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Psychopharmacology Unit, University of Bristol and MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College School of Medicine, London
Psychopharmacology Unit, University of Bristol
MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College School of Medicine, London
MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College School of Medicine, London
MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College School of Medicine, London
Bristol Specialist Drug Service, Blackberry Hill Hospital, Bristol
Psychopharmacology Unit, University of Bristol, UK
Correspondence: Professor David Nutt, Psychopharmacology Unit, University of Bristol, Dorothy Hodgkin Building, Whitson Street, Bristol BS1 3NY. Email: david.j.nutt{at}bristol.ac.uk
Funding detailed in Acknowledgements.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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Aims This study sought to examine changes in opioid receptor availability in early abstinence from opioid dependence.
Method Ten people with opioid dependence who had completed in-patient detoxification and 20 healthy controls underwent [11C]-diprenorphine positron emission tomography. Clinical variables were assessed with structured questionnaires. Opioid receptor binding was characterised as the volume of distribution of [11C]-diprenorphine using a template of predefined brain volumes and an exploratory voxel-by-voxel analysis.
Results Compared with controls, participants with opioid dependence had increased [11C]-diprenorphine binding in the whole brain and in 15 of the 21 a priori regions studied.
Conclusions This study suggests that opioid receptor binding is increased throughout the brain in early abstinence from dependent opioid use. These data complement the findings in cocaine and alcohol dependence.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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and 
opioid receptors, in people with opioid dependence during early
abstinence. We measured [11C]-diprenorphine binding in brain areas
implicated in dependence and its relationship to clinical variables. Our
hypothesis was that in people with opioid addiction, opioid receptor
availability would be increased in early abstinence and that this would be
related to craving. |
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METHOD |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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Twenty healthy people (18 male, 2 female; mean age 34.8 years, s.d.=8.3, range 25-48) with no history of dependence on any drug except nicotine (all current non-smokers) were recruited as controls. Controls had no history of serious psychiatric or medical disorder as determined by clinical interview. They were recruited for this and other studies to form a common pool, to avoid unnecessary duplication and radiation exposure. Therefore, only 8 of the 20 controls completed all the same questionnaires as participants with opioid dependence. The control group for this study was selected to match the age range of participants with opioid dependence.
Local research ethics committees and the UK Administration of Radioactive Substances Advisory Committee approved all procedures and experimental protocols. After full explanation of the study procedures, volunteers gave written informed consent.
Clinical measures
Subjective measures included the Adjective Checklist
(Jasinski, 1997), which
measures effects of opioid agonists (16 items) and opioid withdrawal symptoms
(21 items), and the 49-item short form of the Addiction Research Centre
Inventory (ARCI), which is scored for euphoria, dysphoria and sedation scales
(Haertzen, 1970).
Objective evidence of withdrawal (Opiate Withdrawal Scale; OWS) was measured using an adaptation of the Kolb and Himmelsbach point system as previously described (Law et al, 1997). Drug craving was assessed using two tools; the 45-item Heroin Craving Questionnaire (HCQ; Weinstein et al 1997) and the Obsessive Compulsive Drinking Scale (OCDS), adapted to measure opioid compulsive behaviour and obsessive thoughts, and allowing for mode of drug delivery (Anton et al 1996). Two experienced addiction clinicians (T.W. and M.D.) independently rated each patient for the amount of opioids used in the month and year prior to scanning, as well as lifetime use, using a structured rating scheme taking into account the combination of opioids used, length and route of use. We also looked for associations with published post-mortem data reporting regional densities of µ opioid receptors (Pfeiffer et al, 1982).
Participants also completed the Spielberger State-Trait Anxiety Inventory (SSAI, STAI; Spielberger 1983), the 36-item short form of the General Health Survey (SF-36; McHorney et al, 1994), the revised Eysenck Personality Questionnaire (EPQ-R; Eysenck & Eysenck, 1975) and the Eysenck Impulsiveness Questionnaire (IVE; Eysenck et al, 1985).
