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Early Growth and Development
Study: How Different Family
Constellations Can Inform Science
LESLIE LEVE, PHD, UNIVERSITY OF OREGON, COLLEGE OF EDUCATION AND PREVENTION SCIENCE INSTITUTE
JENAE NEIDERHISER, PHD, PENN STATE UNIVERSITY, DEPARTMENT OF PSYCHOLOGY
JODY GANIBAN, PHD, GEORGE WASHINGTONUNIVERSITY, DEPARTMENT OF PSYCHOLOGY
Neurodevelopmental and Healthy/Unhealthy
Outcomes Tend to Run in Families – Why?
• Genes shared by family members
• Prenatal factors/exposures passed from mother to child
• Post-natal environmental exposures (parenting/socialization)
• Combinations of all 3 factors
11/17/2020
Objectives
1. Describe the benefits of family-based genetic research designs
2. Importance of including interpersonal relations within the family
among ALL family members
Mother-child AND father-child (including bi-directional effects)
Interparental
Sibling
3. Consider/describe developmental mechanisms
4. Use examples from our cohorts to illustrate
5. Next steps/implications11/17/2020
Family-based genetic designs
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Prenatal
influencesChild
BiologicalMother
BiologicalFather
Genetic
influences
Postnatal
environmental
influences
Biological Parent-Child Designs
Prenatal
influencesChild
BiologicalMother
BiologicalFather
AdoptiveMother
AdoptiveFather
Genetic
influences
Postnatal
environmental
influences
Parent-Offspring Adoption Design
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Early Growth and Development Study
561 domestic adoption placements to non-relative families in 2 cohorts (Cohorts I
and II) – includes child, adoptive parent(s) and biological parent(s)
Adoption occurred within 3 mo. post-partum
Infant free of major medical problems
Retention: Adoptive family = 80%; Birth parent = 80% at age 11
216 biological mothers parenting their biological child (Cohort III)
As part of ECHO, we added 500 additional siblings in birth and adoptive homes
Multiple in-person & telephone assessments for birth parents and for adoptive
families from 3 mos. to adolescence (Cohorts I & II) or age 7 to adolescence
(Cohort III)
Multimethod, multiagent approach
Videotaped observations, interviews, questionnaires, dx interviews, teacher reports, school
records, medical records (prenatal care/delivery & child health)
Biological data outside of ECHO: diurnal cortisol, DNA, hair cortisol & puberty hormones
Location of Adoptive Families
Location of Birth Parents
EGDS Demographics
BM BF
Age at TC birth (avg)
23.8 + 6.1 25.3 + 7.4
(14-48) (14-54)
Race/ ethnicity
78% Cauc.
11% Afr. Am.
4%
Hisp./Lat.
5% Multi-eth
2% other
63% Cauc.
20% Afr. Am.
8%
Hisp./Lat.
5% Mult-eth.
4% other
Median Income
$14K $21K
Median Education
completed
trade school
completed
trade school
1At child birth. 2Educational attainment to date (current).
BM BF AM AF
Age at TC birth (avg)
23.8 + 6.1 25.3 + 7.4 37.0 + 5.6 37.9 + 5.9
(14-48) (14-54) (20-54) (21-57)
Race/ ethnicity
78% Cauc.
11% Afr. Am.
4%
Hisp./Lat.
5% Multi-eth
2% other
63% Cauc.
20% Afr. Am.
8%
Hisp./Lat.
5% Mult-eth.
4% other
93% Cauc.
4% Afr. Am.
1%
Hisp./Lat.
2% Multi-eth.
1% other
92% Cauc.
5% Afr. Am.
1%
Hisp./Lat.
2% Multi-eth.
1% other
Median Income1
$14K $21K $119K
Median Education2
completed
trade school
completed
trade school
completed
college
completed
college
EGDS Demographics
1At child birth. 2Educational attainment to date (current).
4 ½
yrs
6 y
rs
7 y
rs
EGDS-School (PI: Leve)NICHD, Aug 2007 – July
2013Cohort I
New: Emergent literacy, executive functioning, HPA
axis functioning
EGDS-Prenatal (PI: Neiderhiser)
NIDA, June 2007 – May 2013Cohort II
New: 200 cases, DNA, enhanced measurement of prenatal exposure effects
(including BFs)
3-6
moPrenatal
Period 9 m
o
18
mo
27
mo
36
-48
mo
EGDS-Toddler (PI: Reiss)NICHD, Sept 2002- Aug 2007
Cohort I
361 cases: parenting, context, externalizing, internalizing, social
competence, birth parent characteristics
8 y
rs
EGDS-MH (MPIs: Neiderhiser & Leve). NIMH, Sept 2010 – July
2015Cohort I & II
New: Psychiatric diagnosis of children and adoptive
parents I
9yr
s
EGDS-Health (PI: Ganiban). NIDDK,
Aug 2011-June 2016
Cohort I & II
New: weight development
I
Early Growth and Development Study & Early Parenting of Children cohorts
EGDS-ECHO (MPIs: Leve, Neiderhiser &
Ganiban). NIH,
Sept 2016 – Aug 2023Cohort I, II & III
New: environmental exposures on child health
outcomes; all siblings
13
yrs
11
yrs
15
yrs
EGDS-Adolescence(PI: Neiderhiser).
