Download METHODS Subjects Thirty-two healthy male volunteers were

METHODS
Subjects
Thirty-two healthy male volunteers were recruited for this study. One tested positive on the opiate
urine screening, while another participant only completed one session. Therefore, the final number
of participants was 30 (mean age = 26.7, SD = 4.7 years). To account for data loss of one task, an
additional group of seven healthy males were recruited, yielding a total N of 23 for the ‘liking’ task
(mean age = 25.5, SD = 4.8 years). During a pre-testing phone screening interview, none of the
participants reported a history of depression or other major psychiatric illness, none were on
medication, and none had multiple complex allergies. AUDIT (Alcohol Use Disorders Identification
Test) and DUDIT (Drug Use Disorders Identification Test) were used to assess drug and alcohol
consumption among participants1, 2. Volunteers reported consuming an average of 5.5 alcoholic
drinks per week. Of the 37 participants included, 27 reported previous use of cannabinoids, 12 during
the last year. Previous use of other drugs was reported as follows: amphetamines (seven
participants), stimulants (cocaine, crack; nine participants), hallucinogens (ecstasy, LSD; nine
participants) and opiates (one participant, three others had used prescribed morphine). None of the
participants reported prior drug dependence or addiction, and none had taken morphine in any form
for at least two years prior to testing3. All participants had normal or corrected-to-normal vision.
Genotyping using predesigned TaqMan single nucleotide polymorphism (SNP) genotyping assays for
the A118G SNP of the mu opioid receptor gene (OPRM1) as previously described4 revealed that there
were 27 AA carriers and ten AG carriers in the sample.
Stimuli and Apparatus
For the purposes of this study, we developed a new database of face stimuli (The Oslo Face
Database), consisting of color photographs of 187 young individuals (103 females). Three full-frontal
view photographs were taken for each individual: one picture with direct gaze, and two pictures with
averted gaze (one looking ~50 degrees to the left and one looking ~50 degrees to the right). For each
set of photographs, the models assumed a neutral, emotionless facial expression. Subsequently, each
image was edited with Adobe Photoshop such that only models’ heads remained visible. In a
separate experiment, 41 participants (21 females, mean age = 24.7; SD = 9.2) rated attractiveness of
all images from the database on a visual analog scale ranging from very unattractive to very
attractive. Three attractiveness categories were calculated separately for each face gender based on
the ratings from male participants only: The less attractive (female faces mean = 3.0±0.4, male faces
mean = 3.0±0.3), attractive (female faces mean = 4.9±0.2, male faces mean = 4.2±0.2), and the most
attractive category (female faces mean = 5.8±0.5, male faces mean = 4.9±0.3). Due to the lack of high
ratings for the male faces, we matched female faces from the attractive category to male faces from
the most attractive category. Photographs of 20 females and 20 males were selected from each of
the three attractiveness categories.
A total of 240 images were used, depicting 60 females and 60 males with both direct and
averted (half to the left and half to the right) gaze. Forty unique images depicting 10 females and 10
males (3 most attractive, 4 attractive and 3 less attractive of each sex) with both direct and averted
gaze were presented in each task, and no images were repeated across tasks or sessions. The
direction of the averted gaze was counterbalanced. The order of presentation was pseudorandomized and counterbalanced.
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Each image (19.5 × 19.5 cm) was presented on a computer screen located about 70 cm in front
of the participant, with a resolution of 1680 x 1050 pixels. Models’ heads in the images subtended
about 9.8 x 13 degrees of visual angle. Luminance-matched gray baseline images with a fixation cross
were created for each of the facial stimuli.
Procedure
Participants were tested on three different days with a minimum inter-session interval of
seven days, and asked to refrain from eating an hour before test onset. The test interval (60-150 min
after drug intake) was chosen to coincide with the maximum plasma concentration of per-oral
morphine5 and naltrexone6. Each session lasted approximately three hours and the participants were
reimbursed 400-500 NOK (about USD 80) per session, depending on their performance in an
independent monetary reward task performed as part of the test battery. The experimental
procedures were approved by the Regional Ethics Committee (2011/1337/REK sør-øst D).
At the end of the last session, participants were debriefed and asked to guess the identity of
the drug received in each session. On average, participants identified the drug received correctly 34%
of the time, indicating successful blinding.
