European Neuropsychopharmacology (2014) 24, 242–250
www.elsevier.com/locate/euroneuro
In vivo type 1 cannabinoid receptor availability in Alzheimer's disease Rawaha Ahmada,b,n, Karolien Goffina,b, Jan Van den Stockc,d, François-Laurent De Winterc,d, Evy Cleerena,b, Guy Bormanse, Jos Tournoyf,g, Philippe Persoonsc,d, Koen Van Laerea,b, Mathieu Vandenbulckec,d a
Nuclear Medicine and Molecular Imaging, University Hospitals Leuven, Belgium Department of Imaging & Pathology, KU Leuven, Belgium c Department of Old Age Psychiatry, University Hospitals Leuven, Belgium d Department of Neurosciences, KU Leuven, Belgium e Laboratory for Radiopharmacy, KU Leuven, Belgium f Geriatric Medicine, University Hospitals Leuven, Belgium g Department of Clinical and Experimental Medicine, KU Leuven, Belgium b
Received 5 August 2013; received in revised form 4 October 2013; accepted 9 October 2013
KEYWORDS
Abstract
Alzheimer's disease; Cannabinoid receptor; Amyloid; PET scan; MMSE; ApoE
The endocannabinoid system (ECS) is an important modulatory and potentially neuroprotective homeostatic system in the brain. In Alzheimer's disease (AD), the role of type 1 cannabinoid receptor (CB1R) is unclear, with contradictory findings in post-mortem studies showing upregulation, downregulation or unchanged CB1R status. We have investigated CB1R availability in vivo in patients with AD, in relation to amyloid deposition, cognitive functioning and apolipoprotein E (ApoE) genotype. Eleven AD patients and 7 healthy volunteers (HV) underwent combined [18F]MK-9470 PET and [11C]PIB PET scans to assess CB1R availability and amyloid deposition, respectively, and T1 volumetric MRI for partial volume correction. We found no difference in CB1R availability between AD and HV, VOI-based fractional uptake values (FUR) were 0.04370.01 for AD and 0.04570.01 for controls (p=0.9). CB1R availability did not correlate with neuropsychological test scores and was not modulated by ApoE genotype. As expected, global [11C]PIB SUVR (standardized uptake value ratio) was increased in AD (SUVR 1.970.3) compared to HV (1.270.1) with po0.001, but no correlation was found between amyloid β (Aβ) deposition and CB1R availability. In conclusion, we found no in vivo evidence for a difference in CB1R availability in AD compared to age-matched controls. Taken together with recently reported in vivo CB1R changes in Parkinson's and Huntington's disease, these data suggest that the CB1R is differentially involved in neurodegenerative disorders. & 2013 Elsevier B.V. and ECNP. All rights reserved.
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Correspondence to: Division of Nuclear Medicine E901, University Hospital Leuven, Herestraat 49, B-3000 Leuven, Belgium. Tel.: +32 16 343715; fax: +32 16 343759. E-mail address: [email protected] (R. Ahmad). 0924-977X/$ - see front matter & 2013 Elsevier B.V. and ECNP. All rights reserved. http://dx.doi.org/10.1016/j.euroneuro.2013.10.002
CB1 PET in Alzheimer's disease
1.
Introduction
Impairment of the cholinergic system and its relation to cognitive dysfunction is well-known in Alzheimer's disease (AD). Various other neurotransmitter systems (e.g. the serotonergic system (Rodriguez et al., 2012)) and concomitant changes of associated receptors and synthetic enzymes have been related to cognitive and behavioral changes. Recent advances in the characterization of different functions of the endocannabinoid system (ECS) suggest that this neurotransmitter system may also play a role in the pathophysiology of AD in different ways as well as in the pathogenesis of cognitive dysfunction. The ECS is generally viewed as a neuromodulatory system that interacts with, and regulates several neurotransmitter systems (Terranova et al., 1996). Growing evidence also shows that type 1 cannabinoid receptors (CB1R) play a fundamental role in neuroprotection including in AD (Aso et al., 2012). In vitro experiments suggest that endogenous cannabinoids promote changes in neural activity related to memory, with a role in long-term plasticity (Ramirez et al., 2005). Overall, in vivo experiments with mice have been ambiguous, with reports of both impaired and enhanced memory performance (Ledent et al., 1999; Reibaud et al., 1999). Administration of CB1R antagonists improved memory in a rodent model of AD, probably through modulation of acetylcholine (Ach) levels (Davies et al., 2002). On the other hand, it has also been shown that chronic administration of the CB1R agonist arachidonyl-2-chloroethylamide (ACEA) reduces cognitive impairment observed in double AβPP(swe)/PS1(1dE9) transgenic mice probably through GSK3β inhibition, reduction of reactive astrocytes and lower expression of interferon-γ (Aso et al., 2012). CB1Rs are also involved in mediating the Aβ neurotoxicity and in protecting against amnesia in hippocampal learning tasks. SR141716A, a CB1R antagonist, improves amnesia induced by Aβ fragments in mice, suggesting that endogenous cannabinoids may be involved in cognitive impairment induced by these fragments (Mazzola et al., 2003). In humans, Walther et al. showed significant improvement of the Neuropsychiatric Inventory scores in late onset dementia after a daily administration of dronabinol, a cannabinoid agonist (Walther et al., 2006). Post-mortem studies in AD on the role of the CB1R and its relation to cognitive function at end-of-life remain unclear. Ramirez et al. reported loss of CB1R – positive neurons in the frontal cortex of AD patients, decreased CB1 protein expression and G-protein decoupling, despite preserved density and binding of the receptor (Ramirez et al., 2005). They also showed consistent CB1R immunoreactivity in senile plaques along with markers of microglial activation, suggesting a direct involvement of these receptors in the effects of microglia. In contrast, Westlake et al. found reduced CB1R density in several areas including the entorhinal cortex and hippocampus, but no association between reduced CB1R expression and neuropathological signs of AD (Westlake et al., 1994). Benito et al. found no changes in CB1R density in the proximity of neuritic plaques (Benito et al., 2003) and also other recent studies described preserved expression of CB1R, even in severe AD (Farkas et al., 2012; Lee et al., 2010). Over the past years, several positron emission tomography (PET) radioligands have been developed that allow in vivo quantification of the CB1R distribution, such as [18F]MK-9470
243 (Burns et al., 2007; Sanabria-Bohorquez et al., 2010), [11C] OMAR (Horti et al., 2006) and [18F]MPePP (Terry et al., 2008). The aim of this study was to measure the in vivo CB1R status in AD in relation to Aβ deposition, cognitive parameters and apolipoprotein E (ApoE) genotype. We therefore conducted a prospective, cross-sectional multitracer study using [18F]MK9470 and [11C]PIB in mild to moderate AD patients and healthy controls.
2. 2.1.
Experimental procedure Subjects
AD patients had to meet following inclusion criteria: (1) Z55 years of age; (2) diagnosis of probable AD according to the NINCDS-ADRDA Criteria (Dubois et al., 2007); (3) magnetic resonance imaging (MRI) scan obtained within the last 12 months consistent with a diagnosis of AD; (4) Modified Hachinski Ischemic Scale (MHIS) score of r4; (5) global CDR (Clinical Dementia Rating score) (Morris, 1993) between 1 and 3, or, if the Global CDR is 0.5, then CDR Sum of Boxes of at least 3.5; (6) at least six years of education, or work history sufficient to exclude mental retardation, and (7) a positive [11C]PIB PET scan. Thirteen patients with probable AD (5 men (M), 8 women (F); age range 57.6–81.8 years) were screened. Two male patients fulfilling screening criteria 1–6 but with a negative [11C]PIB PET scan, were excluded from the study. The patient group therefore consisted of 3 M and 8 F patients (age range 57.6–80.9 years). AD patients were compared to a group of 7 healthy cognitive intact and age-matched elderly volunteers (3 men, 4 women; age range 61.3–79.0 years). These volunteers were prospectively recruited in response to advertisements in local community newspapers and departmental website.
2.2.
Neuropsychological evaluation
All subjects underwent thorough neuropsychological evaluation. The following tests were conducted: Dutch version of the minimental state examination (MMSE) (O’Bryant et al., 2008), auditory verbal learning test (AVLT) (Balthazar et al., 2010; Van der Elst et al., 2005), Boston naming test (BNT) (Karrasch et al.), Raven's colored progressive matrices test (RCPMT), the subtest Object Decision (OD) of the visual object and space perception test (VOSP) (Videaud et al., 2008), clinical dementia rating (CDR) scale (Morris, 1993), the cognitive part of the Alzheimer's disease assessment scale (ADAS-cog) (Skinner et al., 2012), neuropsychiatric inventory (NPI) (Cummings, 1997), Alzheimer's disease cooperative study – activities of daily living (ADCS-ADL) (Galasko et al., 1997), and geriatric depression scale (GDS) (Albinski et al., 2011). Only MMSE and AVLT (total learning (A1–A5), delayed and recognition scores of the AVLT), measures of global cognitive functioning and episodic memory respectively, were used for correlation analyses with CB1R availability. CDR sum of boxes was used as a variable of interest in the correlation analysis with AVLT scores. We have also added the maximum scores to Table 1. Blood sampling for ε4 allele(s) of ApoE ε4 was done in all except one subject that died shortly after the PET scans. The study was approved by the local Ethics Committee and performed in accordance to the latest version of the World Medical Association Declaration of Helsinki. Written informed consent was obtained from healthy controls, subjects with AD and from their primary caregivers, prior to the study.
2.3.
Radiotracer characteristics and preparation
The [18F]MK-9470 precursor was obtained from Merck Research Laboratories and labeled at the PET site using 18F-ethylbromide
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Table 1
Demographic variables and neurocognitive tests in healthy volunteers (HV) and Alzheimer's disease (AD) patients.
Subject
Gender
Age at study
ApoE
MMSE (/30)
Total A1-A5 (/75)
Delayed AVLT (/15)
Recognition AVLT (/15)*
HV 1 HV 2 HV 3 HV 4 HV 5 HV 6 HV 7 Mean SD AD 1 AD 2 AD 3 AD 5 AD 7 AD 8 AD 9 AD 10 AD 11 AD 12 AD 13 Mean SD p-value (Student-t)
F M F F F M M
62.0 79.0 75.9 69.1 61.3 62.3 66.4 68.0 6.5 72.8 71.0 80.9 65.5 81.3 72.4 68.5 57.6 70.7 64.5 70.9 71.8 6.8 0.3
/ / / +/ / / +/
29 27 25 29 28 29 30 28 2 20 22 25 20 24 13 11 23 14 23 23 20 4 o0.001
44 29 35 53 33 38 58 41 10 5 22 21 23 21 2 12 47 4 23 21 18 11 o0.001
7 4 6 11 8 9 10 8 2 0 0 1 0 0 0 3 8 0 0 3 1 2 r0.001
13 10 15 14 11 15 12 13 2 2 1 9 4 2 1 5 15 7 5 6 5 4 r0.001
F F F F M F F F M F M
/ + /+ / Died + /+ +/ / / +/ + /+ + /+
HV: healthy volunteer; AD: AD Alzheimer's disease patient; ApoE ε 4 apolipoprotein homozygote +/+, heterozygote +/ , negative / ; MMSE minimental state examination; AVLT auditory verbal learning test. n Range 15 to +15 (Van der Elst et al., 2005); SD standard deviation.
