Amygdala Function and 5-HTT Gene Variants in
Adolescent Anxiety and Major Depressive Disorder
Jennifer Y. F. Lau, David Goldman, Beata Buzas, Stephen J. Fromm, Amanda E. Guyer,
Colin Hodgkinson, Christopher S. Monk, Eric E. Nelson, Pei-Hong Shen, Daniel S. Pine, and
Background: Associations between a functional polymorphism in the serotonin transporter gene and amygdala activation have been
vs. patients) on amygdala responses to emotional faces.
Methods: Functional magnetic resonance data were collected from 33 healthy adolescents (mean age: 13.71, 55% female) and 31
medication-free adolescents with current anxiety or depressive disorders (or both; mean age: 13.58, 56% female) while viewing fearful,
angry, happy, and neutral facial expressions under varying attention states.
Results: A significant three-way genotype-by-diagnosis-by-face-emotion interaction characterized right amygdala activity while subjects
monitored internal fear levels. This interaction was decomposed to map differential gene–brain associations in healthy and affected
adolescents. First, consistent with healthy adult data, healthy adolescents with at least one copy of the S or LGallele showed stronger
amygdala responses to fearful faces than healthy adolescents without these alleles. Second, patients with two copies of the LAallele
on amygdala responses in patients extended to happy faces. All effects were restricted to the fear-monitoring attention state.
Conclusions: S/LGalleles in healthy adolescents, as in healthy adults, predict enhanced amygdala activation to fearful faces. Contrary
findings of increased activation in patients with LALArelative to the S or LGalleles require further exploration.
Key Words: Adolescence, amygdala, anxiety, depression, emo-
tional faces, serotonin transporter gene polymorphism
Although relationships between genetic variation and brain
function characterize healthy and disordered adults (4), these
have not been studied in adolescents. Assessing gene–brain
relationships in youth may elucidate early risk mechanisms for
Similar to adults, anxious and depressed adolescents exhibit
signs of enhanced amygdala responsivity (5–10). These anoma-
lies emerge when attention is focused on internal fear evaluation
(7) to fearful faces (5–7), occasionally extending to angry or
happy faces as well (9–10).
A variable repeat sequence polymorphism in the promoter
region of the serotonin transporter (5-HTT) gene (SLC6A4) has
been implicated in anxiety and depression (11). This variant
involves short (S) and long (L) alleles with a recently discovered
single nucleotide polymorphism (A-G substitution) within the L
allele generating LAand LGalleles (12). Adult carriers of LGand
dolescent anxiety and mood disorders strongly predict
adult anxiety and mood disorders (1–2), possibly through
genetic influences on brain circuitry development (3).
S alleles show lower levels of 5-HTT than LA-allele homozygotes
(12), findings attributed to differential 5-HTT expression among
allelic variants, but with mixed support (13). Nevertheless, with
varying consistency, adult S-(and LG-)allele carriers report greater
anxiety, depression, neuroticism, and harm avoidance (14,15).
Conflicting results characterize younger samples. Although two
studies found greater emotionality and shyness among S-allele
carriers (16,17), others show these effects for L-allele carriers
(18,19). Still others report associations only under certain envi-
ronmental contexts (20–23).
Inconsistent gene–behavior associations reinforce the need to
identify intermediate phenotypes, such as brain function. Among
healthy and affected adults, S-(and LG-)allele carriers manifest
greater amygdala activation to emotional stimuli than L-allele
homozygotes (4,24–28). Here, we extend this work to adoles-
cents by exploring effects of 5-HTT genotypes, diagnosis, and
their interaction on amygdala responses to fearful faces during
internal fear evaluation.
Methods and Materials
Thirty-one unmedicated adolescents with a current anxiety
disorder, or major depressive disorder (MDD), or both and 33
psychiatrically healthy adolescents were recruited through com-
munity health practitioners and advertisements (Table 1). Data
from 6 patients and 18 healthy adolescents have been presented
previously (7,29). Patients with anxiety or MDD were combined
based on evidence implicating 5-HTT allelic variants in risk for
both (11). Excluding MDD-only patients showed no overall
change in results.
Patients and healthy subjects did not differ on age [t(62) ?
