Dopamine inactivation efficacy related to functional DAT1 and COMT variants influences motor response evaluation.

Abstract

Dopamine plays an important role in orienting, response anticipation and movement evaluation. Thus, we examined the influence of functional variants related to dopamine inactivation in the dopamine transporter (DAT1) and catechol-O-methyltransferase genes (COMT) on the time-course of motor processing in a contingent negative variation (CNV) task.
64-channel EEG recordings were obtained from 195 healthy adolescents of a community-based sample during a continuous performance task (A-X version). Early and late CNV as well as motor postimperative negative variation were assessed. Adolescents were genotyped for the COMT Val(158)Met and two DAT1 polymorphisms (variable number tandem repeats in the 3'-untranslated region and in intron 8).
The results revealed a significant interaction between COMT and DAT1, indicating that COMT exerted stronger effects on lateralized motor post-processing (centro-parietal motor postimperative negative variation) in homozygous carriers of a DAT1 haplotype increasing DAT1 expression. Source analysis showed that the time interval 500-1000 ms after the motor response was specifically affected in contrast to preceding movement anticipation and programming stages, which were not altered.
Motor slow negative waves allow the genomic imaging of dopamine inactivation effects on cortical motor post-processing during response evaluation. This is the first report to point towards epistatic effects in the motor system during response evaluation, i.e. during the post-processing of an already executed movement rather than during movement programming.

Full text

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Dopamine Inactivation Efficacy Related to Functional
DAT1 and COMT Variants Influences Motor Response
Evaluation
Stephan Bender1,2,3*, Thomas Rellum4, Christine Freitag2, Franz Resch3, Marcella Rietschel5,
Jens Treutlein5, Christine Jennen-Steinmetz6, Daniel Brandeis4,7,8, Tobias Banaschewski4,
Manfred Laucht4,9
1Section for Clinical Neurophysiology and Multimodal Neuroimaging, Child and Adolescent Psychiatric Department, Technical University Dresden, Dresden, Germany,
2Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Johann-Wolfgang-Goethe University, Frankfurt am Main, Germany, 3Department
of Child and Adolescent Psychiatry and Psychotherapy, Heidelberg University Hospital, Heidelberg, Germany, 4Department of Child and Adolescent Psychiatry and
Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany, 5Department of Genetic Epidemiology in
Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany, 6Department of Biostatistics, Central Institute of
Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany, 7Department of Child and Adolescent Psychiatry, University of Zu ¨rich, Zu ¨rich,
Switzerland, 8Center for Integrative Human Physiology, University of Zu ¨rich, Zu ¨rich, Switzerland, 9Department of Psychology, University of Potsdam, Potsdam, Germany
Abstract
Background: Dopamine plays an important role in orienting, response anticipation and movement evaluation. Thus, we
examined the influence of functional variants related to dopamine inactivation in the dopamine transporter (DAT1) and
catechol-O-methyltransferase genes (COMT) on the time-course of motor processing in a contingent negative variation
(CNV) task.
Methods: 64-channel EEG recordings were obtained from 195 healthy adolescents of a community-based sample during a
continuous performance task (A-X version). Early and late CNV as well as motor postimperative negative variation were
assessed. Adolescents were genotyped for the COMT Val158Met and two DAT1 polymorphisms (variable number tandem
repeats in the 39-untranslated region and in intron 8).
Results: The results revealed a significant interaction between COMT and DAT1, indicating that COMT exerted stronger
effects on lateralized motor post-processing (centro-parietal motor postimperative negative variation) in homozygous
carriers of a DAT1 haplotype increasing DAT1 expression. Source analysis showed that the time interval 500–1000 ms after
the motor response was specifically affected in contrast to preceding movement anticipation and programming stages,
which were not altered.
Conclusions: Motor slow negative waves allow the genomic imaging of dopamine inactivation effects on cortical motor
post-processing during response evaluation. This is the first report to point towards epistatic effects in the motor system
during response evaluation, i.e. during the post-processing of an already executed movement rather than during movement
programming.