(Burns et al., 2007). Specific activity was 4140 GBq/mmol, the maximum amount of cold MK-9470 injected was o10 mg. [11C]PIB was produced on-site according to standard procedures (Nelissen et al., 2007). Specific activity for [11C]PIB was 4260 GBq/mmol.
2.4.
Imaging procedure
All patients fasted for at least 4 h prior to [18F]MK-9470 PET imaging. Subjects received on average 237 MBq (range 168– 253 MBq) of [18F]MK-9470 and 283 MBq (range 195–329 MBq) of [11C]PIB, with slow intravenous injection under low ambient noise and dimly lit room. PET imaging was performed in 3D mode on a HiRez Biograph16 PET-CT camera (Knoxville, TN, USA;). The subject's head was placed in a head holder and fixed using a vacuum mask to avoid excessive head movement. A low dose (80 kV tube potential, 11 mAs) CT scan was conducted at the beginning of each PET scan for attenuation correction. For [18F]MK-9470 imaging, an emission scan of 60 min (6 10 min) was started 120 min after injection. For [11C]PIB imaging, a dynamic PET emission scan of 30 min was started 40 min after injection (6 frames of 5 min). Images were reconstructed using a 3-dimension ordered subsets expectation-maximization (3D OSEM) iterative reconstruction with 5 iterations and 8 subsets and post smoothing with a 3D isotropic Gaussian (full-width-at-half-maximum (FWHM) of 6 mm).
2.5.
Image processing and data analysis
All subjects also underwent high-resolution MRI, both T1-weighted magnetization prepared rapid acquisition gradient echo (3D-
MPRAGE) and T2-weighted, on a 1.5 Tesla Vision Scanner (Siemens, Germany). Correction for subject motion was performed using the realignment module in statistical parametric mapping version 8 (SPM8) (Welcome Department of Cognitive Neuroscience, London, UK). A summed PET image was created by adding realigned frames. [18F]MK-9470 availability was expressed as fractional uptake ratio (FUR) value, calculated as the ratio of total radioactivity concentration in tissue at the end of the scan and the integral of metabolite-corrected plasma radioactivity from time of injection to the end of the scan (Sanabria-Bohorquez et al., 2010). To obtain FUR values, venous blood samples for radioactivity counting were taken manually from all participants at various time points following injection: 2, 5, 10, 20, 40, 60, 90, 120 and 180 min. Metabolite analysis and [18F]MK-9470 free fraction measurements were performed as described previously (Van Laere et al., 2008). For [11C]PIB imaging, SUVR values were used as a measure of Aβ binding. SUVR was defined as the regional tracer uptake in the summed emission image, normalized to the mean uptake in the cerebellar cortex as defined on the subject's MRI, as it is notably free of fibrillar plaques (Klunk et al., 2004). PET data were corrected for atrophy by post-hoc partial volume correction (PVC) on the reconstructed data, using the Alfano method in the PVEOut software (Quarantelli et al., 2004). Segmentation of T1 MPRAGE images was performed using SPM8. For PVC, PET data were coregistered to the segmented MRI data set. For each subject, parametric FUR and SUVR images were spatially normalized to the standard MNI space. For further voxelbased analyses, data were smoothed with an isotropic Gaussian kernel with a FWHM of 8 mm. A statistical parametric mapping analysis (two sample t-test) was performed for [18F]MK-9470 and
CB1 PET in Alzheimer's disease [11C]PIB data comparing patients to controls in a categorical subject design with and without age and gender as nuisance variables (groups were age-matched see Table 1), since CB1R availability is different for men and women and increases with age in women (Van Laere et al., 2008). When no global group differences were present, a regional analysis was conducted for [18F]MK-9470. In this case, proportional scaling was used with a relative analysis threshold of 80% of the mean, in order to exclude non-gray matter activity. We explored group differences using pheighto0.05 corrected for multiple comparisons with an extend threshold kext450 voxels ( 0.4 cm3). In addition to an analysis of group differences, a correlation analysis with memory tests (MMSE, AVLT) and ApoE genotype was performed in SMP8 using multiple regression analysis at an exploratory pheighto0.001 uncorrected. Additionally, a voxel by voxel comparison of the PIB and FUR PET scan was performed using BPM (biological parametric mapping) version 1.5d beta. Secondly, a volume-of interest (VOI) analysis was performed using PMOD v3.0 using VOIs for striatum, frontal, temporal, mesotemporal, parietal, occipital, central insular and cingulate cortex (Van Laere et al., 2006). Additionally, all subjects were divided in different groups according to their ApoE status. The analysis was done voxel based (non-parametric t-test for independent samples) and spm analysis was performed using two sample t-test. In the spm analysis we found no significant clusters comparing these groups. Additionally, we subdivided all subjects according to their ApoE status and compared the subgroups using VOI based (non-parametric t-test for independent samples) and voxel based spm (two sample t-test) analysis. Conventional statistics were performed using Statistica v10.0 (Statsoft Inc, Tulsa, OK, USA). To ensure robustness of data, the same procedure was also applied to the non-partial volume corrected datasets for CB1 and amyloid imaging.
3. 3.1.
Results Neuropsychological evaluation and ApoE
Table 1 shows the demographic variables and the main results of the neurocognitive evaluation (MMSE and AVLT) for all subjects. Highly significant differences (mean7SD; two sided t-test p-value) were present in MMSE (Table 1), AVLT (Table 1), ADAS (HV: 5.772.5; AD 22.8712.3; p=0.002) and, RCPMT (HV: 3074.2; AD: 18.577.6; p=0.002). NPI (17.8716.8), ADSC-ADL (43.9713.8) and CDR sum of boxes (14.573.0) were only obtained in the AD patients (mean 7 SD). BNT (HV: 46.8717.8; AD: 36.6713.9; p=0.17), OD (VOSP) (HV: 16.872.1; AD: 14.573.0; p=0.26) and GDS (HV: 4.374.4; AD: 7.374.8; p=0.20) did not show significant differences. Four patients and 5 controls were APOE ε4 negative, 2 patients and 2 controls were heterozygous and 4 patients were homozygous. One patient died during the course of the study and has an unknown ApoE status.
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3.3. Relation between CB1R availability and PIB binding As expected, in the voxel-based analysis global [11C]PIB SUVR values were significantly increased in AD patients compared to HV. This was confirmed by VOI based analysis with [11C]PIB SUVR 1.970.3 and HV 1.270.1 (po0.001) (Figure 1B). Figure 2 shows the average parametric maps of CB1 receptor availability (FUR) and PIB SUVR parametric maps for HV and AD patients. Figure 1C depicts a scatter plot of global CB1R availability and PIB binding in AD patients and HVs. In this graph, ApoE ε4 genotype is indicated for each subject. No significant correlation was found between regional or global PIB binding and CB1R availability using voxel-wise and VOI-based analysis.
3.4.
We found no correlation between CB1R availability and neuropsychological tests (MMSE and AVLT). To overcome floor effects (especially for the AVLT Delayed Recall) and to take functional parameters into account, we additionally performed the correlation with CDR sum of boxes as a variable of interest, but again found no correlation between regional CB1R availability and AVLT scores (Total Learning AVLT: r2 = 0.46 and p =0.11; Delayed Recall AVLT:r2 = 0.32 and p 0.31; Recognition AVLT r2 = 0.24 and p= 0.44) (data not shown). For patient 10 the AVLT scores were remarkably high, but this had no effects on our results.
3.5.
No significant group differences were found regarding global CB1R availability using voxel-based analysis. This was confirmed by VOI-based analysis (FUR AD patients 0.0470.01 and HV 0.0570.01, p= 0.9). Effect size measured with Cohen's d were small (between 0.19 and 0.25) (Figure 1A).
Effect of ApoE status
In the ApoE ε4 negative and heterozygous group there was a wide variation in CB1R availability as well as PIB binding. For the ApoE ε4 homozygous group (25%), PIB-binding was in the highest range (PIB SUVR mean 1.7–2.0), the CB1R availability was high for three out of four subjects (mean cortical FUR 0.05–0.06), but low for one subject (FUR 0.03). However, no significant differences between groups were found (Figure 3): ApoE homozygous patients versus ApoE heterozygous and negative patients: p= 0.44; ApoE positive (homozygous and heterozygous) versus ApoE negative patients: p= 0.62; ApoE homozygous patient versus ApoE negative and heterozygous patients and controls: p= 0.53. Also in the spm analysis we found no significant differences between these groups. All results were the same when data uncorrected for partial volume effects were used, indicating the robustness of these findings.
4. 3.2. Group comparison of CB1R availability in AD patients vs. HV
Correlation with cognitive functioning
Discussion
Using [18F]MK-9470 PET, we report the first quantitative in vivo study of CB1R PET in AD, providing whole-brain information by use of a highly-selective and high-affinity compound (Burns et al., 2007). We did not find any changes of CB1R availability in vivo throughout the brain in AD patients compared to HV, nor a relationship with regional Aβ plaque density measured by [11C]PIB PET.
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Figure 1 (A) (upper) Bar chart of CB1R FUR values per volume of interest for Alzheimer's patients (AD) and healthy volunteers (HV) before and after PVC. FUR is decreased in all cortical regions and comparable in the striatum in AD versus controls. These differences are not significant (p =0.83). Effect sizes (Cohen's d) are presented above the bars per volume of interest. (B) (middle) Bar chart of global [11C]PIB-standard uptake value ratio's (SUVR) for regions of interest. Error bars indicate standard deviation (SD). The PIB binding is significantly increased in all AD patients compared to controls (po0.001). (C) (lower) Scatter plot of global CB1R availability and PIB binding (SUVR) in AD patients and HVs.