PET scans
All participants underwent [11C]-diprenorphine PET using a
CTI/Siemens (Munich, Germany) ECAT 953b brain camera in high-sensitivity
three-dimensional mode. A bolus of 370 MBq [11C]-diprenorphine was
given intravenously over 30 s. Dynamic emission data were acquired over 90
min, in 18 time frames (27 frames for 9 controls) and reconstructed into 31
contiguous horizontal image planes (Jones
et al, 1994). Radioactivity in arterial blood was assayed
continuously online in accordance with a standard protocol and discrete blood
samples were taken every 5-10 min for assay of radiolabelled metabolites in
plasma (Ranicar et al,
1991).
Image processing and statistical analysis
The dynamic PET scans were analysed to produce parametric images of ligand
volume of distribution using spectral analysis with in-house receptor
parametric mapping software implemented in Matlab (Mathworks Inc., Natick,
Massachusetts) (Gunn et al,
2002). Spectral analysis with individual metabolite corrected
plasma input function takes account of any difference in tracer delivery
between individuals or groups. The volume of distribution is the ratio of
total free and bound tissue to free plasma ligand concentration at equilibrium
and provides an index of receptor binding. We used Statistical Parametric
Mapping (SPM2, Wellcome Department of Imaging Neuroscience, Institute of
Neurology, University College London, UK) running in Matlab to transform the
volume of distribution images into a standard space as defined by the
Montréal Neurological Institute
(Evans et al, 1993)
using a weighted-mean [11C]-diprenorphine template created inhouse
from the PET scans of seven healthy volunteers.
We performed two types of analysis, first using predefined volumes of interest and then using SPM2 for an exploratory analysis. Twenty-one regions for which we had an a priori hypothesis for increased opioid receptor availability based on previous studies were selected for comparison. These areas were the orbito-frontal cortex, anterior cingulate, ventral striatum (including the nucleus accumbens), dorsal striatum (including the caudate nucleus and putamen), thalamus, amygdala and periaqueductal grey matter. All these regions have been shown to have a role in the addiction process. The anterior cingulate cortex, orbitofrontal cortex, nucleus accumbens and amygdala are key in reward and motivation during drug-using from the evaluation of stimuli to reward-based decision-making and learning. The periaqueductal grey matter is an important element of the endogenous opioid system and is involved in conditioned processes in dependent drug use. Similarly the thalamus, caudate and putamen form part of the emotional reward neurocircuitry which has an important role in motivational factors and links to motor pathways, possibly being a route for the development of locomotor sensitisation with continued drug use (Kalivas & Volkow, 2005; Nutt et al, 2006).
We used statistical parametric mapping to transfer 73 standardised volumes of interest derived from a probabilistic atlas of brain images (Hammers et al, 2003) onto individual scans by inverting the deformations used to spatially normalise the images. The volume of distribution maps were sampled using the individualised atlas for every participant to generate mean volume of distribution values for each volume of interest. These values were then compared between groups using a two-tailed non-paired t-test - unequal variances were assumed. Pearson's correlation statistics were used to assess the association of clinical variables with opioid receptor binding.
In addition, [11C]-diprenorphine volume of distribution images were analysed on a voxel-by-voxel basis using SPM2. Spatially normalised parametric images were smoothed with a 12 mm kernel at full width half maximum. Mean differences between groups were interrogated using non-paired t-tests, and correlations between clinical variables and [11C]-diprenorphine binding were explored using linear regression within the general linear model in SPM2. Proportional scaling was used to normalise global differences throughout. For regions where there existed an a priori hypothesis, results are reported as significant at a threshold of P<0.05 uncorrected. For all other areas familywise error correction was used.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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All participants with opioid dependence reported craving on the HCQ (mean score 15.7, s.d.=6.0) and modified OCDS (mean score 21.67, s.d.=10.6), and the scores were highly correlated (r=0.76, P<0.018). Craving scores were comparable with our previous study of the same stage of detoxification where craving was elicited using an imagery-based procedure (Weinstein et al, 1997).
