Electronic Supplementary Material 3-5
Genetics and brain morphology
Lachlan T. Strike1*, Baptiste Couvy-Duchesne1, Narelle K. Hansell1, Gabriel Cuellar-Partida, Sarah E. Medland, Margaret J.
Wright
Lachlan T. Strike, Baptiste Couvy-Duchesne
Neuroimaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia
School of Psychology, University of Queensland, Brisbane QLD 4072, Australia
Centre for Advanced Imaging, University of Queensland, Brisbane QLD 4072, Australia
Narelle K. Hansell
Neuroimaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia
Gabriel Cuellar-Partida
Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia
Sarah E. Medland
Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia
Margaret J. Wright
Neuroimaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia
School of Psychology, University of Queensland, Brisbane QLD 4072, Australia
1
LS, BCD and NH contributed equally to this work.
*
Corresponding author
Lachlan T. Strike
Lachlan.Strike@qimrberghofer.edu.au
en
Online Resource 3. APOE Genotype Effects on Neuroimaging Structural Phenotypes: Overview of Studies
January 2014 to July 2014
Study
Samplea Size
Structural
(Age)
Phenotypeb
Finding
Babies and Toddlers
Dean et al. (2014)
N=59
(6-25 months)
Knickmeyer et al.
(2014)
N=272
(neonates)
Korja et al. (2013)
N=322
voxel-based
gray matter
volume (GMV)
and white
matter (WM)
myelin water
fraction (MWF)
ɛ4 carriers relative to non-carriers had lower GMV and MWF (an indicator of myelin sheath
integrity) in brain regions preferentially affected by AD, as well asgreater GMV and MWF in
extensive frontal regions. No GMV results survived correction for multiple comparisons.
However, multiple MWF measures survived correction for multiple comparisons (decreased in
corticospinal tract (p≤4.0x10-4), but increased in frontal (p=2.0x10-5), parietal (p=1.0x10-5),
superior corona radiata (p≤2.0x10-5), inferior fronto-occiptal fasciculus (p=3.0x10-4), and genu of
the corpus callosum (p=5.0x10-4), in ε4 carriers compared to non-carriers).
automated
region of
interest (ROI)
GMV
Reduced volumes found in temporal regions known to be vulnerable to atrophy in the elderly, but
also regions of increased volume (in parietal, frontal, and occipital cortices) in ɛ4 carriers
compared to non-carriers (multiple ROIs retained significance after correction for multiple testing
with p≤1.0x10-4).
unspecified
brain pathology
Among this sample of very preterm and/or very low birthweight babies, no genotype effects were
found to be associated with brain pathology
multiple WM
measures
ɛ4 allele was associated with higher WM volume ratio (p=0.022) and increases in axial diffusivity
(p=0.011) and mode of anisotropy (p˂0.05).
voxel-based
GMV
No genotype differences found.
WM fractional
anisotropy
No genotype differences found.
multiple WM
measures
The presence of lobar microbleeds was associated with loss of WM structural integrity in ɛ4
carriers, but not in non-carriers (p=0.022 (fractional anisotropy); p=0.002 (mean diffusivity)).
temporal lobe &
basal ganglia
volume
Longitudinal Study: ɛ4 carriers relative to non-carriers showed greater medial temporal lobe
(MTL) atrophy over 2.4 years (p˂1.0x10-4). Vascular risk factors independently influenced MTL
atrophy.
entorhinal
cortex volume
Longitudinal Study: ɛ4 status was associated with amyloid-beta deposition, but not with amyloidbeta associated volume loss, which only occurred in the presence of phosphor-tau.
WM fiber
bundles
ɛ4 carriers found to have shorter WM fiber bundles in left uncinate fasciculus compared to noncarriers (p=0.038).
multiple brain
volumes
Greater central obesity was associated with reduced frontal lobe volume (p=0.047), greater WM
hyperintensity volume (p=0.033) and worse cognitive function in ɛ4 carriers, but not in noncarriers.
brain infarcts
In ɛ4 carriers, but not non-carriers, the activity of serum amyloid-beta degrading proteases was
associated with small vessel, but not large vessel, infarcts (p˂1.0x10-4).
