Genetic simplex modeling of personality in adolescent Australian twins

N.A. GILLESPIE1, D. M. EVANS1, N.G. MARTIN1

1Queensland Institute of Medical Research and University of Queensland, Joint Genetics Program, Brisbane, Australia.

Supported by Queensland Cancer Fund, Cooperative Research Centre for Discovery of Genes for Common Human Diseases, and NHMRC grants 901061 & 9050998.

Modeling personality change

Eaves, Eysenck & Martin (1989)

Adult personality - High of genetic continuity over time !

Effect stronger in Neuroticism vs Extraversion

Genetic continuity in adolescents?

Simplex modeling (Boomsma, 1989)

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)

TWIN 1 TWIN 2

1 1 1

E11

ζE11 ζE12 ζE13

βE2βE3

ζA12 ζA13

Y11Y12 Y13

ε11 ε12 ε13

ζA11

A11

11 1

βA2 βA3

1 1 1

ζE21 ζE22 ζE23

βE2βE3

ζA22 ζA23

ε21 ε22 ε23

ζA21

11 1

βA2 βA3

Y21Y22 Y23

A12 A13 A23 A23A23

E12 E23E22E21E13

Sample

Twin Mole and Twin MAPS projects

Assess the genetic / environmental etiology of Melanocytic Naevi (common moles) in twins aged 12 & 14 years + Cognition at 16

81 items JEPQ - Psychoticism (P) - Extraversion (E) - Neuroticism (N) - Lie (L)

Twin Mole Twin MAPS12 yrs 14 yrs 16 yrs

P E N L P E N L P E N L

Male 603 604 606 605 465 466 466 467 416 412 416 415

Female 605 602 607 609 471 470 473 473 442 438 442 442

Data

Normal weighted by sex and age

Structural equation modeling using ML analysis of individual observations performed in Mx

Raw continuous data methods

Assumptions of mean and variance homogeneity by twin order and zygosity (and necessarily by sex and age)

Polychoric test-retest correlations

P 12 14 16

12 -14 .55 -16 .45 .55 -

N=505

E 12 14 16

12 -14 .58 -16 .51 .67 -

N=498

N 12 14 16

12 -14 .58 -16 .48 .64 -

N=509

L 12 14 16

12 -14 .57 -16 .47 .63 -

N=510

Twin pair polychoric correlations

Consistent with a genetic hypothesis !

Univariate & Multivariate results

AE best fitting model

Model -2LL df 2LL df p AIC

1. 7630.37 2991 0.00 5 5 -10.00

P12 P14 P16

ε1 ε2 ε3

ζA2 ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3

Psychoticism

AE Simplex model

ζA2

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3

Psychoticism

Drop genetic innovation @ 16 years

P12 P14 P16

ε1 ε2 ε3

Model -2LL df 2LL df p AIC

1. 7630.37 2991 0.00 5 5 -10.00

2. 7635.80 2992 5.43 1 * 3.43

ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3

Psychoticism

Drop genetic innovation @ 14 years

P12 P14 P16

ε1 ε2 ε3

Model -2LL df 2LL df p AIC

1. 7630.37 2991 0.00 5 5 -10.00

2. 7635.80 2992 5.43 1 * 3.43

3. 7634.82 2992 4.45 1 * 2.45

Psychoticism - Best fitting Simplex model

TimeζA /

Var(ηA)ζE /

Var(ηE)