Image analysis
Participants with opioid dependence showed a significantly higher level of
opioid receptor availability, as measured by global
[11C]-diprenorphine volume of distribution, when compared with
controls (19.3 v. 17.1, 11.4% increase, 95% CI 2.1-20.7,
P=0.019). In 15 of the 21 a priori regions studied there was
a significant increase in volume of distribution in people with opioid
dependence when compared with controls (P<0.05 uncorrected). These
were the brain-stem, right amygdala, left medial orbital cortex and bilateral
anterior cingulate, putamen, thalamus, and anterior, lateral and posterior
orbitofrontal cortex. Only the left lateral orbital area remained significant
if these areas are considered independent and the overly conservative
Bonferroni correction is applied (P=0.042, corrected). There was no
significant association between age and global [11C]-diprenorphine
volume of distribution for the whole group (n=30, r=-0.30,
P=0.105) or when the control (n=20, r=-0.31,
P=0.184) and opiod-dependent groups (n=10, r=-0.02,
P=0.962) were analysed separately.
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Regional densities of µ opioid receptors, as reported in post-mortem
tissue (Pfeiffer et al,
1982), correlated with [11C]-diprenorphine binding in
each region for the whole group (r=0.54, P=0.006), and when
control and patient groups were analysed separately (r=0.51,
P=0.010 and r=0.53, P=0.007 respectively). There
was no correlation between [11C]-diprenorphine volume of
distribution and opioid receptor (combined group r=0.05,
P=0.803) or opioid receptor regional densities (combined
group r=0.31, P=0.141). No differences were apparent between
the groups in these correlations.
An exploratory comparison of people with opioid dependence and controls
using statistical parametric mapping showed a significant increase in
[11C]-diprenorphine binding only in the right fusiform and
parahippocampal gyri (MNI coordinates x=38 mm, y=-26 mm,
z=-32 mm, cluster size 594 voxels, peak T=5.15, P=0.016
familywise error corrected). No significant correlations were found using
statistical parametric mapping between [11C]-diprenorphine volume
of distribution and any clinical variables. Using a statistical threshold of
P
0.05 uncorrected to investigate the a priori areas
confirmed the findings of the region of interest analysis.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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Opioid receptor availability in dependence
There is limited preclinical research that helps to interpret the results
of this study. Although it is clear that chronic opioid exposure leads to
reduced opioid receptor function (tolerance), the mechanisms through which
this is achieved are not certain and may include receptor internalisation or
reduced receptor-effector coupling
(Williams et al,
2001). In vitro studies have shown that chronic exposure
to an opioid agonist can lead to a downregulation in opioid receptors
(Goodman et al,
1996). However, this is not a consistent pattern in in
vivo studies, which have reported increases, decreases and no change in
opioid receptors, depending on the paradigm used
(Zadina et al, 1995).
In humans, tolerance to opioid agonists is well characterised but there are
virtually no data on brain opioid receptor imaging. We have previously
demonstrated a dose-related reduction in opioid receptor function in people
with opioid dependence who are on methadone maintenance by showing that they
are less sensitive to the effects of an opioid agonist, hydromorphone
(Melichar et al,
2003). However, in a parallel [11C]-diprenorphine PET
study, we found no difference in binding compared with a healthy control
group, suggesting limited occupancy and no significant changes in receptor
number (Melichar et al,
2005). This complements a study using [18F]-cyclofoxy
PET that also suggested that methadone requires only very low levels of opioid
receptor occupancy for efficacy (Kling
et al, 2000). Lastly, post-mortem studies of people with
heroin dependence have shown inconsistent changes (reduction or no difference)
in µ opioid receptor density compared with healthy controls
(Gabilondo et al,
1994; Ferrer-Alcon et
al, 2004). These studies suggest that chronic opioid exposure
might not alter opioid receptor availability and importantly not increase
receptor availability.
