The genetics of personality Nathan Gillespie & Nick Martin
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The genetics of personality
Nathan Gillespie & Nick Martin
Queensland Institute of Medical Research & University of Queensland,
Joint Genetics Program, Brisbane, Australia
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Rephrasing an old question...
Free will versus determinism
Autonomy of the individual
Nature versus Nurture
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A quantitative question...
Philosopher: “To what extent are behavioral, biomedical, and social outcomes biased by an individual’s DNA sequences?”
Psychologist: “To what extent are individual differences influenced by hereditary factors?”
Geneticist: “How much of the variance is due to genes and individual / family environment ?”
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If genetic - empirical question...
Do monozygotic twins (clones) have identical outcomes ?
MZ twins reared apart - note the same way of supporting their cans of beer
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MZ concordance for human conditions
Asthma 45%
Eczema 84%
Diabetes (type I) 56%
Schizophrenia 50%
Cleft lip/palate 30%
Club foot 23%
Homosexuality (M) 18%
Homosexuality (F) 23%
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Is concordance due to genes (G) or shared-environment (C) ? Family studies - G + C confounded
MZ twins alone - G + C confounded
MZ twins reared apart
- Rare, atypical, selective placement?
Adoptions studies
- Rare, atypical, selective placement?
MZ and DZ twins reared together
Extended twin design
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Twins typical of the population
- Prevalence of psychiatric symptoms - (Virginia 30 000)
- Slightly more middle class and better educated
- effect stronger in males (Australian Twin Registry)
Study design requirements- Appropriate sampling of MZ & DZs reared together
- Correct assignment of zygosity
- Comparison of means & variance in traits of interest in MZ & DZs to exclude zygosity environment
- Appropriate statistical methods to infer causes of variation
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Model Building - Classical Twin Method
Study of MZ and DZ twins reared together in same home
- Most powerful method for detecting genetic & shared environmental effects:
P P =
A- (A) Additive genetic effects
aA
a
C
- (C) Shared environment effects
+ cC
c
D - (D) Non-additive genetic effects
(dominance or epistasis)
+ dD
d
E
- (E) Non-shared environmental effects
+ eE
e
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Path Diagram - Classical twin study
P1
Twin1
P1
Twin2
c1
C1
c2
C2
e1 e2a1
A1 A2
a2
D1
d1 d2
D2 E2E1
1.0 MZ / DZ
1.0 MZ / 0.5 DZ
1.0 MZ / 0.25 DZ
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Tracing rulesStandard rules for reading path diagrams to calculate the expected variance & covariance between variables / factors in the diagram
1.0 MZ / DZ
1.0 MZ / 0.5 DZ
P1
Twin1
e
E1 A1 C1
ac
P1
Twin2
c
C2 A2 E2
ae
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(MZ) T1 T2
T1 a2+c2+e2 a2+c2
T2 a2+c2 a2+c2+e2
(DZ) T1 T2
T1 a2+c2+e2 .5a2+c2
T2 .5a2+c2 a2+c2+e21.0 MZ / DZ
1.0 MZ / 0.5 DZ
P1
Twin1
e1
E1 A1 C1
a1 c1
P1
Twin2
c2
C2 A2 E2
a1 e2
Expected variance / covariance matrices for MZ and DZ twin pairs under ACE model
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Expected variance / covariance matrices for MZ and DZ twin pairs under AE model
(MZ) T1 T2
T1 a2 + e2 a2
T2 a2 a2 + e2
(DZ) T1 T2
T1 a2 + e2 .5a2
T2 .5a2 a2 + e2
1.0 MZ / 0.5 DZ
P1
Twin1
e1
E1 A1
a1
P1
Twin2
A2 E2
a1 e2
DZcorr = ½ MZcorr
