Extrastriatal dopamine D₂ receptor binding in Huntington's disease

Abstract

Huntington's disease (HD) is a neurodegenerative disorder, primarily affecting medium spiny neurones in the striatum. The density of striatal dopamine D₂ receptors is reduced in HD but there is little known about this biomarker in brain regions outside the striatum. The primary objective of this study was to compare extrastriatal dopamine D₂ receptor binding, in age‐matched control subjects and patients with HD. All subjects were examined using a high‐resolution positron emission tomography system and the high‐affinity dopamine D₂ receptor radioligand [¹¹C]FLB 457. A ROI based analysis was used with an atrophy correction method. Dopamine D₂ receptor binding potential was reduced in the striatum of patients with HD. Unlike the striatum, dopamine D₂ receptor binding in thalamic and cortical subregions was not significantly different from that in control subjects. A partial least square regression analysis which included binding potential values from all investigated cortical and subcortical regions revealed a significant model separating patients from controls, conclusively dependent on differences in striatal binding of the radioligand. