Effect of Catechol O-Methyltransferase Val158Met Polymorphism on the P50 Gating Endophenotype in Schizophrenia

Genes, Brain and Behavior (2007) 6: 364–374 # 2006 The AuthorsJournal Compilation # 2006 Blackwell Publishing Ltd

Effect of the catechol-O-methyltransferase val158metgenotype on children’s early phases of facialstimuli processing

M. Battaglia*,†,‡,§, A. Zanoni†, R. Giorda§,

U. Pozzoli§, A. Citterio†, S. Beri§, A. Ogliari†,

M. Nobile§, C. Marino‡,§ and M. Molteni§

†Department of Psychology, ‘Vita-Salute’ San Raffaele University

at the Istituto Scientifico San Raffaele, Milan, Italy, ‡Department

of Psychiatry, Laval University, Quebec, Canada, and§Department of Child Psychiatry, Istituto Scientifico Eugenio

Medea, Bosisio Parini, Italy

*Corresponding author: M. Battaglia, MD, UhSR-DNS, 20 via

Stamira d’Ancona, 20127Milan, Italy. E-mail: [email protected]

The ability to process and identify human faces ma-

tures early in life, is universal and is mediated by a distri-

buted neural system. The temporal dynamics of this

cognitive–emotional task can be studied by cerebral

visual event-related potentials (ERPs) that are stable

from midchildhood onwards. We hypothesized that

part of individual variability in the parameters of the

N170, a waveform that specifically marks the early, pre-

categorical phases of human face processing, could be

associated with genetic variation at the functional poly-

morphism of the catechol-O-methyltransferase (val158met)

gene, which influences information processing, cogni-

tive control tasks and patterns of brain activation during

passive processing of human facial stimuli. Forty-nine

third and fourth graders underwent a task of implicit

processing of other children’s facial expressions of emo-

tions while ERPs were recorded. The N170 parameters

(latency and amplitude) were insensitive to the type of

expression, stimulus repetition, gender or school grade.

Although limited by the absence of met- homozygotes

among boys, data showed shorter N170 latency associ-

ated with the presence of 1-2 met158 alleles, and family-

based association tests (as implemented in the PBAT

version 2.6 software package) confirmed the association.

These data were independent of the serotonin trans-

porter promoter polymorphism and the N400 waveform

investigated in the same group of children in a previous

study. Some electrophysiological features of face pro-

cessing may be stable from midchildhood onwards.

Different waveforms generated by face processing may

have at least partially independent genetic architectures

and yield different implications toward the understand-

ing of individual differences in cognition and emotions.

Keywords: Catechol-O -methyltransferase, chi ldren,

development, ERP, face expressions of emotion, genetics

Received 20 March 2006, revised 6 June 2006 and accepted

for publication 26 June 2006

The act of processing a human face takes place following

a specific temporal and topographic succession of events in

the brain (Adolphs 2002): while imaging studies can identify

precisely the brain areas involved in human face processing,

electrophysiological studies are powerful in addressing the

temporal dynamics of this complex cognitive–emotional task

(Haxby et al. 2002).

Cerebral visual event-related potentials (ERPs) techniques

have identified some face-specific early potentials occurring

within 200 milliseconds (range 120–200 milliseconds) from

stimulus onset (Eimer 2000a; Eimer & Holmes 2002; Puce

et al. 1999). These include the N170waveform, a conspicuous

negative peak that appears to be pre-eminently evoked by

human faces but not, or to a much lesser extent, by other

types of visual stimuli (Bentin et al. 1996; Itier & Taylor, 2004;

Sagiv & Bentin 2001). Although the precise source of the

N170 is not yet determined across ERP studies (Puce et al.

1998; Taylor et al. 1999) and through developmental stages

(Taylor et al. 2004), it can be evoked in children from the age

of 7 to 8 years (Taylor et al. 1999) and responds similarly to

experimental manipulations in adults and children starting

from midchildhood (Taylor et al. 2004). While in paradigms of

facial stimuli presentation, the N170 amplitude and latency are

typically unaffected by the type of expression (Eimer & Holmes

2002), stimulus’ repetition (Schweinberger et al. 2002) or a face’s

degree of familiarity (Bentin & Deouell 2000; Eimer 2000a),

inversion of facial stimuli increases significantly the N170 latency

(Eimer 2000a; Rossion et al. 2000; Taylor et al. 2004).

The bulk of these data led several, but not all, authors (see

e.g. Eimer 2000a; Schweinberger & Burton 2003) to consider

the N170 as a waveform reflecting the perceptual encoding

analysis of the human face, and likely to mark the early, pre-

categorical, rather than the subsequent recognition stage,

processes. Consistent with this view, the N170 parameters

also reflect the degree of cognitive control requested by the

early perceptual encoding of the human face: experi-

mental manipulations obtained by altering, and/or interfer-

ing with, face stimuli encoding via demanding visual tasks

364 doi: 10.1111/j.1601-183X.2006.00265.x

produced significantly delayed N170 latency in most

(Eimer 1998, 2000a; Holmes et al. 2003; Jemel et al. 1999),

but not all (Cauquil et al. 2000), studies of face perception

in adults.