Our study is in agreement with the majority of postmortem studies that suggest no quantitative changes of CB1R availability in human AD. Benito et al. used Western blotting and immunohistochemistry and reported a selective overexpression of FAAH (fatty acid amide hydrolase) and CB2R protein in glial cells, but no changes in CB1R density in the proximity of neuritic plaques (Benito et al., 2003). The lack of association between amyloid pathology measured by [11C]PIB PET and CB1R availability in our study provides in vivo confirmation of this observation. Ramirez et al. also reported alterations of the endocannabinoid system
including decreased CB1 protein expression and G-protein decoupling, but density and binding of the CB1R was preserved (Ramirez et al., 2005). It is important to note that our [18F]MK-9470 PET imaging technique was used to quantify CB1R availability but does not allow to draw conclusions on the functional state of the receptor (activated or deactivated state). Two more recent studies also suggest preserved expression of CB1R, even in severe AD (Farkas et al., 2012; Lee et al., 2010). Lee et al. used immunoblotting and radioligand binding on brain tissue from frontal cortex, anterior cingulate gyrus, hippocampus and
CB1 PET in Alzheimer's disease
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Figure 2 (A) Average parametric maps of CB1R availability (FUR) for HV and (B) AD patients. (C) Average PIB SUVR parametric maps for HV and (D) AD patients.
Figure 3 Mean CB1R availability (upper panel) and mean PIB binding (lower panel) for the study population, divided in groups by ApoE ε4 status. Bar shows mean.
caudate nucleus to assess changes in CB1R. Farkas et al. examined prefrontal cortex tissue from different Braak stages using autoradiography with a CB1R agonist
radioligand 125I-SD-7015 and showed a preserved CB1R in Braak stages III–IV. Our findings do not support the observation of Westlake et al. who reported a reduced CB1R density
248 in several areas including the entorhinal cortex and hippocampus, which was not associated with neuropathological measures of AD. The latter observation was interpreted as a consequence of normal aging, resulting in extensive neuronal loss and reduced density of synapses (Westlake et al., 1994). However, an age-dependent reduction of CB1R has not been confirmed. In contrast, CB1R availability may rather increase with age especially in the memory, limbic and motor circuit (Van Laere et al., 2008). The compound used in the study by Westlake and coworkers, is an agonist for both the CB1R and CB2R. It is however unlikely that this would provide an explanation for the decreased CB1R because CB2R is overexpressed in AD (Solas et al., 2013), which would rather lead to an overestimation (Westlake et al., 1994). It has been suggested that CB1R availability may relate to cognitive functioning in AD. Lee et al. reported unchanged CB1R availability in AD on the whole, but a subgroup of patients with relatively high levels of CB1R in the frontal cortex showed better cognitive function (Lee et al., 2010). It was hypothesized that this might have to do with improved regulation of glutamate release and thus better control of excitotoxicity. However, we were not able to confirm this finding as we did not find any correlation between the CB1R availability and cognitive functioning (measured by MMSE and AVLT). The relatively low number of participants in our study should be taken into account and does not allow us to make firm conclusions in this respect. We also investigated the relation between CB1R availability and ApoE genotype. The presence of ApoE ε4 has been associated with more severe memory impairment and an earlier age of onset (Corder et al., 1993). Pathological studies, spinal fluid markers, and Aβ imaging have shown that Aβ accumulation increases in association with advanced age and presence of the ApoE ε4 allele, even in the absence of cognitive symptoms (Reiman et al., 2004; Villemagne et al., 2011). However, there are no previous data about a relation of ApoE ε4 genotype and the ECS. We did not find a clear association between CB1R availability and ApoE ε4 genotype using VOI-based or voxel-wise analysis. We noticed that 3 out of 4 ApoE ε4 homozygous individuals had CB1R availability in the upper range but more work is needed to investigate the role of the ECS in ApoE ε4 carriers with AD. One of the critical issues in research on neurodegenerative disorders is the specificity of findings. Recently, the CB1R has been investigated in different neurodegenerative disorders. In Huntington's disease (HD), post-mortem studies showed an early decrease of the CB1R availability in the brain (Glass et al., 2000; Glass et al., 1993), a finding confirmed in vivo with the same radioligand as used in the current study (Van Laere et al., 2010), and likely due to CB1R transcription interference of mutant huntingtin. In contrast to this uniform reduction of CB1R availability throughout the entire gray matter in HD, in Parkinson's disease (PD), the CB1R availability shows remarkable regional heterogeneity. Studies on CB1R protein levels in the substantia nigra of PD animals and post-mortem substantia nigra from PD patients have provided mixed findings with decreased, biphasic response or unchanged CB1R levels (Garcia-Arencibia et al., 2009; Lastres-Becker et al., 2001; Walsh et al., 2010). Together with findings in the current
R. Ahmad et al. study, it seems that the ECS is differentially affected in various neurodegenerative disorders. This may be related to direct or indirect effects on glutamate, GABA and dopamine that plays a central role both in HD and PD (Morera-Herreras et al., 2012; Pazos et al., 2008). Dopamine is much less involved in AD. Other systems that are preferentially affected in AD, such as the acetylcholinergic system, have shown a less direct link to the ECS (Davies et al., 2002). The main limitation of our study is the small sample size. Because we did not find any trend towards a difference between AD and controls at group level (Figures 1 and 2), we do not believe that a larger sample size would change the main finding, especially since the effect sizes are small ( 0.19 to 0.25, Figure 1A). However, as noted above more subtle associations with cognitive profile may have been concealed. Secondly, it is important to bear in mind that, using [18F]MK-9470 PET imaging, we have only studied one specific aspect of the ECS being the CB1R availability. Yet, the functional or the signaling state (Perez and Karnik, 2005) of CB1R in AD may well be altered and even contribute to the pathophysiology of AD (Ramirez et al., 2005). Our study overcomes a number of serious limitations associated with post-mortem studies including protein degradation, inclusion of a limited number of brain regions and retrospective correlations with clinical evaluation such as cognitive function in AD. It should be noted that a positive PIB PET scan was used as one of the inclusion criteria for AD subjects in order to study the relationship between CB1R status and amyloid deposition. However, although a PIB-scan may support a diagnosis of AD, it should be emphasized that a positive scan in itself is not diagnostic of AD nor a clear marker of cognitive status (Aizenstein et al., 2008; Mathis et al., 2013). These findings underscore the importance of including both PIB as well as cognitive functioning when exploring the relationship with a third variable. In conclusion, we found no in vivo evidence for a difference in CB1R availability in AD compared to age-matched controls, indicating that the CB1R may be differentially involved in neurodegenerative proteinopathies when compared to published results in Parkinson's and Huntington's disease.
Role of the funding source This project was supported by the Flemish Foundation for Science (FWO Vlaanderen) (grant G.0493.10N). FWO had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Contributors Authors Koen Van Laere and Mathieu Vandenbulcke designed the study and wrote the protocol. Jan Van den Stock, François-Laurent De Winter did the neuropsychological testing. Jos Tournoy, Philippe Persoons and Mathieu Vandenbulcke recruited all the patients. Evy Cleeren was responsible for imaging. Guy Bormans was responsible for radioligand preparation. Rawaha Ahmad and Karolien Goffin managed the literature searches, statistical analyses and they also wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
CB1 PET in Alzheimer's disease
Conflict of interest All authors declare that they have no conflict of interest.
Acknowledgments Merck & Co. Inc. is acknowledged for the availability of the [18F]MK9470 precursor. We also thank Kwinten Porters, Mieke Steukers and the Leuven PET radiopharmacy team for their skilled contributions in patient handling and radiopharmaceutical preparation. This project was supported by the Flemish Foundation for Science (FWO Vlaanderen) (Grant G.0493.10N). FWO had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
References Aizenstein, H.J., Nebes, R.D., Saxton, J.A., Price, J.C., Mathis, C.A., Tsopelas, N.D., Ziolko, S.K., James, J.A., Snitz, B.E., Houck, P.R., Bi, W., Cohen, A.D., Lopresti, B.J., DeKosky, S.T., Halligan, E.M., Klunk, W.E., 2008. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch. Neurol. 65, 1509–1517. Albinski, R., Kleszczewska-Albinska, A., Bedynska, S., 2011. [Geriatric Depression Scale (GDS). Validity and reliability of different versions of the scale—review]. Psychiatr. Pol. 45, 555–562. Aso, E., Palomer, E., Juves, S., Maldonado, R., Munoz, F.J., Ferrer, I., 2012. CB1 agonist ACEA protects neurons and reduces the cognitive impairment of AbetaPP/PS1 mice. J. Alzheimer's Dis.: JAD 30, 439–459. Balthazar, M.L., Yasuda, C.L., Cendes, F., Damasceno, B.P., 2010. Learning, retrieval, and recognition are compromised in aMCI and mild AD: are distinct episodic memory processes mediated by the same anatomical structures? J. Int. Neuropsychol. Soc. 16, 205–209. Benito, C., Nunez, E., Tolon, R.M., Carrier, E.J., Rabano, A., Hillard, C.J., Romero, J., 2003. Cannabinoid CB2 receptors and fatty acid amide hydrolase are selectively overexpressed in neuritic plaque-associated glia in Alzheimer's disease brains. J. Neurosci. 23, 11136–11141. Burns, H.D., Van Laere, K., Sanabria-Bohorquez, S., Hamill, T.G., Bormans, G., Eng, W.S., Gibson, R., Ryan, C., Connolly, B., Patel, S., Krause, S., Vanko, A., Van Hecken, A., Dupont, P., De Lepeleire, I., Rothenberg, P., Stoch, S.A., Cote, J., Hagmann, W. K., Jewell, J.P., Lin, L.S., Liu, P., Goulet, M.T., Gottesdiener, K., Wagner, J.A., de Hoon, J., Mortelmans, L., Fong, T.M., Hargreaves, R.J., 2007. [18F]MK-9470, a positron emission tomography (PET) tracer for in vivo human PET brain imaging of the cannabinoid-1 receptor. Proc. Nat. Acad. Sci. U.S.A 104, 9800–9805. Corder, E.H., Saunders, A.M., Strittmatter, W.J., Schmechel, D.E., Gaskell, P.C., Small, G.W., Roses, A.D., Haines, J.L., PericakVance, M.A., 1993. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science 261, 921–923. Cummings, J.L., 1997. The neuropsychiatric inventory: assessing psychopathology in dementia patients. Neurology 48, S10–S16. Davies, S.N., Pertwee, R.G., Riedel, G., 2002. Functions of cannabinoid receptors in the hippocampus. Neuropharmacology 42, 993–1007. Dubois, B., Feldman, H.H., Jacova, C., DeKosky, S.T., BarbergerGateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., Meguro, K., O’Brien, J., Pasquier, F., Robert, P., Rossor, M., Salloway, S., Stern, Y., Visser, P.J., Scheltens, P., 2007. Research criteria for the diagnosis of Alzheimer's