Drug administration. Morphine is a selective μ-opioid receptor agonist and the most widely
chosen analgesic for moderate to severe pain7. To minimize subjective drug effects we chose 10 mg
per oral morphine (Morfin®, Nycomed Pharma, Asker, Norway).
Naltrexone is a non-selective opioid antagonist with a high affinity to μ- and κ-opioid
receptors. It is used in the treatment of drug and alcohol addiction to block the effects of exogenous
opioids (e.g. heroine) or to reduce drug/alcohol craving. We used 50 mg per oral naltrexone
(Adepend, Orpha-Devel, Purkersdorf, Austria), a standard dosage that has been used with only minor
side-effects in several previous studies 8, 9.
Placebo pills were cherry-flavored breath mints visually matched to morphine and naltrexone
pills. A small amount of the flavored placebo pills were added to the drug dosages to avoid any
recognition of medication taste.
Time Line. After giving written consent, participants were asked to submit a urine sample for
opiate screening (MOP Opiate300 Test Strip; SureScreen Diagnostics Ltd, Derby, UK). After
completing state-relevant questionnaires (including measures of mood: happiness, anxiety,
irritability, feeling good), and if the drug toxicology was negative, participants received one of the
three drugs. In each of the three testing sessions, the ‘liking’ and ‘wanting’ tasks were run as parts of
a larger study. Task orders were pseudo-randomized and counterbalanced between participants.
Throughout each test session, participants completed the mood checklist four times: (1) before drug
administration (session baseline), (2) 60 min after ingestion, before testing began, (3) ~40 min into
testing, and (4) after completion of all tasks. To ensure the study results were not due to reduced
motor functions in either of the drug conditions, the participants completed the BRAIN test
Bradykinesia Akinesia Incoordination task, 10 at 40 minutes into the testing session.
‘Wanting’ Task. Participants were instructed to manipulate the duration of each facial image
presentation according to their own wish, by repeatedly pressing one button to make the current
trial last longer (‘keep’ press), or another button to make it end sooner (‘change’ press); the more
button presses, the more the duration could be manipulated. A visual meter with a moving stripe
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indicated how much time was left of each trial, and also worked as a visual indicator of how much
the participants were manipulating the trial duration. The total duration of the experiment was fixed
to 3.65 minutes. Trials were separated by a 2-second break, and without the participant's
manipulation the experiment was set to consist of 31 trials of 5 seconds each. On average,
participants completed 30.2 trials per each session of the task. Viewing time and the number of
‘keep’ and ‘change’ button presses for each image were recorded. MatLab software R2012a
(Mathworks, Natic, USA) was used to present the stimuli and collect participants' responses.
‘Liking’ Task. After presentation of a fixation point for 2 seconds, a facial image was presented
on the computer screen for 5 seconds. This was followed by presentation of a visual analog scale for
a maximum of 10 seconds. Participants were requested to rate how attractive each face was on a
scale ranging from very unattractive to very attractive. After the response (or when 10 seconds
elapsed), another fixation image was presented, followed by another facial image, and then by the
visual analog scale, etc. E-Prime 2.0® software (Psychology Software Tools Inc., Pittsburg, PA, USA)
was used to present the stimuli and collect subjects’ responses in the ‘liking’ task. Data from 14
participants were excluded from analysis due to a software problem (recording responses in EPrime). Subsequently, an additional group of seven healthy males were pre-screened and tested
using exactly the same experimental paradigm. Therefore, the final sample size for the ‘liking’ task
was 23.
Data analysis
Viewing times and 2.5-SD-trimmed ‘keep’ or ‘change’ button-press data from the ‘wanting’
task, and attractiveness ratings from the ‘liking’ task were analyzed with multiple regressions using a
linear multilevel/mixed models analysis, based on a maximum likelihood approach11 in SPSS. Drug
(morphine, naltrexone, or placebo), Gaze Direction (direct or averted gaze), and Facial Attractiveness
Level (most attractive, attractive, and less attractive) were included as main factors. Session Number,
Stimulus Order, OPRM1 group (AA or GA carriers), and Image Set as control variables. Planned
contrasts were run to elucidate the specific questions central to our hypotheses. Reported effect
sizes (Cohen’s d) were calculated based on the t statistic extracted from the contrast specified within
the mixed models analysis and using the following formula: d = ( t*2 ) / ( sqrt(df)), where df=N-1.
