Siblings of individuals with autism
A novel functional brain imaging endophenotype
of autism: the neural response to facial expression of
A novel functional brain imaging endophenotype
emotion
MD Spencer1, RJ Holt1, LR Chura1, J Suckling2, AJ Calder3, ET Bullmore2 and S Baron-Cohen1
Siblings of individuals with autism have over 20 times the population risk of autism. Evidence of comparable, but less marked,
cognitive and social communication deficits in siblings suggests a role for these traits in the search for biomarkers of familial
risk. However, no neuroimaging biomarkers of familial risk have been identified to date. Here we show, for the first time, that the
neural response to facial expression of emotion differs between unaffected siblings and healthy controls with no family history of
autism. Strikingly, the functional magnetic resonance imaging (fMRI) response to happy versus neutral faces was significantly
reduced in unaffected siblings compared with controls within a number of brain areas implicated in empathy and face
processing. The response in unaffected siblings did not differ significantly from the response in autism. Furthermore,
investigation of the response to faces versus fixation crosses suggested that, within the context of this study, an atypical
response specifically to happy faces, rather than to faces in general, accounts for the observed sibling versus controls
difference and is a clear biomarker of familial risk. Our findings suggest that an atypical implicit response to facial expression of
emotion may form the basis of impaired emotional reactivity in autism and in the broader autism phenotype in relatives. These
results demonstrate that the fMRI response to facial expression of emotion is a candidate neuroimaging endophenotype for
autism, and may offer far-reaching insights into the etiology of autism.
Translational Psychiatry (2011) 1, e19; doi:10.1038/tp.2011.18; published online 12 July 2011
Introduction
Siblings of individuals with autism have a greatly enhanced
risk of developing autism—estimated to be in excess of a 20-
fold increase compared with the general population.1–3
Furthermore, it is increasingly understood that many apparently
unaffected siblings (and their parents, as another
example of first-degree relatives) display subtle impairments
in the cognitive domains characteristically affected by
autism.4–7 Siblings of individuals with autism have however
been the subject of relatively little neuroimaging research.8–10
The concept of an endophenotype—a marker of familial risk
for a condition—has in recent years become the focus of
considerable attention in neuropsychiatric research. Although
the term was first used in the 1960s in the field of insect
biology,11 within a few years it was applied within psychiatry.12
An endophenotype is a heritable feature associated with a
condition, present in affected individuals regardless of
whether their condition is manifested, which co-segregates
with the condition in families and which is present in
unaffected family members at a higher rate than in the
general population.13 In such family members, endophenotypes
represent instances in which genes associated with a
particular condition exert measurable effects in individuals in
whom they are insufficient to cause the condition itself to
become manifest. The promise of characterizing endophenotypes
lies in their hypothesized intermediate position between
genotype and phenotype. Syndromes such as autism,
schizophrenia and bipolar disorder are complex constellations
of clinical signs and symptoms. Considerable phenotypic
heterogeneity exists within clinical populations and it is
likely that the etiologies of these conditions contain heterogeneity
too. In the case of autism, it has been recognized that
a unitary cause is unlikely.14 Attempts to characterize the
genetics of these conditions therefore will ultimately be
hampered by a reliance on traditional classificatory systems
that coalesce this heterogeneity into a unitary diagnosis.
As a smaller and simpler phenotypic unit than the condition
itself, the etiology of the endophenotype is likely to be
correspondingly simpler: it can be said to be ‘closer to the
level of gene action’.15
Difficulties in empathy and in the understanding of social
stimuli and situations form a central aspect of the autistic
phenotype.16 The neurophysiological response to faces, and
in particular facial emotional expressions, is atypical in autism.
This has been documented using electroencephalography,17
magnetoencephalography,18 positron emission tomography
19 and functional magnetic resonance imaging (fMRI)20
Received 21 April 2011; revised 2 June 2011; accepted 3 June 2011
1Department of Psychiatry, Autism Research Centre, University of Cambridge, Cambridge, UK; 2Department of Psychiatry, Herchel Smith Building for Brain and Mind
Sciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK and 3MRC Cognition and Brain Sciences Unit, Cambridge, UK
Correspondence: Dr MD Spencer, Department of Psychiatry, Autism Research Centre, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge
CB2 8AH, UK.
E-mail: mds1003@cam.ac.uk
Keywords: autism; endophenotype; fMRI; genetic; sibling
Citation: Transl Psychiatry (2011) 1, e19, doi:10.1038/tp.2011.18
& 2011 Macmillan Publishers Limited All rights reserved 2158-3188/11
www.nature.com/tp
studies. A considerable body of evidence reveals atypical
fMRI response to faces and other social stimuli within a
network of brain structures that has been termed the ‘social
brain’.21,22 This comprises the amygdala and its interconnections
with the superior temporal sulcus (STS), orbitofrontal
cortex, anterior cingulate cortex and fusiform face area (FFA),
among other regions. The STS is of particular importance not
only in being activated during a range of mentalizing tasks in
controls23 but also as a site within which brain structure and
function correlate with autistic traits in the general population.