(neonates)
Healthy Young & Middle-Aged Adults
Dowell et al. (2013)
N=41
(18-30 years)
Goveas et al. (2013)
N=46
(44-65 years)
Patel et al. (2013)
N=36
(M=45 years)
Healthy Elderly Adults
Akoudad et al.
(2013)
N=4493
(M=63.9 yrs)
de Jong et al.
(2014)
N=361
(~71-99 yrs)
Desikan et al.
(2013)
N=107
(M=75.9 yrs)
Salminen et al.
(2013)
N=64
(aged 50+)
Zade et al. (2013)
N=1969
(M=61 years)
Zhu et al. (2013)
N=323
(M=73.3 yrs)
Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Patients
Goni et al. (2013)
N=65 MCI
voxel-wise
GMV
ɛ4 allele was associated with regions of reduced volume with notable right hemisphere
vulnerability (p’s<0.005).
GMV regions
associated with
Longitudinal Study: 13 of 15 regions showed higher atrophy over 12-48 months in ɛ4 carriers
relative to non-carriers, with largest effects found in amygdalae (baseline atrophy rate = 1.51%
(M=73.4 yrs)
Hostage et al.
N=237 MCI
(2014)
(M=79.9 yrs)
AD
loss in volume per annum; additional effect of ɛ4 = 2.40% loss pa; p<0.001) and hippocampi
(baseline atrophy rate = 2.76% loss in volume per annum; additional effect of ɛ4 = 1.53% loss pa;
p<0.001) – p values survive correction for multiple testing.
Kerchner et al.
(2014)
N=39 AD,
MCI, controls
hippocampal
subfields
Dose-dependent association of ɛ4 allele with greater thinning of the CA1 apical neuropil – a
hippocampal subregion vulnerable to AD (p=0.014) and worse episodic memory – potentially
causally related.
striatum GMV
and surface area
APOE genotype was found to have little or only small effects on striatal atrophy. However,
sample sizes for APOE subgroups were small.
WM
hyperintensities
(WMH)
Greater severity of WMH was associated with more rapid decline in cognitive function in ɛ4
carriers compared to non-carriers.
volume
trajectories
(ventricular,
total brain,
hippocampal)
Longitudinal Study: Brain scans were collected within 36 months of death and again at autopsy.
Ventricular volume trajectory, which correlated positively with ɛ4 status (p<0.00l), was found to
be a more sensitive marker of accruing AD than total brain or hippocampal volume trajectories
voxel-based
GMV
Longitudinal Study: APOE genotype was associated with distinct patterns of gray matter atrophy
over ~2 years in those converting: more pronounced occipital atrophy predicting conversion in ɛ4
carriers, and frontoparietal atrophy (+ worse executive function) predicting conversion in noncarriers (corrected p-values ranged 0.04-0.001).
medial temporal
lobe volume
APOE genotype can influence the classification of medial temporal lobe atrophy (used as a
marker of AD) and must be taken into account to avoid misdiagnosis.
N=100
voxel-based
Parkinson’s
GMV
There are suggestions that ɛ4 status may influence risk of MCI and AD in Parkinson’s patients,
with ɛ4 carriers found to have more severe cortical atrophy in the left parahippocampal gyrus
compared to non-carriers (uncorrected cluster threshold of P<0.001).
(M=70.6 yrs)
Pievani et al. (2013)
N=72 AD,
controls
(M=69.7 yrs)
Yoon et al. (2013)
N=1472 MCI
(M=70.0 yrs:
Korean)
Conversion from MCI to AD
Erten-Lyons et al.
(2013)
N=71:
20 converted
(M=94.7 at
death)
Morgen et al.
(2013)
N=82:
34 converted
(M=69.3 yrs)
Pereira et al. (2014)
N=1147 AD,
MCI, controls
(M=75.1 yrs)
Other Patient Groups
Chung et al. (2013)
(M=68.9 yrs;
Korean)
Fukazawa et al.
(2013)
N=175
medial temporal
lobe volume
and markers of
cerebrovascular
disease
Among AD patients with diabetes, a subgroup appear to be better characterized by diabetesrelated metabolic abnormalities (with clinical features including lower ɛ4 allele frequency and
less severe medial temporal lobe atrophy) and may require alternative therapeutic approaches.