Citation: Bender S, Rellum T, Freitag C, Resch F, Rietschel M, et al. (2012) Dopamine Inactivation Efficacy Related to Functional DAT1 and COMT Variants
Influences Motor Response Evaluation. PLoS ONE 7(5): e37814. doi:10.1371/journal.pone.0037814
Editor: Judith Homberg, Radboud University, Netherlands
Received January 26, 2012; Accepted April 24, 2012; Published May 23, 2012
Copyright: ? 2012 Bender et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by multiple grants from the Deutsche Forschungsgemeinschaft (DFG), the Ministry of Science and Investigation, Baden-
Wu ¨rttemberg, Germany, and a grant by the Medical Faculty of the Goethe University, Frankfurt, Germany (7601002). The funders had no role in study design, data
collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: Stephan.Bender@uniklinik-dresden.de
Introduction
The perception-action-cycle involves different stages, from the
orienting to a warning stimulus to the preparation of a reaction
movement and the evaluation of the given response. Due to the
high time resolution of electroencephalography, these stages can
be excellently assessed in contingent negative variation (CNV)
paradigms, which involve a cue followed by a later imperative
stimulus which requires a motor response [1]. The early
component of the CNV reflects an orienting response and early
response preparation [2,3,4]. The late component of CNV reflects
the preparation of the motor response and the anticipation of the
imperative stimulus [5,6]. Postimperative negative variation
(PINV) refers to motor and cognitive response evaluation and
may include a short-term memory trace of the planned movement
which needs to be compared to reafferent sensory feedback about
the actually performed movement [7,8,9]. Dopamine modulates
the neuronal signal-to-noise ratio in order to focus prefrontal
cortical resources [10] and plays an important role in focusing
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attention on relevant stimulus characteristics [11]. Thus, dopa-
mine plays an important role in all three stages, orienting [12],
response preparation [13] and response evaluation [14]. However,
it has not been examined yet, how specific genetic variations affect
the different cognitive and motor processing stages:
The duration of dopaminergic action is limited by dopamine
inactivation, i.e. mainly methylation by catechol-O-methyltrans-
ferase (COMT) in the prefrontal cortex [15] and reuptake via the
dopamine transporter (DAT1) in the striatum [16].
In the current study, we investigated the effects of three
functional polymorphisms in the COMT and DAT1 genes on the
orientation reaction, movement programming and stimulus post-
processing (indexed by the early and late components of the CNV
as well as the motor postimperative negative variation component),
during a continuous performance test with speeded button press
response movements.
A widely studied functional COMT polymorphism, character-
ized by the substitution of valine for methionine at codon 158 [17],
results in less enzyme activity and higher extracellular dopamine
levels [18]. The 10-repeat allele of a variable number tandem
repeat (VNTR) polymorphism in the 39-untranslated-region of
DAT1 and the 6-repeat allele of a VNTR in intron 8 lead to
greater DAT1 expression [19] and reduced striatal dopamine
levels, though the controversy about whether the 10-repeat allele
results in greater or lower DAT expression [20] is not finally
resolved yet. The co-occurrence of both DAT1-expression
increasing VNTRs, the 6R–10R haplotype, has been reported to
strengthen this effect [21,22]. Thus, here we examined the DAT1
haplotype and its interaction with the COMT Val158Met
polymorphism in relation to motor PINV.
Previous fMRI genomic imaging studies have demonstrated that
higher prefrontal (Met COMT allele [23,24,25]) and lower striatal
(10R DAT1 allele [24]) dopamine levels resulted in more focused
prefrontal cortical activation.
We hypothesized that motor CNV component amplitudes
would be genetically affected in a similar way to prefrontal cortex
BOLD responses in working memory tasks [24]. In this case, the
Met-COMT allele and the 6R–10R DAT1 haplotype would be
associated with more focused motor activation with lower
amplitudes. An alternative hypothesis was that DAT1 and COMT
effects on motor CNV components would show exactly the inverse
pattern because more prefrontal resources could be required in
prefrontal-motor loops to act on less intense motor representations
[26]. Because DAT1 and COMT both affect the termination of
dopaminergic neurotransmission, we hypothesized that motor
PINV would be more strongly affected than early CNV or the
initial motor potential peak, because the duration and amplitude
of motor post-processing during motor PINV could depend on the
speed of inactivation of dopamine released during the preceding
response. Even if this specific hypothesis would be falsified, the
assessment of the two functional genetic polymorphisms would
allow an examination of dopaminergic effects on reaction-related
EEG potentials in healthy adolescents.