.25, p ? .80], sex [?2? .08, p ? .77], IQ [t(60) ? .15, p ? .88], or
SES [t(55) ? 1.66, p ? .10]. Nor were there differences in ethnic
From the Department of Experimental Psychology (JYFL), University of Ox-
ford, Oxford, United Kingdom; Mood and Anxiety Disorders Program
(JYFL, SJF, AEG, EEN, DSP, ME), National Institute of Mental Health, Na-
tional Institutes of Health, Bethesda, Maryland; Laboratory of Neuroge-
netics (DG, CH, P-HS), National Institute of Alcohol Abuse and Alcohol-
ism, and National Institute of Alcohol Abuse and Alcoholism (BB),
National Institutes of Health, Rockville, Maryland; Department of Psy-
chology (CSM), University of Michigan, Ann Arbor.
Address reprint requests to Jennifer Y.F. Lau, Ph.D., Department of Experi-
3UD, United Kingdom. E-mail: email@example.com.
Received April 2, 2008; revised August 28, 2008; accepted August 28, 2008.
BIOL PSYCHIATRY 2008;xx:xxx
© 2008 Society of Biological Psychiatry
ARTICLE IN PRESS
ancestry factor scores between groups [ts ? 1.42, ps ? ns] or
between genotypes within groups [ts ? 1.67, ps ? ns]. These
scores were produced from a seven-factor solution of 186
ancestry-informative markers that differentiate continental and
certain subcontinental populations (30). Ancestry distributions of
individuals in each group are presented in Figure 1.
The Kiddie Schizophrenia and Affective Disorders Schedule—
Present and Lifetime Version (31) psychiatric interview was used
to assign diagnoses. Of 18 anxiety-only patients, 12, 5, and 1
individuals met full criteria for one, two, and three current
anxiety diagnoses, respectively; 5 patients received comorbid
attention-deficit/hyperactivity disorder (ADHD) or oppositional
defiant disorder diagnoses. Four patients met criteria for a past
anxiety disorder, and two met criteria for prior alcohol abuse and
ADHD. Other inclusion criteria comprised clinically significant
symptoms for patients indexed by scores on the Pediatric Anxiety
Rating Scale (? 10), the Children’s Depression Rating Scale
(? 13), and the Child Global Assessment Scale (? 60). Exclusion
criteria were current Tourette’s syndrome, obsessive-compulsive
disorder, or conduct disorder; recent exposure to trauma;1
current use of any psychoactive substance;2suicidal ideation;
lifetime history of mania, psychosis, or pervasive developmental
disorder; and IQ ? 70. The study was approved by the National
Institute of Mental Health (NIMH) Institutional Review Board. All
participants/parents provided written informed assent/consent.
Treatment began 3 weeks after research participation.
DNA extraction, genotyping, and polymerase chain reaction
conditions followed published protocols (12). Stage 1 genotyp-
ing distinguished short from long alleles using an allele-discrim-
inating probe hybridized once to the 43-bp L-insertion and an
internal control probe hybridized to a sequence located within
the same amplicon but specific to a divergent repeat in the
amplicon not involved in insertion/deletion. The L-amplicon was
182 bp, and the S-amplicon was 138 bp. Stage 2 genotyping
distinguished LAfrom LGalleles using fluorogenic probes de-
signed specifically for these alleles. These were labeled at the 5=
end with either FAM or VIC. Genotypes were generated using
ABI PRISM 7700 Sequence Detection system software (Applied
Biosystems, Foster City, California). Twenty percent of the
sample was genotyped twice, revealing error rates of ? .005 and
completion rates of ? .95.
Allelic frequencies for S, LA, and LGacross the sample were 56
(43%), 66 (51%), and 8 (6%) respectively. Subjects belonged to
one of six genotype groups (Table 1), but were assigned to three
groups on the basis of functional similarity of S and LGalleles
(12): LALA, SLA/LALG, and SS/SLG/LGLG. No differences in geno-
typic distribution across patients and healthy subjects emerged
1Definitions of trauma followed DSM-IV criteria for posttraumatic stress
disorder, as having experienced, witnessed, or been confronted by an
event or events that involved actual or threatened death or serious
injury or a threat to the physical integrity of self or others.
2Medication and/or recreational drugs.