24 Similarly, the FFA located within the fusiform gyrus of
the occipitotemporal cortex is particularly activated by facial
stimuli in controls25 and is greatly reduced in activation in
people with autism.20 Given reports of social deficits in
relatives of those with autism,26 the neural response to
emotional expressions in faces seems a promising area within
which to investigate possible endophenotypes of autism.
The aim of this study was to investigate the neural response
to facial expressions of emotion in adolescents with autism,
their unaffected siblings and controls with no family history of
autism, in order to enable the separation of neurobiological
markers associated with familial risk for autism from those
associated with the condition itself, and thus to suggest
candidate endophenotypes of autism.
Participants and methods
Participants. Participants comprised 40 adolescents (aged
12–18 years) with an autism spectrum disorder (ASD)
diagnosed as either autism or Asperger syndrome, 40
unaffected siblings and 40 typically developing controls. All
ASD participants met Diagnostic and Statistical Manual of
Mental Disorders, fourth edition criteria16 for autism or
Asperger syndrome, and were assessed as positive on
both the Autism Diagnostic Interview-Revised27 and the
Autism Diagnostic Observation Schedule-Generic.28
Participants with autism and their siblings were recruited by
approaching support groups for families with autism and
schools; controls were recruited through notices in schools
and community groups in similar neighborhoods to the
participants in the autism and sibling groups—in order to
minimize possible confounds relating to geography and
demographics. All siblings and controls scored below threshold
on a screening tool for ASD—the Social Communication
Questionnaire.29 Siblings were full biological siblings of the
participants with autism, based on parental report; controls
were defined as having no history of an ASD within any first- or
second-degree relative. General exclusion criteria were: fullscale
intelligence quotient (IQ) o70 as measured using the
Wechsler Abbreviated Scale of Intelligence,30 any psychiatric
diagnosis (other than ASD in the autism group), any current or
previous psychotropic medication, any history of seizures,
any history of head injury or intracranial surgery and any
history of drug abuse.
Participants with autism (35 males:5 females) had mean
age 14.56 years (range: 12.01–18.53; s.d.: 1.74) and mean IQ
106.5 (range: 73–146; s.d.: 16.6). Siblings (12 males:28
females) had mean age 14.83 years (range: 12.01–18.95;
s.d.: 2.14) and mean IQ 113.1 (range: 88–133; s.d.: 10.1).
Controls (20 males:20 females) had mean age 15.06 years
(range: 12.08–18.17; s.d.: 1.63) and mean IQ 112.4 (range:
83–136; s.d.: 11.1). Groups did not differ in terms of mean age
(P¼0.481; F¼0.737). The autism group had significantly
lower mean IQ than the sibling group (P¼0.033; F¼4.71) but
not the control group (P¼0.065; F¼3.50). Importantly, for
our investigation of markers of familial risk expressed as
differences between sibling and control groups, sibling and
control groups did not differ in terms of mean IQ (P¼0.753;
F¼0.100).
The protocol was approved by the Cambridgeshire 1
Research Ethics Committee. All participants and their parents
provided written informed consent.
Task protocol. Participants completed a task of implicit
facial emotion processing comprising eight blocks of happy
faces, eight blocks of fearful faces, eight blocks of neutral
faces and eight blocks of fixation crosses. Facial stimuli were
from an established battery of emotional faces,31 and
comprised eight different facial identities expressing happy,
fearful and neutral expressions (that is, 24 faces in total).
Stimuli were presented in a blocked design in one of two
pseudorandom orders (which were counterbalanced across
all participants in each study group) and were presented in
e-Prime version 2.0 Professional (Psychological Software
Tools, Pittsburgh, PA, USA). Each block lasted 20 s and
comprised four stimuli presented for 4 s each with an
interstimulus interval of 1 s. Blocks were separated by a 2 s
interblock interval. During task conditions (happy, fearful and
neutral faces) participants were required to press one of
two buttons to indicate the gender of the face using a
button box held in the right hand. During fixation blocks,
the participants were required to stare passively at a
fixation cross. As with the facial blocks, four fixation cross
stimuli were presented for 4 s each with an interstimulus
interval of 1 s.
Imaging protocol. All participants were scanned using
the same Siemens 3T Tim Trio scanner (Siemens Healthcare,
Erlangen, Germany) at the Medical Research Council Cognition
and Brain Sciences Unit, Cambridge, UK. Functional
images were acquired with a gradient echo planar
imaging sequence with the following parameters: repetition
time¼2000 ms, echo time¼30 ms, voxel size¼3 3 3mm,
field of view¼192 192mm, 64 64 acquisition matrix and a
781 flip angle. In all, 32 slices were acquired descending in the
transverse plane (slice thickness¼3mm, slice gap¼25%).