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Expected variance / covariance matrices for MZ and DZ twin pairs under DE model
(MZ) T1 T2
T1 d2 + e2 d 2
T2 d2 d2 + e2
(DZ) T1 T2
T1 d2 + e2 .25d2
T2 .25d2 d2 + e21.0MZ / .25DZ
P1
Twin1
e1
E1 D1
d1
P1
Twin2
d2
D2 E2
e2
DZcorr < ½ MZcorr
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Expected variance / covariance matrices for MZ and DZ twin pairs under CE model
1.0 MZ / DZ
P1
Twin1
e1
E1 C1
c1
P1
Twin2
c2
C2 E2
e2DZcorr = MZcorr
(MZ) T1 T2
T1 c2 + e2 c 2
T2 c2 c2 + e2
(DZ) T1 T2
T1 c2 + e2 c2
T2 c2 c2 + e2
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Expected variance / covariance matrices for MZ and DZ twin pairs under E model
(MZ) T1 T2
T1 e2 0
T2 0 e2
(DZ) T1 T2
T1 e2 0
T2 0 e2
P1
Twin1
e1
E1
P1
Twin2
E2
e2
DZcorr = MZcorr = 0
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Maximum Likelihood (ML) Analysis
Data is typically summarized in a covariance matrix
Parameter estimates are found by minimising the "maximum likelihood function". This function can be expressed in several ways all of which are equivalent
FML ~= (S - Σ)'WML-1(S - Σ)
S = observed covariance matrix Σ = expected covariance matrixWML = weight matrix
ML analysis finds estimates of a, c, e & d which minimise the difference between the observed & expected covariance matrices
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Neuroticism
r CI
MZFF .40 .31 - .47
MZMM .40 .28 - .50
DZFF .14 -.02 - .25
DZMM .20 .03 - .35
DZFM .15 .04 - .26 Gillespie et al. (2001)
DZcorr = ½ MZcorr A
DZcorr = MZcorr C
DZcorr < ½ MZcorr D
DZcorr = MZcorr = 0 E
Genetic analysis of the dimensions of Eysenck & CloningerN = 3127 Australian twins aged aged 18 -28 yrs
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Neuroticism
A C E -2LL Df df -2LL p
.38 .00 .62 12949.85 3534
Gillespie et al. (2001)
P1
Twin1
e1
E1 A1 C1
a1 c1
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P1
Twin1
e1
E1 A1
a1
Neuroticism
A C E -2LL Df df -2LL p
.38 .00 .62 12949.85 3534
.38 .62 12949.85 3535 1 1.11 .29
Gillespie et al. (2001)
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P1
Twin1
e1
E1 C1
c1
Neuroticism
A C E -2LL Df df -2LL p
.38 .00 .62 12949.85 3534
.38 .62 12949.85 3535 1 1.11 .29
.27 .73 12971.50 3535 1 21.65 ***
Gillespie et al. (2001)
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P1
Twin1
e1
E1
Neuroticism
A C E -2LL Df df -2LL p
.38 .00 .62 12949.85 3534
.38 .62 12949.85 3535 1 1.11 .29
.27 .73 12971.50 3535 1 21.65 ***
1.00 13066.63 3536 2 116.78 ***Gillespie et al. (2001)
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P1
Twin1
e1
E1 A1
a1
Neuroticism
A C E -2LL Df df -2LL p
.38 .00 .62 12949.85 3534
.38 .62 12949.85 3535 1 1.11 .29
.27 .73 12971.50 3535 1 21.65 ***
1.00 13066.63 3536 2 116.78 ***Gillespie et al. (2001)
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A C E
Neuroticism .38 - .62
Extraversion .46 - .54
Psychoticism .40 - .60
Lie .44 - .56
Harm Avoidance .44 - .56
Novelty Seeking .38 - .62
Reward Dependence .35 - .65
Gillespie et al. (2001)
Univariate heritability estimates for dimensions of Eysenck & CloningerN = 3127 Australian twins aged aged 18 -28 yrs
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- Twin pairs reared together- Separated twin pairs- Non-twin adoptees & biological & adoptive families- Twin pairs reared together & their relatives
Personality modelsEysenck - Psychoticism - Extraversion
- Neuroticism - Lie
Cloninger - HA, NS, RD, PERS + 3 characters
Costa & McCrae - NEO-PI FFM
Application to personality researchHow compelling is evidence for a genetic contribution to adult and adolescent personality?