Methods
Participants
The current data analysis was conducted on the sample of the
Mannheim Study of Children at Risk, a prospective longitudinal
study of the outcome of early risk factors from infancy into
adulthood [22]. Children born between 1986 and 1988 were
recruited from two obstetric and six pediatric hospitals of the
Rhine-Neckar Region of Germany. Infants were included
consecutively into the study according to a 2-factorial design
intended to enrich and to control the risk status of the sample (full
details of the sampling procedure have been reported previously
[27]). As a result, approximately two thirds of the study sample
had experienced obstetric complications such as preterm birth,
and about two thirds of the families had psychosocial adversities
such as marital discord or chronic difficulties. Of the initial sample
of 384 participants, 18 (4.7%) were excluded because of severe
handicaps (neurological disorder, intelligence quotient ,70 or
motor quotient ,70), 28 (7.3%) were drop-outs at age 15, 35
(9.1%) refused to take part in blood sampling or had incomplete
genetic data, and from 43 (11.2%), no, or no reliable, EEG data
were available. Intelligence was assessed at the age of 11 years
using the Culture Fair Test 20 [28,29]; the motor quotient was
determined at age 11 years by a short version of the Body
Coordination Test for children KTK [30]. 65 subjects (16.7%)
were excluded from the current analysis due to a current
psychiatric DSM-IV diagnosis. 21 subjects of the remaining 195
(10.8%) had to be excluded because they were not right-handed as
indicated by a handedness index above +60 in the Edinburgh
Handedness Inventory [31]. All subjects were free of psychoactive
medication at the time of the recording. The study was approved
by the ethics committee of the Medical Faculty of the University of
Heidelberg/Mannheim. Written informed consent was obtained
from all participants and their parents. All subjects had a corrected
visual acuity of 0.8 or higher.
Recordings
Continuous 64-channel DC EEG was recorded by Neuroscan
Sympamps amplifiers (Neuroscan Inc., TX, USA). Sintered silver/
silver chloride electrodes were positioned by an equidistant
electrode cap (Easycap, FMS, Germany). Electrode impedances
were kept below 10 kOhm. Vertical electrooculogram (VEOG)
was recorded by electrodes 1 cm below and above the left eye.
Horizontal electrooculogram (HEOG) was calculated by leads F99
and F109 next to the outer canthi. Small deviations of electrode
positions from the international 10-10 system are indicated by
apostrophes. The recording reference was placed near the left
mastoid. Offline, data were transformed to average reference. The
sampling rate was 500 Hz. An anti-aliasing low-pass filter with a
cut-off frequency of 100 Hz was employed. The visual stimulation
was presented by Gentask of the Neuroscan Stim software
package. Reaction times were collected from response triggers
from the response pad.
Task
Subjects performed a computerized A-X version of the
continuous performance test (CPT; constructed by doubling the
number of trials of a common previous multicenter version
[32,33,34]). 800 black-colored capital letters were presented on
white background in the center of the computer screen for 150 ms.
The stimulus onset asynchrony (SOA) between the different letters
was 1600 ms. Whenever an ‘A’ was followed by an ‘X’ (50%
probability), subjects had to respond with a fast right-hand button
press with their index finger on the response pad. The ‘A’ was
followed by an ‘X’ 80 times and by another letter 80 times.
Additionally, single distractor letters were presented.
An ‘X’ without a preceding ‘A’ occurred 80 times. Another nine
letters of the alphabet (‘B’, ‘C’, ‘D’, ‘E’, ‘F’, ‘G’, ‘H’, ‘J’, ‘L’) were
employed as distractors. The distractor ‘H’ occurred 160 times
(frequent distractor). The distractors ‘B’, ‘C’, ‘D’, ‘E’, ‘F’, ‘G’, ‘J’,
and ‘L’ appeared 40 times each.
