children)
Depression(in children)
??
68
Estimating the Effects of Genotype x Environment
Interaction
Note We control simultaneously for the overall
regression of offspring risk on parental
alcoholism (to control for GE correlation effects
associated with parental alcoholism).
69
Genotype x Environment Interaction in
Depression 1989 Twin Cohort (Cohort 2)
70
Genotype x Environment Interaction in
Depression Australian 1981 Twin Cohort (Cohort
1)
A Replication!
71
Danish Adoption Study

• Goodwin, Schulsinger, Knop, Mednick Guze
  (1977)
  
• Neither group (adopted away daughters of
  alcoholics, controls) had higher (than general
  population) rates of psychopathology, e.g.,
  depression. However, daughters of alcoholics
  raised by their biological parents had
  significantly more depression.

72
Iowa Adoption Study

• Major depression in females was predicted by an
  alcoholic diathesis only when combined with the
  disturbed adoptive parent variable.
  
• (Cadoret et al, 1996 Am J Psychiat 153892-9)

73
UPDATE

• High-risk environmental exposures associated with
  parental alcoholism may be important
  (inter-generational) contributors to the observed
  comorbidity of alcohol use and other psychiatric
  disorders.

74
PART B

• G-E Interplay and the Initiation of Substance Use

75
Genetic and shared environmental variance
estimates for early-onset substance use (by age
14) in MOAFTS
76
Genetic and shared environmental variance
estimates for early-onset substance use (by age
14) in MOAFTS
77
Onset of At-Risk Drinking in the Australian Twin
Panel (1989 Cohort)

• Earlier of
• (a) drinking to intoxication
• (b) drinking monthly for six months or longer
  (regular drinking)

78
Age-at-Onset Distribution in Australian Women
Born 1964-1971
79
Age-at-Onset Distribution in Australian Men Born
1964-1971
80
Lifetime Prevalence of Alcohol Dependence in
Women, by age-of-onset of at-risk drinking
81
Lifetime Prevalence of Alcohol Dependence in Men
82
Crude Association of Alcohol Dependence Rates
with Age-at-Onset of At-Risk Drinking
Women OR 5.2 (3.3-8.1) Men OR 2.6
(1.9-3.7)
83
Years of At-Risk Drinking as a Function of
Age-at-Onset
84
Cumulative incidence of alcohol dependence as
function of years of at-risk drinking, stratified
by age at onset
85
(No Transcript)
86
SOME SIMPLE QUESTIONS

• (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?

87
Heaths Paradox (!)

• Alcoholics who start at-risk drinking earlier
  have delayed onset of alcohol dependence.

88
(No Transcript)
89
(No Transcript)
90
Hazard Ratios as a Function of Age Onset of
Alcohol Dependence
91
SOME SIMPLE QUESTIONS

• (2) In the general community, do male alcoholics
  or female alcoholics on average report faster
  progression from first alcohol use to onset of
  alcohol dependence?

92

• IT DEPENDS
• On the distributions of age at initiation of
  drinking in women versus men
  
• AND the shape of the hazard distributions for
  onset of alcohol problems in women versus men.

93
Delay from Onset of Alcohol Use to Onset of
Alcohol Dependence 1989 Cohort
Women 6.5 Years (N535) Men 6.6 Years (N851)
94

• DOES FAMILIAL RISK OF ALCOHOLISM INFLUENCE TIMING
  OF ONSET OF ALCOHOL USE?

95
YES, BUT THROUGH FAMILY NON-INTACTNESS(Note
All analyses of US data-sets control for
ethnicity)
96
Percentage of EA families in MOAFTS where family
dissolution has occurred, as a function of
alcoholism assessed by maternal report vs twin
report
97
(No Transcript)
98
(No Transcript)
99
Contrast Groups

• Parental Status
• Divorced, parental alcoholism
• Divorced, no parental alcoholism
• Never married, parental alcoholism
• Never married, no parental alcoholism
• Still married, parental alcoholism
• Still married, no parental alcoholism
  comparison group

100
MOAFTS Hazard Ratios as a function of parental
alcoholism and marital status First alcohol use
(Waldron et al, unpublished)
101
MOAFTS Hazard Ratios as a function of parental
age and marital status First alcohol use
(Waldron et al, unpublished)
102
MOAFTS Age at First Intoxication
(Waldron et al, unpublished)
103
MOAFTS Age at First Intoxication
(Waldron et al, unpublished)
104
MOAFTS Age at First MJ Use
(Waldron et al, unpublished)
105
MOAFTS Age at First Sex
(Waldron et al, unpublished)
106
Update

• In the MOAFTS birth cohort (female twins)
• Parental divorce or never marriage is strongly
  associated with very early alcohol illicit drug
  use
  
• This association is especially strong in families
  with a parental history of alcoholism
  
• Parental alcoholism, in intact families, is not
  an important predictor of very early onset
  substance use
  
• Early (voluntary) sexual behavior shows a similar
  pattern of association potential mediator?