Table 1. Demographic, Diagnostic and Genotypic Characteristics of
Healthy Subjects and Patients
(n ? 33)
(n ? 31)
Age, Mean (SD)
Males, n (%)
IQ, Mean (SD)
SES, Mean (SD)
Ethnic Ancestry Factor Scores
Far East Asia
Current DSM-IV Diagnoses, n (%)
Generalized Anxiety Disorder
Separation Anxiety Disorder
Generalized Anxiety Disorder
Social Phobia Only
Separation Anxiety Disorder
Major Depressive Disorder
Major Depressive Disorder
Genotype, n (Mean age, % males)
Final Genotype Groups, n (%)
9 (14.03, 33%)
3 (13.25, 67%)
16 (13.51, 56%)
4 (14.83, 25%)
1 (9.83, 0%)
5 (14.72, 20%)
3 (13.97, 33%)
14 (13.44, 57%)
8 (12.99, 38%)
1 (11.50, 0%)
L, long allele; S, short allele; SES, socioeconomic status.
Figure 1. Ancestry distributions across individuals in healthy and patient
groups. Pink, Europe; blue, Middle East; white, Africa; red, Central Asia;
green, America; yellow, Far East Asia; purple, Oceania.
2 BIOL PSYCHIATRY 2008;xx:xxx
J.Y.F. Lau et al.
ARTICLE IN PRESS
[?2? 2.34, p ? .31]. Prior studies (4) and modest sample sizes
warranted further grouping individuals as LALAhomozygotes and
Procedures and stimuli have been described previously
(7–9,29,32–34). Four epochs of 40 trials were presented (Figure
2): 32 trials showed different face emotions (eight fearful, eight
angry, eight happy, eight neutral), and eight trials contained a
fixation point. These 40 trials were divided into four blocks of 10
trials, in which eight faces and two fixation trials were presented
in random order. In each block, participants completed one of
four tasks that varied in attentional focus: rated subjective fear
level to the face, rated the nose width on each face, rated the
level of threat of each face, or passively viewed the face. Order
of blocks was randomized across participants. Each block began
with instructions (3000 msec) followed by 10 trials (4000 msec/
trial). Intertrial intervals ranged from 750 to 1250 msec. Gray-
scale face stimuli were from three sources (35–37). Stimuli were
displayed with Avotec Silent Vision Glasses (Stuart, Florida).
Ratings and reaction times (RT) were recorded with a five-key
button box (MRI Devices Corporation, Waukesha, Wisconsin).
Magnetic Resonance Imaging Data Acquisition
Whole-brain blood oxygen level–dependent (BOLD) func-
tional magnetic resonance imaging (fMRI) data were acquired on
a General Electric (Waukesha, Wisconsin) Signa 3-T scanner.
Following sagittal localization and manual shimming, functional
T2*-weighted images were acquired using an echo-planar single-
shot gradient echo pulse sequence with matrix size of 64 ? 64,
repetition time (TR) of 2000 msec, echo time (TE) of 40 msec,
field of view (FOV) of 240 mm, and voxels of 3.75 ? 3.75 ? 5.0
mm. Images were acquired in 23 contiguous axial slices per brain
volume positioned parallel to the anterior commissure–posterior
commissure line. Functional data were gathered in a single
14-min run. A high-resolution T1-weighted anatomic image was
acquired to aid spatial normalization. A standardized magnetiza-
tion-prepared gradient echo sequence (180 1-mm sagittal slices,
FOV ? 256, number of excitations ? 1, TR ? 11.4 msec, TE ? 4.4
msec, matrix ? 256 ? 256, time to inversion ? 300 msec,
bandwidth ? 130 Hz/pixel, 33 kHz/256 pixels) was used.
Reconstructed fMRI images were examined for excessive
motion (? 3 mm in any plane) using MedX (Medical Numerics,
Sterling, Virginia). Subsequent processing used SPM99 (Univer-
sity College, London, United Kingdom) and Matlab6 (Mathworks,
Natick, Massachusetts). Functional data were corrected for slice
timing and motion, coregistered to anatomic data, spatially
normalized to a Montreal Neurologic Institute (MNI) T1-weighted
template image, and resliced to 2-mm isotropic voxels. After
inspecting images, event-related response amplitudes at the
individual subject level for every face emotion were estimated in
each attention task using the General Linear Model. Dividing
each contrast image by subject-specific voxel time series means
yielded percent fMRI signal change (38).
