Social Demographic Perspectives on Social Demographic

Social Demographic Perspectives on Social Demographic Perspectives on Behavioral Genetics: What do you get when Behavioral Genetics: What do you get when

you cross a Sociologist, a Demographer, you cross a Sociologist, a Demographer, and a Behavioral Geneticist?and a Behavioral Geneticist?

Jason BoardmanJason BoardmanUniversity of ColoradoUniversity of Colorado

Department of Sociology andDepartment of Sociology andPopulation Program,Population Program,

Institute of Behavioral ScienceInstitute of Behavioral Science

Lecture prepared for the Lecture prepared for the Charles B. Nam Lecture, Charles B. Nam Lecture, Center for Demography and Population Health, Center for Demography and Population Health,

Florida State University, February 29th.Florida State University, February 29th. . .

Genetics and the social sciencesGenetics and the social sciences

Tension between outside or inside the body (Duster 2006).

1. Prioritization of “inside” scientific work.2. The rapid emergence “inside” data.3. The blocked access to “outside” data such

as wealth and institutional access.4. The “molecularization” of race

What can “we” do about this “tension”?What can “we” do about this “tension”?

• This tension can be resolved, in part by stressing the obvious fact that bodies do not exist without a particular “outside”.

• Thus, the structure and reproduction of the outside is paramount to the investigation of processes occurring at the molecular level.

Genes and environment interplay: Genes and environment interplay: correlation and interactioncorrelation and interaction

• Gene-Environment Correlation: when genetic characteristics (genotype) are associated with environmental characteristics.

• Gene-Environment Interaction: genotype-phenotype associations are contingent on the environment.

Note: see Plomin (1994) & Deater-Deckard & Mayr (2005) for very useful reviews.

Gene environment interplayGene environment interplay

Social Factors(E)

Genetic factors(G)

Physical Health(Regular Smoker)

GeneGene--Environment CorrelationEnvironment Correlation

Passive CorrelationPassive Correlation

• Exposure to an environmental factor that is provided by a genetic relative– Parent’s with above average IQ are more likely

to provide stimulating environments to their children (see Plomin 1994).

Note: see Plomin (1994) & Deater-Deckard & Mayr (2005) for very useful reviews.

Active CorrelationActive Correlation• Environmental selection

– For example, persons with above average IQ may select into more intellectually stimulating environments because these environments are more personally rewarding (Schooler & Mulatu2001) .

Note: see Plomin (1994) & Deater-Deckard & Mayr (2005) for very useful reviews.

Reactive correlationReactive correlation• Genetic determinants of the environment

– For example, children with elevated levels of behavior problems that are, in part, genetically oriented, will evoke rejection, hostility, and sanctions from peers, parents, and educators (O’Connor et al. 1998).

Note: see Plomin (1994) & Deater-Deckard & Mayr (2005) for very useful reviews.

GeneGene--environment interactionsenvironment interactions

• Two variants:– The effect of the environment is conditioned

by an individual’s genetic makeup.– The effect of a particular gene is conditioned

by the environment.

GxEGxE: Constraint: Constraint

• The social environments may limit the potential of genetic expression for salutary outcomes in one of two ways. – Normative environment (social control): in social contexts

with severe constraints on behaviors most persons will exhibit the same phenotype regardless of their genotype.

– Institutional environment (resource impoverishment): genotypic characteristics may not be fully realized if important resources are unavailable.

• Turkheimer et al. (2003) Genetic effects on of IQ are found to be nearly 7 times higher among siblings from HIGH SES compared to LOW SES backgrounds (same as Rowe et al. (1999))

GxEGxE: Triggering: Triggering• The social environment triggers the expression of a

particular gene. Thus the environment is structured as the “fundamental cause” – Evidence of an association only among individuals within

particular environments.• Caspi et al. (2002)

– MAOA activity only associated with antisocial behavior among those exposed to severe childhood maltreatment.

• Caspi et al. (2003)– 5-HTT only associated with depression among those with

a large number of stressful life-events

Average effect

Normal range

Social expression Social distinction

Peer behaviors, norms, and attitudes

Social risk

Figure 1. Normative moderator GEI models: genetic risks for problem behaviors in average and extreme environments.

Social resource

Social push

How can we study this?How can we study this?

• 1) Compare siblings and twins in different environments

• 2) Use genetic information obtained from individuals across different social environments.

