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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 ++++++=
10 ,uuσ
21uσ
20uσ
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
jjjK
k KKijijijij
ije huuXhgy 10132210
1
1
1log ++++++=
⎥⎥⎦
⎤
⎢⎢⎣
⎡
− ∑ =βββββ
ππ
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
00.5
11.5
22.5
33.5
D9S288D9S286D9S171D9S181
7D17S
175
D9S283D9S167
7D9S168
2BH10
21D9S182
6
Chromosome 9 (Markers)
LOD
(mul
tipoi
nt)
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
2210
33
2321
Time (1-8)
Beh
avio
ral p
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!