At present, although metanalyses of twin studies found

substantial heritability for some ERP waveforms evoked by

cognitive tasks (van Beijsterveldt & van Baal 2002), little is

known about the genes that influence individual variation in

face-evoked ERPs in development, and so far no gene has

been associated with variation in the N170 parameters.

Inasmuch as experimental evidence shows that cognitive

control is a component of the individual variability of the N170

parameters (Eimer 1998, 2000a; Holmes et al. 2003; Jemel

et al. 1999), polymorphic genes that have been shown to

influence different processing tasks constitute reasonable

candidates for the molecular genetic investigation of the

N170.

We believed that the catechol-O-methyltransferase

(COMT) gene could be one such candidate because of its

involvement in several processing tasks, including trials that

implicate cognitive control (Goldberg & Weinberger 2004),

and tasks of passive processing of human facial stimuli

(Smolka et al. 2005). The COMT gene contains a G to A

missense variant (Lachman et al. 1996) that translates into a

substitution of methionine for valine at codon 158 (val158met),

with the enzyme containing met158 having one-third to

one-fourth of the activity of the val158 enzyme (Lotta et al.,

1995; Spielman & Weinshilboum 1981) in degrading dopa-

mine, epinephrine and norepinephrine. Consistently, there

are several reports of increased dopaminergic cortical signal-

ing, enhanced signal/noise ratio and optimized cortical activity

conferred by the met allele during different processing tasks

(Egan et al. 2001; Hariri & Weinberger 2003; Mattay et al.

1996, 2003; Smolka et al. 2005), including an ERP study of

P300 generated by an ‘oddball’ task in healthy controls and

in patients with schizophrenia (Gallinat et al. 2003). Most

recently, two brain imaging studies of healthy adults showed

an influence of COMT val158met genotype on task-related

brain activation. One study (Blasi et al. 2005) showed that the

met allele confers better cognitive performance and optimal

cingulate activation during visual cognitive control tasks,

while another study (Smolka et al. 2005) showed that the

met allele is associated with higher prefrontal, limbic and

cortical sensory (fusiform gyrus and inferior parietal lobule)

activation during the act of passive processing of emotional

stimuli.

We hypothesized that in a paradigm of face expression

presentation to third and fourth graders, neither the amplitude

nor the latency of the N170 would be sensitive to the type of

expression, but that variation of the N170 latency, as an index

of promptness to activate the early stages of face processing,

could be partially influenced by genetic variation at the

COMT val158met genotype, which has been found associated

with human variation in different aspects of information

processing.

Materials and methods

Subjects

This study is part of an ongoing project on the developmental

behavioral genetics of social interactions based on children

and their families randomly selected from the general pop-

ulation of the Lombard provinces of Milan and Lecco,

Northern Italy. The procedures were accepted by the ethical

committee of the participating institutions, and parents

signed a declaration of informed consent. The methods for

subjects’ selection and ERP recording have been described in

detail elsewhere (Battaglia et al. 2004, 2005). Briefly, 1 year

(time 0) before the ERP recording analyzed in this study, an

inception cohort of 149 schoolchildren was characterized by

different psychological variables and the ability to discriminate

other children’s facial expressions of emotions (Battaglia et al.

2004). After random selection and invitation to participate

sent to about 45% of subjects from the original sample, 49

white children of Italian ancestry with normal or corrected-to-

normal visual acuity agreed to take part in the ERP-genetic

study after parental written agreement. Post hoc compar-

isons showed no differences in several major demographic

and psychometric characteristics between 49 participating

and. 100 nonparticipating children (Battaglia et al. 2005).

Because a major focus of the project is set on the relation-

ships occurring between polymorphic genes, neurofunctional

responses to social–emotional stimuli and temperamental

traits, an extensive collection of behavioral data from teach-

ers, parents, direct observation of the children by psycholo-

gists and direct blind independent interviews to children and

their mothers through clinician-administered structured inter-

views was made at time 0 and on the day of the ERP recoding

(Battaglia et al. 2004, 2005).

DNA extraction and genotyping

The genomic DNA of all participating children and their

biological parents was extracted from mouthwash samples

collected in 4% sucrose by means of a reagent for isolation of

genomic DNA (DNAzol Genomic DNA Isolation Reagent,

Molecular Research Center Inc., Cincinnati, OH, USA).

We determined the subject’s COMT V158M genotypes

using the 50-exonuclease Taqman assay (Chenet al. 2004). Sub-

jects with known genotype, previously typed by sequencing,

were used as positive controls. The Taqman primers, probes

and reagents were purchased from Applied Biosystems (Monza,

Italy). The assays were performed and analyzed on a 9700HT

Sequence Detection System (Applied Biosystems).