Increased [11C]-diprenorphine binding
The increase in [11C]-diprenorphine binding reflects an increase
in availability of opioid receptors to this PET tracer. Increased receptor
affinity for the tracer could account for this increased availability, but
there is no preclinical evidence that chronic opioid administration alters
affinity. Therefore, the increase in [11C]-diprenorphine binding
might be due to: (a) an increase in opioid receptors during early abstinence
from opioid drugs; (b) an increase in opioid receptor number that develops
with the chronic use of an opioid agonist; (c) a reduction in competition from
endogenous opioids. We believe that it is most likely that our findings
reflect a significant increase in opioid receptor number immediately following
detoxification from opioids. We know that withdrawal and early abstinence is a
time when the brain is under stress, and that such an increase might represent
a neuroadaptive response. This would explain the similar findings after
cocaine and alcohol dependence (Zubieta
et al, 1996; Gorelick
et al, 2005; Heinz
et al, 2005).
Increased [11C]-diprenorphine binding could also reflect increased opioid receptor availability as a result of suppression of endogenous opioid release. Preclinical evidence shows that chronic treatment with methadone does not alter the concentration or function of endogenous opioids, although later studies with other opioids and other drugs of misuse suggest that endogenous opioids play a role in craving or drug-seeking behaviour (for a review see Gerrits et al, 2003). Activation of the endogenous opioid system is associated with the regulation of emotions, physical and emotional pain (Ribeiro et al, 2005). A possibility is that the exogenous opioids used to alter emotions by people with opioid dependence might lead to suppression of the endogenous opioid system and consequently a compensatory upregulation of receptors. This would leave more receptors available for occupancy by [11C]-diprenorphine in early abstinence. We are not aware of any human studies describing the impact of chronic opioid agonist use on levels of endogenous opioids.
Opioid system after abstinence from substances
In addition to being the primary target for opioid drugs, the opioid
neurotransmitter system is important in initiating and maintaining dependence
on a variety of misused substances (Herz,
1997; Gerrits et al,
2003; Kreek et al,
2004). A number of recent neuroimaging studies in humans using the
µ-selective agonist [11C]-carfentanil have reported elevations
of tracer binding in early abstinence from cocaine and alcohol, which are
associated with craving (Zubieta et
al, 1996; Gorelick et
al, 2005; Heinz et
al, 2005). Detoxification from a short course of
buprenorphine has been shown in a preliminary study to result in a significant
increase in µ opioid [11C]-carfentanil binding in the
inferofrontal cortex and anterior cingulate regions compared with controls
(Zubieta et al,
2000). Therefore, it appears that similar increases in opioid
receptor availability are seen during early abstinence from cocaine and
alcohol, and preliminary data suggest a comparable increase in people with
opioid dependence.
The evidence to date points to elevations in opioid binding being an acute effect of early abstinence, and our results in opioid dependence complement these findings. It is not clear whether these changes persist or even become additive with progressive detoxifications. In cocaine dependence, opioid receptor binding in some but not all regions returns to control levels within 1 week (Gorelick et al, 2005). In alcohol dependence the increase appears more persistent, with no reduction evident after 5 weeks of abstinence (Heinz et al, 2005). It was not possible to scan our participants after a period of abstinence owing to high relapse rates and strict residential rehabilitation programmes, but this would be valuable in future studies.
We found significant increases in [11C]-diprenorphine binding in the majority of regions analysed using the atlas, and significant increases in fusiform/parahippocampal gyri using exploratory voxel-based statistical parametric mapping, although increases were seen throughout the brain when the threshold for significance was lowered. It is not clear why an area incorporating the fusiform/parahippocampal gyri which is involved in processing visual associations and memory was highlighted by statistical parametric mapping. We found no difference in [11C]-diprenorphine binding between people with opioid dependence and controls in several of the a priori areas, notably the periaqueductal grey matter (in the brain-stem), nucleus accumbens and caudate. The template used for the brain-stem region is not precise enough to isolate the periaqueductal grey matter within the brain-stem region of interest, which may account for the lack of association there. However, we are surprised to find no association with the nucleus accumbens and caudate in the light of previous findings of increased receptor number in these areas during withdrawal from cocaine and alcohol. In the two studies of cocaine dependence, significant increases were seen in the ventral striatum and the anterior cingulate, frontal and temporal cortices, caudate and thalamus (Zubieta et al, 1996; Gorelick et al, 2005), whereas in alcohol dependence, significant increases were restricted to the ventral striatum (Heinz et al, 2005). In people with opioid dependence the changes were much more widespread, perhaps because of the direct pharmacological effect of opioids and possible changes in the endogenous opioid system.
