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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Alcohol Clin Exp Res. Author manuscript; available in PMC Dec 1, 2012.
Published in final edited form as:
PMCID: PMC3183368
NIHMSID: NIHMS294761
PET imaging of mu- and delta-opioid receptor binding in alcohol dependent and healthy control subjects
Elise M. Weerts, Ph.D.,1 Gary S. Wand, M.D.,1,2 Hiroto Kuwabara, M.D.,4 Cynthia A. Munro, Ph.D.,1 Robert F. Dannals, Ph.D.,4 John Hilton, Ph.D.,4 J. James Frost, M.D., Ph.D,3,4 and Mary E. McCaul, Ph.D.1,2
1 Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
2 Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
3 Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
4 Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
Address correspondence concerning this manuscript to: Elise Weerts, Ph.D., Johns Hopkins Bayview, BBRC, 5510 Nathan Shock Dr., Suite 3000, Baltimore, MD 21224, eweerts/at/jhmi.edu
Background
The endogenous opioid system plays a significant role in alcohol dependence. The goal of the current study was to investigate regional brain mu opioid receptor (MOR) and delta opioid receptor (DOR) availability in recently abstinent alcohol-dependent and age-matched healthy control men and women with Positron Emission Tomography (PET) imaging.
Methods
Alcohol dependent subjects completed an inpatient protocol, which included medically supervised withdrawal and PET imaging on day 5 of abstinence. Control subjects completed PET imaging following an overnight stay. PET scans with the MOR selective ligand [11C]carfentanil (CFN) were completed in 25 alcohol dependent and 30 control subjects. Most of these same subjects (20 alcohol dependent and 18 controls) also completed PET scans with the DOR selective ligand [11C]methyl-naltrindole (MeNTL).
Results
Volume of interest and statistical parametric mapping analyses indicated that alcohol dependent subjects had significantly higher [11C]CFN binding potential (BPND) than healthy controls in multiple brain regions including the ventral striatum when adjusting for age, gender and smoking status. There was an inverse relationship between [11C]CFN BPND and craving in several brain regions in alcohol dependent subjects. Groups did not differ in [11C]MeNTL BPND; however, [11C]MeNTL BPND in caudate was positively correlated with recent alcohol drinking in alcohol dependent subjects.
Conclusions
Our observation of higher [11C]CFN BPND in alcohol dependent subjects can result from up regulation of MOR and/or reduction in endogenous opioid peptides following long-term alcohol consumption, dependence and/or withdrawal. Alternatively, the higher [11C]CFN BPND in alcohol dependent subjects may be an etiological difference that predisposed these individuals to alcohol dependence or may have developed as a result of increased exposure to childhood adversity, stress and other environmental factors known to increase MOR. Although the direction of group differences in [11C]MeNTL BPND was similar in many brain regions, differences did not achieve statistical significance, perhaps as a result of our limited sample size. Additional research is needed to further clarify these relationships. The finding that alcohol dependent subjects had higher [11C]CFN BPND is consistent with a prominent role of the MOR in alcohol dependence.
Keywords: Alcoholism, abstinence, brain imaging, carfentanil, naltrindole
It is generally accepted that the mesocorticolimbic system mediates the rewarding effects of most drugs of abuse including alcohol (Herz, 1998). Within this key region of the brain, the reinforcing effects of alcohol are modulated in part by an increase in the neurotransmission of opioid peptides and dopamine (for review see Oswald and Wand, 2004). The endogenous opioid peptides (β-endorphin, enkephalins, and dynorphins) bind to different subtypes of OR. Specifically, β-endorphin binds with equal affinity to mu opioid receptor (MOR) and delta opioid receptor (DOR) subtypes. Enkephalins also bind to MOR and DOR subtypes, but show a 20-fold greater affinity for DOR subtypes. β-endorphin and enkephalin opioid peptides increase DA neurotransmission within the nucleus accumbens via interactions with the MOR and DOR (Koob et al., 1998).
There is strong evidence supporting an association between the endogenous opioid system and alcohol drinking and reward in humans and laboratory animals (Gianoulakis, 2004). In laboratory animals, OR antagonists decrease alcohol consumption (Franck et al., 1998; Froehlich, 1995; Froehlich et al., 1991; June et al., 1999; Krishnan-Sarin et al., 1995a; Krishnan-Sarin et al., 1995b; Krishnan-Sarin et al., 1998), and block alcohol-induced activation of the dopamine system (Benjamin et al., 1993; Job et al., 2007). . MOR knockout mice self-administer alcohol at lower levels when compared to wild type controls (Becker et al., 2002; Hall et al., 2001; Roberts et al., 2000). In two related human laboratory studies (McCaul et al., 2000; McCaul et al., 2001), naltrexone significantly attenuated alcohol-induced increases in liking and best effects, heart rate and diastolic blood pressure, and neuroendocrine responses. These findings have been replicated (Peterson et al., 2006) Taken together, the above studies highlight the importance of the opioid system in the reward pathway for alcohol, and provided support for the use of OR antagonists for use in the treatment of alcohol dependence. Indeed, meta-analyses of randomized clinical trials have demonstrated that the OR antagonist naltrexone has an overall small to moderate effect size in reducing drinking and relapse in alcohol dependent subjects (Anton and Swift, 2003; Srisurapanont and Jarusuraisin, 2005).
