Timothy C Bates University of Edinburgh Mike Neale Virginia Institute of Psychiatric Genetics John Gilmore University of North Carolina Foetal brain Illustration by Helen Spiers Brain development and growth ID: 305916
Download Presentation The PPT/PDF document "Genetic and shared environmental influen..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
Slide1
Genetic and shared environmental influences on brain development from birth to age 2-years
Timothy C. Bates
University of Edinburgh
Mike Neale
Virginia Institute of Psychiatric Genetics
John Gilmore
University of North CarolinaSlide2
Foetal brain…
Illustration by Helen
SpiersSlide3
Brain development and growth
Single most important biological marker for
cognition
(McDaniel
, 2005
)
Linked to psychiatric
outcomes
including
schizophrenia
(Steen
, Mull,
Mcclure
,
Hamer
, & Lieberman, 2006
)Slide4
Lifetime consequence, early growth
Much of this critical growth occurs in the earliest years of life
C
ortical gray matter more than doubles in the first year
(Gilmore et al., 2012).
Influences known from adult studies
Parental social and economic status (SES)
(Hackman & Farah, 2009
).Slide5
Logarithmic link of cortical volume to SES (Noble et al. 2015)Slide6
Forbes magazineSlide7
©
Roslin
Institute
Common ancestor ~100 generations ago (h
2
growth ~ 0.3)
However:
Genes can effect biological volumes…Slide8
However…
Brain volumes are a highly heritable
endophenotype
Blokland
, de
Zubicaray
, McMahon, & Wright, 2012
Morphology & psychological function genetic correlated
Posthuma
et al., 2002.
Specific genetic variants identified influencing structural volumes
Hibar
et al., 2015;
Ikram
et al., 2012.Slide9
Genes found for specific brain regional volumesSlide10
Genetic or Environmental?
No studies have combined genetic and neurological examination in infancySlide11
Prior data
Knowledge largely from studies of adults and children
Nature and number of
influences during earliest
years of infant brain
development
virtually unknown (Gilmore et al., 2012
)
Potential
interaction effects with SES in the expression of genetic potential
untestedSlide12
Unique infant twin sample
Assessed longitudinally from shortly after birth through age-2 in three consecutive waves of brain imaging
Characterized on family environment.
285 infants
174 DZ (87 pairs)
106 MZ (53 pairs)Slide13
Landmark studies from 4-20 years(Geed et al., 1999)
Large increases in gray and white matter from ages 4- thru 20-years
G
ray matter volumes similarly increasing until a period of volume-reduction initiating at adolescence
Giedd et al. ( 1999)
These studies also showed the importance of temporal patterning per se
IQ
is associated with cortical thickness in 6 to 11 year olds (
Karama
et al., 2009)
but also
Complex and non-linear pattern of prolonged cortical thickening (Shaw et al., 2006). Slide14
Cortical thickness linked to IQShaw
et al. (2006)Slide15
Plasticity higher in high-IQ kids
Shaw
(2006
)Slide16
Shaw (2006): Higher IQ association with delay growth, and extended pruningSlide17
Prior to age-4
Much less is known about the nature and time course of brain development.
Heritabilities surprisingly high early in life.
Note: studies of IQ indicate much
lower
heritability in children compared to adults
(Haworth et al., 2010
)Slide18
Neonate heritabilities
Analyses of the neonatal wave of the present sample indicated heritability values only slightly lower than those found in child samples
h
2
of .73 and .85 for total intracranial and white matter volumes respectively
(Gilmore et al., 2010).
Period from birth to age 2 is associated both with rapid increases in gray and white matter volumes and, in one study, with the emergence of gene × environment interaction
(Tucker-
Drob
,
Rhemtulla
, Harden,
Turkheimer
, &
Fask
, 2011)Potential for complex interactions, and multiple genetic and environmental factors across time or operating at one, but not other developmental windows.Slide19
Present Study Initial Steps
Characterise
Genetic
and environmental factors influencing whole-brain volumetric
development
D
erived
separately for gray and for white matter
N
eonatal
, and 1- and 2-years of age
Testing:
Continuities
discontinuities
modes
of operationincluding gene environment interactions.Slide20
Subjects
This paper reports on subjects taking part in the large, prospective study of early brain
development
(Gilmore
et al.,
2010).