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Data pre-processing
For the analysis of early and late CNV, continuous recordings
were segmented into stimulus-locked segments from 400 ms prior
to the distractor before the warning stimulus ‘A’ to 1600 ms after
the imperative stimulus ‘X’ (5.2 seconds in total). The 400 ms
before the warning stimulus ‘A’ served as baseline.
For the analysis of the initial motor potential peak during
movement execution and the analysis of motor post-processing,
response-locked epochs of 4 seconds were created, beginning
2800 ms before the response until 1200 ms afterwards. The first
400 ms of this interval served as baseline (2800 to 2400 ms before
the response). Only trials with correct responses within 800 ms
were included in the analysis. Taking into account the stimulus
onset asynchrony of 1600 ms, this assured that the baseline
interval was situated before the onset of the warning letter ‘A’ even
for slow responses. The warning letter ‘A’ of a target sequence was
never directly preceded by another target sequence. Thus, during
the baseline, the subjects had processed a distractor letter and were
waiting for the next stimulus to occur. Reaction times took at least
approximately 150–200 ms, even for fast responses. We verified
that there were no gene effects on the baseline time interval which
could have influenced the results.
Data were corrected for eye movements and blinks by the
algorithm of Gratton and Coles (Brain Vision Analyzer,
BrainProducts GmbH, Munich, Germany). Average reference
was calculated offline. Data were 30 Hz low-pass filtered by a
zero-phase shift Butterworth filter with a slope of 48 dB/octave.
Potentials exceeding 150 mV amplitude were rejected automati-
cally as artifacts; remaining smaller artifacts were removed by an
experienced EEG technician who was blind to the study
hypotheses.
We calculated lateralized movement-related potentials by
subtracting the potentials at each electrode on the right
hemisphere from the potentials measured at its homologue on
the left side of the head (e.g. C3–C4). In this way, the resulting
polarity reflects the polarity for potentials which were lateralized
contralateral to the response movement with the right hand. In a
previous study, we had found that lateralization in trials with the
dominant right hand closely resembled the final lateralized
movement-related potential [9]. A complete calculation of the
lateralized movement-related potential to eliminate all stimulus-
related lateralized potentials was not possible because only
responses by the right hand were available. However, due to a
mean reaction time of about 350 ms and a motor PINV interval
400–800 ms after the response, summing up to a window 750–
1150 ms after the imperative stimulus ‘X’ which was presented in
the center of the visual field, there should be only very small
influences of lateralized stimulus-related processes.
Data analysis
Early CNV (orienting reaction).
measured at its topographical maximum at Fz during the time
interval 600–900 ms [2,35].
LateCNV(movementpreparation
ing).
The amplitude of the motor part of late CNV amplitude
was determined as the mean potential 200 ms before the
imperative stimulus (‘X’) over the left (contralateral to the response
movement) motor (pooled leads C3, CP39, C59) and the
supplementary motor area (pooled leads Cz, FCz9, FC19, FC29;
[6,36]). Lateralization of CNV over the motor area was also
assessed (pooled leads C3, CP39, C59 minus C4, CP49, C69).
Motor potential (movement execution).
initial motor potential peak was determined from 120 to 0 ms
before the button press and represents a correlate of the sending of
the command to muscle contraction from the primary motor
cortex (pooled leads C3–C4, CP39–CP49, C59–C69 [9]).
Motor PINV (movement post-processing).
lateralized movement-related post-processing (mPINV) over the
motor area (pooled leads C3–C4, CP39–CP49, C59–C69) during
the interval 400–800 ms after the unilateral index finger response
movement, comparable to our previous studies [9,14,37,38].
Early CNV amplitude was
and programm-
The lateralized
We analyzed
Source analysis
Source analysis was carried out on the group grand averages,
which provide the best signal-to-noise ratio. Dipole source
modelling with equivalent dipoles allows the examination of
group differences in the time course of event-related potential
components. According to our previous study [9], we performed a
Table 1. Genetic influences on reaction times and reaction time variability (6 standard deviation).
