Document Sample
Variable Powered By Docstoc
					                                                  MS # 08-08-0434

  S Bodenmann 1, S Xu 1, UFO Luhmann 2,5, M Arand 1, W Berger 2, HH Jung 3 and HP Landolt 1,4
                     Institute of Pharmacology & Toxicology, University of Zürich, Switzerland
           Division of Medical Molecular Genetics & Gene Diagnostics, Institute of Medical Genetics,
                                     University of Zürich, Switzerland
                           Department of Neurology, University Hospital Zürich, Switzerland
           Zürich Center for Integrative Human Physiology (ZIHP), University of Zürich, Switzerland
      Present address: Division of Molecular Therapy, UCL Institute of Ophthalmology, London, UK

Submitted to:                        Clinical Pharmacology and Therapeutics
                                     April 9, 2011

Keywords:                            Dopamine; prefrontal cortex; executive functioning; cognitive enhancer;
                                     electroencephalogram; sleep homeostasis

Address for correspondence:
Hans-Peter Landolt, Ph.D.
Institute of Pharmacology & Toxicology
University of Zürich
Winterthurerstrasse 190
8057 Zürich
Tel.         + 41 – 1 – 635 59 53
Fax          + 41 – 1 – 635 57 07
Bodenmann et al.

Supplementary Information

Genotyping, pre-experimental procedures and study protocol

        Genomic DNA was extracted from 3 ml fresh blood using standard procedures and stored at

4 °C. A TaqMan SNP Genotyping Assay (Applied Biosystems, Rotkreuz, Switzerland; Assay ID:

C__25746809_50) was used for the allelic discrimination of the Val158Met single nucleotide

polymorphism (SNP; NCBI SNP-ID: rs4680) of the COMT gene. The polymerase chain reaction

(PCR) for selective amplification of each allele contained 20 ng genomic DNA, 4 l TaqMan

Universal Master Mix, 0.4 l 20X SNP Genotyping Assay Mix, and 1.6 l H2O, for a total volume of

8 l. The PCR conditions for the TaqMan SNP Genotyping Assays were as follows: One

initialization step at 95 °C for 10 min, and 40 alternating cycles of denaturation at 92 °C for 15 sec,

and annealing and extension at 60 °C for 1 min. All PCRs were performed on an MJ Research

PTC-225 thermal cycler (MJ Research / Bio-Rad, Reno, NV, USA). An end point fluorescence

measurement was obtained using the Applied Biosystems PRISM® 7900HT system to examine the

samples and determine the respective genotypes with the SDS 2.2 software package (Applied

Biosystems, Rotkreuz, Switzerland). All PCRs were independently replicated for data confirmation.

        Prior to the study, the experiment was explained in detail and written informed consent was

obtained from all volunteers. Individuals with nocturnal myoclonus (> 10 per hour of sleep), sleep

apnea (apnea-hypopnea index > 10), and low sleep efficiency (< 80 %) as confirmed by

polysomnography in the sleep laboratory were excluded. Twenty-two young men (age range: 20-

29 years) were selected based on their Val158Met genotype of COMT, and paid for participation in

the study. Ten individuals were homozygous Val/Val allele carriers, and 12 individuals were

homozygous Met/Met allele carriers. All subjects were non-smokers, reported good sleep quality, had

no history of neurological or psychiatric disease, and denied intake of medications or illicit drugs

during the 2 months before the study. The two groups were carefully matched for age, body-mass-

index, habitual alcohol and caffeine consumption, anxiety (Trait Anxiety Inventory (1)), subjective

Bodenmann et al.

daytime sleepiness (Epworth Sleepiness Scale (2)), and chronotype (Horne-Östberg Morningness-

Eveningness Questionnaire (3) and Munich ChronoType Questionnaire (4)).

        During the 2 weeks prior to the study, participants were asked to abstain from all sources of

caffeine, to wear a wrist activity monitor on the non-dominant arm, and to keep a sleep and caffeine

diary. They were also requested to abstain from ethanol, and to maintain regular 8-hour sleep/16-hour

wake-cycles for 3 days before and during the experiment. Bedtimes were scheduled from 24:00 to

08:00 h. Participants were not allowed to deviate from these times by more than 1 hour. Compliance

with these instructions was verified by inspection of the wrist-activity plots and sleep diaries at the

beginning of each experimental block.