WM integrity of
corpus callosum
ɛ4 carriers had greater memory impairment and white matter damage among stage III HIVpositive individuals than non-carriers (survived correction for multiple comparisons, p≤0.007).
voxel-based
GMV
Longitudinal study: Gray matter density was examined before, and again one month after,
chemotherapy in breast cancer patients. Changes did not differ for APOE genotype.
(M=75.3 yrs)
Temporal lobe
ROI volumes
(cumulative
atrophy)
Longitudinal Study: Study assessed biases that can arise when tracing brain changes in
longitudinal imaging and showed that smaller sample sizes are needed to track AD progression if
data is stratified by APOE ɛ4 status. A faster rate of atrophy was observed in ɛ4 carriers relative to
non-carriers among AD, MCI, and healthy control groups.
N=843 AD,
hippocampal
A newly developed automated registration system is introduced. It outperformed two other
systems (FIRST, SPHARM) in assessing the hippocampus, and successfully showed APOE
diabetes
(M=76.8 yrs;
Japanese)
Hoare et al. (2013)
N=45 HIV
(18-35 years;
African)
McDonald et al.
(2013)
N=79
breast cancer
(M=49.9 yrs)
Methodological
Hua et al. (2013)
Shi et al. (2013)
N=468 AD,
MCI, controls
MCI, controls
volume
effects (regions of smaller volume in ɛ4 carriers versus non-carriers) in individuals with MCI and
in healthy controls (p=0.0014).
voxel-wise
GMV
APOE-MAPT: ɛ4 carriers who were also MAPT H1/H1 had smaller frontal and parietal regions
compared to other genotype combinations (p<0.005).
(55-90 years)
Gene-Gene Interaction
Goni et al. (2013)
N=65 MCI
(M=73.4 yrs)
NOTE: PubMed search: ((Brain) OR ("white matter") OR ("gray matter") OR ("grey matter")) AND (*MRI OR DTI OR FA) AND (gene OR genes) AND
(APOE) AND (“2013/01/01"[Date - Publication] : "2014/07/15"[Date - Publication]) NOT (genome-wide OR “genome wide” OR GWA OR GWAS). The search
was further filtered for human samples and English language and only candidate gene studies were retained.
a
As most samples are Caucasian (or predominantly Caucasian), ancestry is only noted when it is known to differ.
b
ROI = Region of interest, GMV = gray matter volume; WM = white matter; AD = Alzheimer’s disease, MCI = mild cognitive impairment
Online Resource 4. BDNF Val66Met Genotype Effects on Neuroimaging Structural Phenotypes: Overview
of Studies January 2014 to July 2014
Study
Samplea Size
Structural
(Age)
Phenotypeb
Finding
Healthy Individuals
Brooks et al. (2014)
N=345
(70-75 years)
Forde et al. (2014)
N=60
(18-55 years)
Harrisberger et al.
(2014)
1. N=5298
voxel-based
GM, WM and
CSF volumes
Elderly Met66 carriers had better working memory performance compared to Val66 homozygotes,
as well as larger gray matter volumes in memory, decision-making, and motor regions (e.g.
prefrontal cortex, p<0.001), with reduced volumes in somatorsensory/arousal regions (e.g.
occipito-temporal lobe, p=0.001), leading the authors to propose that their better performance
may be due to greater cognitive control and reduced arousal interference.
multiple voxelbased GM and
WM measures
The met-dose effect in relation to brain morphology was examined and an “inverted-U” shaped
profile rather than the expected linear effect was found for gray matter volume (including the
cerebellum: val/met > val/val (p=0.006) and met/met (p=0.09)) and fractional anisotropy (right
dorsal cingulum bundle: val/met > met/met (p=0.02) and val/val (p=0.26)). **bonferonni
corrected**
hippocampal
volume
1. Meta-analysis: Data from 32 samples were analysed and a weak effect showing Met 66 carriers
having smaller volumes relative to non-carriers was identified (p=0.04, g=0.09 (Hedges’s g values
above 0.2, 0.5, and 0.8 correspond to small medium, and large effect sizes respectively)).