Opioid receptor availability and clinical variables
We found no correlation between craving and opioid receptor availability,
which is at variance with our hypothesis and previous findings in alcohol and
cocaine dependence (Zubieta et
al, 1996; Gorelick et
al, 2005; Heinz et
al, 2005). Our participants with opioid dependence
demonstrated high scores on two rating scales for craving, which were
comparable with those in a previous study
(Weinstein et al,
1997) and with individuals maintained on methadone who had
withdrawal induced by naloxone (Schuster
et al, 1995) but were higher than scores for people
maintained on methadone (Schuster et
al, 1995). Furthermore, our participants experienced levels
of and variance in craving scores that were comparable with earlier studies in
which craving was induced and resulting brain activation detected
(Daglish et al, 2001).
Craving measures vary and so comparison with other studies is hampered.
However, in our study we chose two commonly used scales with a total of seven
craving subscales, so the absence of a correlation here is robust.
In other studies reporting a relationship between craving and opioid
receptor levels, [11C]-carfentanil, a µ-selective tracer was
used (Zubieta et al,
1996,
2000;
Gorelick et al, 2005;
Heinz et al, 2005).
It may be that since [11C]-diprenorphine labels µ, and
opioid receptors, µ receptor-related changes were obscured by
alterations in the other subtypes. However we think this unlikely as the
[11C]-diprenorphine signal correlated only with the reported µ
opioid receptor density in each brain region and not with the and
opioid receptor density. Nevertheless, it would be beneficial to
repeat this study using a more selective opioid receptor tracer, such as
[11C]-carfentanil, to determine whether the increase in opioid
receptor binding demonstrated here is mainly due to increase in any particular
subtype.
Opioid receptor binding levels were not related to withdrawal symptoms as found in cocaine and alcohol dependence (Zubieta et al, 1996; Gorelick et al, 2005). This is consistent with the clinical picture where opioid withdrawal can be ameliorated by non-opioid pharmacotherapy. We did not find a correlation between age and opioid receptor levels in either the group with opioid dependence or controls. In a [11C]-carfentanil PET study of healthy controls with a wider age range, increasing age was associated with higher opioid receptor levels in the neocortex (Zubieta et al, 1999). Our more limited age range and younger average age likely contributed to the absence of such a correlation. All of our group with dependence were tobacco smokers and controls were current non-smokers, but there was no correlation between quantity of cigarettes smoked and [11C]-diprenorphine binding. Furthermore, another study of alcoholism reported no significant interaction between smoking status and µ opioid receptor availability in patients and controls (Heinz et al, 2005).
Limitations
Although this study was appropriately powered to detect the measured effect
in a PET study of this nature, it may have been underpowered to determine
associations with clinical variables, especially craving. The studies
reporting an association between craving and opioid receptor levels had
dependent groups of 10, 17 and 25 respectively
(Zubieta et al, 1996;
Gorelick et al, 2005;
Heinz et al, 2005).
However, the participants in our study were craving at similar levels and with
a wide range of craving scores, making it likely that any association should
have been apparent.
Implications
We have reported a significant widespread increase in brain opioid receptor
availability in people with opioid dependence during early abstinence from
methadone. Together with previous evidence, we argue that this reflects an
increase after cessation of methadone rather than a chronic change. If this is
the case, it could give us a crucial insight into the mechanisms that underlie
opioid craving. Although clinically we know that substitution treatment is
effective we do not know whether prolonged agonist exposure permanently alters
brain neurochemistry and whether these changes hamper recovery. Furthermore,
since such an increase in opioid receptors has also been shown in alcohol and
cocaine dependence, this argues for a fundamental role of the opioid system in
addiction, or at least in the early abstinence syndrome. The contribution of
this to clinical states and treatment outcomes has yet to be fully
characterised.
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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Received for publication September 18, 2006. Revision received February 1, 2007. Accepted for publication February 19, 2007.
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) and controls
(
).
*P<0.05 unpaired t-test.