        All subjects completed 2 experimental blocks consisting of 4 consecutive nights and 2 days

separated by one week. The first and second night of each block served as 8-hour adaptation and

baseline nights, respectively. Upon arrival in the sleep laboratory, saliva samples for caffeine

determination were taken, and the breath ethanol concentration was measured. After rising from the

baseline night (at 08:00 h), volunteers stayed awake for 40 hours until bedtime of a 10-hour recovery

night (at 24:00 h). To ensure wakefulness, the subjects remained under continuous supervision of

members of the research team. They were allowed to read, study, play games, watch films and

occasionally take a walk outside the laboratory.

Melatonin profile in saliva

        Saliva samples for determination of the melatonin concentration were collected at 3-hour

intervals starting at 20:00 h on day 1 of sleep deprivation. The saliva samples were stored at -80 °C.

The samples were centrifuged for 10 min at 4‟000 x g and the supernatant was collected for the

analyses. A direct double-antibody radioimmunoassay for melatonin validated by gas chromato-

graphy-mass spectroscopy was used (5) (Bühlmann Laboratories, Schönenbuch, Switzerland). The

minimum detectable dose of melatonin was 0.2 pg/ml (analytical sensitivity). The area under the

Bodenmann et al.

curve (AUC) was estimated using the trapezoidal method, and the phase of the melatonin rhythm was

defined as the time of the midpoint between the upward and downward mean crossing (6).

        Statistical analyses showed no significant effects of factors „genotype‟, „treatment‟ or

„genotype‟ x „treatment‟ interaction on melatonin concentration in saliva (Fig. S1). No significant

differences between the two groups were found for AUC, mean melatonin concentration and

melatonin peak concentration. The Val/Val allele carriers (n = 10) tended to have an earlier melatonin

phase than the Met/Met allele carriers (n = 12; 04:18 ± 13 min vs. 05:38 ± 36 min; mean ± SEM) (p <

0.06, two-tailed, paired t-test).

Quantification of modafinil in saliva

        A pilot study showed that 2 hours after 100 mg oral modafinil the plasma:saliva ratio of

modafinil is approximately 2.9  0.2 (SEM, n = 5). Previous studies used (phenyl-thio-)acetic acid as

internal standard for quantification of modafinil in plasma and urine (7). Our pre-experimental

analyses, however, showed that this substance is not appropriate as internal standard for the

determination of modafinil from saliva because the recovery rate for the compound was highly

variable under the applied conditions. Therefore, di-hydro-carbamazepine (DHC), for which the

recovery rate was very stable, was used as internal standard.

        Modafinil extraction: 100 l of the thawed and homogenized samples were mixed with 300

l H2O and 400 l extraction buffer (9.37 mol/l DHC in ethyl acetate/formic acid 100:1). After

vigorous vortexing and centrifugation for 10 min at 13‟000 rpm, 200 l of the upper, organic phase

was collected and evaporated to dryness in a Speedvac concentrator. The residues were re-

suspended in 100 l methanol and allowed to dissolve for 15 min at room temperature. Thereafter,

200 l H2O was added and the mixture was centrifuged at 13‟000 rpm for 10 min. 160 l of the

supernatant were filtered using regenerated cellulose membrane filters (diameter, 4 mm; pore size,

0.45 m; Infochroma AG, Zug, Switzerland) and used for the analyses.

Bodenmann et al.

        Liquid chromatography – mass spectrometry (LC-MS): For liquid chromoatography (LC) an

Agilent 1100 system composed of a G1312A LC binary pump, a G1329A thermo autosampler, and a

G1316A column oven, equipped with a ZORBAX eclipse 5 m XDB-C18 reverse phase column, 4.6

x 150 mm with a corresponding opti-gard pre-column, was used. The mobile phase consisted of (A)

H2O containing 0.1 % formic acid and (B) acetonitrile containing 0.1 % formic acid. The flow rate

was 200 l/min and the injection volume was 10 l. Starting conditions of 40 % B were maintained

for 2 min. After that, a linear gradient from 40-85 % B within 10 min, followed by 85 % B isocratic

conditions for 3 min, were applied. Finally the column was re-equilibrated for 2 min with 40 % B.