Protocol

Because third- and fourth-grade schoolchildren spendmost of

their time among other children, not adults, we chose to use

standardized faces of other children of similar age (two

models, a boy and a girl, aged 8–9 years), instead of adults.

Stimuli consisted of six black-and-white pictures standardized

Genes, Brain and Behavior (2007) 6: 364–374 365

COMT genotype and face processing in children

for size, contrast and luminosity, displaying three emotions:

joy, anger and a neutral expression (Fig. 1). These belonged to

the same pool of pictures used for the emotional expressions

discrimination study (Battaglia et al. 2004) that preceded the

ERP study at time 0, for which we found a 72% rate of correct

identification across seven different facial affects and no

significant gender-associated differences in accuracy. The

three expressions of joy, anger and neutrality not only reflect

Figure 1: Face expression stimuli and grand averages of waveforms generated by facial expressions at the reference

electrodes. EOG indicates electro-oculogram. Reproduced partially from Battaglia et al. (2005), with permission of the American

Medical Association.

366 Genes, Brain and Behavior (2007) 6: 364–374

Battaglia et al.

the conditions of acceptance, prosocialization, rejection hos-

tility and ambiguity, that characterize several possible social

interactions in childhood but also are processed by at least

partially independent brain networks (Adolphs 2002; Camras &

Allison 1985; Canli et al. 2002).

Children were told that this was a video game in which they

would get a gift ‘if they carefully followed the instructions and

performed well’.

Trials

On each trial, the children were first presented with a child’s

face (total time on screen, 1300 milliseconds), which they

were instructed to watch carefully until a blue circle appeared

superimposed around the center of the picture. As soon as

a blue circle appeared (700 milliseconds after the appearance

of the stimulus), they had to click a mouse. Thus, the ERPs

relevant to this study were all generated before the motor

task, which was merely set up to stimulate children’s

cognitive control and participation.

The monitor screen remained dark between trials for

periods that varied randomly from 1200 to 1600 milliseconds.

The stimuli were presented to all the children in a sequence

that alternated male and female pictures and avoided close

repetition of the same expression. To simulate a real video

game and sustain children’s participation, non-face screen

pictures with increasing scoring values (as reinforcements)

appeared about every six face pictures (stimuli). The possible

ERP signal evoked by such non-face stimuli was ignored and

therefore excluded from the baseline used to estimate the

waveforms. Each face stimulus was presented 20 times to

ensure sufficient ERP acquisition (total, 120 presentations

in a complete session). Every child was exposed to a pre-

experiment trial of six pictures not belonging to the same set

used for the experiment to make sure she or he understood

the procedure well. Each child received a gift of a value

equivalent to e30.

ERP acquisition and analysis

As in other studies of ERP and facial expressions of children

and adults (Batty & Taylor 2002; Eimer 2000a; Kestenbaum &

Nelson 1992; Pollak et al. 2001), electroencephalographic

activity was recorded at sites Fz, C3, Cz, C4 and Pz of the

10–20 systemwith the use of silver–silver chloride electrodes

referred to linked mastoids with an amplifier (Neuroscan

SynAmp, Neuroscan Labs, Sterling, VA, USA), with head

preamplified gain 150 and acquisition software (SCAN,

version 4.2, Neuroscan Labs). The ground electrode was

attached to the forehead. Electro-oculographic activity was

recorded from electrodes placed above and below the right

eye. Electrode impedance was maintained below 5 kV. The

electroencephalogram and electro-oculogram were amplified

(gain 500), analogically band-pass filtered (1–30 Hz), digitized

and acquired at a1000-Hz sampling rate. Electroencephalo-

gram and electro-oculogram epochs between –50 and

1300 milliseconds from the stimulus onset were obtained

by means of different trigger codes for each image, allowing

for later off-line artifact rejection, sorting and digital averaging

with the Neuroscan EDIT software (Neuroscan Labs). All

epochs from all electrodes were rejected if affected by

artifacts (greater than þ65 mV or less than –65 mV between

–50 and 700 milliseconds). The ERP averages were con-

structed from artifact-free epochs for each trigger code and

for each electrode. Amplitude was measured in relation to the

baseline mean voltage level preceding the onset of a wave-

form, and latency was defined as the time that occurred

between the appearance of the stimulus (set at time 0) and

the waveform’s peak.

Although there were 49 participants, results are shown for

number of participants that vary between 37 and 45 because

of removal of subjects who had artifacts such as eyeblinks in

recordings.

Genetic analyses

Between-individuals associations of phenotypes (N170 ampli-

tude and latency) with the COMT val158met genotype were

tested by analysis of variance (ANOVA).