Ratings and RT data during “how afraid” were examined using
repeated-measures analyses of variance (ANOVAs) with two
between-subjects factors (Diagnosis: patients, control subjects;
Genotype: LALAhomozygotes, S/LGcarriers) and one within-
subjects factor (Face Emotion: fearful, angry, happy, neutral).
Greenhouse-Geisser (G-G) adjustment was applied in cases of
For group-level fMRI analyses, a random-effects model per-
mitted population-level inferences (39). Analyses focused on
the amygdala during “how afraid” using a region-of-interest
approach (40). The boundaries of the amygdala were defined
using standard anatomic criteria3on a single MNI template and
applied to all normalized brains at the group level. BOLD signal
changes for each event type (fearful, angry, happy, neutral faces)
during afraid ratings relative to fixations were averaged across all
voxels in the left and right amygdala for each subject. Left and
right amygdala values were analyzed separately with repeated-
measures ANOVAs in SPSS-14, examining main effects and
interactions of two between-subjects factors (Diagnosis: patients,
controls; Genotype: LALAhomozygotes, S/LGcarriers) and one
within-subjects factor (Face Emotion: fearful, angry, happy,
neutral). The G-G correction was applied. Because amygdala
values correlated significantly with age and ethnic ancestry
scores, these were covariates in subsequent analyses. Voxelwise
SPM analyses using small-volume Gaussian random field correc-
tion procedures for multiple comparisons confirmed significant
Genotype-by-Diagnosis interactions in the amygdala during
Ratings and RT data during “how afraid” are presented in
Figure 3. Data for three healthy participants were not recorded.
Significant Face Emotion [F(3,171) ? 33.69, p ? .001] and
Diagnosis [F(1,57) ? 4.99, p ? .05] effects emerged on ratings.
Angry faces received highest ratings (2.38), followed by fearful
(2.00), neutral (1.56), and happy (1.24) faces. Patients gave
higher ratings to face emotions (2.02) relative to control subjects
3Consistent with a prior publication (41), the amygdala was measured
from the slice at the level of the mammillary bodies to its anterior
boundary, including the uncus.
resonance acquisition to all subjects. The paradigm consists of four tasks
(afraid, nose width and hostility ratings, and passive viewing) across 160
trials. Reprinted with permission from (37).
J.Y.F. Lau et al.
BIOL PSYCHIATRY 2008;xx:xxx 3
ARTICLE IN PRESS
(1.59). Similar Face-Emotion effects characterized RTs [F(3,171) ?
23.29, p ? .001]: rating angry faces was slowest (1932.92 msec)
followed by fearful (1825.83 msec), neutral (1650.47 msec), and
happy faces (1492.62 msec).
Significant effects of Diagnosis on both left and right amyg-
dala responses indicated greater activity across Face Emotions
(relative to fixations) among patients. Significant Genotype-by-
Diagnosis and Genotype-by-Diagnosis-by-Face-Emotion interac-
tions characterized right [F(3,159) ? 2.66, p ? .05] but not left
amygdala activity (Figure 4A). The three-way interaction was
decomposed by examining Genotype and Diagnosis effects on
right amygdala activity to each Face Emotion separately.
Significant Genotype-by-Diagnosis interactions characterized
fearful [F(1,59) ? 18.65, p ? .001] and happy [F(1,59) ? 5.50,
p ? .05] faces. For fearful faces, this interaction was driven by
differential amygdala responses across genotype in each diag-
nostic group. Among healthy subjects, S/LGcarriers showed
greater activity than LALAhomozygotes [F(1,31) ? 5.24, p ? .05,
Cohen’s d ? .95]. In patients, greater activity occurred among
LALAindividuals than S/LGcarriers [F(1,27) ? 14.17, p ? .01,
Cohen’s d ? 1.61]. For happy faces, the Genotype-by-Diagnosis
interaction was explained by patient data only: LALAindividuals
manifested more amygdala activity than S/LGcarriers [F(1,27) ?