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Genetic Variance
AdditiveEpistatic
(AA)
M F M F
Extraversion 10 13 37 39
Neuroticism 16 38 22 13
Sex differences & non-additivity in Neuroticism and Extraversion US, Australian & Finnish twins, their siblings, parents & spouses (N = 42,374) (Eaves et al., 1998)
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Multivariate analysis of personality
Univariate analysis - estimates the contribution of A C & E within a dimension- says nothing about the underlying genetic & environmental causes of covariation between dimensions
Multivariate analysis - analyses cross-twin cross-trait correlations- determines the degree to which separate genetic & environmental factors are responsible for the correlations between variables
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Multivariate genetic analyses
1. Cholesky Triangular Decomposition2. Common Pathway3. Independent Pathway
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Multivariate Analysis
Var1 Var2 Var3
F
e e e
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Multivariate Analysis
Var1 Var2 Var3
G
G G GE
E
E E
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1. Cholesky Triangular Decomposition
Var1 Var2 Var3
A3A2A1
C3C2C1 E3E2E1
- Number of latent factors equals number of
variables
- Does not distinguish between common factor & specific factor effects except for final variable
- Analogous to Principle Components Analysis
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Multivariate genetic analysis - Cholesky Decomposition
Cloninger’s 3 dimensions of character
- Self-directedness (DIRECT) - Cooperativeness (COOP)- Self-transcendence (TRANS)
Study of 3040 twins aged 50-96 years (Gillespie et al., submitted)
Univariate modeling
A C E
DIRECT .35 - .65
COOP .27 - .73
TRANS .44 - .56
Polychoric correlations
1. 2. 3.
1. DIRECT 1
2. COOP .17 1
3. TRANS -.04 .26 1
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A1 A3
DIRECT COOP TRANS
A2
E1 E3E2C1 C3C2
Multivariate model fitting – DIRECT, COOP, TRANS
-2ll df -2ll df p AIC
ACE 26421.11 8166
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A1 A3
DIRECT COOP TRANS
A2
E1 E3E2
Multivariate model fitting – DIRECT, COOP, TRANS
-2ll df -2ll df p AIC
ACE 26421.11 8166
AE 26421.13 8172 .02 6 1.00 -11.98
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C1 C3
DIRECT COOP TRANS
C2
E1 E3E2
Multivariate model fitting – DIRECT, COOP, TRANS
-2ll df -2ll df p AIC
ACE 26421.11 8166
AE 26421.13 8172 .02 6 1.00 -11.98
CE 26447.01 8172 25.90 6 *** 13.90
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DIRECT COOP TRANS
E1 E3E2
Multivariate model fitting – DIRECT, COOP, TRANS
-2ll df -2ll df p AIC
ACE 26421.11 8166
AE 26421.13 8172 .02 6 1.00 -11.98
CE 26447.01 8172 25.90 6 *** 13.90
E 26716.93 8178 295.82 12 *** 271.82
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Best fitting multivariate model with standardized path coefficientsfrom latent additive genetic (A1 – A3) & non -shared environmental(E1 – E3) factors to the three dimensions of character
A1A3
DIRECT COOP TRANS
A2
E1 E3E2
.60
-.06
.16
-.46-.23
.62
.80
-.01
.10
.87 .73.19
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2. Common Pathway 3. Independent Pathway
Latent Factor
A E
Var1 Var2 Var3
A EA EA E CC C
CA E
Var1 Var2 Var3
A EA EA E CC C
C
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Multivariate genetic analysis - Common & Independent Pathway Models
- 3512 female twins aged 18-45 yrs
Measures of maternal / paternal behaviourFactor analysis of Parental Bonding Instrument (PBI) (Parker)
- Autonomy - Overprotection- Coldness
Measures of psychiatric distressFactor analysis of DSSI/sAD & SCL90 items
- Depression - Anxiety - Somatic Distress
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Best fitting multivariate model for the three PBI dimensions: Coldness, Overprotecting & Autonomy
PARENTING
A E
Cold Overp Auto
EA EA E
C
.45 .27.28
.33.47.41.28.30
.35.82.65
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Best fitting multivariate model for the dimensions of Depression, Anxiety & Somatic Distress
DISTRESS
A E
Depression Anxiety Somatic
EA EA E
.48 .52
.33.22.12.31.08
.82.69.78
A
.19
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Important applications
- Recursive Models- Social Interaction- Modeling Direction of Causation
- Simplex modeling- Sex limitation- Genotype Environment Interactions- Genotype Environment Correlations- Assortment & Cultural Transmission
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Important applications
- Recursive Models- Social Interaction- Modeling Direction of Causation
- Simplex modeling- Sex limitation- Genotype Environment Interactions- Genotype Environment Correlations- Assortment & Cultural Transmission
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Recursive models: Direction of Causation
Under some circumstances we can model ‘direction of causation’ on cross sectional data
- Genetically informative data- Qualitatively or quantitatively distinct
Does parenting have an effect on psychological distress outcomes or vice a versa? Or is association between psychological distress and parenting determined by a common diathesis?