Reaction time RTSD1
DAT1
6R–10R/6R–10R (N=79) 353663 ms 91628 ms
at least one non-6R–10R allele (‘‘DAT 1 other’’; N=95)353656 ms89631 ms
COMT
Met/Met (N=35) 359665 ms 89631 ms
Val/Met (N=96) 349660 ms 89629 ms
Val/Val (N=43)359653 ms 92630 ms
DAT16COMT
6R–10R/6R–10R+Met/Met (N=15)
6R–10R/6R–10R+Val/Met (N=46)
6R–10R/6R–10R+Val/Val (N=18)
DAT1 other+Met/Met (N=20)
DAT1 other+Val/Met (N=50)
DAT1 other+Val/Val (N=25)
346652 ms 90626 ms
354666 ms 91626 ms
359668 ms91636 ms
369673 ms 89635 ms
344654 ms 87632 ms
358641 ms93626 ms
1RTSD=intraindividual standard deviation of reaction times (reaction time variability).
doi:10.1371/journal.pone.0037814.t001
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source analysis by the automated RAP-MUSIC algorithm with
SBSI on the motor PINV peak (400–600 ms after the response
trigger). Two topographies were allowed according to the
complexity of the scalp surface potential. Separate models were
fit on the DAT1 6R–10R/6R–10R+COMT Met/Met (highest
motor PINV amplitudes) and the DAT1 other+COMT Val/Val
group (low motor PINV amplitudes), because qualitative differ-
ences in motor PINV topography were found between the genetic
groups.
In a second complementary approach with distributed sources
instead of equivalent dipoles, sLORETA with the BESA default
parameters (BESA GmbH, Munich, Germany) was performed on
the same motor PINV time interval (non-lateralized data) in order
to describe the extension of the distributed cortical sources of the
lateralized motor PINV as exact as possible.
Genotyping
EDTA anticoagulated venous blood samples were collected.
Leukocyte genomic deoxyribonucleic acid (DNA) was isolated with
the Qiamp DNA extraction kit (Qiagen, Chatsworth, California).
Genotyping of the COMT single nucleotide polymorphism
(SNP) was completed using TaqMan (SNP) Genotyping Assays
(7900HT Fast Real-Time-PCR-System; Applied Biosystems,
Foster City, California). Amplification conditions for COMT
rs4680 were: 3.0 ml TaqManH Mastermix, 0.3 ml/0.15 ml Taq-
ManH oligonucleotide mix (206/406), 1.70 ml dH2O and 1 ml
DNA solution (,30 ng) in 96-well format in a 6 ml reaction.
Amplification was performed by initial heating of 10 min–95uC,
40 cycles of 15 sec–95uC/1 min-60uC and final 10 min-4uC.
TaqManH assay-on-demand ID C_25746809_50 detected the
alleles of rs4680 (hCV25746809) in the sequence context of
CCAGCGGATGGTGGATTTCGCTGGC[A/G]TGAAGGA-
CAAGGTGTGCATGCC.
The 40-bp VNTR polymorphism in the 39-untranslated-region
(UTR) of DAT1 was genotyped with the primers and reaction
conditions of Sano et al. [39]. Polymerase chain reaction was
carried out using a nucleotide mix consisting of 7.4 mM
deoxyadenosine triphosphate, deoxycytidine triphosphate, and
deoxythymidine triphosphate and 3.7 mM deoxyguanosine tri-
phosphate and 7-deaza-29-deoxyguanosine 59-triphosphate (Amer-
sham Biosciences, Piscataway, NJ). After an initial denaturation
step, 35 cycles of amplification of 1 minute at 94uC, 1 minute at
63uC, and 35 seconds at 72uC were performed. The 30-bp intron
8 VNTR polymorphism was genotyped according to the
procedure by Vandenbergh et al. [40]. All genotypes were scored
independently by 2 individuals who were blind to the presented
data. The VNTRs had been genotyped in the context of the study
of Laucht et al. [22]. No deviations from Hardy Weinberg
equilibrium were detected (DAT1 30 bp VNTR intron 8 p=0.78;
DAT1 40 bp VNTR 39UTR p=0.10; COMT p=0.20).