Given the evidence for a functional involvement of the endorphin and enkephalin systems in alcohol drinking and dependence, it is highly likely that the opioid system is altered in human alcoholics. Positron emission tomography (PET) is the only technique available for examining brain receptor characteristics in living human subjects. Three PET imaging studies available to date showed conflicting results on OR in alcohol dependent men. In the first study, (Bencherif et al., 2004), MOR were lower in the right dorsal lateral prefrontal cortex, the right anterior frontal cortex, and right parietal cortex in eight recently detoxified alcohol-dependent men when compared with eight normal healthy men. The second study (Heinz et al., 2005) found an increase in MOR in the ventral striatum in twenty-five recently abstinent (1–3 weeks) alcohol-dependent men when compared to ten healthy control men. A third PET study (Williams et al., 2009) examined OR in eleven alcohol dependent and thirteen healthy control men using the non-selective opioid receptor ligand [11C]diprenorphine, which binds to all three OR subtypes. Subjects were scanned while undergoing an outpatient detoxification with chlordiazepoxide after 2–4 weeks of self-reported alcohol abstinence. In this study, global and regional [11C]diprenorphine volumes of distribution were higher in alcohol dependent patients when compared with controls, although this effect was not statistically significant.
The current study therefore assessed binding characteristics of MOR and DOR with PET using [11C]-carfentanil (CAR), a MOR ligand, and [11C]-methylnaltrindole (MeNTL), a DOR ligand, in recently abstinent alcohol dependent and age-matched healthy control subjects. Alcohol dependent subjects were admitted to the clinical research unit (CRU), completed medically supervised withdrawal, and completed PET scans on day 5, after withdrawal symptoms had subsided. Control subjects completed PET scans after an overnight stay on the GCRC. Two types of analyses were utilized, volumes of interest (VOI) and statistical parametric mapping analysis.
Subjects
Current heavy, alcohol dependent drinkers and healthy control subjects between 21 and 60 years of age were recruited via advertisement and provided informed consent, in the sober state, using an Institutional Review Board approved informed consent document. Subjects were interviewed by a Masters level research assistant who utilized a battery of standardized diagnostic and psychological instruments. For inclusion in the study, alcohol dependent subjects met DSM-IV criteria for alcohol dependence based on the Semi-Structured Assessment of the Genetics of Alcoholism (Bucholz et al., 1994) and were actively drinking at NIAAA defined hazardous levels as determined by completion of a 90-day Time Line Follow Back (Sobell and Sobell, 1992). Healthy control subjects did not drink above the NIAAA recommended guidelines (less than 8 drinks/week for women and less than 15 drinks/week for men) and had never meet DSM-IV criteria for either alcohol abuse or dependence. Healthy control subjects were age-matched with alcohol dependent participants. Alcohol dependent and healthy control subjects were excluded from study participation based any on the following criteria: 1) if they met current or lifetime DSM-IV diagnostic criteria for any other Axis I disorder, including other drug abuse/dependence (except nicotine), 2) if urine drug toxicology was positive at screening or hospital admission, 3) if they had other ongoing health problems or 4) if their mother drank during pregnancy, subject was excluded from further study participation. Alcohol dependent subjects were excluded if they reported alcohol-related seizures or the need for medication during previous detoxifications. Using these inclusion and exclusion criteria, a total of twenty-five alcohol dependent subjects and thirty healthy control subjects completed the protocol. Basic demographic characteristics for alcohol dependent and healthy control subjects are shown in Table 1.
Table 1
Table 1
Demographics for alcohol dependent (AD) and healthy control (HC) subjects. Data shown are group means (SD) or number (n) of subjects as indicated.
The Alcohol Dependence Scale (ADS) (Skinner and Allen, 1982) was administered to characterize alcohol use and associated problems. The Fagerstrom Nicotine Dependence Test (FNDT) was administered to determine nicotine dependence status in individuals who smoked cigarettes. Scores for each of these assessments are shown in Table 1. The Family History Assessment Module (FHAM) (Rice et al., 1995) was completed to determine the number of first and second degree relatives with symptoms of alcohol and drug abuse or dependence. Subjects were classified as family history positive (FHP) if at least 3 diagnostic criteria for alcohol dependence were met by either parent (father or mother) or three or more other first or second degree relatives. If mother drank during pregnancy, subject was excluded from further study participation. Subjects were classified as family history negative (FHN) if they reported 1) no first degree relative who met alcohol dependence criteria and 2) no or one second degree relative who met alcohol dependence criteria. Subjects were designated as family history undetermined (FHU) who did not meet criteria for FHP or FHN, had multiple relatives with drug problems but no alcohol problems, or could not provide sufficient information on alcoholism status of relatives.
Inpatient Procedures following admission to Clinical Research Unit
Healthy control subjects completed PET imaging following an overnight stay in the hospital or under an inpatient protocol. Alcohol dependent subjects completed the study under an inpatient protocol that included hospital admission and medically supervised alcohol withdrawal prior to PET imaging on day 5 of supervised abstinence. Alcohol dependent subjects remained on the clinical research unit for subsequent naltrexone treatment (50 mg per day) and PET imaging to determine naltrexone blockade of mu and delta receptors. The methodology and results for [11C]CFN BPND in the context of naltrexone treatment in 21 of the 25 alcohol dependent subjects was reported in a separate paper (Weerts et al., 2008). The analysis of the basal scan data in the control subjects and comparison with basal scan data in the alcohol dependent subjects is unique to the current manuscript.
Following admission to the GCRC and regularly throughout their hospital stay, subjects completed a second battery of psychological assessments, which included a visual analog scale of alcohol craving, Penn Craving Scale (Flannery et al., 1999), the Obsessive Compulsive Drinking Scale (OCDS) (Anton et al., 1996), Beck Depression Inventory (BDI–II) (Beck et al., 1996), the Beck Anxiety Inventory (BAI) (Beck et al., 1988) and the Brief Symptom Inventory (BSI) (Derogatis and Melisaratos, 1983).