Because between-individuals association tests are suscep-

tible to confounding effects due to population stratification,

those variables that yielded significant results in between-

individuals associations were submitted to within-family

analyses. The transmission disequilibrium test (TDT) is a test

of linkage in the presence of association that was originally

developed for dichotomous traits (Spielman et al. 1993). The

family-based association test (FBAT) was successively intro-

duced as an extension of the original TDT to deal with

quantitative phenotypes (Laird et al. 2000); the FBAT statistic

computes the distribution of the offspring’s genotype condi-

tioning on parental genotypes or family genotype configura-

tion, assuming that H0 is true (Laird et al. 2000).

In this study, we adopted the FBAT methodology to cal-

culate the FBAT statistics as implemented in the phenotype-

based extension of the family-based association test (PBAT),

which allows for the use of covariates; the PBAT software

package version 2.6 is available at http://www.biostat.

harvard.edu/~clange/default.htm (Lange et al. 2004; Steen &

Lange 2005).

The N170 waveform is likely to be a multifactorial condi-

tion, and the transmission pattern of inheritance of N170

parameters is likely to be complex. No information is avail-

able to choose a priori the proper model of transmission of

N170 parameters; therefore, we performed the analyses

with all the four possible models (i.e. additive, dominant, re-

cessive and codominant) of transmission. As a consequence,

the nominal alpha level of the FBAT statistics was adjusted

for the number of FBAT statistics. The offset was set in order

to maximize the power of the FBAT statistic (Lange et al.

2004).

Genes, Brain and Behavior (2007) 6: 364–374 367

COMT genotype and face processing in children

Results

ERP analyses

Analyses of general effects

Analyses of the waveforms generated by the facial expres-

sions (Fig. 1, Table 1) showed an enhanced early negativity

occurring after stimulus presentation at a mean of 136 milli-

seconds for the Fz, 153 milliseconds for the Cz, 152 milli-

seconds for the C4, 154 milliseconds for C3, and

159 milliseconds for the Pz electrode. These latency values

are compatible with those reported by studies of N170

elicitation by facial stimuli in midchildhood (Taylor et al.

2004) and adulthood (Eimer & Holmes 2002), and thus these

waveforms were putatively identified as N170. By visual

inspection (Fig. 1), the N170 had maximum amplitudes and

clearest waveforms at the central (Cz) and centrolateral (C3,

C4) electrodes, similarl to other studies of N170 elicitation by

face perception (Eimer 2000b), while on the posterior

electrode (Pz), the N170 assumed the bifid shape typically

recorded by posterior electrodes in children of the 8–11 age

span, the so-called N170a and N170b (Taylor et al. 2004)

waveforms. According to ANOVA, the mean amplitudes of the

three expressions (joy, neutral and anger) were significantly

different across the five electrodes (ANOVA-repeated meas-

ures: F4,96 ¼ 47.14, P ¼ 0.00001) and significantly larger at

Cz, C3 and C4 than the amplitudes at Fz and Pz (Post hoc

Newman–Keuls P range ¼ 0.00010–0.00014); moreover,

the mean amplitude at Cz was larger than mean amplitude

at C3 and C4 (Post hoc Newman–Keuls: Cz vs. C3 P ¼ 0.03;

Cz vs. C4 P ¼ 0.06).

Similarly, ANOVA of the mean N170 latencies of the three

expressions (joy, neutral and anger) showed significant

differences across the five electrodes (ANOVA-repeated

measures: F4,96 ¼ 19.34, P ¼ 0.00001), with latencies at

central electrodes not significantly different from each other

(Post hoc Newman–Keuls P ¼ nonsignificant, for all Cz, C3

and C4 cross-comparisons) but significantly different from

both Fz and Pz latencies (Post hoc Newman–Keuls compar-

isons of Cz, C3 and C4 vs. Fz and Pz p range ¼ 0.00010–

0.00033).

In the light of these data and of the fact that Cz was the

electrode with the highest number of valid observations

(n ¼ 45), we focused the rest of the analyses on N170

parameters (latency and amplitude) as obtained at Cz.

Consistently, a visual inspection analysis of the topography

of the N170 waveform in our children showed a clear

prevalence of negativity at a central location compatible

with the choice of the Cz, and with the topographic

distribution found by Taylor et al. (2004, fig. 8) in children

aged 8–9 years in the context of an implicit emotional task.

To ascertain the degree of variability of measures across

trials (habituation effects), we performed ANOVA with ‘time’

(on two levels: first block, encompassing the first 50% of

repetitions; and second block, with the remaining repeti-

tions) as a repeated-measures factor, separately for N170 Table

1:N170amplitudesandlatenciesevokedbyfacialexpressionsatthereferenceelectrodesin

thesample

Joy

Neutral

Anger

Meanofthreeexpressions

Amplitude�

SD

(mV)

Latency

�SD

(milliseconds)

Amplitude�

SD

(mV)

Latency

�SD

(milliseconds)

Amplitude�

SD

(mV)

Latency�

SD

(milliseco

nds)

Amplitude�

SD

(mV)

Latency

�SD

(milliseconds)

Fz

�4.58�

2.25

(n¼

37)

135.92�

8.05

(n¼

37)