SUPPLEMENTARY RESULTS
Main effects of drug on viewing time in the ‘wanting’ task. Both morphine and naltrexone
treatment decreased the average viewing time of female faces with around 200 ms compared to
placebo (main effect of Drug, F(2,1208)=3.6, p=0.026; average viewing time: morphine M = 4.58±0.08,
placebo M = 4.79±0.08, and naltrexone M = 4.55±0.07). As reported in the main text, analysis of
button press data revealed that these opioid-related decreases were driven by different ‘wanting’
behavior, such that the expected pattern of ‘wanting’ increases with morphine and decreases with
naltrexone emerged when analysis was constricted to keep button presses for the most attractive
female faces.
Effects of gaze direction of faces on ‘liking’ and ‘wanting’. Gaze affected viewing preferences in
the ‘wanting’ task, specifically increasing motivation to view the most attractive faces with direct
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gaze (Attractiveness*Gaze Direction interaction (F (2, 1208) = 5.27, p = 0.005)). There were no
significant interactions between Gaze Direction and Drug (all Fs < 0.79). As expected, there was a
trend for the participants to rate female faces with direct gaze as more attractive than faces with
averted gaze (main effect of Gaze Direction, F (1, 1314) = 3.27, p = 0.071).
Effects of controlling for variability in the A118G SNP of OPRM1. The pattern of finding and
statistics/ effect sizes remained the same for both the liking and wanting analyses with and without
the genetic information in the model.
Effects of drug manipulations on mood. ANOVA tests were employed to evaluate the effect of
drugs for all mood types with Drug (morphine, placebo, naltrexone), Mood Type (happy, anxious,
irritated, feeling good), and Time of Mood Check (before drug administration, 60 min after ingestion,
~40 min into testing, after completion of all tasks). Neither morphine, nor naltrexone treatment
significantly affected mood (Drug main effects/interactions): Fs≤1.29, ps≥0.22).
Motor coordination test. In this this test, participants were asked to use their dominant index
finger to alternate between two keybord keys, 15 cm apart, as quicky and accurately as possible. The
dysmetria score (DS) is a weighted score of number of incorrect presses corrected for speed. The
repeated-measures ANOVA of the Dysmetria x Drug showed no significant effect of drug: F (2, 58) =
0.91, p = 0.38, p2 =0.03). This result indicates that the differences in performance on the test across
drug conditions were unlikely to result from significant decreases in motor or eye-hand coordination.
Plasma levels of drugs and their metabolites. Participants provided a blood sample at the end
of each experiment session. Analyses were performed at The Norwegian Institute of Public Health,
Division of Forensic Medicine and Drug Abuse Research, using a high-performance liquid
chromatography–tandem mass spectrometry method12 to identify plasma levels of morphine and its
two major metabolites: morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G); and
naltrexone and its major metabolite, 6-β-naltrexol (6βN). The results are presented in Supplementary
Table 1.
Supplementary Table 1.
Plasma levels of morphine, naltrexone and major metabolites ~150 min after oral drug ingestion
Mean
(ng/ML)
Morphine
M3G
M6G
Naltrexone
6βN
SD
0.155
0.032
0.009
0.157
0.016
0.041
0.010
0.003
0.038
0.009
SUPPLEMENTARY DISCUSSION
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The current study provides evidence for the opioid system involvement in mediating
motivational responses for the social stimuli. In relation to stimulus specificity, it raises a question of
whether a similar pattern of opioid system modulation would be obtained for other, non-social,
rewards. Since facial attractiveness is processed by the same opioid-driven limbic reward system as
other types of rewards13,14,15, we believe that the current findings could generalize to non-human
rewarding stimuli as well. The data from rodent studies cited in the manuscript offer support for this
assumption. Specifically, when using food stimuli, MOR agonism increases and antagonism decreases
preference specifically for the most palatable option16. MOR antagonism in humans has similarly
been shown to most strongly affect ‘liking’ and ‘wanting’ of foods high in sugar and fat17, 18. Overall,
we believe that response to all types of stimuli that are rewarding in a certain context would be
affected by manipulation of opioid neurotransmission.
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