To monitor the severity of withdrawal symptoms, CRU nursing staff completed the Clinical Institute Withdrawal Assessment-Alcohol Revised (CIWA-Ar) (Sullivan et al., 1989) with alcohol dependent participants 3 times each day for the first 5 days. CIWA-Ar items were scored to reflect the time period since the last measurement. No subject required withdrawal medication based on CIWA scores, vital signs and physician assessment.
During hospitalization and all study procedures, cigarette smoking was prohibited. Smokers who were nicotine dependent as determined by a FNDT score of 3 or higher, received a new transdermal nicotine patch (21 mg nicotine) at the time of hospital admission, in the morning of each day while on the CRU and three hours prior to the PET scan. This standardized approach was used to limit the possible impact of nicotine withdrawal on the day of the scan. All subjects received a calorie-controlled breakfast 3 hours before the first scan. Before PET procedures and randomly during the hospital stay, urine toxicology screens and breath alcohol tests were conducted in all subjects to verify abstinence from alcohol and drugs.
PET procedures
Subjects underwent two PET scans in a fixed order on the same day; the [11C]MeNTL, a specific DOR antagonist (Lever et al., 1992; Madar et al., 1996), and [11C]CFN, a specific MOR agonist (Frost et al., 1985; Titeler et al., 1989), scans were conducted at 8:30 and 10:45 am, respectively. A total of 25 alcohol dependent subjects and 24 healthy control subjects completed [11C]CFN scans concurrently between 7/2001 through 7/2008. Among these subjects who completed the [11C]CFN scan, 20 alcohol dependent and 18 healthy controls completed the [11C]MeNTL scan. Specifically, [11C]MeNTL scans were lost due to problems with the arterial line and blood sampling (N=4 healthy control subjects and N=3 alcohol dependent) and failure of radioligand synthesis (N=2 alcohol dependent and N=2 healthy control subjects). Six additional healthy controls who were smokers without alcohol problems were recruited specifically to control for possible effects of smoking on [11C]CFN BPND and completed [11C]CFN scans between 4/2009 and 2/2010; these subjects also did not complete the [11C]MeNTL scans. The decrease in subjects that completed the [11C]MeNTL did not alter the demographic distributions shown in Table 1. Alcohol dependent subjects were about 44 years old, mostly male (n=15) and Caucasian (n=12), with 55% (n=11) reporting a positive family history of alcoholism. Healthy controls were also about 44 years old, mostly male (n=11) and Caucasians (n=10), with 28% (n=5) reporting a positive family history of alcoholism.
PET scans were acquired in 3D mode on a GE Advance PET scanner (GE Medical Systems, Milwaukee, WI). A thermoplastic mask was individually fitted to each subject’s face for immobilization and positioning during imaging. A transmission scan of 10-min duration was obtained using rotating germanium-68 rods before injection of the radiotracer. After intravenous bolus administration of the radiotracer, a set of 25 images with variable time period (6 × 30 sec, 5 × 60 sec, 5 × 120 sec, 9 × 480 sec) was acquired during a 90-min period for each study. Table 2 shows the injected dose, specific activity, and mass for alcohol dependent and control subjects. During [11C]MeNTL scans, small amounts of arterial blood samples were collected every 5 seconds initially, and then increasing intervals throughout out the scan (e.g.,1-min, 2-min, 5-min, 10-min and 15-min) and counted for the radioactivity. Selected samples were analyzed with HPLC for metabolites (Hilton et al., 2000). PET images were reconstructed using the back projection algorithm with a ramp filter using the software provided by the manufacturer correcting for attenuation, scatter, and dead-time (Kinahan and Rogers, 1989). The radioactivity was corrected for physical decay to the injection time. Each PET frame consisted of a 128 × 128 × 35 matrix with voxel size of 2 × 2 × 4.25 mm in a spatial resolution of 5.5 and 6.1 mm full-width-at-half-maximum (FWHM) in the radical and tangential directions, respectively at 10 cm radius from the center of the field-of-view (Lewellen et al., 1996).
Table 2
Table 2
Mean and standard deviation (SD) of drug, injected specific activity, body weights (BW) and mass of a. [11C]CFN and b. [11C]MeNTL in alcohol dependent (AD) and healthy control (HC) groups.
About 1 week before CRU admission, subjects underwent magnetic resonance imaging (MRI) to allow anatomical localization and alignment of PET imaging planes within subjects (Meltzer et al., 1990).
Volumes of Interest (VOI) Analyses
VOIs were limited in this study to the ventral striatum, cingulate cortex, caudate nucleus, putamen, insula, globus pallidus, thalamus and amygdala. The VOIs were manually defined on SPGR MRI for putamen, caudate nucleus, and thalamus using a locally developed VOI defining tool. The ventral striatum was defined as described previously (Baumann et al., 1999; Martinez et al., 2003; Oswald et al., 2005). For the remaining VOIs, a standard VOI template [(Hammers et al., 2003; Mazziotta et al., 1995) available at http://www.loni.ucla.edu] was spatially transferred to individual subjects’ MRI using the MRI-to-MRI spatial normalization parameters obtained with the SPM spatial normalization module (Friston et al., 2003; available at http://www.fil.ion.ucl.ac.uk/spm), and edited to suit outlines of the structures given by the MRI. Those VOIs were transferred to PET space according to the MRI-to-PET co-registration parameters obtained with the SPM2 coregistation module and applied to individual PET frames to obtain time-radioactivity curves (TACs) of VOIs.