Subjects
were recruited prenatally and scanned shortly after birth, and at ages 1 and 2
years.
Also
assessed with the Mullen Scales of Early Learning (Mullen, 1995) at ages 1 and 2
years.
Neonates
were scanned at a median age of 35 days (range 9 and 161 days). Year 1 scans took place at a median age of 402 days (min 351, max 511), and year 2 follow-up scans at 770 days (min 661, max 879
).Slide21
Method
MRI scans were performed on a Siemens 3T head-only scanner (Allegra, Siemens Medical System, Erlangen, Germany
).
The
infants were not sedated, were fed before scanning, and given ear
protection.
To
reduce movement artifact, the head was aligned in using a weak
vacuum-cup.
A
nurse was present during all
scans
Heart
rate and oxygen saturation were monitored with a pulse oximeter
.Slide22
Scans
T1-weighted structural pulse sequences were a 3D magnetization prepared rapid gradient echo (MP- RAGE time repetition [TR] = 1820
ms
, inversion time = 1100
ms
, echo time = 4.38
ms
, flip angle = 7°, and n = 144
).
Proton
density and T2-weighted images were obtained with a turbo spin echo sequence (TR = 6200
ms
, time echo [TE]1 = 20
ms
, TE2 = 119
ms, and flip angle 150°).Spatial resolution was 1 × 1 × 1-mm voxel for T1-weighted images, 1.25 × 1.25 × 1.5-mm voxel with 0.5-mm inter-slice gap for proton density/T2-weight images.For children who failed or were deemed likely to fail due to difficulty sleeping, a ‘fast’’ sequence was done; 12 neonates had a ‘‘fast’’ T2 scan with a decreased TR, image matrix and number of slices (5270 ms, 104 3 256 mm, 50) and 3 one year olds had a ‘‘fast’’ T1 scan with a decreased image matrix (144 3 256 mm).A clinical radiologist evaluated all scans; no gross abnormalities were reported.Slide23
Quantization
Pre-processing
A
daptive
fuzzy c-means automatic brain tissue segmentation method was performed to correct intensity inhomogeneity (Pham & Prince, 1999).
Volumes
of white and gray matter were quantitated
automatically
A
tlas-moderated
iterative expectation maximization segmentation algorithm followed by
parcellation
achieved by nonlinear
warping (Gilmore
et al., 2007
)Subject-specific tissue probabilistic maps.Maximize precision and longitudinally consistency of segmentation resultsParcels aggregated to form whole-brain volume vectors for analysis.Slide24
Mapping and Segmentation
Gray and white matter (GM and WM respectively), and cerebrospinal fluid (CSF) maps in 2-year olds were used as probabilistic atlases to guide segmentation of 2-week-old and 1-year-old images of the same subject using an iterative, simultaneous, registration and segmentation framework.
(Gilmore et al., 2012; Shi et al., 2011).
Based on this 4D segmentation and registration algorithm, GM and WM volumes at were extracted from 90 regions identified at each age.
T1 images were used for 1 and 2 year olds and T2 images for neonates.Slide25
Present Study: Hypotheses
Characterise
Genetic
and environmental factors influencing whole-brain volumetric
development
D
erived
separately for gray and for white matter
N
eonatal
, and 1- and 2-years of age
Testing:
Continuities
discontinuities
modes
of operationincluding gene environment interactions.Slide26
Heritability across time
The heritability of
volumes may
alter with
time.