- 3500 female twins aged 18-45 years - questionnaire containing SCL90, DSSI & PBI
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MZ=(a2+d2)iB
DZ=(½a2+¼d2)iB
aBdB aB
1
1MZ, ½DZ
1MZ, ¼DZ
dBeB eB
cA eAeA cA
iB iB
At1
Bt1
E A D
E C
At2
Bt2
D A E
C E
aBdB aB
1
1MZ, ½DZ
1MZ, ¼DZ
dBeB eB
cA eAeA cA
iA iA
At1
Bt1
E A D
E C
At2
Bt2
D A E
C E
MZ=c2iB
DZ=c2iB
A B B A
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Direction of causation (DOC) modeling
C E C EC EAE EAEA
COLD AUTOOVERP
A E
DEP SOMANX
DISTRESS PARENTING
A EC
.63.67 .49 .56
.16 .52
.55 .20 .25.38 .45
.36 .13 .21 .11 .40 .17 .26 .21 .14 .49 .11 .37
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Measuring stability of genetic effects over timeEaves, Eysenck & Martin (1989)
- Adult personality - High genetic continuity over time
- Effect stronger in Neuroticism vs Extraversion
Genetic continuity in adolescents?- Simplex modeling (Boomsma, 1989)
- Changes in the magnitude of G & E over time?- Do same G & E effects operate throughout time?
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Genetic Simplex modeling
Autoregressive model
Structural equation model
ηi = βi ηi-1 + ζi
var (ηi) = βi2 var (ηi-1) + var (ζi)
ζ i-1
i-1
Yi-1Yi Yi+1
ζ i ζ i+1
λ i-1 λ i λ i+1ε i-1
β iβ i+1i i+1
ε i ε i+1
Measurement model
Yi = λi ηi + εi
var (Yi) = λi2 var (ηi) + var (εi)
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Extraversion - Best fitting Simplex model
.23
.92
.53 .72
E12
A1
E1
E14
A2
E2
E16
A3
E3
.23 .23
.12.38
.93
.35 .18 .17
1 1 1
1 1 1
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Neuroticism - Best fitting Simplex model
.22
.93
.49 .91
N12
A1
E1
N14
A2
E2
N16
A3
E3
.22 .22
.11.36 .11
.76
.39 .22 .15
1 1 1
1 1 1
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Genes, personality & psychopathology
1. Dopamine receptor gene (DRD4)2. Monoamine oxidase (MAO) gene3. Quantitative trait loci (QTLs) for Neuroticism
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Genes, personality & psychopathology
1. Dopamine receptor gene (DRD4)2. Monoamine oxidase (MAO) gene3. Quantitative trait loci (QTLs) for Neuroticism
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3. Detecting QTLs for Anxiety & Depression
Difficult task - Polygenetic traits
Significant linkage between Harm Avoidance (HA) & locus on chromosone 8p21-23
- 38% of trait variance in HA- 758 sib-pairs- replication?