249 disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 6, 734–746. Farkas, S., Nagy, K., Palkovits, M., Kovacs, G.G., Jia, Z., Donohue, S., Pike, V., Halldin, C., Mathe, D., Harkany, T., Gulyas, B., Csiba, L., 2012. [(125)I]SD-7015 reveals fine modalities of CB (1) cannabinoid receptor density in the prefrontal cortex during progression of Alzheimer's disease. Neurochem. Int. 60, 286–291. Galasko, D., Bennett, D., Sano, M., Ernesto, C., Thomas, R., Grundman, M., Ferris, S., 1997. An inventory to assess activities of daily living for clinical trials in Alzheimer's disease. The Alzheimer's disease cooperative study. Alzheimer Dis. Assoc. Disord. 11 (Suppl 2), S33–S39. Garcia-Arencibia, M., Garcia, C., Fernandez-Ruiz, J., 2009. Cannabinoids and Parkinson's disease. CNS Neurol. Disord. Drug Targets 8, 432–439. Glass, M., Dragunow, M., Faull, R.L., 2000. The pattern of neurodegeneration in Huntington's disease: a comparative study of cannabinoid, dopamine, adenosine and GABA(A) receptor alterations in the human basal ganglia in Huntington's disease. Neuroscience 97, 505–519. Glass, M., Faull, R.L., Dragunow, M., 1993. Loss of cannabinoid receptors in the substantia nigra in Huntington's disease. Neuroscience 56, 523–527. Horti, A.G., Fan, H., Kuwabara, H., Hilton, J., Ravert, H.T., Holt, D.P., Alexander, M., Kumar, A., Rahmim, A., Scheffel, U., Wong, D.F., Dannals, R.F., 2006. 11C-JHU75528: a radiotracer for PET imaging of CB1 cannabinoid receptors. J. Nucl. Med. 47, 1689–1696. Karrasch, M., Myllyniemi, A., Latvasalo, L., Soderholm, C., Ellfolk, U., Laine, M., 2010. The diagnostic accuracy of an incidental memory modification of the Boston Naming Test (memo-BNT) in differentiating between normal aging and mild Alzheimer's disease. Clin. Neuropsychol. 24, 1355–1364. Klunk, W.E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D.P., Bergstrom, M., Savitcheva, I., Huang, G.F., Estrada, S., Ausen, B., Debnath, M.L., Barletta, J., Price, J.C., Sandell, J., Lopresti, B.J., Wall, A., Koivisto, P., Antoni, G., Mathis, C.A., Langstrom, B., 2004. Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann. Neurol. 55, 306–319. Lastres-Becker, I., Cebeira, M., De Ceballos, M.L., Zeng, B.Y., Jenner, P., Ramos, J.A., Fernandez-Ruiz, J.J., 2001. Increased cannabinoid CB1 receptor binding and activation of GTP-binding proteins in the basal ganglia of patients with Parkinson's syndrome and of MPTP-treated marmosets. Eur. J. Neurosci. 14, 1827–1832. Ledent, C., Valverde, O., Cossu, G., Petitet, F., Aubert, J.F., Beslot, F., Bohme, G.A., Imperato, A., Pedrazzini, T., Roques, B.P., Vassart, G., Fratta, W., Parmentier, M., 1999. Unresponsiveness to cannabinoids and reduced addictive effects of opiates in CB1 receptor knockout mice. Science 283, 401–404. Lee, J.H., Agacinski, G., Williams, J.H., Wilcock, G.K., Esiri, M.M., Francis, P.T., Wong, P.T., Chen, C.P., Lai, M.K., 2010. Intact cannabinoid CB1 receptors in the Alzheimer's disease cortex. Neurochem. Int. 57, 985–989. Mathis, C.A., Kuller, L.H., Klunk, W.E., Snitz, B.E., Price, J.C., Weissfeld, L.A., Rosario, B.L., Lopresti, B.J., Saxton, J.A., Aizenstein, H.J., McDade, E.M., Kamboh, M.I., DeKosky, S.T., Lopez, O.L., 2013. In vivo assessment of amyloid-beta deposition in nondemented very elderly subjects. Ann. Neurol. 73, 751–761. Mazzola, C., Micale, V., Drago, F., 2003. Amnesia induced by betaamyloid fragments is counteracted by cannabinoid CB1 receptor blockade. Eur. J. Pharmacol. 477, 219–225. Morera-Herreras, T., Miguelez, C., Aristieta, A., Ruiz-Ortega, J.A., Ugedo, L., 2012. Endocannabinoid modulation of dopaminergic motor circuits. Front. Pharmacol. 3, 110. Morris, J.C., 1993. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 43, 2412–2414. Nelissen, N., Vandenbulcke, M., Fannes, K., Verbruggen, A., Peeters, R., Dupont, P., Van Laere, K., Bormans, G., Vandenberghe, R., 2007.
250 Abeta amyloid deposition in the language system and how the brain responds. Brain 130, 2055–2069. O’Bryant, S.E., Humphreys, J.D., Smith, G.E., Ivnik, R.J., GraffRadford, N.R., Petersen, R.C., Lucas, J.A., 2008. Detecting dementia with the mini-mental state examination in highly educated individuals. Arch. Neurol. 65, 963–967. Pazos, M.R., Sagredo, O., Fernandez-Ruiz, J., 2008. The endocannabinoid system in Huntington's disease. Curr. Pharm. Des. 14, 2317–2325. Perez, D.M., Karnik, S.S., 2005. Multiple signaling states of G-protein-coupled receptors. Pharmacol. Rev. 57, 147–161. Quarantelli, M., Berkouk, K., Prinster, A., Landeau, B., Svarer, C., Balkay, L., Alfano, B., Brunetti, A., Baron, J.C., Salvatore, M., 2004. Integrated software for the analysis of brain PET/SPECT studies with partial-volume-effect correction. J. Nucl. Med. 45, 192–201. Ramirez, B.G., Blazquez, C., Gomez del, P.T., Guzman, M., De Ceballos, M.L., 2005. Prevention of Alzheimer's disease pathology by cannabinoids: neuroprotection mediated by blockade of microglial activation. J. Neurosci. 25, 1904–1913. Reibaud, M., Obinu, M.C., Ledent, C., Parmentier, M., Bohme, G. A., Imperato, A., 1999. Enhancement of memory in cannabinoid CB1 receptor knock-out mice. Eur. J. Pharmacol. 379, R1–R2. Reiman, E.M., Chen, K., Alexander, G.E., Caselli, R.J., Bandy, D., Osborne, D., Saunders, A.M., Hardy, J., 2004. Functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer's dementia. Proc. Nat. Acad. Sci. U.S.A 101, 284–289. Rodriguez, J.J., Noristani, H.N., Verkhratsky, A., 2012. The serotonergic system in ageing and Alzheimer's disease. Prog. Neurobiol. 99, 15–41. Sanabria-Bohorquez, S.M., Hamill, T.G., Goffin, K., De, L.I., Bormans, G., Burns, H.D., Van, L.K., 2010. Kinetic analysis of the cannabinoid-1 receptor PET tracer [(18)F]MK-9470 in human brain. Eur. J. Nucl. Med. Mol. Imaging 37, 920–933. Skinner, J., Carvalho, J.O., Potter, G.G., Thames, A., Zelinski, E., Crane, P.K., Gibbons, L.E., 2012. The Alzheimer's Disease Assessment Scale-Cognitive-Plus (ADAS-Cog-Plus): an expansion of the ADAS-Cog to improve responsiveness in MCI. Brain Imaging Behav. 6, 489–501. Solas, M., Francis, P.T., Franco, R., Ramirez, M.J., 2013. CB2 receptor and amyloid pathology in frontal cortex of Alzheimer's disease patients. Neurobiol. Aging 34, 805–808. Terranova, J.P., Storme, J.J., Lafon, N., Perio, A., Rinaldi-Carmona, M., Le Fur, G., Soubrie, P., 1996. Improvement of memory in rodents by the selective CB1 cannabinoid receptor antagonist, SR 141716. Psychopharmacology (Berl) 126, 165–172.
R. Ahmad et al. Terry, G., Liow, J.S., Chernet, E., Zoghbi, S.S., Phebus, L., Felder, C.C., Tauscher, J., Schaus, J.M., Pike, V.W., Halldin, C., Innis, R. B., 2008. Positron emission tomography imaging using an inverse agonist radioligand to assess cannabinoid CB1 receptors in rodents. Neuroimage 41, 690–698. Van der Elst, W., van Boxtel, M.P., van Breukelen, G.J., Jolles, J., 2005. Rey's verbal learning test: normative data for 1855 healthy participants aged 24-81 years and the influence of age, sex, education, and mode of presentation. J. Int. Neuropsychol. Soc.: JINS 11, 290–302. Van Laere, K., Casteels, C., Dhollander, I., Goffin, K., Grachev, I., Bormans, G., Vandenberghe, W., 2010. Widespread decrease of type 1 cannabinoid receptor availability in huntington disease in vivo. J. Nucl. Med. 51, 1413–1417. Van Laere, K., Goffin, K., Casteels, C., Dupont, P., Mortelmans, L., de Hoon, J., Bormans, G., 2008. Gender-dependent increases with healthy aging of the human cerebral cannabinoid-type 1 receptor binding using [(18)F]MK-9470 PET. Neuroimage 39, 1533–1541. Van Laere, K., Nuttin, B., Gabriels, L., Dupont, P., Rasmussen, S., Greenberg, B.D., Cosyns, P., 2006. Metabolic imaging of anterior capsular stimulation in refractory obsessive-compulsive disorder: a key role for the subgenual anterior cingulate and ventral striatum. J. Nucl. Med. 47, 740–747. Videaud, H., Torny, F., Prado-Jean, A., Couratier, P., 2008. Use of the Visual Object and Space Perception (VOSP) test battery in two cases of posterior cortical atrophy. Neurocase 15, 32–36. Villemagne, V.L., Pike, K.E., Chetelat, G., Ellis, K.A., Mulligan, R. S., Bourgeat, P., Ackermann, U., Jones, G., Szoeke, C., Salvado, O., Martins, R., O’Keefe, G., Mathis, C.A., Klunk, W.E., Ames, D., Masters, C.L., Rowe, C.C., 2011. Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann. Neurol. 69, 181–192. Walsh, S., Mnich, K., Mackie, K., Gorman, A.M., Finn, D.P., Dowd, E., 2010. Loss of cannabinoid CB1 receptor expression in the 6-hydroxydopamine-induced nigrostriatal terminal lesion model of Parkinson's disease in the rat. Brain Res. Bull. 81, 543–548. Walther, S., Mahlberg, R., Eichmann, U., Kunz, D., 2006. Delta-9tetrahydrocannabinol for nighttime agitation in severe dementia. Psychopharmacology (Berl) 185, 524–528. Westlake, T.M., Howlett, A.C., Bonner, T.I., Matsuda, L.A., Herkenham, M., 1994. Cannabinoid receptor binding and messenger RNA expression in human brain: an in vitro receptor autoradiography and in situ hybridization histochemistry study of normal aged and Alzheimer's brains. Neuroscience 63, 637–652.