6.88, p ? .05, Cohen’s d ? 1.27].
Post hoc analyses contrasting amygdala responses to fearful
faces across the three genotype groups (LA/LA, SLA/LALG, SS/SLG/
LGLG) showed that SLA/LALGand SS/SLG/LGLGindividuals were
comparable in healthy subjects and patients, but they differed
significantly from LA/LAindividuals (Supplement 1). This justified
pooling S- and LG-allele carriers. For happy faces, differences in
amygdala responses across genotype groups were more appar-
ent in patients, but these were inconsistent. Whereas SLA/LALG
and SS/SLG/LGLGindividuals showed similar responses, only
SLA/LALGindividuals differed significantly to LA/LAindividuals
Voxelwise SPM analyses confirmed strong Genotype-by-Di-
agnosis interactions to afraid ratings of fearful faces in the right
amygdala [F ? 2.20, p ? .001] (Figure 4B; Supplement 3). All
regions where significant Genotype-by-Diagnosis interactions
emerged to fearful faces are shown in Table 2. Weaker interac-
tions characterized the right amygdala during afraid ratings of
happy faces [F ? 5.44, p ? .05] (details on further request).
Parallel analyses employing a biallelic classification of 5-HTT
genotypes (SS/SL vs. LL) on right amygdala activation yielded
significant effects of Diagnosis, Face Emotion, and a two-way
Diagnosis-by-Genotype interaction. Post hoc analyses showed sig-
nificant Genotype-by-Diagnosis interactions for fearful [F(1,59) ?
12.07, p ? .01] and happy [F(1,59) ? 6.97, p ? .05] faces. For
fearful faces, healthy SS/SL individuals showed greater amygdala
activity than LL individuals [F(1,31) ? 4.65, p ? .05, Cohen’s d ?
.80]. Among patients, greater amygdala activity was found among
Figure 4. (A) Bar graphs of activation in the right amygdala for the “how
afraid” condition relative to the task null-event baseline in various face
emotions for patient and healthy adolescents across combined genotype
groups (S/LGcarriers and LALAhomozygotes). (B) The topography of peak
activations in the right amygdala (Montreal Neurological Institute coordi-
nates: 26, 2, ?16) where the significant Genotype-by-Diagnosis interaction
on afraid ratings of fearful faces emerged (p ? .05). L, long; S, short allele.
Figure 3. (A) Afraid ratings of various face emotions (fearful, angry, happy,
neutral) across healthy and anxious adolescents in each genotype group
(S/LGcarriers, LALAhomozygotes). (B) Mean reaction times (msec) during
afraid ratings of different face emotions (fearful, angry, happy, neutral)
across patient and healthy adolescents belonging to each genotype group
(S/LGcarriers, LALAhomozygotes). L, long; S, short allele.
4 BIOL PSYCHIATRY 2008;xx:xxx
J.Y.F. Lau et al.
ARTICLE IN PRESS
LL than SL/SS-individuals [F(1,27) ? 6.64, p ? .05, Cohen’s d ?
.50]. For happy faces, LL individuals showed enhanced amygdala
activity relative to SS/SL individuals [F(1,27) ? 5.66, p ? .05,
Cohen’s d ? .67]. Thus, results were broadly comparable to using
a triallelic classification, but effect sizes for patient genotype
differences were smaller. Amygdala responses to fearful and
happy faces across the three genotype groups of the biallelic
classification followed similar trends to the triallelic classification
(Supplements 4 and 5).
To test specificity of results to the how afraid condition,
analyses were repeated for data from other attention tasks, but
no main or interaction effects emerged for left or right amygdala
responses for triallelic or biallelic classifications. Modest sample
sizes and low statistical power precluded testing a four-way
To aid interpretation of fMRI results, we examined genotype
and diagnosis effects on self-reported anxiety and depressive
symptoms (42,43) among current subjects, as well as from
healthy and anxious/depressed adolescents recruited for other
NIMH studies (n ? 230). Neither revealed significant effects of
5-HTT genotype on symptoms.