Each volume was acquired over 2 s and the first three volumes
were discarded to avoid equilibration effects.
Statistical analysis
Behavioral data. Behavioral data comprising accuracy and
reaction time of response on the sex discrimination task were
recorded in order to investigate whether any participant
performed at or below the level of chance and analyzed using
analysis of variance in PASW Statistics 18, Release Version
18.0.0 (SPSS, Chicago, IL, USA). The effect of group on
accuracy (P¼0.111; F¼2.241) and reaction time
(P¼0.191; F¼1.679) of response was not statistically
significant (analyses covarying for age and sex). Only two
A novel functional brain imaging endophenotype of autism
MD Spencer et al
2
Translational Psychiatry
participants (one participant with autism and one control)
performed at or below the level of chance on the sex
discrimination task. In case this was indicative of reduced
attention to the facial stimuli, all analyses were repeated
excluding these two participants to confirm that all
statistically significant results reported were robust to the
exclusion of the data from these two participants.
Imaging data. Preprocessing and first-level analyses were
performed in SPM8 (Wellcome Department of Cognitive
Neurology, London, UK) implemented using the automatic
analysis platform as previously described32 (Medical Research
Council Cognition and Brain Sciences Unit, Cambridge, UK)
according to the standard Medical Research Council Cognition
and Brain Sciences Unit pipeline comprising sinc
interpolation to correct for the acquisition of different brain
slices at different times, coregistration of echo planar imaging
and structural scans, normalization to Montreal Neurological
Institute (MNI) space33 and smoothing using a Gaussian
kernel of 10mm full width at half maximum. For each
subject, fMRI responses were modeled using a canonical
hemodynamic response function and the general linear model
was used to perform a first level, within-participants analysis
on the functional data from each subject individually for the
primary contrasts (happy minus neutral and fearful minus
neutral faces), with spatial realignment parameters entered as
covariates.
To characterize the patterns of activation within the brain in
the three participant groups, the first-level contrast images for
each study group were taken through to a second-level
analysis using a random-effects model, with age and sex
specified as covariates. Group-level activation maps were
generated with a global threshold set at Po0.05 following
correction for multiple comparisons on a whole-brain level
family-wise error (FWE) basis, and with a cluster extent (kE)
threshold set at 20 voxels. In the same way, all activation
results quoted (Table 1) are after the whole-brain level FWE
correction for multiple comparisons and kE threshold of
20 voxels.
To investigate possible biomarkers of familial risk as compared
with autism versus control differences, we examined
between-group differences in the fMRI response in autism,
sibling and control participants within the specific brain regions
identified as being significantly activated in the control group.We
therefore defined our regions of interest as the clusters of FWE
corrected Po0.05 significant activation within the control group
activation maps (Table 1), and used MarsBar34 to extract mean
activations for the primary contrast (happy minus neutral and
fearfulminus neutral) for each subject for each region of interest.
For illustration, we plotted these FWE corrected activation
maps onto the canonical Montreal Neuroimaging Institute
(MNI) 152 template brain image33 using SPM8, and onto a
three-dimensional-rendered template brain image using MRIcron
software (http://www.sph.sc.edu/comd/rorden/mricron/).35
Table 1 Main activations to happy and fearful versus neutral faces
MNI coordinates P-value
(FWE-corrected)
Z-score Cluster
size
Region
x y z kE (voxels)
Happy versus neutral faces
Control group
28 10 54 0.002 5.07 129 Left superior frontal gyrus
46 20 16 0.003 4.90 78 Right temporal pole
42 14 16 0.004 4.86 200 Left temporal pole
36 62 24 0.006 4.76 77 Left temporoparietal junction
54 64 10 0.009 4.66 115 Left posterior STS
44 52 28 0.010 4.65 60 Right FFA
4 26 54 0.012 4.60 64 Left dorsomedial prefrontal cortex
66 28 2 0.015 4.54 32 Right middle STS
28 92 8 0.018 4.51 26 Right cuneus
62 52 4 0.026 4.41 26 Left middle STS
24 94 8 0.031 4.37 20 Left cuneus
Sibling group
Nil
Autism group
Nil
Fearful versus neutral faces
Control group
44 48 22 0.006 4.78 38 Right FFA
Sibling group
40 42 16 0.005 4.80 33 Right FFA
Autism group
Nil
Abbreviations: FFA, fusiform face area; FWE, family-wise error; MNI, Montreal Neuroimaging Institute; STS, superior temporal sulcus.
Activated brain regions, corresponding MNI coordinates, cluster sizes, Z-scores and P-values. All analyses are corrected for multiple comparisons, and P-values are
expressed following whole brain level FWE correction at the threshold of Po0.05.