www.elsevier.com/locate/euroneuro
In vivo type 1 cannabinoid receptor availability in Alzheimer's disease Rawaha Ahmada,b,n, Karolien Goffina,b, Jan Van den Stockc,d, François-Laurent De Winterc,d, Evy Cleerena,b, Guy Bormanse, Jos Tournoyf,g, Philippe Persoonsc,d, Koen Van Laerea,b, Mathieu Vandenbulckec,d a
Nuclear Medicine and Molecular Imaging, University Hospitals Leuven, Belgium Department of Imaging & Pathology, KU Leuven, Belgium c Department of Old Age Psychiatry, University Hospitals Leuven, Belgium d Department of Neurosciences, KU Leuven, Belgium e Laboratory for Radiopharmacy, KU Leuven, Belgium f Geriatric Medicine, University Hospitals Leuven, Belgium g Department of Clinical and Experimental Medicine, KU Leuven, Belgium b
Received 5 August 2013; received in revised form 4 October 2013; accepted 9 October 2013
KEYWORDS
Abstract
Alzheimer's disease; Cannabinoid receptor; Amyloid; PET scan; MMSE; ApoE
The endocannabinoid system (ECS) is an important modulatory and potentially neuroprotective homeostatic system in the brain. In Alzheimer's disease (AD), the role of type 1 cannabinoid receptor (CB1R) is unclear, with contradictory findings in post-mortem studies showing upregulation, downregulation or unchanged CB1R status. We have investigated CB1R availability in vivo in patients with AD, in relation to amyloid deposition, cognitive functioning and apolipoprotein E (ApoE) genotype. Eleven AD patients and 7 healthy volunteers (HV) underwent combined [18F]MK-9470 PET and [11C]PIB PET scans to assess CB1R availability and amyloid deposition, respectively, and T1 volumetric MRI for partial volume correction. We found no difference in CB1R availability between AD and HV, VOI-based fractional uptake values (FUR) were 0.04370.01 for AD and 0.04570.01 for controls (p=0.9). CB1R availability did not correlate with neuropsychological test scores and was not modulated by ApoE genotype. As expected, global [11C]PIB SUVR (standardized uptake value ratio) was increased in AD (SUVR 1.970.3) compared to HV (1.270.1) with po0.001, but no correlation was found between amyloid β (Aβ) deposition and CB1R availability. In conclusion, we found no in vivo evidence for a difference in CB1R availability in AD compared to age-matched controls. Taken together with recently reported in vivo CB1R changes in Parkinson's and Huntington's disease, these data suggest that the CB1R is differentially involved in neurodegenerative disorders. & 2013 Elsevier B.V. and ECNP. All rights reserved.
n
Correspondence to: Division of Nuclear Medicine E901, University Hospital Leuven, Herestraat 49, B-3000 Leuven, Belgium. Tel.: +32 16 343715; fax: +32 16 343759. E-mail address: [email protected] (R. Ahmad). 0924-977X/$ - see front matter & 2013 Elsevier B.V. and ECNP. All rights reserved. http://dx.doi.org/10.1016/j.euroneuro.2013.10.002
CB1 PET in Alzheimer's disease
1.
Introduction
Impairment of the cholinergic system and its relation to cognitive dysfunction is well-known in Alzheimer's disease (AD). Various other neurotransmitter systems (e.g. the serotonergic system (Rodriguez et al., 2012)) and concomitant changes of associated receptors and synthetic enzymes have been related to cognitive and behavioral changes. Recent advances in the characterization of different functions of the endocannabinoid system (ECS) suggest that this neurotransmitter system may also play a role in the pathophysiology of AD in different ways as well as in the pathogenesis of cognitive dysfunction. The ECS is generally viewed as a neuromodulatory system that interacts with, and regulates several neurotransmitter systems (Terranova et al., 1996). Growing evidence also shows that type 1 cannabinoid receptors (CB1R) play a fundamental role in neuroprotection including in AD (Aso et al., 2012). In vitro experiments suggest that endogenous cannabinoids promote changes in neural activity related to memory, with a role in long-term plasticity (Ramirez et al., 2005). Overall, in vivo experiments with mice have been ambiguous, with reports of both impaired and enhanced memory performance (Ledent et al., 1999; Reibaud et al., 1999). Administration of CB1R antagonists improved memory in a rodent model of AD, probably through modulation of acetylcholine (Ach) levels (Davies et al., 2002). On the other hand, it has also been shown that chronic administration of the CB1R agonist arachidonyl-2-chloroethylamide (ACEA) reduces cognitive impairment observed in double AβPP(swe)/PS1(1dE9) transgenic mice probably through GSK3β inhibition, reduction of reactive astrocytes and lower expression of interferon-γ (Aso et al., 2012). CB1Rs are also involved in mediating the Aβ neurotoxicity and in protecting against amnesia in hippocampal learning tasks. SR141716A, a CB1R antagonist, improves amnesia induced by Aβ fragments in mice, suggesting that endogenous cannabinoids may be involved in cognitive impairment induced by these fragments (Mazzola et al., 2003). In humans, Walther et al. showed significant improvement of the Neuropsychiatric Inventory scores in late onset dementia after a daily administration of dronabinol, a cannabinoid agonist (Walther et al., 2006). Post-mortem studies in AD on the role of the CB1R and its relation to cognitive function at end-of-life remain unclear. Ramirez et al. reported loss of CB1R – positive neurons in the frontal cortex of AD patients, decreased CB1 protein expression and G-protein decoupling, despite preserved density and binding of the receptor (Ramirez et al., 2005). They also showed consistent CB1R immunoreactivity in senile plaques along with markers of microglial activation, suggesting a direct involvement of these receptors in the effects of microglia. In contrast, Westlake et al. found reduced CB1R density in several areas including the entorhinal cortex and hippocampus, but no association between reduced CB1R expression and neuropathological signs of AD (Westlake et al., 1994). Benito et al. found no changes in CB1R density in the proximity of neuritic plaques (Benito et al., 2003) and also other recent studies described preserved expression of CB1R, even in severe AD (Farkas et al., 2012; Lee et al., 2010). Over the past years, several positron emission tomography (PET) radioligands have been developed that allow in vivo quantification of the CB1R distribution, such as [18F]MK-9470
243 (Burns et al., 2007; Sanabria-Bohorquez et al., 2010), [11C] OMAR (Horti et al., 2006) and [18F]MPePP (Terry et al., 2008). The aim of this study was to measure the in vivo CB1R status in AD in relation to Aβ deposition, cognitive parameters and apolipoprotein E (ApoE) genotype. We therefore conducted a prospective, cross-sectional multitracer study using [18F]MK9470 and [11C]PIB in mild to moderate AD patients and healthy controls.
2. 2.1.
Experimental procedure Subjects
AD patients had to meet following inclusion criteria: (1) Z55 years of age; (2) diagnosis of probable AD according to the NINCDS-ADRDA Criteria (Dubois et al., 2007); (3) magnetic resonance imaging (MRI) scan obtained within the last 12 months consistent with a diagnosis of AD; (4) Modified Hachinski Ischemic Scale (MHIS) score of r4; (5) global CDR (Clinical Dementia Rating score) (Morris, 1993) between 1 and 3, or, if the Global CDR is 0.5, then CDR Sum of Boxes of at least 3.5; (6) at least six years of education, or work history sufficient to exclude mental retardation, and (7) a positive [11C]PIB PET scan. Thirteen patients with probable AD (5 men (M), 8 women (F); age range 57.6–81.8 years) were screened. Two male patients fulfilling screening criteria 1–6 but with a negative [11C]PIB PET scan, were excluded from the study. The patient group therefore consisted of 3 M and 8 F patients (age range 57.6–80.9 years). AD patients were compared to a group of 7 healthy cognitive intact and age-matched elderly volunteers (3 men, 4 women; age range 61.3–79.0 years). These volunteers were prospectively recruited in response to advertisements in local community newspapers and departmental website.
2.2.
Neuropsychological evaluation
All subjects underwent thorough neuropsychological evaluation. The following tests were conducted: Dutch version of the minimental state examination (MMSE) (O’Bryant et al., 2008), auditory verbal learning test (AVLT) (Balthazar et al., 2010; Van der Elst et al., 2005), Boston naming test (BNT) (Karrasch et al.), Raven's colored progressive matrices test (RCPMT), the subtest Object Decision (OD) of the visual object and space perception test (VOSP) (Videaud et al., 2008), clinical dementia rating (CDR) scale (Morris, 1993), the cognitive part of the Alzheimer's disease assessment scale (ADAS-cog) (Skinner et al., 2012), neuropsychiatric inventory (NPI) (Cummings, 1997), Alzheimer's disease cooperative study – activities of daily living (ADCS-ADL) (Galasko et al., 1997), and geriatric depression scale (GDS) (Albinski et al., 2011). Only MMSE and AVLT (total learning (A1–A5), delayed and recognition scores of the AVLT), measures of global cognitive functioning and episodic memory respectively, were used for correlation analyses with CB1R availability. CDR sum of boxes was used as a variable of interest in the correlation analysis with AVLT scores. We have also added the maximum scores to Table 1. Blood sampling for ε4 allele(s) of ApoE ε4 was done in all except one subject that died shortly after the PET scans. The study was approved by the local Ethics Committee and performed in accordance to the latest version of the World Medical Association Declaration of Helsinki. Written informed consent was obtained from healthy controls, subjects with AD and from their primary caregivers, prior to the study.
2.3.
Radiotracer characteristics and preparation
The [18F]MK-9470 precursor was obtained from Merck Research Laboratories and labeled at the PET site using 18F-ethylbromide
244
R. Ahmad et al.
Table 1
Demographic variables and neurocognitive tests in healthy volunteers (HV) and Alzheimer's disease (AD) patients.
Subject
Gender
Age at study
ApoE
MMSE (/30)
Total A1-A5 (/75)
Delayed AVLT (/15)
Recognition AVLT (/15)*
HV 1 HV 2 HV 3 HV 4 HV 5 HV 6 HV 7 Mean SD AD 1 AD 2 AD 3 AD 5 AD 7 AD 8 AD 9 AD 10 AD 11 AD 12 AD 13 Mean SD p-value (Student-t)
F M F F F M M
62.0 79.0 75.9 69.1 61.3 62.3 66.4 68.0 6.5 72.8 71.0 80.9 65.5 81.3 72.4 68.5 57.6 70.7 64.5 70.9 71.8 6.8 0.3
/ / / +/ / / +/
29 27 25 29 28 29 30 28 2 20 22 25 20 24 13 11 23 14 23 23 20 4 o0.001
44 29 35 53 33 38 58 41 10 5 22 21 23 21 2 12 47 4 23 21 18 11 o0.001
7 4 6 11 8 9 10 8 2 0 0 1 0 0 0 3 8 0 0 3 1 2 r0.001
13 10 15 14 11 15 12 13 2 2 1 9 4 2 1 5 15 7 5 6 5 4 r0.001
F F F F M F F F M F M
/ + /+ / Died + /+ +/ / / +/ + /+ + /+
HV: healthy volunteer; AD: AD Alzheimer's disease patient; ApoE ε 4 apolipoprotein homozygote +/+, heterozygote +/ , negative / ; MMSE minimental state examination; AVLT auditory verbal learning test. n Range 15 to +15 (Van der Elst et al., 2005); SD standard deviation.