Effects of 5-HTT gene variants on amygdala responses to
emotional faces were studied in healthy and anxious/depressed
adolescents during internal fear evaluation. A significant Geno-
type-by-Diagnosis-by-Face-Emotion interaction emerged on right
amygdala activity, reflecting three key findings. First, in healthy
adolescents, stronger amygdala responses to fearful faces char-
acterized S/LGcarriers, relative to LALAindividuals. Second, this
was opposite in patients in whom LALAindividuals exhibited
greater amygdala responses to fearful faces. Third, effects in
patients extended to happy faces.
These data are the first to document conservation of gene–
brain associations across typical development, supporting con-
ceptualizations that S/LGalleles increase risks for psychopathol-
ogy in healthy individuals (4), possibly through stress reactivity
(11,44,45). However, gene–brain associations in affected adoles-
cents differed from those in affected adults (4), with opposite
gene–amygdala response patterns to fearful and happy faces.
That these effects characterized happy faces as well may be
because of ambiguity from discrepancies between stimulus
valence and a potential threat context (9,46–48).
Although no theoretical accounts speak directly to these
contrary findings in adolescent patients, three issues are relevant.
First, literature on associations between 5-HTT gene variants and
brain function or symptoms is mixed. A recent meta-analysis on
adult gene–brain associations noted potential publication biases
when three unpublished data sets reporting no association or
associations in opposite directions were excluded (4). Moreover,
far fewer studies have been conducted in adult patients, calling
for more independent replications generally but in especially
clinical groups. Data for gene–symptom associations in adoles-
cents are also inconsistent over whether the S or L allelic variant
predicts risk for psychopathology (16–19).
Second, some anxious responses to threat show developmen-
tal differences. Relative to healthy subjects, anxious adults ex-
hibit selective attention toward threat stimuli (49), whereas
anxious adolescents shift attention away from these stimuli (50).
Whether these reflect distinct compensatory responses used by
affected adolescents to regulate emotional arousal is unknown,
but regardless, they illustrate developmental changes in clinical
behaviors. Variable expression of S/LGalleles on brain function
from adolescence to adulthood among affected individuals is
Finally, incomplete penetrance from reduced exposure to
environmental factors in patient S/LGcarriers could also explain
lowered amygdala activity in this group.
In summary, we present new but preliminary data on the
genetics of neural function in adolescents. Although current
sample sizes constrain power to interpret gene–brain associ-
ations in relation to differences across risk alleles (biallelic vs.
triallelic classification; “dose-response” vs. “threshold” effect),
diagnosis (anxiety vs. depression), and attentional conditions
(nose ratings, hostility ratings, passive viewing), notably our
effect sizes of genotype differences are comparable, if not
larger, than previous studies (4) using similar-sized samples
(24–28). Because imaging genetics research is still in its
infancy, any data clarifying these associations is informative.
Furthermore, our data lay the groundwork for considering
interactions among genes, brain function, and emotional
processes across development.
We thank Jessica Jenness, Nina Shiffrin, Elizabeth Shroth,
Veronica Temple, and Amber Williams for data processing
assistance; Longina Akhtar and Gary Jenkins for assistance with
genotyping; Dave Luckenbaugh for advice on statistical proce-
dures; Harvey Iwamoto for programming and computer support;
and Ellen Leibenluft, Ken Towbin, and Alan Zametkin for
medical oversight. This study was supported by the Intramural
Research Program of the National Institute of Mental Health,
National Institutes of Health.
The authors report no biomedical financial interests or po-
tential conflicts of interest.
Supplementary material cited in this article is available
Table 2. Voxels with Significant Genotype-by-Diagnosis Interactions During Afraid Ratings of Fearful Faces (p ? .01)
Brodmann Area RegionVolume (mm)xyzFp Value
Afraid fear relative to baseline (p ? .01)
Gyrus frontal superior
Gyrus frontal superior
Gyrus frontal superior
J.Y.F. Lau et al.
BIOL PSYCHIATRY 2008;xx:xxx 5
ARTICLE IN PRESS
1. Beesdo K, Bittner A, Pine DS, Stein MB, Hofler M, Lieb RH, et al. (2007):
Incidence of social anxiety disorder and the consistent risk for second-
ary depression in the first three decades of life. Arch Gen Psychiatry
2. Pine DS, Cohen P, Gurley D, Brook J, Ma Y (1998): The risk for early-
and depressive disorders. Arch Gen Psychiatry 55:56–64.