However, evidence of a publication bias among studies using manual tracing was observed, and
after excluding these studies, no genotype effect was found.
2. N=643
(M=22.9 yrs)
2. No genotype effect observed.
Huang et al. (2014)
N=90
(65-92 years;
Chinese)
Knickmeyer et al.
(2014)
N=272
(neonates)
Lim et al. (2013)
N=165
WM
hyperintensity
(WMH) volume
Val66 homozygotes had inferior memory performance and larger WMH volumes than Met66
carriers (temporal, P=0.035; occipital, P=0.006; global WMH, P=0.025).
automated
region of
interest (ROI)
GMV
Val158 homozygotes relative to Met158 carriers had multiple clusters of increased and/or reduced
volumes in regions including occipital and primary motor and somatosensory areas (multiple
ROIs retained significance after correction for multiple testing with p≤1.0x10-4).
hippocampal
volume
Longitudinal (3 year follow-up): APOE genotype interacted with amyloid-beta. Among
individuals with high amyloid-beta (but not low amyloid-beta), Val66 homozygotes showed
reduced cognitive decline and less hippocampal atrophy over 3 years than Met66 carriers (cohen’s
d = 0.73 (95% CIs 0.08, 1.35)). Also, among Met66 carriers, atrophy was reduced in those with
low amyloid-beta (cohen’s d = 1.11 (95% CIs 0.46, 1.73)).
multiple WM
measures
Decreases in fractional anisotropy and widespread increases in radial diffusivity, particularly in
prefrontal and occipital pathways were found in Val66 homozygotes compared to Met66 carriers
(P<0.05). Authors proposed that increased axonal branching, as shown in Met/Met mice
compared to wild type Val/Val (Cao et al. 2007), may underlie diminished radial diffusivity in
human Met66 carriers.
cortical surface
area
Met66 was dose-related to larger surface area for the anterior insular cortex (p<0.001).
(M=71.4 yrs)
Tost et al. (2013)
N=85
(M=33.5 yrs)
C. Wang et al.
(2014)
N=280
(18-30 years;
Han Chinese)
Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), Major Depressive Disorder (MDD), and Other Patient Groups
Cardoner et al.
(2013)
N=37 MDD
regional GM
volumes
Met66 carriers had regions of reduced volume in the left hippocampus (P=0.003) but larger
orbitofrontal cortex volumes (P<0.0005) compared to Val66 homozygotes.
multiple WM
measures
Val66Met did not differentiate between temporal lobe white matter abnormalities found in patients
with first episode, treatment-naïve, MDD and controls.
hippocampal
and whole brain
volume
Longitudinal (381 with 2 year follow-up): The influence of 8 BDNF SNPs was examined. Six
were associated with hippocampal and/or whole brain atrophy over two years. Met 66 carriers
showed greater right hippocampal atrophy than Val66 homozygotes (only found in controls,
N=127, p=0.027). However, cross-sectional analyses suggested Val66 homozygotes had greater
whole brain atrophy with increasing age than Met66 carriers (N=578, p<0.005).
voxel-based
GM volumes
Among adolescents with an anxiety disorder (N=39), Met66 carriers had smaller anterior insula
(p=0.004, Cohen’s d = 0.79) and posterior insula volumes (p=0.008, Cohen’s d = 0.57)
compared to Val66 homozygotes, while no genotype-related differences were found in healthy
controls (N=63).
(44-75 years)
Hayashi et al.
(2014)
N=30 MDD
(M=44 years)
Honea et al. (2013)
N=645 AD,
MCI, controls
(55-90 years)
Mueller et al.
(2013)
N=102
anxiety,
controls
(M=13.3 yrs)
Mon et al. (2013)
N=62 alcohol
dependent
GM, WM, and
CSF volumes
Longitudinal (41 with 5 week follow-up during abstinence): This is the first study examining
Val66Met effects on recovery of brain tissue volume during short-term abstinence. Genotype was
associated with different recovery patterns. Val66 homozygotes showed increases in gray matter
volumes (e.g. for frontal GM % change = 0.30 for Val/Met, p=ns; % change = 1.20 for Val/Val,
p<0.001). However, Met66 carriers showed increases predominantly in white matter volumes (e.g.
for frontal WM % change = 1.49 for Val/Met, p=0.020; % change = -0.07 for Val/Val, p=ns).