Univariate ACE Model for a Twin Pair

Sm2

1

Sm1

A AC CE E

1/.5

A (Additive Genetic)*: .48 (.22, .69)C (Shared Environment): .32 (.17, .47)E (Unshared Environment): .20 (.11, .33)

Wave II of the Add Health Study (most respondents 14-19)*Mx Estimates

1616

More heritability estimates from TwinsMore heritability estimates from Twins

Phenotype rMZ rDZ

BMI (age 20 yrs) .80 .42 [Fabsitz et al, 1992]IQ (age 7 years) .76 .40 [Bishop et al, 2001]IQ (age 16 years) .84 .41 [Friedman et al, 2006]Any drug, ever use .82 .75 [Rhee et al, 2003]Any drug, problem use .82 .46 [Rhee et al, 2003]Depression (Finns, female) .43 .16 [Wamboldt et al, 2000]Heart rate, resting (age 7) .65 .44 [VanHulle et al, 2000]HDL cholesterol (14 years) .81 .21 [Nance et al, 1998]Neuroticism (fem, Aus) .42 .17 [Keller et al, 2005]Extraversion (fem, Aus) .46 .18 [Keller et al, 2005]

76.)38(.2

)42.80(.2

2

2

2

=

=

−=

hhh)(22

dzmz rrh −=

Quantitative Genetic EstimatesQuantitative Genetic Estimates

Phenotype Genetic EnvironmentalShared Non-shared

BMI (age 20 yrs) .76 .04 .20 IQ (age 7 years) .72 .04 .24IQ (age 16 years) .82 .00 .18Any drug, ever use .14 .68 .18Any drug, problem use .72 .10 .18Depression (Finns, female) .43 --- .57Heart rate, resting (age 7) .42 .23 .35HDL cholesterol (14 years) .81 --- .19Neuroticism (females, Australia) .42 --- .58Extraversion (females, Australia).46 --- .54

Boardman, Jason D. “State-level Constraints on Genetic Tendencies to Smoke”. Revised manuscript under review at American Journal of Public Health.

p1 (score of sibling 1)

p2 (s

core

of s

iblin

g 2)

MZ (g= 1.0)

DZ (g= .5)

iegpbgbpbap ++++= )( 132112

estimate of shared env. estimate of heritability

Sibling pair data to estimate Sibling pair data to estimate heritability (heritability (DeFriesDeFries & & FulkerFulker 1985)1985)

• Genetic similarity score (g)– Identical twins =1 Fraternal twins= .5

• Interaction between genetic similarity and the phenotype of twin1 (b3) provides an estimate of heritability.

iegpbgbpbap ++++= )( 132112

Elaborating on the DF regression: the use of Elaborating on the DF regression: the use of mixed models to identify social moderators.mixed models to identify social moderators.

• Include error terms for the intercept and the slope.

• Interpretation

– (random intercept). Extent to which the average level of smoking varies across environments.

– (random slope). Extent to which the heritability estimate given by b3 varies across environments.

– (covariance; intercept and slope). Is heritability higher in environments with higher (social expression) or lower (genetic distinction) levels of smoking.

)()( 110132112 ijijjjijijijijijij gpuuegpbgbpbap ++++++=

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Generalized linear and mixed Generalized linear and mixed model extension of DFmodel extension of DF

Boardman, Jason D. Jarron M. Saint Onge, Brett C. Haberstick, David S. Timberlake, and John K. Hewitt. “Schools and the Heritability of Smoking Behaviors.” Forthcoming, Behavior Genetics

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Table 3. School-level factors that shape the direction and magnitude of the heritability of daily smoking p.e. beta s.e. t pr < Social and demographic characteristics Proportion of college educated mothers -25.23 -0.357 23.78 -1.061 0.292 Proportion non-Hispanic and white -6.55 -0.685 2.41 -2.718 0.008Smoking norms Popular students do not smoke -6.77 -0.177 8.02 -0.845 0.401 Popular students are also smokers 51.04 1.334 8.56 5.962 0.000Institutional control of smoking Teachers not allowed to smoke on campus -3.31 -0.144 5.05 -0.656 0.514 School penalties for smoking infractions 1.72 0.264 2.34 0.736 0.464Smoking prevalence Proportion of students who have smoked -19.32 -0.213 174.91 -0.110 0.912 Smoking prevalence squared 31.01 0.233 236.9 0.131 0.896Note: Cell entries are parameter estimates the latent school-level heritability factor for daily smoking regressed on various school-level factors. These models were estimated using the GEQS command in the GLLAMM procedure available in STATA 9.2. Data obtained from the sibling and twin pair sample of the National Longitudinal Study of Adolescent Health (n=1,198 pairs). Parameter estimates were weighted for individual and school-level weights. The inclusion of these estimates significantly improved overall fit (Chi-square = 16.38, df=8, p<.037).

Boardman, Jason D. Jarron M. Saint Onge, Brett C. Haberstick, David S. Timberlake, and John K. Hewitt. “Schools and the Heritability of Smoking Behaviors.” Forthcoming, Behavior Genetics

Boardman, Jason D. Jarron M. Saint Onge, Brett C. Haberstick, David S. Timberlake, and John K. Hewitt. “Schools and the Heritability of Smoking Behaviors.” Forthcoming, Behavior Genetics

Boardman, Jason D. Jarron M. Saint Onge, Brett C. Haberstick, David S. Timberlake, and John K. Hewitt. “Schools and the Heritability of Smoking Behaviors.” Forthcoming, Behavior Genetics

Boardman, Jason D. Jarron M. Saint Onge, Brett C. Haberstick, David S. Timberlake, and John K. Hewitt. “Schools and the Heritability of Smoking Behaviors.” Forthcoming, Behavior Genetics

Boardman, Jason D. “State-level Constraints on Genetic Tendencies to Smoke”. Revised manuscript under review at American Journal of Public Health.