NIDA, Apr 2018-Jan 2023
Cohort I & II
New: hormones & substance use risk
EGDS-EPoCh (PI: Leve). NIDA,
Sept 2013-May 2018Cohort III
New: 216 siblings from birth family, 60 from adoptive family
EGDS-MSCH (PI: Leve). NICHD,
Sept 2014-Aug 2017Cohort I
New: transition to adolescence
Example findings from our cohorts
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Fathers’ parenting matters
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Measures
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Outcome measure: Age 4.5-6 years, child self-regulation
(effortful control, Go-No Go)
Birth parent predictor (genetic): birth parent Go-No Go
Adoptive parenting predictor (post-natal E): mother and
father negative parenting observed in free play and clean-up
tasks in toddlerhood (27 months)
Control variables: child gender, child anger (18 months),
prenatal risk, adoption openness
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Parenting effects can vary depending
on genetic influences
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Maternal structured guidance/scaffolding
3-min clean-up task. Parents asked to
have their child clean up the toys by
putting everything back in its
individualized container/box
Coded using microsocial system
capturing each partner’s real time
behavior. Duration of time mother
spent issuing structured requests to the
child (k = 0.71)
Birth parent risk (genetic): depression,
anxiety, drug use, antisocial behavior
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The effects of maternal guidance vary by genetic risk
70
65
60
55
50
45
40
35
30
0 20 40 60 80 100 120
Maternal Structured Guidance
CB
CL T
ota
l P
rob
lem
T-s
core
(1
8 m
o)
Low Inherited Risk, R2 = .07
High Inherited Risk, R2 = .33
Replication for birth mother and birth father data
11/17/2020
Birth mothers Birth fathers
Developmental pathways – Dual G and E risk
(and protection)
11/17/202018 mo. 27 mo. 54 mo.18 months 27 months age 4.5
Lo G, Lo Parenting
Lo G, Hi Parenting
Hi G, Lo Parenting
Hi G, Hi Parenting
Gro
up
s w
ith
po
ore
st
ou
tco
me
s a
t T1
CB
CL
Tota
l Pro
ble
ms
Specificity by type of parenting
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Positive reinforcement effective for all children
70
65
60
55
50
45
40
35
30
0 20 40 60 80 100 120
Maternal Positive Reinforcement
CB
CL T
ota
l P
rob
lem
T-s
core
(1
8 m
o)
Combined effects of heritable, prenatal, and postnatal
exposures on development
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Children’s temperament can affect parenting
Do genetic, prenatal, or postnatal factors “drive” this effect?
Prenatal
Exposure
Heritable
Tendencies
Rearing Environment
(Parenting)
Liu et al. (2020). Child Development
11/17/2020
Combined effects of heritable, prenatal, and postnatal
exposures on development: BMI trajectories
BMI
24 months
BMI
48 months
BMI
60 months
BMI
72 months
BMI
84 months
BMI
108 months
IS
QBirth
MotherBMI
Birth
FatherBMI
Pregnancy
Weight Gain
Maternal Smoking
During Pregnancy
Birth Weight
z-score
.034
-.499
9.9
21
Legend: Solid lines signify statistically significant paths (alpha=.05). Broken lines denote statistically nonsignificant paths or associations.
Unstandardized path estimates are only provided for significant paths (alpha=.05); Child gender is included as a covariate.
Analytical model with significant unstandardized path estimates
What factors predict change in BMI across childhood?
Heritable tendencies
Prenatal Exposures Postnatal
Growth
Growth rate
from 0 to 9 mos
Implications
11/17/2020
Child behavior/health outcomes are affected by heritable, prenatal, and postnatal factors
Genetically informed family designs can tease apart these effects
Identify different pathways to health vs. disease
Developmental mechanisms: e.g., G x E interactions, child evocative effects, “hidden” relationships between risk factors
Family based approach highlights that fathers contribute to child development as much as mothers
Can also help disentangle prenatal from genetic influences
Practice:
Personalized interventions that reflect unique combinations of risk factors & pathways
One treatment approach will not work for all children
Sources of support
R01 DA035062 and R01 DA020585
R01 HD042608 and R56 HD042608
R01 MH092118
R01 DK090264
UG3/UH3 OD023389
11/17/2020
GWUPI: Jody Ganiban, Ph.D.
Project Coordinator/Supervisor:Amy Whitesel, Ph.D.Kathleen Mion
Post-Doctoral Scientist:Chang Liu
Interviewers and Recruiters:Minh CaoAllison CurwinSeon LeeChristine An
Data Management:Samuel Simmens, Ph.D.
University of OregonPI: Leslie Leve, Ph.D.
Project Coordinator/Supervisor:Alyssa RayhelKelsey Van Brocklin
Post-Doctoral Scientist:Hanna Tavalire
Interviewers and Recruiters:Jaimyn EmeryLue WilliamsDebbie PiersonDenise FordKatie RemmersSamantha Lim
Data Management:Brian CarperBrendan LindseySally Guyer
Penn State UniversityPI: Jenae Neiderhiser, Ph.D.
Project Coordinator/Supervisor:Danielle Seay, Ph.D.Andrew Dismukes, Ph.D.
Interviewers and Recruiters:Allison MitchellEmily KellyCourtney WycheErica Anderson
Data Management:Marielena De Araujo-Greecher, Ph.D.
Early Growth and Development Study
Yale UniversityDavid Reiss, M.D.
University of PittsburghDaniel Shaw, Ph.D.
University of CA, RiversideMisaki Natsuaki, Ph.D.
AcknowledgementsTHANKS to all of the families who have participated in EGDS!