�4.35�

2.46

(n¼

38)

133.77�

11.96

(n¼

38)

�4.23�

2.37

(n¼

38)

135.92�

22.59

(n¼

38)

�4.33�

1.65

(n¼

37)

135.60�

8.56

(n¼

37)

Cz

�10.92�

4.21

(n¼

45)

154.16�

8.64

(n¼

45)

�11.81�

5.16

(n¼

45)

152.76�

10.53

(n¼

45)

�11.13�

4.10

(n¼

45)

151.90�

9.04

(n¼

45)

�11.29�

3.46

(n¼

45)

152.94�

7.85

(n¼

45)

Pz

�6.48�

4.83

(n¼

38)

161.65�

28.13

(n¼

38)

�8.07�

4.02

(n¼

38)

158.33�

32.84

(n¼

38)

�7.29�

4.83

(n¼

38)

155.62�

31.84

(n¼

38)

�7.28�

3.07

(n¼

38)

158.88�

28.98

(n¼

38)

C3

�9.80�

4.02

(n¼

40)

152.16�

8.32

(n¼

40)

�10.28�

4.40

(n¼

41)

153.43�

12.65

(n¼

40)

�9.67�

4.04

(n¼

41)

154.89�

10.50

(n¼

41)

�9.89�

3.16

(n¼

40)

153.55�

7.40

(n¼

39)

C4

�9.88�

4.37

(n¼

39)

153.62�

10.23

(n¼

39)

�10.34�

4.13

(n¼

40)

152.41�

9.91

(n¼

40)

�10.62�

3.96

(n¼

40)

149.61�

8.98

(n¼

40)

�10.23�

3.10

(n¼

39)

151.93�

7.65

(n¼

39)

368 Genes, Brain and Behavior (2007) 6: 364–374

Battaglia et al.

amplitude and latency for each expression recorded at Cz. We

found no evidence of significant habituation effects on either

amplitude or latency (with the possible exception of a trend

toward significantly decreased amplitude in the second vs.

first block of stimulations with the neutral expression ANOVA-

repeated measures: F1,41 ¼ 3.85, P ¼ 0.060), confirming

previous findings that the face-evoked N170 waveform is

unaffected by stimulus repetition.

To ascertain the possible effect of the type of expression

on the N170 parameters at Cz, we performed two separate

ANOVA-repeated measures tests on latency and amplitude,

with the three different expressions (joy, neutral and anger)

as a repeated measures factor. Results (latency: F2,88 ¼ 1.43,

P ¼ 0.24; amplitude: F2,88 ¼ 0.78, P ¼ 0.46) confirmed

that the N170 waveform is insensitive to the type of face

expression. Consequently, we focused all the following

analyses on the N170 latency and amplitude values calcu-

lated as a mean of the three expressions. The distributions

of these two parameters did not deviate significantly

from normality (N170 amplitude mean of three expressions

skewness ¼ �0.007, kurtosis ¼ �0.640, Lilliefors test

P ¼ 0.20; N170 latency mean of three expressions: skew-

ness ¼ 0.650, kurtosis ¼ 1.330; Lilliefors test P ¼ 0.20).

Moreover, two separate two-way ANOVA with age (8–

10 years) and sex as independent variables conducted on

Cz N170 latency and amplitude (mean of three expressions)

showed no significant influence of either of these demo-

graphic variables (latency: age F2,39 ¼ 0.52, P ¼ 0.60, sex

F1,39 ¼ 3.13, P ¼ 0.10, sex by age interaction P ¼ 0.62;

amplitude: sex F1,39 ¼ 0.56, P ¼ 0.46, age F2,39 ¼ 0.43, P

¼ 0.65, sex by age interaction P ¼ 0.73). However, as

commonly reported in the literature (e.g. Taylor et al. 2004),

a Student’s t-test showed that girls had slightly shorter N170

latency than boys (150.19 � 6.33 vs. 155.36 � 8.37, t ¼�2.30, P ¼ 0.03).

Genetic analyses

Genotyping

Forty-nine index children and their biological parents were

genotyped for the COMT val158met polymorphism. Both

parents were available for 42 children; only the mother was

available for two children; neither parent was available for five

children. The allele frequencies in children were 55 (56%) for

the val allele and 43 (44%) for the met allele, and the

genotypic frequencies were 14 (29%) val/val, 27 (55%) val/

met and 8 (16%)met/met, consistent with those expected in

European populations (Palmatier et al. 1999) and in Hardy–

Weinberg equilibrium (P ¼ 0.60). There were no differences

in the genotypes’ distribution of children in the study owing to

age, education (based on school grade 3 or 4) or socioeco-

nomic status (divided into lower, middle and upper and

calculated on the basis of the Hollingshead scale, 1975).