(Burns et al., 2007). Specific activity was 4140 GBq/mmol, the maximum amount of cold MK-9470 injected was o10 mg. [11C]PIB was produced on-site according to standard procedures (Nelissen et al., 2007). Specific activity for [11C]PIB was 4260 GBq/mmol.
2.4.
Imaging procedure
All patients fasted for at least 4 h prior to [18F]MK-9470 PET imaging. Subjects received on average 237 MBq (range 168– 253 MBq) of [18F]MK-9470 and 283 MBq (range 195–329 MBq) of [11C]PIB, with slow intravenous injection under low ambient noise and dimly lit room. PET imaging was performed in 3D mode on a HiRez Biograph16 PET-CT camera (Knoxville, TN, USA;). The subject's head was placed in a head holder and fixed using a vacuum mask to avoid excessive head movement. A low dose (80 kV tube potential, 11 mAs) CT scan was conducted at the beginning of each PET scan for attenuation correction. For [18F]MK-9470 imaging, an emission scan of 60 min (6 10 min) was started 120 min after injection. For [11C]PIB imaging, a dynamic PET emission scan of 30 min was started 40 min after injection (6 frames of 5 min). Images were reconstructed using a 3-dimension ordered subsets expectation-maximization (3D OSEM) iterative reconstruction with 5 iterations and 8 subsets and post smoothing with a 3D isotropic Gaussian (full-width-at-half-maximum (FWHM) of 6 mm).
2.5.
Image processing and data analysis
All subjects also underwent high-resolution MRI, both T1-weighted magnetization prepared rapid acquisition gradient echo (3D-
MPRAGE) and T2-weighted, on a 1.5 Tesla Vision Scanner (Siemens, Germany). Correction for subject motion was performed using the realignment module in statistical parametric mapping version 8 (SPM8) (Welcome Department of Cognitive Neuroscience, London, UK). A summed PET image was created by adding realigned frames. [18F]MK-9470 availability was expressed as fractional uptake ratio (FUR) value, calculated as the ratio of total radioactivity concentration in tissue at the end of the scan and the integral of metabolite-corrected plasma radioactivity from time of injection to the end of the scan (Sanabria-Bohorquez et al., 2010). To obtain FUR values, venous blood samples for radioactivity counting were taken manually from all participants at various time points following injection: 2, 5, 10, 20, 40, 60, 90, 120 and 180 min. Metabolite analysis and [18F]MK-9470 free fraction measurements were performed as described previously (Van Laere et al., 2008). For [11C]PIB imaging, SUVR values were used as a measure of Aβ binding. SUVR was defined as the regional tracer uptake in the summed emission image, normalized to the mean uptake in the cerebellar cortex as defined on the subject's MRI, as it is notably free of fibrillar plaques (Klunk et al., 2004). PET data were corrected for atrophy by post-hoc partial volume correction (PVC) on the reconstructed data, using the Alfano method in the PVEOut software (Quarantelli et al., 2004). Segmentation of T1 MPRAGE images was performed using SPM8. For PVC, PET data were coregistered to the segmented MRI data set. For each subject, parametric FUR and SUVR images were spatially normalized to the standard MNI space. For further voxelbased analyses, data were smoothed with an isotropic Gaussian kernel with a FWHM of 8 mm. A statistical parametric mapping analysis (two sample t-test) was performed for [18F]MK-9470 and
CB1 PET in Alzheimer's disease [11C]PIB data comparing patients to controls in a categorical subject design with and without age and gender as nuisance variables (groups were age-matched see Table 1), since CB1R availability is different for men and women and increases with age in women (Van Laere et al., 2008). When no global group differences were present, a regional analysis was conducted for [18F]MK-9470. In this case, proportional scaling was used with a relative analysis threshold of 80% of the mean, in order to exclude non-gray matter activity. We explored group differences using pheighto0.05 corrected for multiple comparisons with an extend threshold kext450 voxels ( 0.4 cm3). In addition to an analysis of group differences, a correlation analysis with memory tests (MMSE, AVLT) and ApoE genotype was performed in SMP8 using multiple regression analysis at an exploratory pheighto0.001 uncorrected. Additionally, a voxel by voxel comparison of the PIB and FUR PET scan was performed using BPM (biological parametric mapping) version 1.5d beta. Secondly, a volume-of interest (VOI) analysis was performed using PMOD v3.0 using VOIs for striatum, frontal, temporal, mesotemporal, parietal, occipital, central insular and cingulate cortex (Van Laere et al., 2006). Additionally, all subjects were divided in different groups according to their ApoE status. The analysis was done voxel based (non-parametric t-test for independent samples) and spm analysis was performed using two sample t-test. In the spm analysis we found no significant clusters comparing these groups. Additionally, we subdivided all subjects according to their ApoE status and compared the subgroups using VOI based (non-parametric t-test for independent samples) and voxel based spm (two sample t-test) analysis. Conventional statistics were performed using Statistica v10.0 (Statsoft Inc, Tulsa, OK, USA). To ensure robustness of data, the same procedure was also applied to the non-partial volume corrected datasets for CB1 and amyloid imaging.
3. 3.1.
Results Neuropsychological evaluation and ApoE
Table 1 shows the demographic variables and the main results of the neurocognitive evaluation (MMSE and AVLT) for all subjects. Highly significant differences (mean7SD; two sided t-test p-value) were present in MMSE (Table 1), AVLT (Table 1), ADAS (HV: 5.772.5; AD 22.8712.3; p=0.002) and, RCPMT (HV: 3074.2; AD: 18.577.6; p=0.002). NPI (17.8716.8), ADSC-ADL (43.9713.8) and CDR sum of boxes (14.573.0) were only obtained in the AD patients (mean 7 SD). BNT (HV: 46.8717.8; AD: 36.6713.9; p=0.17), OD (VOSP) (HV: 16.872.1; AD: 14.573.0; p=0.26) and GDS (HV: 4.374.4; AD: 7.374.8; p=0.20) did not show significant differences. Four patients and 5 controls were APOE ε4 negative, 2 patients and 2 controls were heterozygous and 4 patients were homozygous. One patient died during the course of the study and has an unknown ApoE status.
245
3.3. Relation between CB1R availability and PIB binding As expected, in the voxel-based analysis global [11C]PIB SUVR values were significantly increased in AD patients compared to HV. This was confirmed by VOI based analysis with [11C]PIB SUVR 1.970.3 and HV 1.270.1 (po0.001) (Figure 1B). Figure 2 shows the average parametric maps of CB1 receptor availability (FUR) and PIB SUVR parametric maps for HV and AD patients. Figure 1C depicts a scatter plot of global CB1R availability and PIB binding in AD patients and HVs. In this graph, ApoE ε4 genotype is indicated for each subject. No significant correlation was found between regional or global PIB binding and CB1R availability using voxel-wise and VOI-based analysis.
3.4.
We found no correlation between CB1R availability and neuropsychological tests (MMSE and AVLT). To overcome floor effects (especially for the AVLT Delayed Recall) and to take functional parameters into account, we additionally performed the correlation with CDR sum of boxes as a variable of interest, but again found no correlation between regional CB1R availability and AVLT scores (Total Learning AVLT: r2 = 0.46 and p =0.11; Delayed Recall AVLT:r2 = 0.32 and p 0.31; Recognition AVLT r2 = 0.24 and p= 0.44) (data not shown). For patient 10 the AVLT scores were remarkably high, but this had no effects on our results.
3.5.
No significant group differences were found regarding global CB1R availability using voxel-based analysis. This was confirmed by VOI-based analysis (FUR AD patients 0.0470.01 and HV 0.0570.01, p= 0.9). Effect size measured with Cohen's d were small (between 0.19 and 0.25) (Figure 1A).
Effect of ApoE status
In the ApoE ε4 negative and heterozygous group there was a wide variation in CB1R availability as well as PIB binding. For the ApoE ε4 homozygous group (25%), PIB-binding was in the highest range (PIB SUVR mean 1.7–2.0), the CB1R availability was high for three out of four subjects (mean cortical FUR 0.05–0.06), but low for one subject (FUR 0.03). However, no significant differences between groups were found (Figure 3): ApoE homozygous patients versus ApoE heterozygous and negative patients: p= 0.44; ApoE positive (homozygous and heterozygous) versus ApoE negative patients: p= 0.62; ApoE homozygous patient versus ApoE negative and heterozygous patients and controls: p= 0.53. Also in the spm analysis we found no significant differences between these groups. All results were the same when data uncorrected for partial volume effects were used, indicating the robustness of these findings.
4. 3.2. Group comparison of CB1R availability in AD patients vs. HV
Correlation with cognitive functioning
Discussion
Using [18F]MK-9470 PET, we report the first quantitative in vivo study of CB1R PET in AD, providing whole-brain information by use of a highly-selective and high-affinity compound (Burns et al., 2007). We did not find any changes of CB1R availability in vivo throughout the brain in AD patients compared to HV, nor a relationship with regional Aβ plaque density measured by [11C]PIB PET.
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R. Ahmad et al.
Figure 1 (A) (upper) Bar chart of CB1R FUR values per volume of interest for Alzheimer's patients (AD) and healthy volunteers (HV) before and after PVC. FUR is decreased in all cortical regions and comparable in the striatum in AD versus controls. These differences are not significant (p =0.83). Effect sizes (Cohen's d) are presented above the bars per volume of interest. (B) (middle) Bar chart of global [11C]PIB-standard uptake value ratio's (SUVR) for regions of interest. Error bars indicate standard deviation (SD). The PIB binding is significantly increased in all AD patients compared to controls (po0.001). (C) (lower) Scatter plot of global CB1R availability and PIB binding (SUVR) in AD patients and HVs.