Pharmacokinetic modelling
The primary outcome variable of interest for MOR and DOR was binding potential (BPND) (Innis et al., 2007) of [11C]CFN and [11C]MeNTL, respectively. For [11C]CFN the reference tissue graphical analysis (RTGA) (Logan et al., 1996) was used, with occipital lobe as the reference region and setting the brain-to-blood clearance rate constant of the reference region (k2R) at 0.104 min−1 (Endres et al., 2003; Frost et al., 1990). Estimates of BPND using RTGA have been shown to be highly correlated with those obtained from the arterial input-based kinetic model (Endres et al., 2003). The analyses for [11C]MeNTL differed from that used for [11C]CFN. First we analyzed data using a two-tissue compartmental model (TTCM). It was determined that, although TTCM fit the data well, there were occasional outliers (<10% of regions). We then examined data using the plasma reference graphical analysis (PRGA) (Logan et al., 1990) to obtain distribution volume (VT); [11C]MeNTL BPND was obtained as target-reference VT ratio less 1. Regional [11C]MeNTL BPND values of PRGA correlated with those of TTCM (TTCM = 0.94·PRGA + 0.15; R2 = 0.601) without yielding apparent outliers. For this reason, PRGA was selected for [11C]MeNTL. Reference Logan plots for [11C]CFN approached linear starting 10 min after the injection, as described previously (Zubieta et al., 2001). Plasma Logan plots for [11C]MeNTL approached linear in all regions examined by 20 min in all subjects. t* was set at 20 min for both ligands.
VOI Statistical Analyses
All statistical analyses were carried out using SAS version 9.2. Possible differences in regional binding of [11C]CFN and [11C]MeNTL between groups (alcohol dependent and healthy control subjects) were determined by using independent analyses of covariance (ANCOVAs) for each of the eight brain volumes. We included both age and gender as covariates in the model because both have been shown to influence [11C]CFN BPND (Zubieta et al., 1999). Smoking status was added as covariate in a secondary analysis, based on findings as indicated in the results. Independent ANCOVAs for each brain volume were performed over a model including the volumes of interest as an independent variable because of non-homogenous variance between volumes of interest. The adaptive step-down Bonferroni adjustment (Hochberg and Benjamini, 1990), which is based on the Bonferroni-Holm (Holm, 1979) approach, was applied to correct for multiple comparisons. The unadjusted p values and the adjusted p values (shown as Q) are reported. Third, the association of regional binding of [11C]CFN and [11C]MeNTL with family history of alcoholism, psychological problems (BDI, BAI, BSI scores), craving (OCDS, VAS and Penn Craving scale scores), recent drinking from the TLFB (drinks per episode, episodes per week, total drinks) and alcohol withdrawal severity (CIWA scores) were each analyzed as independent ANCOVAs. The adaptive step-down Bonferroni adjustment (Hochberg and Benjamini, 1990) was applied to correct for multiple comparisons (i.e., all 8 VOIs) and the adjusted p values (shown as Q) are reported.
Statistical Parametric Mapping (SPM) analyses
SPM analyses was conducted to corroborate VOI findings and determine if the regional increases in [11C]CFN BPND in alcohol dependent subjects were more generalized and extended to other regions not examined in our VOI analysis. Functional volumes (voxel-by-voxel maps) of BPND were spatially normalized to a standard brain using MRI-to-MRI spatial normalization, and PET-to-MRI co-registration parameters using SPM5 modules and smoothed with a Gaussian filter of 12 mm full-width at half maximum (FWHM). Parametric statistical models are assumed at each voxel, using the General Linear Model (GLM). Additional analysis was conducted controlling for current smoking status as a nuisance variable. To reduce chances of false positives, the search volume was limited to gray matter voxels to eliminate white matter clusters. Voxel-wise statistical tests were performed to examine the differences in BPND between alcohol dependent and healthy control subjects. A significance level of p<0.05, family wise error (FWE) corrected was employed for the group difference (t > 4.6).
VOI Analysis of Covariance of Alcohol Dependent vs. Healthy Control Subjects
When controlling for age and gender, alcohol dependent subjects had higher [11C]CFN BPND than healthy control subjects across all VOIs. This effect was highly significant across regions [amygdala (p and Q = 0.004), cingulate (p and Q =0.002), insula, ventral striatum, caudate, globus pallidus, putamen and thalamus (all p and Q <0.001)]. In contrast, [11C]MeNTL BPND did not differ between alcohol dependent and healthy controls subjects in any region. The mean (±SD) distribution volume of cerebellum (VND) was not different between alcohol dependent subjects (7.75 ±1.57 ml/ml) and healthy control subjects (8.0 ±1.53 ml/ml) (t = 0.47; df = 36; p=0.638).
ANCOVA also confirmed an overall effect for gender on [11C]CFN BPND. When compared to males, females had lower mean [11C]CFN BPND in cingulate (0.74 ± 0.02 vs. 0.65 ± 0.3, p and Q =0.01) and ventral striatum (1.76 ±0.06 vs.1.47 + 0.08, p and Q =0.005). Females also had a trend towards higher in [11C]MeNTL BPND in amygdala than males (0.91 ±0.08 vs. 0.64 ± 0.06, p =0.009, Q =0.07).
Adding smoking as a covariate did not change the increases in [11C]CFN BPND in alcohol dependent when compared to healthy control subjects. Alcohol dependent subjects had significantly higher [11C]CFN BPND when compared to healthy control subjects in amygdala (p and Q = 0.002), cingulate, insula, ventral striatum, caudate, globus pallidus, putamen and thalamus (all p and Q <0.001). Figure 1 shows mean [11C]CFN BPND adjusted for age, gender and smoking status. As shown in Figure 1, the mean difference in [11C]CFN BPND between groups was greatest in the globus pallidus and ventral striatum. The greater [11C]CFN BPND in alcohol dependent compared to healthy control subjects can be seen clearly in the averaged [11C]CFN BPND images shown at the level of ventral striatum in Figure 2. As shown in Figure 3, although the direction of effects in several brain regions was similar to that observed for [11C]CFN BPND, mean [11C]MeNTL BPND was not significantly different in alcohol dependent and healthy control subjects when adjusted for age, gender and smoking status. When adjusting for age, gender and group (alcohol dependent vs. control) [11C]CFN BPND did not differ between smokers (n=29) and nonsmokers (n=26) except that smokers had lower [11C]CFN BPND in the globus pallidus (Table 3a). When adjusting for age and gender, [11C]MeNTL BPND did not differ between smokers (n=18) and nonsmokers (n=20) in any of the VOI (Table 3b). Tables 4a and b, respectively, show mean [11C]CFN BPND and [11C]MeNTL BPND in the 8 VOI in alcohol dependent and healthy control subjects when adjusted for age, gender and smoking.