Need to screen ~20,000 sib pairs to identify QTL for 10% variance
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NEU ANX DEP
A
a a a
35%35%
30%
16% 3% 6%
Neuroticism, Anxiety & Depression have been shown to be influenced by the same genes
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Increasing power to detect QTLs
Zhang & Risch - Extreme Discordant & Concordant sib pair design (EDAC)
Majority of twin pairs provide little power to detect linkage
Only pairs that are concordant for high values, low values, or extremely discordant pairs (e.g. top & bottom 10%) provide substantial power
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Anxiety Project
1988-1991 Twins and family members - Neuroticism data - scores fell into top two or bottom two deciles- 2918 individuals
1999 Anxiety Project- 2470 individuals - Blood & bucal samples
- DSM-IV & ICD-10 diagnoses
- Depression - Dysthymia - Social phobia
- Agoraphobia - GAD - Panic disorder
- OCD
NEURO
14.0012.0010.008.006.004.002.000.00
NEURO
Fre
qu
en
cy
2000
1000
0
Std. Dev = 3.41
Mean = 5.13
N = 9147.00149
581
973
1385
17841854
1718
703
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Prevalences (%) - FemalesDeciles
Diagnosis1,2
(852)9,10(676) OR p
Depression 14.0 41.1 2.9 <.001
Dysthymia 0.2 1.9 9.5 <.001
OCD 1.4 9.2 6.4 <.001
Social Phobia 2.1 11.4 5.4 <.001
GAD 1.1 1.6 1.5 0.33
Panic w/o agoraphobia 1.3 4.1 3.2 <.001
Panic w agoraphobia 0.5 2.4 4.8 0.001
Agoraphobia w/o panic 0.7 4.1 5.9 <.001
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QTL analysis of Neuroticism (Mailed questionnaires 1989 & 1999)
Chromosome ‘a’
0
5
10
15
20
25
Position in cM
Ch
isq
uar
e
N99 (mail)
N89 (mail)
chisq (joint - 2df)
C 21 = 23.82
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http://ibgwww.colorado.edu/twins2002/
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Important applications
- Recursive Models- Social Interaction- Modeling Direction of Causation
- Simplex modeling- Sex limitation- Genotype Environment Interactions- Genotype Environment Correlations- Assortment & Cultural Transmission
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Recursive models: Social Interaction
Social / Sibling interaction - cooperative or negative effects
P1 = sP2 + aA1 + cC1 + eE1
P2 = sP1 + aA2 + cC2 + eE2
Little evidence- IQ- education- personality- social attitudes- BMI- heart rate etc
P1
e
E1 A1 C1
ac
1.0 MZ / DZ
1.0 MZ / 0.5 DZ
P2
c
C2 A2 E2
ae
s
s
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Recursive models: Direction of Causation
Under some circumstances we can model ‘direction of causation’ on cross sectional data
Does parenting have an effect on psychological distress outcomes or vice a versa? Or is association between psychological distress and parenting determined by a common diathesis?
- 3500 female twins aged 18-45 years - questionnaire containing SCL90, DSSI & PBI
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MZ=(a2+d2)iB
DZ=(½a2+¼d2)iB
aBdB aB
1
1MZ, ½DZ
1MZ, ¼DZ
dBeB eB
cA eAeA cA
iB iB
At1
Bt1
E A D
E C
At2
Bt2
D A E
C E
aBdB aB
1
1MZ, ½DZ
1MZ, ¼DZ
dBeB eB
cA eAeA cA
iA iA
At1
Bt1
E A D
E C
At2
Bt2
D A E
C E
MZ=c2iB
DZ=c2iB
A B B A
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Direction of causation (DOC) modeling
C E C EC EAE EAEA
COLD AUTOOVERP
A E
DEP SOMANX
DISTRESS PARENTING
A EC
.63.67 .49 .56
.16 .52
.55 .20 .25.38 .45
.36 .13 .21 .11 .40 .17 .26 .21 .14 .49 .11 .37
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Measuring stability of genetic effects over timeEaves, Eysenck & Martin (1989)
- Adult personality - High genetic continuity over time
- Effect stronger in Neuroticism vs Extraversion
Genetic continuity in adolescents?- Simplex modeling (Boomsma, 1989)
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Genetic Simplex modeling
Autoregressive model
Structural equation model
ηi = βi ηi-1 + ζi
var (ηi) = βi2 var (ηi-1) + var (ζi)
ζ i-1
i-1
Yi-1Yi Yi+1
ζ i ζ i+1
λ i-1 λ i λ i+1ε i-1
β iβ i+1i i+1
ε i ε i+1
Measurement model
Yi = λi ηi + εi
var (Yi) = λi2 var (ηi) + var (εi)
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Extraversion - Best fitting Simplex model
ε1.23
.92
.53 .72
E12
A1
E1
E14
A2
E2
E16
A3
E3
ε1.23
ε1.23
ζA2
.12ζA1
.38
.93
ζE1
.35
ζE2
.18
ζE3
.17
1 1 1
1 1 1
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Neuroticism - Best fitting Simplex model
ε1.22
.93
.49 .91
N12
A1
E1
N14
A2
E2
N16
A3
E3
ε1.22
ε1.22
ζA2
.11ζA1
.36ζA3
.11
.76
ζE1
.39
ζE2
.22
ζE3
.15
1 1 1
1 1 1
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Sex limitation
Is the magnitude of A, C & E effects equivalent across sex? Sex specific genes?
