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

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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

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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

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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

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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!