14 .27 .55

16 .37 .25

ε1

.36

.93

.55 1.15

P12

A1

E1

P14

A2

E2

P16

A3

E3

ε1

.36ε1

.36

ζA2

.12ζA1

.37ζA3

.13

.70

ζE1

.15

ζE2

.06

ζE3

.05

1 1 1

1 1 1

Extraversion

AE Simplex model

Model -2LL df 2LL df p AIC

1. 7538.80 2981 0.00E12 E14 E16

ε1 ε2 ε3

ζA2 ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3

Extraversion

Drop genetic innovation @ 16 years

E12 E14 E16

ε1 ε2 ε3

ζA2

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7538.80 2981

2. 7538.96 2982 0.16 1 .69 -1.84

Extraversion

Drop genetic innovation @ 14 years

E12 E14 E16

ε1 ε2 ε3

ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7538.80 2981

2. 7538.96 2982 0.16 1 .69 -1.84

3. 7544.34 2982 5.54 1 * 3.54

Extraversion - Best fitting Simplex model

ε1

.23

.92

.53 .72

E12

A1

E1

E14

A2

E2

E16

A3

E3

ε1

.23ε1

.23

ζA2

.12ζA1

.38

.93

ζE1

.35

ζE2

.18

ζE3

.17

1 1 1

1 1 1

TimeζA /

Var(ηA)ζE /

Var(ηE)

14 .27 .64

16 .00 .53

Time Var(η A1-3 ) Var(η E1-3 )Var(ε) Total

E12 .38 .35 .23 .96

E14 .922 .38 + .12= .44 .532 .35 + 18 = .28 .23 1.00

E16 .932 .44 + .00 = .38 .722 .28 + .17 = .32 .23 .93

N12 N14 N16

ε1 ε2 ε3

ζA2 ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7724.22 2999 2.26 5 .81 -7.74

Neuroticism

AE Simplex model

N12 N14 N16

ε1 ε2 ε3

ζA2

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7724.22 2999 2.26 5 .81 -7.74

2. 7730.57 3000 6.35 1 * 4.35

Neuroticism

Drop genetic innovation @ 16 years

N12 N14 N16

ε1 ε2 ε3

ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7724.22 2999 2.26 5 .81 -7.74

2. 7730.57 3000 6.35 1 * 4.35

3. 7728.02 3000 3.80 1 .05 1.80

Neuroticism

Drop genetic innovation @ 14 years

Time ζA /Var(ηA)

ζE /Var(ηE)

14 .26 .70

16 .31 .37

Neuroticism - Best fitting Simplex model

ε1

.22

.93

.49 .91

N12

A1

E1

N14

A2

E2

N16

A3

E3

ε1

.22ε1

.22

ζA2

.11ζA1

.36ζA3

.11

.76

ζE1

.39

ζE2

.22

ζE3

.15

1 1 1

1 1 1

Lie

AE Simplex model

L12 L14 L16

ε1 ε2 ε3

ζA2 ζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7685.48 3000 6.75 5 .24 -3.25

Lie

Drop genetic innovation @ 16 yearsζA2

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7685.48 3000 6.75 5 .24 -3.25

2. 7694.64 3001 9.17 1 ** 7.17 L12 L14 L16

ε1 ε2 ε3

Lie

Drop genetic innovation @ 14 yearsζA3

1 1 1

E1

ζE1 ζE2 ζE3

βE2βE3

E2 E3

ζA1

11 1

βA2 βA3A1 A2 A3Model -2LL df 2LL df p AIC

1. 7685.48 3000 6.75 5 .24 -3.25

2. 7694.64 3001 9.17 1 ** 7.17

3. 7690.30 3001 4.83 1 * 2.83

L12 L14 L16

ε1 ε2 ε3

Lie - Best fitting Simplex model

ε1

.24

.84

.46 .75

L12

A1

E1

L14

A2

E2

L16

A3

E3

ε1

.24ε1

.24

ζA2

.10ζA1

.45ζA3

.15

.87

ζE1

.28

ζE2

.23

ζE3

.09

1 1 1

1 1 1

Time ζA /Var(ηA)

ζE /Var(ηE)

14 .24 .79

16 .32 .35

Discussion

Uni- and multivariate analyses

Small BUT significant genetic innovations @ 12 & 14 years

Genes which effect personality traits at all three ages +

New genetic innovations

Different environments are salient at different ages

Limitations

Normal weighted data

Removes age and sex effectsDoes not capture phenotypic variance with age

Analyses based on transformed data to remove skewness

Equivalent results !

Sex limitation

Evidence of general sex limitation for Neuroticism at 16 years

Home

Simplex model

Neuroticism final model