Figure 1
Figure 1
[11C]CFN BPND in alcohol dependent (AD) vs. healthy control (HC) subjects. Bars are the mean ± SEM [11C]CFN BPND adjusted for age, gender and smoking for cingulate (Cg), amygdala (Am), Insula (In), ventral Striatum (vS), putamen (Pu), caudate (more ...)
Figure 2
Figure 2
Mean [11C]CFN BPND images in control (a) and alcohol dependent subjects (b). Colored legend depicts [11C]CFN BPND from 0 (light blue) to 1.85 (red). Mean MRI image of all subjects is shown (c). Images are taken at the level of ventral striatum.
Figure 3
Figure 3
[11C]MeNTL BPND in alcohol dependent (AD) vs. healthy control (HC) subjects. Bars are the mean ± SEM [11C]MeNTL BPND adjusted for age, gender and smoking for cingulate (Cg), amygdala (Am), Insula (In), ventral Striatum (vS), putamen (Pu), caudate (more ...)
Table 3
Table 3
Effects of smoking status on Mean [11C]CFNBPND. Data shown are group means and SEM with P values for smokers and non-smokers adjusted for age, gender and group (alcohol dependent vs. control) for each VOI. Q values show adjusted p values using the step-down (more ...)
Table 4
Table 4
Table 4 a.Mean [11C]CFNBPND. and b. Mean [11C]MeNTLBPND in alcohol dependent (AD) and healthy control (HC) subjects. Data shown are group means and SEM, F and P values adjusted for age, gender and smoking for each VOI. Q(Holm) values show adjusted p (more ...)
SPM Analyses of Alcohol Dependent vs. Healthy Control Subjects
SPM analysis of [11C]CFN BPND in alcohol dependent and healthy control subjects confirmed that alcohol dependent subjects had higher [11C]CNF BPND. The addition of smoking status as a nuisance variable in the contrast analysis of alcohol dependent and healthy control subjects did not change this result. Specifically, group differences were identified as two large, symmetrical volumes of 218 ml (left) and 222 ml (right), which peaked at thalamus (Figure 4). The x,y,z coordinates were 20, −12, 4 (Peak T=7.5) for left and −22, 12, 6 (Peak T=7.49) for right volumes, respectively (Figure 4). There were no differences between alcohol dependent and healthy control subjects in [11C]CNF BPND in para-sagittal areas.
Figure 4
Figure 4
[11C]CFN BPND brain images shown in lateral, anterior and superior views of bi-hemispheric clusters of SPM. The intersection of the blue lines targets the peak in the thalamus. Smoking status was added a nuisance variable in the contrast analysis of alcohol (more ...)
In contrast, consistent with the VOI analysis, SPM analysis did not reveal any significant differences in [11C]MeNTL BPND between alcohol dependent and healthy control subjects.
Secondary Analyses of Impact of Severity of Alcohol Dependence and Drinking History
As shown in Table 1, alcohol dependent subjects scored significantly higher than healthy controls on measures of alcohol dependence severity (ADS) and recent alcohol drinking recorded on the TLFB (Drinks per drinking day, drinks per week, total drinks last 90 days) (all p<0.0001, t-test). There was a significant positive association of recent drinking and [11C]MeNTL BPND in the caudate [mean drinks per drinking day (coefficient 20.4, p=0.001, Q =0.003), mean drinks per week (coefficient 15.5, p=0.002, Q =0.01), and total number of drinks (coefficient 15.8, p=0.001, Q =0.01)]. There was, however, no association of drinking reported in the 90-day timeline follow back and [11C]CFN BPND in any of the VOIs. [11C]CFN BPND and [11C]MeNTL BPND were also not significantly associated with ADS score, age first met criteria for alcohol dependence, or years of heavy drinking in alcohol dependent subjects.
During the inpatient protocol, moderate alcohol withdrawal symptoms, as determined by peak scores on the CIWA-AR across days 1 – 5 post-admission were observed and ranged from 1 to 12 (mean peak score = 5 ± 2.6 SD) for alcohol dependent subjects. Alcohol withdrawal symptoms had subsided by day 5 (mean CIWA score on day 5 = 0.44 + 1.1 SD) when PET scans were conducted. CIWA scores on the day of the PET scans did not differ between alcohol dependent and healthy control groups (Table 1). When controlling for smoking status, age, and gender, neither peak CIWA across days 1 – 5, nor pre-scan CIWA scores predicted [11C]CFN BPND or [11C]MeNTL BPND.