A novel functional brain imaging endophenotype of autism
MD Spencer et al
3
Translational Psychiatry
We conducted analyses of variance within PASW Statistics
18 to measure the overall effect of group on the primary
contrast activation data (happy minus neutral and fearful
minus neutral) for each region of interest. Age and sex were
modeled as covariates in all analyses. Similarly, we used
analyses of variance to investigate autism versus control,
control versus sibling and autism versus sibling differences,
again taking age and sex as covariates. We investigated
linear trend effects across the three groups using polynomial
regression, and where a statistically significant linear effect
was found, we examined the quadratic effect to confirm that
this was nonsignificant. We plotted the mean activation
contrast estimate (expressed in arbitrary units±standard
error of the mean) for the three study groups.
To investigate whether the atypical response to happy
versus neutral faces was driven by an atypical response to
happy or neutral faces, or to both, we examined the response
to faces versus fixation crosses. First-level analysis was as
above, taking the primary contrasts as happy and neutral
faces versus fixation crosses. Second-level statistical analysis
proceeded as described above for the emotional versus
neutral contrasts.
Results
Neural response to facial expressions of emotion: happy
versus neutral faces. We examined the differential
response within the brain to happy compared with neutral
faces. In controls, happy faces elicited increased activation
compared with neutral faces (Figure 1 and Table 1) within a
range of areas strongly implicated in face processing,
empathy and mentalizing: the right (P¼0.003) and left
(P¼0.004) temporal poles, left temporoparietal junction
(P¼0.006), left posterior STS (P¼0.009), right FFA
(P¼0.010), dorsomedial prefrontal cortex (P¼0.012) and
right (P¼0.015) and left (P¼0.026) middle STS. Increased
activation was also detected in the left superior frontal gyrus
(P¼0.002) and the right (P¼0.018) and left (P¼0.031)
cuneus. All P-values are expressed following correction for
multiple comparisons on a whole-brain level FWE basis. In
contrast, no activation differences were detected within
sibling and autism groups at the threshold of Po0.05 FWE
corrected.
To investigate biomarkers of familial risk compared with
autism versus control differences, we examined betweengroup
differences in the fMRI response in autism, sibling and
control participants within the specific brain regions identified
above as being significantly activated in controls to happy
versus neutral faces (listed in Table 1). For all 11 brain
regions, activation was significantly reduced in autism
compared with controls, with siblings demonstrating an
intermediate degree of impairment.
Activation in siblings was significantly reduced compared
with controls for 7 of the 11 brain regions: the left superior
frontal gyrus (P¼0.001; F¼11.664), the right (P¼0.002;
F¼9.986) and left (P¼0.005; F¼8.551) temporal poles, the
right middle (P¼0.004; F¼9.068) and left posterior
(P¼0.016; F¼6.064) STS, the left dorsomedial prefrontal
cortex (P¼0.005; F¼8.570) and the right FFA (P¼0.044;
F¼4.184) (univariate analyses of variance, covarying for age
and sex; Figures 1 and 2). Furthermore, for all 11 regions,
activation in the autism group was significantly reduced
compared with controls, the effect of group was significant
across all the three groups, and polynomial regression linear
contrast effects across all the three groups were significant
Middle
STS
Temporal
pole
FFA
-28 -16 +2
4.6
4.8
5.2
5.0
Superior DMPFC
frontal
Cuneus
Left Right
Posterior
STS
TPJ
P = 0.001 P = 0.002 P = 0.004
+10
0.2
0.1
0.0
0.3
-0.1
autism sibling control
autism sibling control
autism sibling control
autism sibling control autism sibling control
autism sibling control autism sibling control
autism sibling control autism sibling control
autism sibling control autism sibling control
contrast estimate +/- SE
0.3
0.2
0.1
0.0
-0.1
0.4
-0.2
contrast estimate +/- SE
0.2
0.1
0.0
-0.1
0.3
-0.2
contrast estimate +/- SE
0.3
0.2
0.1
0.0
-0.1
contrast estimate +/- SE
0.3
0.2
0.1
0.0
contrast estimate +/- SE
0.1
0.2
0.0
contrast estimate +/- SE
0.2
0.1
0.3
0.0
contrast estimate +/- SE
0.3
0.2
0.1
0.0
-0.1
-0.2
contrast estimate +/- SE
0.2
0.1
0.0
-0.1
0.3
-0.2
contrast estimate +/- SE
0.3
0.2
0.1
0.0
-0.1
contrast estimate +/- SE
0.3
0.2
0.1
0.0
-0.1
-0.2
contrast estimate +/- SE
+24 +54
P < 0.001 P < 0.001 P < 0.001
Left superior
frontal gyrus
Right temporal pole Right middle STS
Left posterior
STS
Left DMPFC Left temporal pole
P = 0.005
P < 0.001
P = 0.016
P = 0.002
P = 0.005
P < 0.001
Right FFA Left middle STS
P = 0.044
P < 0.001
P = 0.003 P = 0.007
P < 0.001 P = 0.001
Left cuneus
Left TPJ Right cuneus
Figure 1 Neural response to happy versus neutral faces. Activation differences
(means±s.e.m.) between the functional magnetic resonance imaging response to
happy and neutral faces in adolescents with autism (n¼40), unaffected siblings
(n¼40) and controls (n¼40). Activation map indicates neural response to happy
versus neutral faces in controls, and shows activations to happy versus neutral
faces (Po0.05, FWE corrected) overlaid onto the canonical Montreal Neurological
Institute (MNI) 152 template brain image (axial section, z-coordinate indicated in
Montreal Neurological Institute space), with the colored bar indicating the T-value of
the plotted activation differences. DMPFC, dorsomedial prefrontal cortex; FFA,
fusiform face area; STS, superior temporal sulcus; TPJ, temporoparietal junction.