H
eritability
of
IQ increased from
childhood into old age
(
Deary
,
Spinath
, & Bates, 2006)
But… heritability of gray & white matter volumes high in neonates (Gilmore et al., 2012)Prediction 1: Heritability at 1 & 2 should exceed that found in neonates.Contrasting model: Unlike IQ gray and white matter volumes always under strong genetic influenceSlide27
Shared environments:
Magnitude
and
trajectory
Existing
theories make strongly contrasting
predictions
Model 1: Large
role of shared environment
Model 2: Model 1: Mostly geneticSlide28
Model 1: Large role of shared environment
Large
role of shared environment on IQ scores prior to
school
Olson
et al., 2014;
Tucker-
Drob
et al.,
2011
SES implicated in brain
development
Noble
& Farah,
2013Predict C increasing with time (and exposure to the rate-limiting environment)Slide29
Model 2: Model 1: Mostly genetic
Very high heritability suggests little room for shared environment
Familial influences on brain development may be confounding genetic effects.
Contrasting prediction: minimal shared environment at all three waves.Slide30
Developmental Hypotheses: Almost nothing is known
Number
of
genetic
and environmental factors impacting brain development over this
period
Time-course
Increasing
Decreasing
L
imited
to a single
ages
Compensatory
reversals of effect over time
.Slide31
One common genetic factor
The generalist genes model of cognitive
ability
(
Kovas
& Plomin,
2006)
Relative
lack of genetic innovation in intelligence from pre-school to the
teens
(Bartels
,
Rietveld
, Van Baal, & Boomsma,
2002)Predict that this heritable component will be carried by a single vector.Slide32
Alternative hypothesis:Multiple factors:
Unclear
how brain development is impacted by the genome during these early periods of rapid
growth:
genes
act
(
albeit with diverse mechanisms) so as to exert a monolithic
effect
two
, three, or more distinct patterns, some with time-limited influence.
Predict
: General
influences
AND
time-delimited or gray-white matter specific actions. Slide33
Longitudinal impact of family environment
Simplest
model
suggests
a single family environment
factor
S
ignificant
and constant influence on gray and white matter
volumes
Perhaps
declining in influence with time
.Slide34
Canalization model of volume growth
Distinct predictions emerge from models in which brain development is tightly canalized
internal programs causing brain to remain on a programmed course
Able to recover from external shocks or stresses to regain this programmed trajectory via compensatory control mechanisms
(
Giedd
et al., 1999; Gilmore et al., 2010).
Applied to brain development suggests that environmental influences should be impact brain volume, but that these should decay and be reversed.Slide35
Impact of Shared environment reversed by canalized growth program
F
amilial environmental effects compensated (reversed) by canalization processes
Waddington, 1957
Quantitatively, this would manifest as a factor strongly loading on shared environment, and showing sign-reversal between its neonatal and year 1 and 2 loadingsSlide36
4 Pathways to Brain GrowthSlide37
Factor 1: largely CSlide38
Factor 3: Largely ASlide39
Factor 2: A+ESlide40
Factor 4: A+CSlide41
4-factors over time…Slide42
4 Pathways to Brain GrowthSlide43
Time CourseSlide44
Putting it all together longitudinallySlide45
Interactions: Gene x SESA main effect model (Bates et al, 2015)Slide46
Gene × SES moderation of genetic varianceSlide47
Scarr-Salapatek (1971)Slide48
World’s literature
(Tucker-
Drob
& Bates, 2015)Slide49
G x SES and Brain Development
Main effect: significant
associations of both gray- and white-matter volumes with parental SES.
G x SES
amplification of children’s
genetic
potential
Tucker-
Drob
& Bates,
2015
Bates
, Lewis, & Weiss,
2013
Predict gene × SES interactions may be present, with increased heritability of brain volumes among higher SES infants.Slide50
Logarithmic link of cortical volume to SES (Noble et al. 2015)Slide51
Results: No support for G x SES
(and reverse/wrong trend)Slide52
Psychometric IQ resultSlide53
Annual Reviews
Why no G x SES?
Effects on a microscopic level?Slide54
The post-synaptic density and IQ
(Hill, … Bates, &
Deary
, 2014)Slide55
Gene interactions later in life?(then why are early years important?Slide56
Forbes magazine
GENESSlide57
SES in parents partly driven by their own genes, which they pass on…
Ritchie,
Plomin
& Bates (2014)Slide58
Summary: No evidence for interaction up to age 3 for gray or white matterSlide59
Infant brain: Complex, Canalized, and Highly Heritable