Secondary Analyses of Family History of Alcoholism
Since family history is a known risk factor for alcoholism, we examined whether family history predicted [11C]CFN BPND or [11C]MeNTL BPND. We adjusted for age, gender, smoking status and group in the analyses comparing family history positive (FHP) and family history negative (FHN) subjects. FHP subjects (n=23) did not differ from FHN subjects (n=26) in [11C]CFN BPND in any of the VOI(p > 0.09, Q >0.8). When stratified by group, alcohol dependent FHP subjects (n=14) did not differ from FHN subjects (n=10) in [11C]CFN BPND in any of the VOI(all p > 0.1, all Q >0.2). Likewise, healthy control FHP subjects (n=9) did not differ from FHN subjects (n=16) in [11C]CFN BPND in any of the VOI(p > 0. .2, Q =1.0). When compared to FHN subjects (n=19), FHP subjects (n=16) had a trend towards lower mean [11C]MeNTL BPND in the insula (FHN: 0.95 ± 0.04 vs. FHP:1.07 ± 0.04, p=0.04, Q =0.073). Using the observed group means and standard deviations, we then completed a sample-size analysis to detect an effect with 0.90% power. A sample size of 70 (or 35 in each group) was estimated for p=0.05 in insula. When stratified by group, alcohol dependent FHP subjects (n=11) did not differ from FHN subjects (n=8) in any of the VOI(p > 0.1, Q =1.0), and healthy control FHP subjects (n=5) did not differ from FHN subjects (n=11) in any of the VOI(p > 0.08, Q >0.3)
Secondary Analyses on Impact of Psychological Problems and Alcohol Craving
As shown in Table 1, alcohol dependent subjects reported significantly more symptoms of anxiety (BAI), depression (BDI) and psychological problems (BSI) than healthy control subjects (all p<0.0001, t-test). ANCOVA of these data indicated there was not a direct relationship between anxiety, depression or global measures of psychological problems as measured by the BAI, BDI–II and BSI and [11C]CFN BPND or [11C]MeNTL BPND.
Alcohol dependent subjects reported higher alcohol craving in the Penn Craving Scale, VAS, and OCDS than healthy control subjects (Table 1, all p<0.0001, t-test). There was a negative correlation with peak VAS alcohol craving scores across days 1 – 5 post-admission and [11C]CFN BPND in the amygdala (F=5.0, p and Q =0.04), ventral striatum (F=10.6, p and Q =0.004), and thalamus (F=4.5, p and Q =0.05); there was also a trend for the cingulate (p and Q =0.055). There was no relationship between scores on other craving instruments (the OCDS or the Penn craving scales) for either [11C]CFN BPND or [11C]MeNTL BPND in alcohol dependent subjects.
There were five primary findings of the current study. First, 5-day abstinent alcohol dependent men and women had higher [11C]CFN BPND when compared to age matched healthy control men and women in brain regions which included the ventral striatum, amygdala, caudate, globus pallidus, insula, putamen and thalamus. This observation remained after adjusting for age, gender and smoking status. The SPM analysis corroborated this finding and indicated that the alcohol effect is even more global than the VOI analyses suggest. Second, although the direction of effects in several brain regions was similar to that observed for [11C]CFN BPND, VOI and SPM analyses did not reveal significant differences in [11C]MeNTL BPND between alcohol dependent and healthy control subjects. Third, [11C]MeNTL BPND in the caudate was positively correlated with recent alcohol drinking in alcohol dependent subjects. Fourth, there was a significant negative correlation between [11C]CFN BPND and peak VAS alcohol craving in several VOIs. Fifth, other measures of alcohol dependence and withdrawal severity, mood and other psychological symptoms, were not associated with [11C]CFN BPND or [11C]MeNTL BPND. Each of these findings is discussed below.
The findings of our current study, which compared [11C]CFN BPND in 25 alcohol dependent and 30 age-matched healthy control men and women, are consistent with the higher [11C]CFN BPND in ventral striatum in 25 alcohol dependent men compared to 10 healthy controls reported by Heinz and colleagues (2005). In addition, alcohol dependent subjects had significantly higher [11C]CFN BPND in amygdala, caudate, globus pallidus, insula, putamen and thalamus. Our finding that the increase in [11C]CFN BPND may be more extensive is consistent with the reported trend towards an increase in regional and global [11C]diprenorphine volumes of distribution in alcohol dependent patients (n=11) when compared with controls (n=13), although this effect was not statistically significant (Williams et al., 2009). The authors note the study may have been under-powered and that there was substantial variability possibly related to [11C]diprenorphine binding to all three subunits (μ, δ and κ) of the OR.
The methodology for the current study differs from these previous studies in the following important ways. First, we enrolled both male and female alcohol dependent and age-matched healthy subjects and used stringent psychological assessment procedures to ensure no current drug use, no other drug use disorders and no other current or lifetime Axis I psychiatric disorders. Age, gender, other drug use disorders and psychiatric problems are important confounds that are known to influence the endogenous opioid system. Second, all subjects were housed in the same inpatient research unit where diet was controlled, smoking was prohibited, and urine toxicology screens verified no other drug use prior to imaging. For alcohol dependent subjects, all scans were conducted under an inpatient detoxification protocol where alcohol abstinence was supervised, and the timing of onset of alcohol abstinence and imaging was fixed. Alcohol dependent subjects were enrolled in the study while actively drinking, and abstinence was initiated at the time of inpatient admission. Third, both MOR and DOR were examined via PET scans with carbon 11-labeled [11C]carfentanil (CFN), a MOR-selective radioligand, and [11C]methylnaltrindole (MeNTL), a DOR-selective radioligand, in the same subjects under conditions of validated alcohol abstinence, and on the same day (day 5) of abstinence. Change in the endogenous opioid system following alcohol abstinence is a dynamic process, and these changes are likely greatest during early abstinence. Thus, fixing the time of scanning to a specific day during early abstinence minimizes the variance in the data introduced when the scanning time is allowed to vary by days or weeks. Fourth, withdrawal medications (e.g., benzodiazepines), which can alter OR function (Cox and Collins, 2001) were not used. Fifth, we examined eight brain volumes of interest (VOI) in mesolimbic opioid-rich regions, including the ventral striatum and the amygdala which have been associated with alcohol reinforcement, dependence and craving. Lastly, as many alcohol dependent subjects were also smokers, we specifically recruited healthy smokers without heavy drinking or alcohol problems to balance and control for smoking. This point is particularly relevant as approximately 80% of alcohol-dependent subjects report regular tobacco use (Batel et al., 1995; DiFranza and Guerrera, 1990) and smoke at high rates (Dawson, 2000), when compared to social drinkers. Comparison subjects used in previous PET studies did not include smokers without alcohol problems. Thus, the current study used a rigorous level of control over other drug use and psychiatric disorders, the duration of alcohol abstinence and cigarette smoking. It is likely that significance was achieved in the current study because of the larger sample size, and control over these potential confounding effects.