A novel functional brain imaging endophenotype of autism
MD Spencer et al
4
Translational Psychiatry
with no significant quadratic component. For all 11 regions,
activation in the autism group did not differ statistically
significantly from activation in siblings (Table 2).
Neural response to facial expression of emotion: fearful
versus neutral faces. In controls and in siblings, fearful
faces elicited increased activation compared with neutral
faces (Figure 3 and Table 1) within the right FFA (controls:
P¼0.006, siblings P¼0.005; FWE corrected). However, the
autism group did not display any significant activation
differences at the threshold Po0.05 FWE corrected.
As with the happy versus neutral analyses above, we
examined between-group differences in the fMRI response in
autism, sibling and control participants within the right FFA,
characterized above as the brain region significantly activated
in controls in fearful versus neutral faces. Activation in the
autism group was significantly reduced compared with
controls and a significant polynomial regression linear
contrast effect with no significant quadratic component was
detected across all the three groups (Figure 3 and Table 2).
However, activation in the sibling group did not differ
significantly from activation in controls or the autism group.
Neural response to faces versus fixation crosses. These
findings demonstrate a clear linear progression across
autism, sibling and control groups for atypical fMRI
activation to happy versus neutral faces. To address the
question as to whether the neural basis for this marker is an
atypical neural response to happy faces, neutral faces or to
both, we used the same brain regions defined by the
significant activations within controls to happy versus
neutral faces (comprising the 11 clusters listed in Table 1)
0.2
0.1
0.0
-0.1
0.3
-0.2
autism sibling
Middle STS Superior frontal
gyrus
Right Left
Temporal pole Temporal pole
control autism sibling control
autism sibling control autism sibling control
contrast estimate +/- SE
0.2
0.1
0.0
-0.1
0.3
-0.2
contrast estimate +/- SE
0.2
0.1
0.0
0.3
-0.1
contrast estimate +/- SE
0.2
0.1
0.0
0.3
-0.1
-0.2
contrast estimate +/- SE
P = 0.004 P = 0.001
P = 0.005
P < 0.001
P < 0.001 P < 0.001
P < 0.001
P = 0.002
Figure 2 Differences between ‘unaffected’ siblings and controls with no family history of autism in the neural response to happy versus neutral faces. Activation differences
(means±s.e.m.) between the functional magnetic resonance imaging response to happy and neutral faces in adolescents with autism (n¼40), unaffected siblings (n¼40)
and controls (n¼40). Activation map corrected for multiple comparisons at Po0.05 family-wise error corrected, and overlaid onto a three-dimensional-rendered template
brain within MRIcron. STS, superior temporal sulcus.
Table 2 Between-group differences in activations to emotional versus neutral faces
Region of significant activation
in controls
Between-group differences
P-value (F-statistic)
Effect of group
(across all three groups)
Polynomial regression
linear trend effect
Control versus
sibling
Control
versus
autism
Sibling versus
autism
P-value
(F statistic)
P-value
Happy versus neutral faces
Left superior frontal gyrus 0.001 (11.664) o0.001 (17.222) NS o0.001 (9.448) o0.001
Right temporal pole 0.002 (9.986) o0.001 (13.703) NS o0.001 (8.994) o0.001
Right middle STS 0.004 (9.068) o0.001 (18.608) NS o0.001 (11.073) o0.001
Left dorsomedial prefrontal cortex 0.005 (8.570) o0.001 (18.714) NS o0.001 (8.957) o0.001
Left temporal pole 0.005 (8.551) o0.001 (15.181) NS o0.001 (8.763) o0.001
Left posterior STS 0.016 (6.064) 0.002 (9.790) NS 0.002 (6.335) 0.001
Right FFA 0.044 (4.184) o0.001 (21.161) NS o0.001 (9.813) o0.001
Left middle STS NS o0.001 (13.595) NS 0.002 (6.711) o0.001
Left cuneus NS 0.001 (10.918) NS 0.004 (5.899) 0.001
Left temporoparietal junction NS 0.003 (9.769) NS 0.010 (4.802) 0.003
Right cuneus NS 0.007 (7.772) NS 0.014 (4.400) 0.004
Fearful versus neutral faces
Right FFA NS 0.025 (5.193) NS NS 0.017
Abbreviations: FFA, fusiform face area; NS, not significant; STS, superior temporal sulcus.