Sociological Perspectives on Sociological Perspectives on Quantitative Genetics (summary)Quantitative Genetics (summary)

• Genetic factors operate differently across different environments.– Social institutions

• Schools• Families

– Social norms• Controls• Causes

– Social groups (gender, race, and class)• Resources• Norms

Why is this important?Why is this important?

CollectionTube withLysisBuffer

Swabs

Completed

ieE +++= πβφβαφ 2112 )(φ1 = trait of probandφ2 = trait of siblingβ1 = slope (phenotypes) β2 = slope (linkage)π = IBD sharing

jjijijij uueEij 102112 )( ππβφβαφ +++++=

φ1 = trait of probandφ2 = trait of siblingβ1 = slope (phenotypes) β2 = slope (linkage)π = IBD sharing

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22.5

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D9S288D9S286D9S171D9S181

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D9S283D9S167

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Chromosome 9 (Markers)

LOD

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LODVAR

GenomeGenome--Wide Wide Association StudiesAssociation Studies

Thanks to Matt McQueen for this image and slide

The human genomeThe human genome

• 22 chromosomes

• ~30,000-50,000 genes• ~8,000,000 SNPs

Thanks to Matt McQueen for this image and slide

Image borrowed from Image borrowed from http://en.wikipedia.org/wiki/Image:Dnahttp://en.wikipedia.org/wiki/Image:Dna--SNP.svgSNP.svg

SNP (single nucleotide polymorphism)

Sociology and stress responseSociology and stress response

• The same fundamental cause may be at the root of seemingly different processes.

• In other words, social forces may lead to similar genetic responses but the EXPRESSION of the genes may look different.

Stress response

Internalization Externalization

Depression Obesity Alcohol and tobacco Marijuana

White White BlackBlack

Women Men

Stress exposure

Life course perspectiveLife course perspective

• Two people may look the same but they may have traveled very different paths.

• Two people may have started out the same but end up in very different places.

d1

d2

d3

d4

d5

d6

d7

d8

e

e

e

e

e

e

e

e

Intercept

Growth (linear)

Growth (quadratic)

Growth (cubic)

ijijjijjijjjijijijij xxxxxxy εζζζζββββ ++++++++= 33

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Time (1-8)

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heno

type

(d)

Trajectory

Growth (cubic)

Growth (quadratic)

Growth (linear)

Intercept

EB estimates Genetic effect size Weights HeritabilitySNP 1 ζ0, ζ1, ζ2, ζ3 α1,1, α1,2,α1,3,α1,4 w1,1, w1,2,w1,3,w1,4 h2

Max1

SNP 2 ζ0, ζ1, ζ2, ζ3 α2,1, α2,2,α2,3,α2,4 w2,1, w2,2,w2,3,w2,4 h2Max2

SNP 3 ζ0, ζ1, ζ2, ζ3 α3,1, α3,2,α3,3,α3,4 w3,1, w3,2,w3,3,w3,4 h2Max3

SNP 4 ζ0, ζ1, ζ2, ζ3 α4,1, α4,2,α4,3,α4,4 w4,1, w4,2,w4,3,w4,4 h2Max4

. . . .

. . . .

. . . .SNP n ζ0, ζ1, ζ2, ζ3 αn,1, αn,2,αn,3,αn,4 wn,1, wn,2,wn,3,wn,4 h2

Maxn

0%

20%

40%

60%

80%

100%

Infancy Adolsecence Adulthood Elderly

EGEG

0%

20%

40%

60%

80%

100%

Infancy Adolsecence Adulthood Elderly

EGEG

The genetic effects are nearly all contingent upon the environment.

The environmental effects are nearly all contingent upon genotype.

0%

20%

40%

60%

80%

100%

Infancy Adolsecence Adulthood Elderly

EGEG

Differential contribution across the life course

SummarySummary• The molecularization of individual differences is

real.– Genes cause people to be different from one another.

• But..the social and physical environment has a far better score card.– In terms of effect size– And reliability of findings.

• And the social environment seems to structure the way that genes operate.

• This prioritizes “outside” the body processes as an a priori point of initiation.

AcknowledgementsAcknowledgements• NIH/NICHD

– KO1 HD 50336: “The social determinants of genetic expression”

– P01 HD31921: “The National Longitudinal Study of Adolescent Health”

• Institute of Behavioral Science and CU Population Center, University of Colorado

• Institute for Behavioral Genetics, University of Colorado

• Center for Demography and Population Health, Florida State University

Thank you!Thank you!