The column was coupled to a 4000 Q TRAPTM mass spectrometer (Applied Biosystems, Rotkreuz,

Switzerland) with a TurboIonSpray® probe. Turbospray parameters were: IS 5500V, with N2 as

curtain gas (CUR = 10), nebulizer gas (GS1 = 40), heater gas (GS2 = 50) and collision gas (CAD =

5). The compound specific parameters for modafinil and DHC were obtained by infusion of standards

using the quantitative optimization function of Analyst software 1.4.2. Analytes were recorded by

multiple reaction monitoring in the positive ion mode (+MRM). Two mass transitions were used per

analyte in order to guarantee unambiguous identification, with the more sensitive transitions being

the quantifiers and the less sensitive transitions being the qualifiers. The used transitions, collision

energies, collision exit potential energies, entrance potential energies and declustering potential

energies are specified in supplementary Table S1.

        Assay validation of salivary modafinil analysis: The area under the curve (AUC) was

determined using Analyst software 1.4.2. For the quantification of modafinil, the AUC of transition

274→167 and for DHC, the AUC of transition 239→194.2 was used. The background noise was

assessed by analyzing 66 blank saliva samples collected immediately before the oral application of

modafinil and in the placebo condition. A standard curve was generated using drug-free saliva

samples with DHC as internal standard (correlation coefficient R2 = 0.996). For modafinil, the limit

of detection was 0.7 ng/ml and the limit of quantification was 2.4 ng/ml, corresponding to a signal-to-

noise ratio of 3 and 10, respectively.

Bodenmann et al.

Table S1. MS/MS-transition, collision energy (CE), collision exit potential (CXP), entrance potential

(EP) and declustering potential (DP)

Compound           Transition (m/z)      CE (V)        CXP (V)          EP (V)        DP (V)
Modafinil            274  167             13            12             10             21
                     274  152             51            10             10             21
DHC                  239  194.2           31            14             10             21
                     239  91.1            53              6            10             21

DHC: Di-hydro-carbamazepine.

Random number generation task (RNG)

        Performance on the random number generation (RNG) task relies on the subjects‟ ability to

suppress stereotyped responses such as counting and to keep track of recent responses (8). These

cognitive functions have been referred to as the executive functions “inhibition” and “updating”. The

subjects were instructed to orally generate at each of two paces two random sequences of 225

numbers using the response alternatives 0, 1, 2, 3, 4, 5, 6, 7, 8, 9. The pace was set by a tone

generated by a computer. The slow pace required the subjects to generate one number each 1800 ms,

the fast pace one number each 750 ms. The slow portion of the task always preceded the fast portion.

The entire task lasted for approximately 10 min. Responses were recorded on a dictation machine and

transcribed after completion of the study. Here we report the outcome variable, redundancy, a

measure of zero-order response stereotypy quantifying the extent to which some response alternatives

occurred more frequently than others (for further details, see (9, 10)). Redundancy on the RNG is

thought to provide a sensitive index of the subjects‟ ability to update and monitor information (8).

Psychomotor vigilance task (PVT)

Bodenmann et al.

        The psychomotor vigilance task (PVT) is a simple visual reaction time task, which has no

learning curve and is virtually independent of aptitude (11). It is one of the most often used measures

of sustained vigilant attention in human sleep and chronobiology research. The task was implemented

on a PC using the software e-Prime (Psychology Software Tools Inc., Pittsburgh, PA, USA). All

subjects were instructed to press a button on a response box as quickly as possible, in order to stop a

digital millisecond counter appearing in the middle of the computer screen. The counter started to

scroll at variable intervals (inter-stimulus intervals: 2-10 sec). A total of 100 stimuli was presented

during roughly 10 minutes. The task requires continuous attention to detect the randomly occurring

stimuli. During 20 min before each PVT session, all participants stayed in the nonsocial environment

of their bedroom and were engaged in filling-in questionnaires and the recording of the waking

electroencephalogram. Here we report the PVT outcome variables, lapses (reaction times [RT] > 500

ms, transformed by x       x  1 ), slowest 10th percentile of RT (expressed as speed, 1/RT), and the

90th – 10th inter-percentile range of speed. All RT < 100 ms („errors of commission‟) were excluded

from analyses..