A novel functional brain imaging endophenotype of autism
MD Spencer et al
5
Translational Psychiatry
to extract activation contrast data for happy and neutral faces
versus fixation crosses. For happy faces versus fixation
crosses, we demonstrated a significant polynomial regression
linear contrast effect (with no significant quadratic
component) for all 11 regions: the right FFA (P¼0.001), left
dorsomedial prefrontal cortex (P¼0.001), left (P¼0.001) and
right (P¼0.013) temporal poles, left posterior STS
(P¼0.010), right (P¼0.002) and left (P¼0.016) middle
STS, right (P¼0.007) and left (P¼0.008) cuneus, left
temporoparietal junction (P¼0.007) and left superior frontal
gyrus (P¼0.026). In contrast, no statistically significant
polynomial regression linear contrast effects were
demonstrated for neutral faces versus fixation crosses. This
strongly suggests that, within the context of this study, an
atypical response specifically to happy faces accounts for the
atypical response to happy versus neutral faces in autism and
sibling groups. This therefore provides a clear biomarker of
familial risk for autism.
Discussion
Hypoactivation of the FFA and related ‘social brain’ areas in
response to facial stimuli is one of the most consistently
reported fMRI findings in autism.20 We have shown that
activation in a range of brain areas, including the FFA, is
significantly reduced in autism compared with controls in
response to emotional versus neutral faces, and furthermore
our findings indicate that the response within the FFA itself
differs significantly between siblings and controls. Moreover,
in siblings with no autism spectrum diagnosis and no manifest
severe behavioral features of autism, we have demonstrated
significant differences from controls in terms of the fMRI
response to happy versus neutral faces within a range of other
brain areas, particularly regions related to the STS and
temporal poles.
Importantly, the emotion and control conditions differed
only in terms of facial expression—with all other aspects of
these conditions, such as those related to the sex discrimination
task, being identical. This suggests that it is specifically
the implicit response to facial expression of emotion rather
than some other aspect of the task that is associated with the
significant sibling versus control differences observed.
The temporal poles, STS, temporoparietal junction and
medial prefrontal cortex form a network of brain areas strongly
implicated23,36–38 in empathy, mentalizing and theory of mind
(the ability to attribute mental states to others). On the basis of
the set of emotions tested here (happiness and fear), the
finding of an atypical neural response within these brain areas
in autism and sibling groups specifically to happy faces may
reflect the possibility that an implicit response to happy faces
is driven by empathy—impairments of which have a central
role within the phenotype of autism—whereas the response to
fearful stimuli (found in this study to be intact in siblings but not
individuals with autism) is likely driven by their role as
indicators of threat. Observed facial fear and anger may be
of sufficient evolutionary importance as danger cues that,
unlike facial happiness, they elicit an intact response in the
broader phenotype of autism. This is consistent with reports39
of an intact ‘anger superiority effect’ in autism, where angry
faces are salient and easier to spot within a collection of faces
than happy faces.
We did not select sibling pairs on the basis of gender and
hence, in keeping with known gender ratios in high-functioning
autism and Asperger syndrome, there is an over-representation
of males in the autism group. Gender is a very unlikely
explanation for our results, particularly as we have demonstrated
a strong fit to a linear trend across all three study
groups (autismosiblingsocontrols), whereas the gender
differences between autism versus sibling and sibling versus
control groups are in opposite directions. Furthermore, our
main findings of significant sibling versus control differences
(see Table 2) are most unlikely to be driven by gender as there
was no significant effect of gender in our analysis of variance
for happy versus neutral faces for these seven brain regions.
A potential statistical limitation of this study is that
participants with autism, their siblings and controls were
compared within the same analysis of variance models,
whereas the autism and sibling groups are not independent of
one another. However, our main findings of sibling versus
control differences are not affected by this potential limitation.
The heterogeneous phenotype and likely non-unitary
nature14 of autism require a dissection of the condition into
simpler building blocks with the goal of characterizing the
etiology of autism at the fine-resolution level of specific
components of neural structure or function and their genetic
associates. We propose that the fMRI response to happy
versus neutral faces within these brain areas is an endophenotype
of autism. As a biomarker of familial risk for autism, this
candidate endophenotype has the advantage of being a
quantitative measure, with greater statistical power than
categorical measures. These findings offer an attractive
autism
5.0
-48
4.8
4.6
sibling
Right FFA
control
P = 0.025
0.2
0.1
0.3
0.0
contrast estimate +/- SE
Figure 3 Neural response to fearful versus neutral faces. Activation differences
(means±s.e.m.) between the functional magnetic resonance imaging response to
fearful and neutral faces in the right FFA in adolescents with autism (n¼40),
unaffected siblings (n¼40) and controls (n¼40). Activation map indicates neural
response to fearful versus neutral faces in controls, corrected for multiple
comparisons at Po0.05 family-wise error corrected and overlaid onto the canonical
Montreal Neurological Institute (MNI) 152 template brain image (coronal section,
y-coordinate indicated in Montreal Neurological Institute space), with the colored bar
indicating the T-value of the plotted activation differences. Activation map overlaid
onto a three-dimensional-rendered template brain within MRIcron. FFA, fusiform
face area.