There was, however, a significant difference in the genotype-

by-sex distribution (w2 ¼ 17.360, df ¼ 2, P ¼ 0.001), owing

to a relative excess of boys with the val/met, and absence of

boys with the met/met genotype (Table 2). To better clarify

the nature of genotype distribution among boys, and to

conduct further analyses with the FBAT methodology, we

analyzed allelic and genotypic frequencies in parents. Hardy–

Weinberg equilibrium was also observed among parents

(P ¼ 0.37); frequencies for the val allele in parents were

52% among fathers and 64% among mothers (total fre-

quency among parents: 58%) and for the met allele were

48% among fathers and 36% among mothers (total fre-

quency among parents: 42%). The distribution of COMT

Table 2: Demographic and N170 electrophysiological features across genotypes in children

Catechol-O-methyltransferase val158met genotype

val/val (n ¼ 14) val/met (n ¼ 27) met/met (n ¼ 8)

Age, years (mean � SD) 8.79 � 0.80 8.78 � 0.70 9.12 � 0.64

Sex, girls (%)* 5 (64.28) 6 (22.22) 8 (100)

Education

Grade 3 8 17 3

Grade 4 6 10 5

Socioeconomic status (%)

Lower 2 (14.29) 3 (11.11) 1 (12.5)

Middle 7 (50) 13 (48.15) 4 (50)

Upper 5 (35.71) 11 (40.74) 3 (37.5)

N170 amplitude (mV) mean � SD

of three expressions

�11.44 � 2.51 (n ¼ 11) �11.37 � 3.79 (n ¼ 26) �10.79 � 3.81 (n ¼ 8)

N170 latency (ms)† mean � SD

of three expressions

154.98 � 8.09 (n ¼ 11) 153.96 � 7.43 (n ¼ 26) 146.83 � 6.60 (n ¼ 8)

All differences nonsignificant except *w2 ¼ 17.35, df ¼ 2, P ¼ 0.001, and †ANOVA F2,42 ¼ 3.33, P ¼ 0.044.

Genes, Brain and Behavior (2007) 6: 364–374 369

COMT genotype and face processing in children

val158met alleles in parents (Table 3) was entirely consis-

tent with that of children, indicating that the skewed

distribution of alleles among boys was simply due to

chance, as it can occur in samples of small size like this

one. Call rate was>99% and error rate<1% in the population

tested.

Between-subjects association tests

Two separate ANOVA conducted on N170 latency and ampli-

tude at Cz (mean of three expressions), with the COMT

val158met polymorphism as the independent variable on three

levels (0, 1 and 2 met alleles), showed no influence on

amplitude (F2,42 ¼ 1.00, P ¼ 0.91), but showed a significant

effect on latency, in the direction of a reduced time of onset of

the N170 waveform predicted by the number of met alleles

(F2,42 ¼ 3.33, P ¼ 0.044; regression beta ¼ �.32, adjusted

R2 ¼ 0.08; Newman–Keuls post hoc: met/met vs. val/val

P ¼ 0.03, met/met vs. val/met P ¼ 0.025, val/met vs. val/

val P ¼ 0.74), consistent with our hypothesis (Table 2,

Fig. 2). There was one outlier (a boy) in the val/val group with

a latency of 177.40 milliseconds (Fig. 2): when ANOVA on Cz

N170 latency was repeated after removal of this subject,

differences remained significant (F2,41 ¼ 3.58, P ¼ 0.037,

Newman–Keuls post hoc: met/met vs. val/val P ¼ 0.039,

met/met vs. val/met P ¼ 0.036, val/met vs. val/val P ¼ 0.66).

When ANOVA was repeated following the dichotomic

approach of Meyer-Lindenberg et al. (2005), i.e. contrasting

met homozygotes vs. val carriers (which was possible in

female subjects only, due to the absence of met homozy-

gotes among boys), the differences in N170 latency by

genotype were confirmed (met homozygotes 146.83 � 6.60

milliseconds vs. val carriers 152.26 � 5.41 milliseconds;

F1,23 ¼ 4.230, P ¼ 0.054) again.

Within-family association test

Following the between-subjects associations tests, the N170

latency was further tested for family-based association with

the COMT val158met polymorphism. Univariate analyses

were run with the N170 latency as a quantitative phenotype

and sex as a covariate (Lange et al. 2004), given the difference

in genotype-by-sex distribution among children in the study.

Among the four alternative models of transmission (domi-

nant, recessive, codominant and additive), only the codomi-

nant model yielded a significant result for the COMT

val158met polymorphism (FBAT statistic P ¼ 0.0034) with

25 informative families, and a nominal alpha level adjusted

to 0.013.

Relationships of the N170 to other salient

waveforms, and of the COMT genotype

to behavioral variables

The distribution of the COMT val158met genotypes was

independent of the distribution of the serotonin transporter

(5HTT) promoter polymorphism (5-HTTLPR, w2 ¼ 1.453,

df ¼ 4, P ¼ 0.834), which we (Battaglia et al. 2005) had

previously investigated in this group of children in relation to

social shyness and another waveform, namely the N400,

associated with face processing.