Previous studies in healthy human volunteers using [C11]-MeNTL PET imaging have shown that DOR rich areas include neocortical regions (insular, parietal, frontal, cingulate, and occipital), caudate nucleus, putamen and amygdala (Madar et al., 1996). In addition, [11C]MeNTL PET imaging has been utilized successfully to examine group differences in other disease states such as epilepsy (Madar, 1997) and carcinoma (Madar, 2007). This is the first study to compare DOR availability in recently-abstinent alcohol dependent and healthy control human subjects. Interestingly, we found a positive association of recent drinking (average drinks per drinking day) with [11C]MeNTL BPND in the caudate for alcohol dependent subjects. These data suggest that the delta receptor may be sensitive to recent alcohol drinking history. These data provide evidence of some role of the DOR in alcoholism, particularly when taken together with our previous report showing that the clinical dose of naltrexone (50 mg) produced only partial inhibition (21%) and substantial inter-subject variability of [11C]MeNTL binding in alcohol dependent subjects (Weerts et al., 2008). Since this same dose of naltrexone produces near complete inhibition (95%) of [11C]CFN binding, it seems likely that the magnitude of DOR blockade by naltrexone may contribute to the variability of naltrexone treatment outcomes and may be influenced by baseline differences in DOR availability prior to treatment. The current study did not reveal significant [11C]MeNTL BPND differences between groups. These data are in contrast to preclinical studies in alcohol preferring and non-preferring rodent strains which have shown increases and decreases in DOR density in mesolimbic regions (de Waele et al., 1995; Marinelli et al., 2000; McBride et al., 1998; Soini et al., 1998). Since inter-subject variations (measured as coefficient of variation) were similar between [11C]CFN and [11C]MeNTL for examined regions, the lack of group differences for [11C]MeNTL cannot be attributed to greater variability in binding. A possible caveat is that the regional estimates of [11C]MeNTL BPND were lower than estimates of [11C]CFN BPND. Thus, it may be argued that the observed lower signal-to-noise (i.e., specific-to-non-specific binding) ratio of [11C]MeNTL may mask potential group differences. Alternatively, the lack of differences between groups may be related to the smaller sample size for the [11C]MeNTL scans. It is possible that a larger sample size might reveal a significant increase in [11C]MeNTL BPND.
The higher [11C]CFN BPND in alcohol dependent subjects can be interpreted in several ways. It may reflect greater MOR availability due to decreased mu receptor occupancy by endogenous opioids. Alternatively, the increase in [11C]CFN BPND in alcohol dependent subjects also may reflect an increase in MOR density (e.g., an up regulation of MOR) compared to controls. This elevation in [11C]CFN BPND in alcohol dependent subjects compared with healthy controls could be a consequence of 1) alcohol withdrawal 2) long-term hazardous alcohol drinking/dependence, 3) inherited differences in the opioid system and/or 4) acquired differences due to environmental factors (e.g., childhood adversity, chronic stress) that might alter [11C]CFN BPND. There is support for some of these possibilities. Studies in rodents have reported increased MOR binding in limbic areas, including the nucleus accumbens, after extended alcohol consumption (5 weeks) (Cowen et al., 1998; Cowen et al., 1999; Djouma and Lawrence, 2002) and during alcohol withdrawal (1–10 days) (Djouma and Lawrence, 2002). Studies examining genetic variations in opioid activity in rodent lines have also demonstrated greater MOR density in limbic structures, such as the nucleus accumbens, and amygdala in the alcohol preferring lines, when compared the non-preferring lines (de Waele et al., 1995; Marinelli et al., 2000; McBride et al., 1998), although not in all studies (Fadda et al., 1999). Although we did not find a direct relationship between [11C]CFN BPND and measures of anxiety, depression and psychological problems, alcohol dependent subjects reported significantly greater symptoms of for all of these measures than healthy control subjects, even after exclusion of people with a history of other Axis I disorders.
In the current study, detailed family histories were obtained from the participants and subjects were classified according to family histories of alcoholism. The increase in [11C]CFN BPND does not appear to be directly related to family history of alcoholism. Subjects with positive family histories of alcoholism did not differ in [11C]CFN BPND from subjects with negative family histories of alcoholism in any of the VOI. Heinz and colleagues (Heinz et al., 2005) also did not observe an effect of family history of alcoholism on [11C]CFN BPND. Likewise, previously we reported there were no significant differences in amphetamine-induced mesolimbic dopamine release, subjective responses, or stress hormone measures as a function of family history of alcoholism (Munro et al., 2006). It seems unlikely that the observed elevation in [11C]CFN BPND can be attributed to acute abstinence alone. We did not observe a relationship between binding potential and alcohol withdrawal severity as measured by the CIWA-Ar in the current study. Our selection of alcohol dependent subjects with relatively mild alcohol withdrawal symptoms may have diminished our ability to observe such an effect. In the study by Heinz and colleagues (Heinz et al., 2005) increased MOR availability in the ventral striatum was observed after 1–3 weeks of alcohol abstinence and remained elevated and stable 5 weeks later when [11C]CFN PET scans were repeated in a subset of alcohol-dependent subjects. Similarly, [11C]diprenorphine volumes of distribution were stable when examined at 2 weeks and again 2 months after alcohol abstinence (Williams et al., 2009).