Our study is in agreement with the majority of postmortem studies that suggest no quantitative changes of CB1R availability in human AD. Benito et al. used Western blotting and immunohistochemistry and reported a selective overexpression of FAAH (fatty acid amide hydrolase) and CB2R protein in glial cells, but no changes in CB1R density in the proximity of neuritic plaques (Benito et al., 2003). The lack of association between amyloid pathology measured by [11C]PIB PET and CB1R availability in our study provides in vivo confirmation of this observation. Ramirez et al. also reported alterations of the endocannabinoid system
including decreased CB1 protein expression and G-protein decoupling, but density and binding of the CB1R was preserved (Ramirez et al., 2005). It is important to note that our [18F]MK-9470 PET imaging technique was used to quantify CB1R availability but does not allow to draw conclusions on the functional state of the receptor (activated or deactivated state). Two more recent studies also suggest preserved expression of CB1R, even in severe AD (Farkas et al., 2012; Lee et al., 2010). Lee et al. used immunoblotting and radioligand binding on brain tissue from frontal cortex, anterior cingulate gyrus, hippocampus and
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Figure 2 (A) Average parametric maps of CB1R availability (FUR) for HV and (B) AD patients. (C) Average PIB SUVR parametric maps for HV and (D) AD patients.
Figure 3 Mean CB1R availability (upper panel) and mean PIB binding (lower panel) for the study population, divided in groups by ApoE ε4 status. Bar shows mean.
caudate nucleus to assess changes in CB1R. Farkas et al. examined prefrontal cortex tissue from different Braak stages using autoradiography with a CB1R agonist
radioligand 125I-SD-7015 and showed a preserved CB1R in Braak stages III–IV. Our findings do not support the observation of Westlake et al. who reported a reduced CB1R density
248 in several areas including the entorhinal cortex and hippocampus, which was not associated with neuropathological measures of AD. The latter observation was interpreted as a consequence of normal aging, resulting in extensive neuronal loss and reduced density of synapses (Westlake et al., 1994). However, an age-dependent reduction of CB1R has not been confirmed. In contrast, CB1R availability may rather increase with age especially in the memory, limbic and motor circuit (Van Laere et al., 2008). The compound used in the study by Westlake and coworkers, is an agonist for both the CB1R and CB2R. It is however unlikely that this would provide an explanation for the decreased CB1R because CB2R is overexpressed in AD (Solas et al., 2013), which would rather lead to an overestimation (Westlake et al., 1994). It has been suggested that CB1R availability may relate to cognitive functioning in AD. Lee et al. reported unchanged CB1R availability in AD on the whole, but a subgroup of patients with relatively high levels of CB1R in the frontal cortex showed better cognitive function (Lee et al., 2010). It was hypothesized that this might have to do with improved regulation of glutamate release and thus better control of excitotoxicity. However, we were not able to confirm this finding as we did not find any correlation between the CB1R availability and cognitive functioning (measured by MMSE and AVLT). The relatively low number of participants in our study should be taken into account and does not allow us to make firm conclusions in this respect. We also investigated the relation between CB1R availability and ApoE genotype. The presence of ApoE ε4 has been associated with more severe memory impairment and an earlier age of onset (Corder et al., 1993). Pathological studies, spinal fluid markers, and Aβ imaging have shown that Aβ accumulation increases in association with advanced age and presence of the ApoE ε4 allele, even in the absence of cognitive symptoms (Reiman et al., 2004; Villemagne et al., 2011). However, there are no previous data about a relation of ApoE ε4 genotype and the ECS. We did not find a clear association between CB1R availability and ApoE ε4 genotype using VOI-based or voxel-wise analysis. We noticed that 3 out of 4 ApoE ε4 homozygous individuals had CB1R availability in the upper range but more work is needed to investigate the role of the ECS in ApoE ε4 carriers with AD. One of the critical issues in research on neurodegenerative disorders is the specificity of findings. Recently, the CB1R has been investigated in different neurodegenerative disorders. In Huntington's disease (HD), post-mortem studies showed an early decrease of the CB1R availability in the brain (Glass et al., 2000; Glass et al., 1993), a finding confirmed in vivo with the same radioligand as used in the current study (Van Laere et al., 2010), and likely due to CB1R transcription interference of mutant huntingtin. In contrast to this uniform reduction of CB1R availability throughout the entire gray matter in HD, in Parkinson's disease (PD), the CB1R availability shows remarkable regional heterogeneity. Studies on CB1R protein levels in the substantia nigra of PD animals and post-mortem substantia nigra from PD patients have provided mixed findings with decreased, biphasic response or unchanged CB1R levels (Garcia-Arencibia et al., 2009; Lastres-Becker et al., 2001; Walsh et al., 2010). Together with findings in the current
R. Ahmad et al. study, it seems that the ECS is differentially affected in various neurodegenerative disorders. This may be related to direct or indirect effects on glutamate, GABA and dopamine that plays a central role both in HD and PD (Morera-Herreras et al., 2012; Pazos et al., 2008). Dopamine is much less involved in AD. Other systems that are preferentially affected in AD, such as the acetylcholinergic system, have shown a less direct link to the ECS (Davies et al., 2002). The main limitation of our study is the small sample size. Because we did not find any trend towards a difference between AD and controls at group level (Figures 1 and 2), we do not believe that a larger sample size would change the main finding, especially since the effect sizes are small ( 0.19 to 0.25, Figure 1A). However, as noted above more subtle associations with cognitive profile may have been concealed. Secondly, it is important to bear in mind that, using [18F]MK-9470 PET imaging, we have only studied one specific aspect of the ECS being the CB1R availability. Yet, the functional or the signaling state (Perez and Karnik, 2005) of CB1R in AD may well be altered and even contribute to the pathophysiology of AD (Ramirez et al., 2005). Our study overcomes a number of serious limitations associated with post-mortem studies including protein degradation, inclusion of a limited number of brain regions and retrospective correlations with clinical evaluation such as cognitive function in AD. It should be noted that a positive PIB PET scan was used as one of the inclusion criteria for AD subjects in order to study the relationship between CB1R status and amyloid deposition. However, although a PIB-scan may support a diagnosis of AD, it should be emphasized that a positive scan in itself is not diagnostic of AD nor a clear marker of cognitive status (Aizenstein et al., 2008; Mathis et al., 2013). These findings underscore the importance of including both PIB as well as cognitive functioning when exploring the relationship with a third variable. In conclusion, we found no in vivo evidence for a difference in CB1R availability in AD compared to age-matched controls, indicating that the CB1R may be differentially involved in neurodegenerative proteinopathies when compared to published results in Parkinson's and Huntington's disease.
Role of the funding source This project was supported by the Flemish Foundation for Science (FWO Vlaanderen) (grant G.0493.10N). FWO had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Contributors Authors Koen Van Laere and Mathieu Vandenbulcke designed the study and wrote the protocol. Jan Van den Stock, François-Laurent De Winter did the neuropsychological testing. Jos Tournoy, Philippe Persoons and Mathieu Vandenbulcke recruited all the patients. Evy Cleeren was responsible for imaging. Guy Bormans was responsible for radioligand preparation. Rawaha Ahmad and Karolien Goffin managed the literature searches, statistical analyses and they also wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
CB1 PET in Alzheimer's disease
Conflict of interest All authors declare that they have no conflict of interest.
Acknowledgments Merck & Co. Inc. is acknowledged for the availability of the [18F]MK9470 precursor. We also thank Kwinten Porters, Mieke Steukers and the Leuven PET radiopharmacy team for their skilled contributions in patient handling and radiopharmaceutical preparation. This project was supported by the Flemish Foundation for Science (FWO Vlaanderen) (Grant G.0493.10N). FWO had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
References Aizenstein, H.J., Nebes, R.D., Saxton, J.A., Price, J.C., Mathis, C.A., Tsopelas, N.D., Ziolko, S.K., James, J.A., Snitz, B.E., Houck, P.R., Bi, W., Cohen, A.D., Lopresti, B.J., DeKosky, S.T., Halligan, E.M., Klunk, W.E., 2008. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch. Neurol. 65, 1509–1517. Albinski, R., Kleszczewska-Albinska, A., Bedynska, S., 2011. [Geriatric Depression Scale (GDS). Validity and reliability of different versions of the scale—review]. Psychiatr. Pol. 45, 555–562. Aso, E., Palomer, E., Juves, S., Maldonado, R., Munoz, F.J., Ferrer, I., 2012. CB1 agonist ACEA protects neurons and reduces the cognitive impairment of AbetaPP/PS1 mice. J. Alzheimer's Dis.: JAD 30, 439–459. Balthazar, M.L., Yasuda, C.L., Cendes, F., Damasceno, B.P., 2010. Learning, retrieval, and recognition are compromised in aMCI and mild AD: are distinct episodic memory processes mediated by the same anatomical structures? J. Int. Neuropsychol. Soc. 16, 205–209. Benito, C., Nunez, E., Tolon, R.M., Carrier, E.J., Rabano, A., Hillard, C.J., Romero, J., 2003. Cannabinoid CB2 receptors and fatty acid amide hydrolase are selectively overexpressed in neuritic plaque-associated glia in Alzheimer's disease brains. J. Neurosci. 23, 11136–11141. Burns, H.D., Van Laere, K., Sanabria-Bohorquez, S., Hamill, T.G., Bormans, G., Eng, W.S., Gibson, R., Ryan, C., Connolly, B., Patel, S., Krause, S., Vanko, A., Van Hecken, A., Dupont, P., De Lepeleire, I., Rothenberg, P., Stoch, S.A., Cote, J., Hagmann, W. K., Jewell, J.P., Lin, L.S., Liu, P., Goulet, M.T., Gottesdiener, K., Wagner, J.A., de Hoon, J., Mortelmans, L., Fong, T.M., Hargreaves, R.J., 2007. [18F]MK-9470, a positron emission tomography (PET) tracer for in vivo human PET brain imaging of the cannabinoid-1 receptor. Proc. Nat. Acad. Sci. U.S.A 104, 9800–9805. Corder, E.H., Saunders, A.M., Strittmatter, W.J., Schmechel, D.E., Gaskell, P.C., Small, G.W., Roses, A.D., Haines, J.L., PericakVance, M.A., 1993. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science 261, 921–923. Cummings, J.L., 1997. The neuropsychiatric inventory: assessing psychopathology in dementia patients. Neurology 48, S10–S16. Davies, S.N., Pertwee, R.G., Riedel, G., 2002. Functions of cannabinoid receptors in the hippocampus. Neuropharmacology 42, 993–1007. Dubois, B., Feldman, H.H., Jacova, C., DeKosky, S.T., BarbergerGateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., Meguro, K., O’Brien, J., Pasquier, F., Robert, P., Rossor, M., Salloway, S., Stern, Y., Visser, P.J., Scheltens, P., 2007. Research criteria for the diagnosis of Alzheimer's