The correlations of the N170 and N400 amplitudes and

latencies across the three expressions were modest to

moderate and varied between .07 and .29 for latency, and

between .19 and .35 for amplitude (all correlations nonsignifi-

cant for this sample size). Likewise, by ANOVAs, we found no

significant association of the 5-HTTLPR genotype with N170

latency or amplitude (P ¼ 0.18 and P ¼ 0.17, respectively) or

COMT val158met genotype with N400 latency or amplitude

(P ¼ 0.25 and P ¼ 0.91, respectively).

To further clarify possible relationships of the COMT

val158met genotypes to other variables that we had collected

in our children, we ran separate ANOVAs with the number of

COMTmet alleles as the independent variable on three levels

(0, 1 and 2 met alleles) and found no significant effect

pertaining to a comprehensive index of observed degree of

shyness (Battaglia et al. 2005), the number of spontaneous

Figure 2: Scatterplot of subjects in the experiment ordered

by catechol-O-methyltransferase (COMT) val158met geno-

type. The graph shows the latency of the N170waveform evoked

by face expressions (mean of three expressions) at the Cz

electrode for each subject.

Table 3: Results of catechol-O-methyltransferase val158met

parental genotyping

Subjects Typing n

Total (n ¼ 86) val 32

val/met 36

met 18

Fathers (n ¼ 42) val 13

val/met 18

met 11

Mothers (n ¼ 44) val 19

val/met 18

met 7

370 Genes, Brain and Behavior (2007) 6: 364–374

Battaglia et al.

comments made on the ERP experiment day, all the Children

Behavior CheckList (CBCL 4–18, Achenbach, 1991) scales [(1)

withdrawn, (2) somatic complaints, (3) anxious/depressed, (4)

social problems, (5) thought problems, (6) attention problems,

(7) delinquent behavior, (8) aggressive behavior, and the

broadband internalizing and externalizing scores encompass-

ing syndromes 1, 2, 3, and 7, 8, respectively), or the number

of misclassifications made in a face expression discrimination

task completed by children 1 year before the ERP study.

Discussion

Our results indicate that variation at the COMT val158met

genotype influences the time of onset of the N170 waveform,

an electrophysiological event mapping the early phases of the

cognitive–emotional act of human face processing in the

brain. Specifically, the met allele is associated with a signifi-

cantly reduced latency of the N170, the earliest detectable

electrophysiological waveform in our experiment, and awave-

form that has been repeatedly shown to be specifically

evoked by human face in children and adults.

The finding of better promptness to face processing

associated with the met allele is consistent with the notion

that the enzyme containing the met allele has one-third to

one-fourth of the activity of the enzyme containing the val

allele (Chen et al. 2004; Lotta et al. 1995; Spielman &

Weinshilboum 1981) in degrading dopamine. The enzyme

containing the met allele is thus likely to confer increased

cortical dopamine signaling (Weinberger et al. 2001), which in

turn can explain better cortical signal-to-noise ratio (Gallinat

et al. 2003; Mattay et al. 1996), more effective interaction

between prefrontal activity and midbrain dopaminergic syn-

thesis (Meyer-Lindenberg et al. 2005), better performances in

tests of executive cognition (Goldberg & Weinberger 2004)

and shorter reaction time in visual cognitive control tasks

(Blasi et al. 2005) reported in adults with one or two copies of

the met allele. Likewise, children homozygous for the met

allele perform better in cognitive tasks that specifically

engage the dorsolateral prefrontal cortex (Diamond et al.

2004). Due to chance, the distribution of genotypes is

significantly different between boys and girls in this sample;

however, there is robust enough evidence that gender affects

only modestly the function of this gene, and only after

puberty: functional analyses of COMT genetic variation on

dorsolateral prefrontal cortex specimens show only small

effects of sex on COMT enzyme activity, with adult women

having slightly but significantly lower activity than adult men

(Chen et al. 2004), likely due to the regulatory activity of

estrogen on COMT promoter activity (Chen et al. 2004;

Weinshilboum et al. 1999). Because all our subjects were

prepubertal, an influence of sexual hormones on COMT

enzymatic activity should be excluded, and the uneven

distribution of genotypes by gender should therefore be

considered only a relative limitation to the generalizability of

these findings in midchildhood.

Turning our attention to the electrophysiological data, they

confirm earlier findings (Taylor et al. 1999) that even in

midchildhood the face-evoked N170 waveform is a reliable

marker of the early phases of face processing. The lack of

influence of the type of emotional expression and the

absence of habituation effects on N170 amplitude or latency

in our data are consistent with experimental evidence

that this waveform is not affected by emotional valence

(Eimer & Holmes 2002; McCarthy et al. 1999) or repetition

(Schweinberger et al. 2002) of stimuli in adults and extends

the same notion to children.