Neither our study nor the study by Heinz et al. observed any relationship between MOR availability and alcohol drinking history or severity of alcohol dependence. Likewise, Williams et al. did not see a correlation between alcohol drinking history or severity of alcohol dependence and the volumes of distribution of the non-selective tracer [11C]diprenorphine (Williams et al., 2009). We did, however, observe a positive correlation between recent alcohol drinking and [11C]MeNTL BPND in caudate. It should be acknowledged, however, that the ability to observe a relationships between drinking measures and [11C]CFN BPND within the alcohol dependent subjects may be compromised by the homogeneity and chronicity of the sample (i.e., all were long-term heavy drinkers). Increases in MOR binding were observed in rodents after only 5 weeks of alcohol consumption. If chronic alcohol drinking produced an up regulation of MOR, it likely occurred earlier in the progression from regular drinking to dependence and could not be detected in our relatively homogonous sample of long-term alcohol dependent drinkers.
We found an inverse relationship between craving scores on the VAS and [11C]CFN BPND in several brain regions including the ventral striatum, thalamus and cingulate. Interesting, alcohol dependent subjects show greater activation of these same brain regions in response to alcohol cues (a sip of alcohol and pictures of alcoholic beverages) when compared to control cues in fMRI studies (George et al., 2001, Myrick et al. 2004); activation in cingulate and nucleus accumbens were correlated with higher craving in alcoholic and not social drinkers (Myrick et al. 2004). The inverse correlation with craving in the current study was unexpected, as alcohol dependent subjects reported higher craving and had higher [11C]CFN BPND when compared to controls. In addition, our data contrasts with positive correlations of self-reported craving with [11C]CFN and [11C]diprenorphine receptor availability reported previously (Heinz et al., 2005; Williams et al., 2009). The OCDS scores obtained on the day of the PET scans in the current study were comparable to those in the Heinz study. An inverse relationship between craving and dopamine D2 receptor ligand [18F]desmethoxyfallypride BPND in the ventral striatum in alcohol dependent subjects has been reported (Heinz et al., 2004). Although it appears that D2 and MOR receptors behave oppositely in alcohol dependence, a similar inverse relationship with craving may occur. For example, if opioid peptides are reduced by chronic alcohol drinking leading to up regulation of MOR, then greater up regulation of MOR may result in greater opioid transmission and less craving compared to individuals with less up regulation. In the case of alcohol-related reductions in endogenous opioid release, the up regulation of receptors would have to be proportionally more than the reduction in opioids for there to be net increase in opioid neurotransmission. This would bring craving closer to that in normal individuals, but not normalize it completely. This mechanism is speculative and further studies are needed to determine if this hypothesis is supported.
There were some study limitations that may limit generalization of these findings. We selected alcohol dependent subjects without prior histories of serious withdrawal symptoms and excluded subjects who had previously required benzodiazepine treatment for withdrawal symptoms. Thus, subjects who experienced more severe forms of alcohol withdrawal were excluded from participation in the study. Yet, despite this conservative selection of subjects with modest withdrawal symptoms, differences in [11C]CFN BPND between alcohol dependent subjects and controls were highly significant across multiple brain volumes. An additional consideration is subjects were long-term alcohol-dependent drinkers (i.e., an average of 15 years of alcohol dependent drinking). Thus, similar long-term exposure to alcohol for this homogenous sample may have reduced the ability to show relationships between [11C]CFN BPND and behavior/clinical measures. Additional studies in subjects with a wider range of drinking levels and with and without diagnosis of alcohol use disorders are needed to better understand the transitions in the opioid system as alcohol consumption progresses from social drinking to heavy drinking and then to alcohol dependence.
In summary, our observations that [11C]MeNTL BPND was associated with recent drinking and that [11C]MeNTL BPND showed the same direction of group differences as [11C]CFN BPND suggest a potential role of DOR in alcohol dependence and clearly warrant further investigation. Particularly, when taken together with the our previous report showing the clinical dose of naltrexone (50 mg) produced only partial blockade of [11C]MeNTL binding and thus likely contributes to the variability of naltrexone treatment outcomes. The higher [11C]CFN BPND in alcohol dependent subjects may represent a predisposing risk factor for alcohol dependence, or could be a result of long-term drinking, alcohol dependence or withdrawal. The finding that [11C]CFN BPND was increased in alcoholics, provides evidence of a prominent role of the MOR in alcohol dependence.
Acknowledgments
Support: The National Institute of Alcohol Abuse and Alcoholism (NIAAA) provided financial support for research related to the subject matter of this manuscript from the grants R01AA11872 (PI: J.J. Frost), R01AA11855 (PI:M.E. McCaul) and R37AA12303 (PI: G.S. Wand). Dr. Wand is the recipient of a gift fund from the Kenneth Lattman Foundation. Dr. McCaul was principal investigator on a contract ( A Phase 2 Study of LY2196044 Compared with Naltrexone and Placebo in the Treatment of Alcohol Dependence) funded by Lilly Research Laboratories; Drs. Weerts and Wand were co-investigators on this project.
The authors would like to acknowledge the technical support of Dr. Hayden T. Ravert, Mr. Robert Smoot, and Mr. Daniel Holt for their radiochemistry expertise; Ms. Karen Edmonds, Mr. David Clough, Mr. Michael Hans and Mr. Bineyam Gebrewold for PET acquisition. The authors also wish to acknowledge the excellent technical assistance of Courtney Cook for data management and Xiaoqiang Xu for statistical analyses.
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