107
Impact of divorce and/or parental alcoholism on
very early-onset alcohol use women,
NESARC(Hazard Ratios)
(Waldron et al, unpublished)
108
Impact of divorce and/or parental alcoholism on
very early-onset alcohol use men,
NESARC(Hazard Ratios)
109

• What are potential confounders in relationship
  between parental marital status and early
  substance involvement?
  
• Severity of parental alcoholism
• Number of alcoholic parents (1 vs 2)
• Comorbid anti-social traits (in parents,
  offspring)
  
• History of major depression (in parents,
  offspring)

110
Final Model Very-early Onset Alcohol Use in
MOAFTS Hazard Ratios (and 95 confidence
interval)
12 13-14 Early sex 3.5 (1.1-11.4) 4.2 (3.2-5.5
) Divorce 2.1 (1.2-3.6) 1.4 (1.1-1.8) Maternal a
lcoholism 2.0 (1.1-3.6) 1.4 (1.0-2.0)
Paternal alcoholism 1.9 (1.1-3.1) 0.9NS (0.7-1.2)
(Waldron et al, unpublished)
111
Parenting correlates of early onset alcohol use
(controlling for parental alcoholism family
dissolution)
112
PART C

• Should we pay greater attention to differences
  in dependence vulnerability, i.e., conditioning
  on drinking history?

113
Percent alcohol dependent by gender, as a
function of heaviness-of-drinking
114
Percent alcohol dependent by gender, as a
function of heaviness-of-drinking
115
Percent alcohol dependent by number of alcoholic
parents WOMEN
116
Percent alcohol dependent by number of alcoholic
parents MEN
117
Percent alcohol dependent by history of major
depression WOMEN
118
Percent alcohol dependent by history of nicotine
dependence WOMEN
119
Percent alcohol dependent by history of Childhood
Sexual Abuse WOMEN
120
Percent alcohol dependent by history of conduct
disorder WOMEN
121
Percent alcohol dependent by history of parental
divorce WOMEN
122
Percent alcohol dependent by history of parental
divorce MEN
123

• And, of course, we should not neglect influences
  of heaviness of drinking (including genetic
  factors)
  
• And also factors that influence persistence of
  problems (including genetic?)

124
(No Transcript)
125
Major Depression

• Predicts -- increased vulnerability
• -- earlier onset
• -- NOT heaviness of drinking
• -- NOT persistence of problems

126
Childhood Sexual Abuse

• Predicts -- increased vulnerability
• -- earlier onset (in women)
• -- heaviness of drinking
• -- persistence of problems

127
Conduct Disorder

• Predicts -- earlier onset
• -- heaviness of drinking
• -- persistence of problems
• -- NOT increased vulnerability

128
Parental Divorce

• Predicts -- earlier onset
• -- ?? reduced vulnerability (Men)

129
Tobacco Dependence

• Predicts -- everything

130
CONCLUSIONS

• We can consider genes that influence alcohol
  dependence risk as risk-factors that act jointly
  with other risk-factors (psychiatric,
  environmental, etc.)
• This perspective forces us to ask questions that
  traditionally have been neglected by psychiatric
  geneticistsabout
  
• timing of onset of use
• level of use
• vulnerability conditional on use
• Persistence.

131
CONCLUSIONS

• Consideration of these different aspects of risk
  should provide a firmer foundation for dissecting
  the joint contributions of genetic and
  environmental factors to alcoholism risk.
• It may also lead us to adopt new approaches for
  gene discovery efforts, taking advantage of
  information about ENVIRONMENTAL risk-factors.

132
AcknowledgementsMary Waldron, PhD (NIAAA
postdoc)

• Washington University Faculty Collaborators
• Kathy Bucholz, PhD Elliot Nelson, MD Wendy Reich,
  PhD
  
• Pam Madden, PhD Anne Glowinski, MD
  RichardTodd,PhD,MD
  
• Rosalind Neuman, PhD John Rohrbaugh, PhD Michael
  Lynskey, PhD
  
• Alexandre Todorov, PhD Michele Pergadia, PhD Erik
  Sirevaag, PhD
  
• External Faculty Collaborators
• Bill True, PhD, and Qiang Fu, PhD St. Louis
  University
  
• Ted Jacob, PhD, and Randy Haber, PhD, Palo Alto
  Veterans Administration
  
• Ken Sher, PhD, and Wendy Slutske, PhD, University
  of MissouriColumbia
  
• Nicholas Martin, PhD, QIMR, Brisbane, Australia
• Valerie Knopik, PhD, Brown University
• AND MANY OTHER COLLEAGUES AND TRAINEES!