A novel functional brain imaging endophenotype of autism
MD Spencer et al
6
Translational Psychiatry
strategy to future genetic research, investigating the genetic
correlates of this candidate endophenotype.
Kanner’s original description of autism40 highlighted the role
of impaired ‘emotional reactivity’ in the phenotype of autism,
together with the observation of similar traits in family
members. Our findings suggest that an atypical implicit
response to facial expression of emotion may form the basis
of impaired emotional reactivity in autism and in the broader
autism phenotype26,41 in relatives. The identification of this
fMRI endophenotype of autism may serve as an important
step toward an understanding of the causal mechanisms that
underlie autism at a neural and genetic level.
Conflict of interest
ETB is employed half-time by the University of Cambridge and
half-time by GlaxoSmithKline plc. All the other authors declare
no conflict of interest.
Acknowledgements. We are grateful to all participants and their families
for their participation in our study and to all autism support organizations that helped
with recruitment. We are grateful for the technical assistance of Dr Cinly Ooi. This
research was funded by an MRC Clinician Scientist Fellowship to MDS from the UK
Medical Research Council (G0701919). LRC is supported by the Gates Cambridge
Scholarship Trust.
1. Constantino JN, Zhang Y, Frazier T, Abbacchi AM, Law P. Sibling recurrence and the
genetic epidemiology of autism. Am J Psychiatry 2010; 167: 1349–1356.
2. Ritvo ER, Jorde LB, Mason-Brothers A, Freeman BJ, Pingree C, Jones MB et al. The
UCLA-University of Utah epidemiologic survey of autism: recurrence risk estimates and
genetic counseling. Am J Psychiatry 1989; 146: 1032–1036.
3. Lauritsen MB, Pedersen CB, Mortensen PB. Effects of familial risk factors and place of
birth on the risk of autism: a nationwide register-based study. J Child Psychol Psychiatry
2005; 46: 963–971.
4. Bolton P, Macdonald H, Pickles A, Rios P, Goode S, Crowson M et al. A case-control family
history study of autism. J Child Psychol Psychiatry 1994; 35: 877–900.
5. Baron-Cohen S, Ring H, Chitnis X, Wheelwright S, Gregory L, Williams S et al. fMRI of
parents of children with Asperger syndrome: a pilot study. Brain Cogn 2006; 61: 122–130.
6. Piven J. The broad autism phenotype: a complementary strategy for molecular genetic
studies of autism. Am J Med Genet 2001; 105: 34–35.
7. Losh M, Adolphs R, Poe MD, Couture S, Penn D, Baranek GT et al. Neuropsychological
profile of autism and the broad autism phenotype. Arch Gen Psychiatry 2009; 66:
518–526.
8. Dalton KM, Nacewicz BM, Alexander AL, Davidson RJ. Gaze-fixation, brain activation, and
amygdala volume in unaffected siblings of individuals with autism. Biol Psychiatry 2007; 61:
512–520.
9. Kaiser MD, Hudac CM, Shultz S, Lee SM, Cheung C, Berken AM et al. Neural signatures of
autism. Proc Natl Acad Sci USA 2010; 107: 21223–21228.
10. Belmonte MK, Gomot M, Baron-Cohen S. Visual attention in autism families: ‘unaffected’
sibs share atypical frontal activation. J Child Psychol Psychiatry 2010; 51: 259–276.
11. John B, Lewis KR. Chromosome variability and geographic distribution in insects. Science
1966; 152: 711–721.
12. Gottesman II, Shields J. Genetic theorizing and schizophrenia. Br J Psychiatry 1973; 122:
15–30.
13. Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and
strategic intentions. Am J Psychiatry 2003; 160: 636–645.
14. Happe F, Ronald A, Plomin R. Time to give up on a single explanation for autism. Nat
Neurosci 2006; 9: 1218–1220.
15. Kendler KS, Neale MC. Endophenotype: a conceptual analysis. Mol Psychiatry 2010; 15:
789–797.
16. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders:
DSM-IV, 4th edn. American Psychiatric Association: Washington, DC, 1994.
17. Dawson G, Carver L, Meltzoff AN, Panagiotides H, McPartland J, Webb SJ. Neural
correlates of face and object recognition in young children with autism spectrum disorder,
developmental delay, and typical development. Child Dev 2002; 73: 700–717.