Requires data from opposite-sex DZ twins
1. General model for sex limitation2. Common effects sex limitation3. Scalar sex limitation
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Sex limitation1. General model for sex limitation
ef
Ef Af
af
AmEm
ama’m
A’m
em
Pf Pm
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Sex limitation1. General model for sex limitation2. Common effects sex limitation
ef
Ef Af
af
AmEm
amem
Pf Pm
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Sex limitation1. General model for sex limitation2. Common effects sex limitation3. Scalar sex limitation
Body Mass Index (BMI)Personality
L1f
e
Ef Af
a
L1m
AmEm
ae
L2f L2m
1.0
1.0
k
k
Pf Pm
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Genotype Environment InteractionGenetic control of sensitivity to differences in the environment. Components of phenotypic variance conditional on environmental exposure
- 5967 twin pairs aged 18 to 88 yrs- Genetic heritability of depression differs with marital status: Singles = 42% vs Married = 30%
Genotype Environment CorrelationEnvironments which individuals experience may not be random but may be caused by or correlated with their genes (CorGE)
- depression & adverse environments- IQ & education / enriched environment
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Detecting GE and corrGE- Requires large sample sizes + data from twin & relatives
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Assortment & Cultural TransmissionAssortative mating ‘like marrying like’
- based on social background / relatives (C) - Social homogamy
- based on phenotype of spouse (ACE)- Phenotypic assortment
Cultural transmission- environmental influences in present generation stem from parental phenotypes
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Assortment & Cultural Transmission
Pm
g
Gm
e
Em
Child 1
g
Gm
e
Em
Pf
e g
e g
Ef Gf
u
b bbb
1/21/2
Child 2
Ef Gf
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AT2CTAT1
PT2
ET2a e
PT1
eET1 a
c c
rAT1 rAT1
1/2 1/2
CM
PM
e
EM AM
ac
PM
EFAFCF
a ec
Cultural transmission & social homogamy
m f
rCT
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Does ‘like marry like’? Marital correlations for personality & social attitudes
Psychoticism = 0.16 Religion = 0.52Extraversion = 0.06 Socialism = 0.54Neuroticism = 0.13 Prejudice = 0.35Lie = 0.28 Permissiveness = 0.52
Authoritarianism = 0.56
Distinguishing environmental & biological transmission
- little evidence for environmental transmission
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Neuroticism - Lake et al. (1999)- 45 850 twins & relatives- modest assortative mating, A, D & E- no environmental transmission - Neuroticism little more complex than found
from earlier, simpler designs
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Dopamine receptor gene (DRD2) genotype & heroin addiction: A1 allele frequency
05
1015202530354045
Succes
s
Dropout
Poor
f(A1)
- 95 Brisbane heroin addicts on methadone treatment program
- 54 successful treatment outcome
- 22 dropped out
- 19 poor treatment outcome
Lawford et al (2000) Am J Med Genet 96:592-8