In a previous report based on the same group of children,

we have shown that a pattern of decreased centroparietal

cortical activation (as indexed by the N400 waveform) in

response to peers’ expressions of anger is associated with

social shyness and the –S allele of the 5-HTTLPR (Battaglia

et al. 2005), a finding independent of the present association

of N170 latency with COMT val158met genotype.

In our effort to investigate the causal architecture of the

complex cognitive–emotional act of human face processing,

we are thus focusing on different electrophysiological

phases, each of which may be underpinned by relatively

separate biological mechanisms and independent genetic

causes. The use of N170 latency as a measure of early face

structural encoding influenced by the COMT val158met geno-

type, however, is exposed to some limitations and caveats,

which need to be taken into account.

First, several previous ERP studies have typically examined

an earlier and more occipital response, such as the P1 (see

Luck et al. 2000, for review), and we cannot rule out defini-

tively the possibility that our data may reflect in part some

more general aspects of perceptual processing, perhaps even

arising at P1; however, the N170 is clearly the earliest

waveform evoked by our paradigm (Fig. 1) at the available

electrodes. Moreover, the evidences of rapid emotional face

processing, mostly at posterior sensors, found within the

100–200-millsecond time range (e.g. Pizzagalli et al. 1999,

2002; Vuillemier 2002) were based on different paradigms,

which makes direct comparisons between studies difficult:

the strongest evidence that early ERP activity can be influ-

enced by the type of emotional facial stimulus rests on data

(Pizzagalli et al. 1999, 2002) recorded to individually assessed

liked, neutral and disliked faces in adults, while we used

a paradigm of implicit processing of other children’s faces in

prepubertal subjects. A conservative interpretation of the par-

tial inconsistencies regarding the effects of affective com-

ponents of facial stimuli on early ERP waveforms is offered

by Eimer & Holmes (2002), who suggest that structural

encoding of faces and emotional expression analysis may

be parallel processes indexed by different waveforms.

Second, the relationship between the source of the N170

and the brain areas for which there is clearer evidence for

expression of the COMT gene deserves a specific caveat.

While the precise source for the N170 is still debated,

a reanalysis of combined samples (Taylor et al. 2004) found

Genes, Brain and Behavior (2007) 6: 364–374 371

COMT genotype and face processing in children

two separate N170 sources for children aged 10–11: one

occipital and the other lateral temporal. This may sound

problematic when one considers that most studies of COMT

expression and COMT val158met genotype influence on brain

activation are focused on prefrontal and frontal cortices

(Goldberg & Weinberger 2004). However, the functional

magnetic resonance data by Smolka et al. (2005) show that

a task of passive processing of human faces elicits a pattern

of brain activation that is significantly affected by the COMT

val158met genotype at the levels of the fusiform gyrus,

inferior parietal lobule, amygdala and thalamus, in addition

to the ventrolateral prefrontal cortex (where it is most pro-

nounced) and middlefrontal gyrus. Thus, inasmuch as the role

of the COMT val158met genotype in influencing cerebral

activation in response to passive viewing of human faces

extends to a wider network of brain areas and functions

beyond the prefrontal cortex, the relationship between N170

latency and the met158 allele can be viable.

Third, although our study group was under many social,

behavioral and genetic vantage points, an unbiased sample

of a cohort of schoolchildren characterized by their ability to

discriminate facial expressions of emotions (Battaglia et al.

2004, 2005), there were distributional differences in the

COMT val158met genotype, which we addressed in the ana-

lyses but call for replication in a sample without genotype-

by-sex distribution differences, thus leaving this first study

as a pilot and tentative investigation.

Altogether, while our data need replication in a more

balanced sample and information from more electrodes, they

do suggest that the complex emotional behavioral task of

human face processing can be partitioned into different

phases, each characterized by at least partially independent

genetic architectures. While earlier phases of face processing

are associated with the earlier ’exogenous‘ potentials, the

later potentials may reflect more the nature of interaction

between the subject and the event (Battaglia et al. 2005) and

may covary with other psychophysiological indexes of affec-

tive processing (Palomba et al. 2000); thus earlier and later

phases of face processing yield different implications for

psychology and psychopathology.

From a developmental behavioral genetic perspective, the

study of the molecular genetic bases of face processing can

open new avenues to understanding individual differences in

human interpersonal abilities. Changes in patterns of brain

activation in response to facial stimuli together with modifi-

cations of genes’ expression along development may consti-

tute new instruments for the implementation of more

scientifically based treatments of mental disorders, including

psychotherapies (Etkin et al. 2005).

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Acknowledgments

Supported by the Italian Ministry of University and Research (Co-

Fin grant 11/2001-113555_004 to M. B. ), the Anna Villa & Felice

Rusconi Foundation and the LiberaMente Foundation. The au-

thors of this paper do not recognize any form of a conflict of

interest. We thank Linda Camras, L. Brenna, N. Stillitano, and all

children, parents and teachers who took part in this study.

Battaglia et al.

374 Genes, Brain and Behavior (2007) 6: 364–374