249 disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 6, 734–746. Farkas, S., Nagy, K., Palkovits, M., Kovacs, G.G., Jia, Z., Donohue, S., Pike, V., Halldin, C., Mathe, D., Harkany, T., Gulyas, B., Csiba, L., 2012. [(125)I]SD-7015 reveals fine modalities of CB (1) cannabinoid receptor density in the prefrontal cortex during progression of Alzheimer's disease. Neurochem. Int. 60, 286–291. Galasko, D., Bennett, D., Sano, M., Ernesto, C., Thomas, R., Grundman, M., Ferris, S., 1997. An inventory to assess activities of daily living for clinical trials in Alzheimer's disease. The Alzheimer's disease cooperative study. Alzheimer Dis. Assoc. Disord. 11 (Suppl 2), S33–S39. Garcia-Arencibia, M., Garcia, C., Fernandez-Ruiz, J., 2009. Cannabinoids and Parkinson's disease. CNS Neurol. Disord. Drug Targets 8, 432–439. Glass, M., Dragunow, M., Faull, R.L., 2000. The pattern of neurodegeneration in Huntington's disease: a comparative study of cannabinoid, dopamine, adenosine and GABA(A) receptor alterations in the human basal ganglia in Huntington's disease. Neuroscience 97, 505–519. Glass, M., Faull, R.L., Dragunow, M., 1993. Loss of cannabinoid receptors in the substantia nigra in Huntington's disease. Neuroscience 56, 523–527. Horti, A.G., Fan, H., Kuwabara, H., Hilton, J., Ravert, H.T., Holt, D.P., Alexander, M., Kumar, A., Rahmim, A., Scheffel, U., Wong, D.F., Dannals, R.F., 2006. 11C-JHU75528: a radiotracer for PET imaging of CB1 cannabinoid receptors. J. Nucl. Med. 47, 1689–1696. Karrasch, M., Myllyniemi, A., Latvasalo, L., Soderholm, C., Ellfolk, U., Laine, M., 2010. The diagnostic accuracy of an incidental memory modification of the Boston Naming Test (memo-BNT) in differentiating between normal aging and mild Alzheimer's disease. Clin. Neuropsychol. 24, 1355–1364. Klunk, W.E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D.P., Bergstrom, M., Savitcheva, I., Huang, G.F., Estrada, S., Ausen, B., Debnath, M.L., Barletta, J., Price, J.C., Sandell, J., Lopresti, B.J., Wall, A., Koivisto, P., Antoni, G., Mathis, C.A., Langstrom, B., 2004. Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann. Neurol. 55, 306–319. Lastres-Becker, I., Cebeira, M., De Ceballos, M.L., Zeng, B.Y., Jenner, P., Ramos, J.A., Fernandez-Ruiz, J.J., 2001. Increased cannabinoid CB1 receptor binding and activation of GTP-binding proteins in the basal ganglia of patients with Parkinson's syndrome and of MPTP-treated marmosets. Eur. J. Neurosci. 14, 1827–1832. Ledent, C., Valverde, O., Cossu, G., Petitet, F., Aubert, J.F., Beslot, F., Bohme, G.A., Imperato, A., Pedrazzini, T., Roques, B.P., Vassart, G., Fratta, W., Parmentier, M., 1999. Unresponsiveness to cannabinoids and reduced addictive effects of opiates in CB1 receptor knockout mice. Science 283, 401–404. Lee, J.H., Agacinski, G., Williams, J.H., Wilcock, G.K., Esiri, M.M., Francis, P.T., Wong, P.T., Chen, C.P., Lai, M.K., 2010. Intact cannabinoid CB1 receptors in the Alzheimer's disease cortex. Neurochem. Int. 57, 985–989. Mathis, C.A., Kuller, L.H., Klunk, W.E., Snitz, B.E., Price, J.C., Weissfeld, L.A., Rosario, B.L., Lopresti, B.J., Saxton, J.A., Aizenstein, H.J., McDade, E.M., Kamboh, M.I., DeKosky, S.T., Lopez, O.L., 2013. In vivo assessment of amyloid-beta deposition in nondemented very elderly subjects. Ann. Neurol. 73, 751–761. Mazzola, C., Micale, V., Drago, F., 2003. Amnesia induced by betaamyloid fragments is counteracted by cannabinoid CB1 receptor blockade. Eur. J. Pharmacol. 477, 219–225. Morera-Herreras, T., Miguelez, C., Aristieta, A., Ruiz-Ortega, J.A., Ugedo, L., 2012. Endocannabinoid modulation of dopaminergic motor circuits. Front. Pharmacol. 3, 110. Morris, J.C., 1993. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 43, 2412–2414. Nelissen, N., Vandenbulcke, M., Fannes, K., Verbruggen, A., Peeters, R., Dupont, P., Van Laere, K., Bormans, G., Vandenberghe, R., 2007.
250 Abeta amyloid deposition in the language system and how the brain responds. Brain 130, 2055–2069. O’Bryant, S.E., Humphreys, J.D., Smith, G.E., Ivnik, R.J., GraffRadford, N.R., Petersen, R.C., Lucas, J.A., 2008. Detecting dementia with the mini-mental state examination in highly educated individuals. Arch. Neurol. 65, 963–967. Pazos, M.R., Sagredo, O., Fernandez-Ruiz, J., 2008. The endocannabinoid system in Huntington's disease. Curr. Pharm. Des. 14, 2317–2325. Perez, D.M., Karnik, S.S., 2005. Multiple signaling states of G-protein-coupled receptors. Pharmacol. Rev. 57, 147–161. Quarantelli, M., Berkouk, K., Prinster, A., Landeau, B., Svarer, C., Balkay, L., Alfano, B., Brunetti, A., Baron, J.C., Salvatore, M., 2004. Integrated software for the analysis of brain PET/SPECT studies with partial-volume-effect correction. J. Nucl. Med. 45, 192–201. Ramirez, B.G., Blazquez, C., Gomez del, P.T., Guzman, M., De Ceballos, M.L., 2005. Prevention of Alzheimer's disease pathology by cannabinoids: neuroprotection mediated by blockade of microglial activation. J. Neurosci. 25, 1904–1913. Reibaud, M., Obinu, M.C., Ledent, C., Parmentier, M., Bohme, G. A., Imperato, A., 1999. Enhancement of memory in cannabinoid CB1 receptor knock-out mice. Eur. J. Pharmacol. 379, R1–R2. Reiman, E.M., Chen, K., Alexander, G.E., Caselli, R.J., Bandy, D., Osborne, D., Saunders, A.M., Hardy, J., 2004. Functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer's dementia. Proc. Nat. Acad. Sci. U.S.A 101, 284–289. Rodriguez, J.J., Noristani, H.N., Verkhratsky, A., 2012. The serotonergic system in ageing and Alzheimer's disease. Prog. Neurobiol. 99, 15–41. Sanabria-Bohorquez, S.M., Hamill, T.G., Goffin, K., De, L.I., Bormans, G., Burns, H.D., Van, L.K., 2010. Kinetic analysis of the cannabinoid-1 receptor PET tracer [(18)F]MK-9470 in human brain. Eur. J. Nucl. Med. Mol. Imaging 37, 920–933. Skinner, J., Carvalho, J.O., Potter, G.G., Thames, A., Zelinski, E., Crane, P.K., Gibbons, L.E., 2012. The Alzheimer's Disease Assessment Scale-Cognitive-Plus (ADAS-Cog-Plus): an expansion of the ADAS-Cog to improve responsiveness in MCI. Brain Imaging Behav. 6, 489–501. Solas, M., Francis, P.T., Franco, R., Ramirez, M.J., 2013. CB2 receptor and amyloid pathology in frontal cortex of Alzheimer's disease patients. Neurobiol. Aging 34, 805–808. Terranova, J.P., Storme, J.J., Lafon, N., Perio, A., Rinaldi-Carmona, M., Le Fur, G., Soubrie, P., 1996. Improvement of memory in rodents by the selective CB1 cannabinoid receptor antagonist, SR 141716. Psychopharmacology (Berl) 126, 165–172.
R. Ahmad et al. Terry, G., Liow, J.S., Chernet, E., Zoghbi, S.S., Phebus, L., Felder, C.C., Tauscher, J., Schaus, J.M., Pike, V.W., Halldin, C., Innis, R. B., 2008. Positron emission tomography imaging using an inverse agonist radioligand to assess cannabinoid CB1 receptors in rodents. Neuroimage 41, 690–698. Van der Elst, W., van Boxtel, M.P., van Breukelen, G.J., Jolles, J., 2005. Rey's verbal learning test: normative data for 1855 healthy participants aged 24-81 years and the influence of age, sex, education, and mode of presentation. J. Int. Neuropsychol. Soc.: JINS 11, 290–302. Van Laere, K., Casteels, C., Dhollander, I., Goffin, K., Grachev, I., Bormans, G., Vandenberghe, W., 2010. Widespread decrease of type 1 cannabinoid receptor availability in huntington disease in vivo. J. Nucl. Med. 51, 1413–1417. Van Laere, K., Goffin, K., Casteels, C., Dupont, P., Mortelmans, L., de Hoon, J., Bormans, G., 2008. Gender-dependent increases with healthy aging of the human cerebral cannabinoid-type 1 receptor binding using [(18)F]MK-9470 PET. Neuroimage 39, 1533–1541. Van Laere, K., Nuttin, B., Gabriels, L., Dupont, P., Rasmussen, S., Greenberg, B.D., Cosyns, P., 2006. Metabolic imaging of anterior capsular stimulation in refractory obsessive-compulsive disorder: a key role for the subgenual anterior cingulate and ventral striatum. J. Nucl. Med. 47, 740–747. Videaud, H., Torny, F., Prado-Jean, A., Couratier, P., 2008. Use of the Visual Object and Space Perception (VOSP) test battery in two cases of posterior cortical atrophy. Neurocase 15, 32–36. Villemagne, V.L., Pike, K.E., Chetelat, G., Ellis, K.A., Mulligan, R. S., Bourgeat, P., Ackermann, U., Jones, G., Szoeke, C., Salvado, O., Martins, R., O’Keefe, G., Mathis, C.A., Klunk, W.E., Ames, D., Masters, C.L., Rowe, C.C., 2011. Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann. Neurol. 69, 181–192. Walsh, S., Mnich, K., Mackie, K., Gorman, A.M., Finn, D.P., Dowd, E., 2010. Loss of cannabinoid CB1 receptor expression in the 6-hydroxydopamine-induced nigrostriatal terminal lesion model of Parkinson's disease in the rat. Brain Res. Bull. 81, 543–548. Walther, S., Mahlberg, R., Eichmann, U., Kunz, D., 2006. Delta-9tetrahydrocannabinol for nighttime agitation in severe dementia. Psychopharmacology (Berl) 185, 524–528. Westlake, T.M., Howlett, A.C., Bonner, T.I., Matsuda, L.A., Herkenham, M., 1994. Cannabinoid receptor binding and messenger RNA expression in human brain: an in vitro receptor autoradiography and in situ hybridization histochemistry study of normal aged and Alzheimer's brains. Neuroscience 63, 637–652.