Two-back task

        The n-back task is one of the most popular experimental paradigms to investigate working

memory functions. Performance on an intermediate level of task difficulty (2-back) was recently

shown to be enhanced by 200 mg modafinil after over-night sleep deprivation (12). A verbal 2-back

task was administered at 14:45 h on day 1 and day 2 of prolonged wakefulness. Single consonants

with varying letter case were presented in random order on a computer screen. Participants had to

compare each current letter with each consonant presented two trials back (e.g., G-c-g), and as

quickly and accurately as possible press “J” on a response box for same letters, and press “N” for

different letters. The task consisted of 24 targets and 56 non-targets, preceded by a practice block

including 3 targets and 7 non-targets. Completion of the task took roughly 10 min. The task was

Bodenmann et al.

programmed in e-Prime (Psychology Software Tools Inc., Pittsburgh, PA, USA). All subjects

completed a training session prior to each baseline night.

        Only correct responses were included in the calculation of mean reaction time (RT). Outliers

(4 x median deviation) and RT  50 ms were excluded. The statistical analyses were performed with

1/RT (speed) values. Accuracy was expressed as the percentage of incorrect responses.


(1)   Spielberger, C.D., Gorsuch, R.L. & Lushene, R.E. Manual for the state-trait anxiety inventory.

      (Consulting Psychologists Press, Palo Alto, Calif., 1970).

(2)   Johns, M.W. A new method for measuring daytime sleepiness - the epworth sleepiness scale.

      Sleep 14, 540-545 (1991).

(3)   Horne, J.A. & Östberg, O. A self-assessment questionnaire to determine morningness-

      eveningness in human circadian rhythms. Internat. J. Chronobiol. 4, 97-110 (1976).

(4)   Roenneberg, T., Wirz-Justice, A. & Merrow, M. Life between clocks: Daily temporal patterns

      of human chronotypes. J. Biol. Rhythms 18, 80-90 (2003).

(5)   Weber, J.M., Unger, I., Wirz-Justice, A. & Schwander, J.C. Sensitive monitoring of alterations

      in circadian rhythms by supersensitive melatonin immunoassays. J. Sleep Res. 7, 302 (1998).

(6)   Viola, A.U. et al. Per3 polymorphism predicts sleep structure and waking performance. Curr.

      Biol. 17, 613-618 (2007).

(7)   Schwertner, H.A. & Kong, S.B. Determination of modafinil in plasma and urine by reversed

      phase high-performance liquid-chromatography. J. Pharm. Biomed. Anal. 37, 475-479 (2005).

(8)   Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A. & Wager, T.D. The

      unity and diversity of executive functions and their contributions to complex "Frontal lobe"

      Tasks: A latent variable analysis. Cogn. Psychology 41, 49-100 (2000).

Bodenmann et al.

(9)   Towse, J.N. & Neil, D. Analyzing human random generation behavior: A review of methods

      used and a computer program for describing performance. Behav. Res. Methods Instrum.

      Comput. 30, 583-591 (1998).

(10) Gottselig, J.M., Adam, M., Rétey, J.V., Khatami, R., Achermann, P. & Landolt, H.P. Random

      number generation during sleep deprivation: Effects of caffeine on response maintenance and

      stereotypy. J. Sleep Res. 15, 31-40 (2006).

(11) Durmer, J.S. & Dinges, D.F. Neurocognitive consequences of sleep deprivation. Semin.

      Neurol. 25, 117-129 (2005).

(12) Thomas, R.J. & Kwong, K. Modafinil activates cortical and subcortical sites in the sleep-

      deprived state. Sleep 29, 1471-1481 (2006).