Notably, only gray matter increases were associated with improvements in neurocognitive
measures. No genotype effects were seen in cross-sectional analyses.
total brain
tissue, plus GM,
WM, ventricles,
& CSF volumes
Longitudinal (3 year follow-up): No genotype effects were found for brain volume changes in
first episode non-affective psychosis patients and controls.
WM lesion ratio
A trend for greater lesion ratio in the frontal corpus callosum in Met 66 carriers compared to Val66
homozygotes was identified (P=0.0375).
ROI brain
volumes
Higher levels of physical activity were associated with larger hippocampal and temporal lobe
volumes in Val66 homozygotes, but smaller temporal lobe volume in Met66 carriers (hippocampus:
p=0.02, standardised β = -0.22; temporal lobe: p=0.003, standardised β = -0.28 (significance
threshold adjusted for multiple comparisons p≤0.0083)).
hippocampal
volume
The association between number of stressful life events and hippocampal volume in healthy
individuals was positive in Met66 carriers, but negative in Val66 homozygotes (p=0.003, corrected
for multiple comparisons).
ventricular and
hippocampal
volumes
Childhood abuse was negatively associated with cognitive performance and right hippocampal
volume in Met66 carriers, but not Val homozygotes (p=0.005 & 0.008 respectively, significant
after correction for multiple testing).
hippocampal
volume
Among those with no history of childhood adversity (CA), Met66 carriers (both MDD and
controls) had larger left hippocampal volumes than Val66 homozygotes (p=0.042, corrected for
multiple comparisons). However, having a history of CA, relative to none, was associated with
reduced left hippocampal volume in Met66 carriers (p=0.028), but not in Val66 homozygotes.
hippocampal
volume
A history of childhood trauma was tentatively associated with increased hippocampal volume in
Met66 carriers relative to Val66 homozygotes among patients, but the opposite (decreased volume)
among their non-psychotic siblings. However, substance abuse was found to be confounding
factor and no genotype effects were found after controlling for substance abuse (compared to
patients, alcohol consumption was higher, but cannabis and other drug use was lower, in healthy
siblings).
hippocampal
volume
COMT-BDNF-SLC6A4: No gene-gene interactions were observed. However, a cumulative risk
score (reflecting the number of COMT Met158 alleles, SLC6A4 5-HTTLPR Short alleles, and
BDNF Val66 homozygotes) was highly predictive of hippocampal volume in interaction with
number of adverse life events (p<1.0x10-5, β=-0.41).
(M=50.8 yrs)
Suarez-Pinilla et al.
(2013)
N=123
psychosis,
controls
(M=29.6 yrs)
Taylor et al. (2013)
N=62 MDD,
controls
(aged 60+)
Interaction with Environmental Factors
Healthy Individuals
Brown et al. (2014)
N=114
(60+ years)
Rabl et al. (2014)
N=153
(18-45 years)
Patients (psychosis, depression)
Aas et al. (2013)
N=106
Psychosis
(N=32.7 yrs)
Carballedo et al.
(2013) and Frodl et
al. (2014)
N=133 MDD,
controls
(18-65 years)
(Hernaus et al.
(2014))
N=184
psychosis,
controls
(M=28.9)
Gene-Gene Interactions
Healthy Individuals
Rabl et al. (2014)
N=153
(18-45 years)
NOTE: PubMed search: ((Brain) OR ("white matter") OR ("gray matter") OR ("grey matter")) AND (*MRI OR DTI OR FA) AND (gene OR genes) AND
(BDNF) AND (“2013/01/01"[Date - Publication] : "2014/07/15"[Date - Publication]) NOT (genome-wide OR “genome wide” OR GWA OR GWAS). The search
was further filtered for human samples and English language and only candidate gene studies were retained.
a
As most samples are Caucasian (or predominantly Caucasian), ancestry is only noted when it is known to differ.
b
ROI = region of interest, GM = gray matter; WM = white matter; CSF = cerebrospinal fluid, AD = Alzheimer’s disease, MCI = mild cognitive impairment
Online Resource 5. COMT Val158Met Genotype Effects on Neuroimaging Structural Phenotypes: Overview
of Studies January 2014 to July 2014
Study
Samplea Size
Structural
(Age)
Phenotypeb
Finding
Healthy Individuals
Knickmeyer et al.