3. Gross C, Hen R (2004): The developmental origins of anxiety. Nat Rev
4. Munafo MR, Brown SM, Hariri AR (2008): Serotonin transporter (5-HT-
(2001): Amygdala response to fearful faces in anxious and depressed
6. Killgore WD, Yurgelun-Todd DA (2005): Social anxiety predicts amyg-
dala activation in adolescents viewing fearful faces. Neuroreport 16:
7. McClure EB, Monk CS, Nelson EE, Parrish JM, Adler A, Blair RJR, et al.
(2007): Abnormal attention modulation of fear circuit function in pedi-
atric generalized anxiety disorder. Arch Gen Psychiatry 64:97–106.
8. Roberson-Nay R, McClure EB, Monk CS, Nelson EE, Guyer AE, Fromm SJ,
et al. (2006): Increased amygdala activity during successful memory
encoding in adolescent major depressive disorder: An FMRI study. Biol
9. Perez-Edgar K, Roberson-Nay R, Hardin MG, Poeth K, Guyer AE, Nelson
EE, et al. (2007): Attention alters neural responses to evocative faces in
behaviorally inhibited adolescents. NeuroImage 35:1538–1546.
10. Monk CS, Telzer EH, Mogg K, Bradley BP, Mai X, Louro HM, et al. (2008):
Amygdala and ventrolateral prefrontal cortex activation to masked an-
nin transporter gene regulatory region. Science 274:1527–1531.
12. Hu XZ, Lipsky RH, Zhu G, Akhtar LA, Taubman J, Greenberg BD, et al.
the serotonin transporter in neural function. Trends Cogn Sci 10:
14. Munafo MR, Clark TG, Moore LR, Payne E, Walton R, Flint J. Genetic
polymorphisms and personality in healthy adults: A systematic review
and meta-analysis. Mol Psychiatry 8:471–484.
15. Sen S, Burmeister M, Ghosh D (2004): Meta-analysis of the association
between a serotonin transporter promoter polymorphism (5-HTTLPR)
and anxiety-related personality traits. Am J Med Genet B Neuropsychiatr
16. Ebstein RP, Levine J, Geller V, Auerbach J, Gritsenko I, Belmaker RH
(1998): Dopamine D4 receptor and serotonin transporter promoter in
17. Battaglia M, Ogliari A, Zanoni A, Citterio A, Pozzoli U, Giorda R, et al.
(2005): Influence of the serotonin transporter promoter gene and shy-
ness on children’s cerebral responses to facial expressions. Arch Gen
Relation of shyness in grade school children to the genotype for the
tion of a functional polymorphism of the serotonin transporter gene
with anxiety-related temperament and behavior problems in children:
A longitudinal study from infancy to the mid-teens. Mol Psychiatry
20. Cicchetti D, Rogosch FA, Sturge-Apple ML (2007): Gene–environment
interaction. Dev Psychopathol 19:957–959.
21. Eley TC, Sugden K, Corsico A, Gregory AM, Sham P, McGuffin P, et al.
(2004): Gene–environment interaction analysis of serotonin system
markers with adolescent depression. Mol Psychiatry 9:908–915.
22. Fox NA, Nichols KE, Henderson HA, Rubin K, Schmidt L, Hamer D, et al.
(2005): Evidence for a gene–environment interaction in predicting be-
havioral inhibition in middle childhood. Psychol Sci 16:921–926.
23. Kaufman J, Yang BZ, Douglas-Palumberi H, Houshyar S, Lipschitz D,
Krystal JH, et al. (2004): Social supports and serotonin transporter gene
moderate depression in maltreated children. Proc Natl Acad Sci U S A
24. Smolka MN, Buhler M, Schumann G, Klein S, Hu XZ, Moayer M, et al.
25. Dannlowski U, Ohrmann P, Bauer J, Kugel H, Baune BT, Hohoff C, et al.
(2007): Serotonergic genes modulate amygdala activity in major de-
26. Dannlowski U, Ohrmann P, Bauer J, Deckert J, Hohoff C, Kugel H, et al.
(2008): 5-HTTLPR biases amygdala activity in response to masked facial
expressions in major depression. Neuropsychopharmacology 33:418–
27. Furmark T, Tillfors M, Garpenstrand H, Marteinsdottir I, Langstrom B,
Oreland L, et al. (2004): Serotonin transporter polymorphism related to
bia. Neurosci Lett 362:189–192.