18. Bailey AJ, Braeutigam S, Jousmaki V, Swithenby SJ. Abnormal activation of face
processing systems at early and intermediate latency in individuals with autism spectrum
disorder: a magnetoencephalographic study. Eur J Neurosci 2005; 21: 2575–2585.
19. Hall GB, Szechtman H, Nahmias C. Enhanced salience and emotion recognition in Autism:
a PET study. Am J Psychiatry 2003; 160: 1439–1441.
20. Pierce K, Muller RA, Ambrose J, Allen G, Courchesne E. Face processing occurs outside
the fusiform ‘face area’ in autism: evidence from functional MRI. Brain 2001; 124(Part 10):
2059–2073.
21. Baron-Cohen S, Ring HA, Wheelwright S, Bullmore ET, Brammer MJ, Simmons A et al.
Social intelligence in the normal and autistic brain: an fMRI study. Eur J Neurosci 1999; 11:
1891–1898.
22. Brothers L. The social brain: a project for integrating primate behaviour and
neurophysiology in a new domain. Concepts Neurosci 1990; 1: 27–51.
23. Frith U, Frith CD. Development and neurophysiology of mentalizing. Philos Trans R Soc
Lond B Biol Sci 2003; 358: 459–473.
24. von dem Hagen EA, Nummenmaa L, Yu R, Engell AD, Ewbank MP, Calder AJ. Autism
spectrum traits in the typical population predict structure and function in the posterior
superior temporal sulcus. Cereb Cortex 2011; 21: 493–500.
25. Kanwisher N, McDermott J, Chun MM. The fusiform face area: a module in human
extrastriate cortex specialized for face perception. J Neurosci 1997; 17: 4302–4311.
26. Piven J, Palmer P, Jacobi D, Childress D, Arndt S. Broader autism phenotype: evidence
from a family history study of multiple-incidence autism families. Am J Psychiatry 1997;
154: 185–190.
27. Lord C, Rutter M, Le Couteur A. Autism diagnostic interview-revised: a revised version of a
diagnostic interview for caregivers of individuals with possible pervasive developmental
disorders. J Autism Dev Disord 1994; 24: 659–685.
28. Lord C, Rutter M, Goode S, Heemsbergen J, Jordan H, Mawhood L et al. Autism diagnostic
observation schedule: a standardized observation of communicative and social behavior.
J Autism Dev Disord 1989; 19: 185–212.
29. Berument SK, Rutter M, Lord C, Pickles A, Bailey A. Autism screening questionnaire:
diagnostic validity. Br J Psychiatry 1999; 175: 444–451.
30. Wechsler D. Wechsler Abbreviated Scale of Intelligence (WASI). Psychological
Corporation: London, 1999.
31. Ekman P, Friesen WV. Pictures of Facial Affect. Consulting Psychologists Press: Palo Alto,
California, 1976.
32. Cusack R, Mitchell DJ, Duncan J. Discrete object representation, attention switching, and
task difficulty in the parietal lobe. J Cogn Neurosci 2009; 22: 32–47.
33. Evans AC, Collins DL, Milner B. An MRI-based stereotactic brain atlas from 300 young
normal subjects. Proc 22nd Annu Symp Soc Neurosci, Anaheim, CA 1992, 408.
34. Brett M, Anton J, Valabregue R, Poline J. Region of interest analysis using an SPM toolbox.
Neuroimage 2002; 16: S497.
35. Rorden C, Brett M. Stereotaxic display of brain lesions. Behav Neurol 2000; 12: 191–200.
36. Vollm BA, Taylor AN, Richardson P, Corcoran R, Stirling J, McKie S et al. Neuronal
correlates of theory of mind and empathy: a functional magnetic resonance imaging study
in a nonverbal task. Neuroimage 2006; 29: 90–98.
37. Schulte-Ruther M, Markowitsch HJ, Fink GR, Piefke M. Mirror neuron and theory of mind
mechanisms involved in face-to-face interactions: a functional magnetic resonance
imaging approach to empathy. J Cogn Neurosci 2007; 19: 1354–1372.
38. Olson IR, Plotzker A, Ezzyat Y. The enigmatic temporal pole: a review of findings on social
and emotional processing. Brain 2007; 130(Part 7): 1718–1731.
39. Ashwin C, Wheelwright S, Baron-Cohen S. Finding a face in the crowd: testing the anger
superiority effect in Asperger syndrome. Brain Cogn 2006; 61: 78–95.
40. Kanner L. Autistic disturbances of affective contact. Nervous Child 1943; 2: 217–250.
41. Bailey A, Palferman S, Heavey L, Le Couteur A. Autism: the phenotype in relatives.
J Autism Dev Disord 1998; 28: 369–392.
Translational Psychiatry is an open-access journal
published by Nature Publishing Group. This work is
licensed under the Creative Commons Attribution-Noncommercial-Share
Alike 3.0 Unported License. To view a copy of this