(2014)
N=272
(neonates)
Y. Wang et al.
(2013)
N=320
automated
region of
interest (ROI)
GMV
Val158 homozygotes relative to Met158 carriers had multiple clusters of increased and/or reduced
volumes in regions including temporal, parietal, occipital and supplementary motor areas (multiple
ROIs retained significance after correction for multiple testing with p≤1.0x10-4).
hippocampal
volume
Both working memory performance and hippocampal volume were greater in Val158 homozygotes,
with Met158 alleles having a negative load effect (right hippocampal volume P=0.019, β=-0.118)
(19-21 years,
Chinese)
Major Depressive Disorder (MDD) and Other Patient Groups
Hayashi et al.
(2014)
N=30 MDD,
controls
multiple WM
measures
MDD was associated with white matter changes, with decreased temporal lobe fractional anisotropy
and axial diffusivity in Met158 carriers with MDD compared with sex- and age-matched controls
(P<0.05).
multiple WM
measures
Increased fractional anisotropy was found in right hemisphere clusters in Met158 carriers compared
to Val158 homozygotes, for patients (corrected p<0.05), but not for matched controls.
multiple WM
measures
Reduced fractional anisotropy (temporal, frontal, cingulum) was found for MDD Val158
homozygotes compared to Met158 carriers but not controls (e.g. bilateral frontal WM and genu of
corpus callosum, p<0.001). Threshold free cluster enhancement corrected p value (family-wise
error corrected p<0.01).
multiple WM
measures
In the context of addiction, Met158 homozygotes showed greater vulnerability to drug-related
changes in prefrontal fractional anisotropy (e.g. p=0.009, corrected for family-wise error).
cortical
thickness
COMT-GAD1: Cortical thickness (left parahippocampal gyrus) was found to be reduced by 7.5% in
GAD1 G allele homozygotes, relative to A allele carriers (p=0.008), but only in the presence of the
COMT Val158 allele (p=0.006), reflecting and interaction between the GABAergic and dopaminergic
systems. Results corrected for multiple comparisons.
fronto-limbic
GM volumes
COMT-SLC6A4: Hippocampal and amygdalar volumes were smaller in individuals with both
COMT Met158 and 5-HTTLPR Short alleles, or COMT Val158 and r-HTTLPR Long alleles (e.g. left
parahippocampal gyrus: p<0.001), compared to other allelic combinations. Bonferroni-Holm
correction for multiple comparisons.
(M=44 years)
Kim et al. (2013)
N=52 panic
disorder,
controls
(18-60 years,
Korean)
Seok et al. (2013)
N=148 MDD,
controls
(M=43.6 yrs,
Korean)
Zhang et al. (2013)
N=274
substance
abuse,
controls
(M=32.6 yrs)
Gene-Gene Interaction
Healthy Individuals
Brauns et al. (2013)
N=94
(18-60 years)
Radua et al. (2014)
N=91
(M=33 years)
Rabl et al. (2014) – see Gene-Gene Interaction, COMT-BDNF-SLC6A4, Table 5
NOTE: PubMed search: ((Brain) OR ("white matter") OR ("gray matter") OR ("grey matter")) AND (*MRI OR DTI OR FA) AND (gene OR genes) AND
(COMT) AND (“2013/01/01"[Date - Publication] : "2014/07/15"[Date - Publication]) NOT (genome-wide OR “genome wide” OR GWA OR GWAS). The search
was further filtered for human samples and English language and only candidate gene studies were retained.
a
As most samples are Caucasian (or predominantly Caucasian), ancestry is only noted when it is known to differ.
b
ROI = region of interest, GM = gray matter; WM = white matter; CSF = cerebrospinal fluid, AD = Alzheimer’s disease, MCI = mild cognitive impairment
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