28. Domschke K, Braun M, Ohrmann P, Suslow T, Kugel H, Bauer J, et al.
(2006): Association of the functional -1019C/G 5-HT1A polymorphism
with prefrontal cortex and amygdala activation measured with 3T fMRI
in panic disorder. Int J Neuropsychopharmacol 9:349–355.
30. Hodgkinson C, Xu K, Qiaoping Y, Pei-Hong S, Heinz E, Lobos EA, et al.
Addictions biology: Haplotype based analysis for 130 candidate genes
on a single array. Alcohol Alcohol 43:505–515.
31. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, et al. (1997):
dren—Present and Lifetime Version (K-SADS-PL): Initial reliability and
(2003): Adolescent immaturity in attention-related brain engagement
to emotional facial expressions. NeuroImage 20:420–428.
33. Pine DS, Klein RG, Mannuzza S, Moulton JL 3rd, Lissek S, Guardino M, et
al. (2005): Face-emotion processing in offspring at risk for panic disor-
EB, et al. (2006): Limbic hyperactivation during processing of neutral
facial expressions in children with bipolar disorder. Proc Natl Acad Sci
35. Ekman P, Friesen WV (1976): Pictures of Facial Affect. Palo Alto, CA: Con-
sulting Psychology Press.
36. Gur RC, Ragland JD, Moberg PJ, Turner TH, Bilker WB, Kohler C, et al.
(2001): Computerized neurocognitive scanning, I: methodology and
validation in healthy people. Neuropsychopharmacology 25:766–776.
37. Tottenham N, Tanaka J, Leon AC, McCarry T, Nurse M, Hare TA, et al. (in
press): The NimStim set of facial expressions: judgements from un-
trained research participants. Psychiatry Res.
38. Zarahn E, Aguirre G, D’Esposito M (1997): A trial-based experimental
design for fMRI. Neuroimage 6:122–138.
ulation inference. Neuroimage 7:S754.
40. Hariri AR, Mattay VS, Tessitore A, Kolachana B, Fera F, Goldman D, et al.
(2002): Serotonin transporter genetic variation and the response of the
human amygdala. Science 297:400–403.
41. Szeszko PR, Robinson D, Alvir JM, Bilder RM, Lencz T, Ashtari M, et al.
(1999): Orbital frontal and amygdala volume reductions in obsessive
42. Birmaher B, Khetarpal S, Brent D, Cully M, Balach L, Kaufman J, Neer SM
(1997): The Screen for Child Anxiety Related Emotional Disorders
(SCARED): Scale construction and psychometric characteristics. J Am
43. Kovacs M (1985): The Children’s Depression Inventory (CDI). Psycho-
44. Barr CS, Newman TK, Shannon C, Parker C, Dvoskin RL, Becker ML, et al.
(2004): Rearing condition and rh5-HTTLPR interact to influence limbic-
hypothalamic-pituitary-adrenal axis response to stress in infant ma-
caques. Biol Psychiatry 55:733–738.
6 BIOL PSYCHIATRY 2008;xx:xxx
J.Y.F. Lau et al.
ARTICLE IN PRESS
45. Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, Harrington H, et al.
phism in the 5-HTT gene. Science 301:386–389.
al. (2008): Amygdala and nucleus accumbens activation to emotional
facial expressions in children and adolescents at risk for major depres-
press): Amygdala and Ventrolateral Prefrontal Cortex Function dur-
ing Anticipated Peer Evaluation in Pediatric Social Anxiety. Arch Gen
48. Dugas MJ, Buhr K, Ladouceur R (2004): The role of intolerance of uncer-
tainty in etiology and maintenance. In: Heimberg RG, Turk CL, Mennin
tice. New York: Guilford Press, 143–163.
for emotional faces in generalized anxiety disorder. Br J Clin Psychol
response to angry faces in adolescents with generalized anxiety disor-
J.Y.F. Lau et al.
BIOL PSYCHIATRY 2008;xx:xxx 7
ARTICLE IN PRESS