Both DAT1 VNTRs were analyzed combined as haplotype. In
accordance with the previous literature and in order to avoid small
groups containing only a low number of subjects, with respect to
the DAT1 haplotype, subjects were dichotomized into homozygous
carriers of the 6R–10R haplotype, which have previously been
demonstrated to increase the risk of psychiatric disorders [22], and
those who carried at least one non-risk haplotype.
In detail, the following genotype groups were formed: (1) DAT1
haplotype: 6R–10R/6R–10R (N=79) versus at least one non-6R–
10R haplotype (N=95); and (2) COMT: Val/Val (N=43) versus
Val/Met (N=96) versus Met/Met (N=35).
Statistical analysis
To examine the effect of the DAT1 haplotype (at least one non-
6R–10R-haplotype was coded as ‘0’; 6R–10R/6R–10R was coded
as ‘1’) and COMT (Val/Val=0; Val/Met=1; Met/Met=2) on
the target parameters (early CNV, late CNV, motor potential peak
and lateralized motor PINV amplitudes), linear regression analyses
were performed. In order to test for a significant epistasis between
DAT1 and COMT, regression models with and without an
interaction term were compared. Significant interactions were
further examined by conducting separate regression analyses for
each DAT1 haplotype level with COMT genotype as a predictor.
All analyses included gender as a covariate. The same regression
analysis as for EEG parameters was performed on behavioral
measures, i.e. reaction time, reaction time variability, the number
of omission and commission errors. In order to further examine
the functional meaning of motor PINV, Pearson correlation
coefficients were calculated between motor PINV amplitude and
the behavioral measures.
Results
Behavioral data
Mean reaction time was 352658 ms (6 SD), with no significant
effects of genetic variants. Trend level towards genetic influences
on reaction time variability was not reached either (Table 1).
There were on average 2.562.7 omission errors and 2.463.0
commission errors in the CPT task. While DAT1 and COMT did
not show any significant main effects or interactions on the
number of commission errors, there was a significant interaction
between the two functional polymorphisms with respect to
omission errors (DAT1 haplotype beta=20.25; t=1.8; p=0.07;
COMT beta=20.16; t=1.7; p=0.098; DAT1 haplotype x COMT
beta=0.31; t=2.0; p=0.047). However, separate regression
analyses for the two DAT1 haplotype groups with respect to
COMT effects on omission errors did not yield significant results.
Figure 1. Time course and topography of the motor PINV by DAT1 haplotype. Top: The time course of the response-locked motor PINV
over the contra- and the ipsilateral motor area is shown. Negativity is up. There were no differences between the genotype groups during response
preparation (contingent negative variation, CNV) after the cue (‘A’). Differences selectively affected the post-processing interval. During the button
press (vertical dashed line), response selection during the P300 shadows the movement-related potentials. Thus, we calculated the lateralized motor
PINV: Time course of the lateralized motor PINV when the potential over the contra- and ipsilateral motor areas is subtracted. This eliminates the
symmetrically distributed parts of stimulus-related processing. Negativity is up. The peak immediately preceding the button press, which is related to
the cortico-spinal command to muscle contraction, was influenced rather in the opposite direction to the motor PINV. Middle: Topography of the
motor PINV: Isopotential line maps of the voltage topography and of the current source density (CSD) are shown, the head is presented in the top
view from above, the nose is pointing upwards. Negativity and current sinks are reflected by blue areas, positivity and current sources are illustrated
by red areas. Note the contralateral lateralization. Bottom: sLORETA source analysis results illustrating the effects of DAT1 polymorphisms on the
lateralized motor PINV: Note the stronger centro-parietal activation in Brodman areas 1–4 and 40 for the 6R–10R/6R–10R group, which is missing in
the non 6R–10R/6R–10R group (marked by squares and blue arrows). Activation in the premotor area and frontal eye field (BA 6/8) was more bilateral
in the non 6R–10R/6R–10R group (red arrows). The blue dipole indicates that RAP-MUSIC yielded a spatial component that showed a localization and
orientation which explained the lateralized centro-parietal activation only for the 6R–10R/6R–10R group (details not shown). The crossing red lines
were set to a point near the motor cortex hand area in order to illustrate the cortical activation in this area (cf. Figure 4).
doi:10.1371/journal.pone.0037814.g001
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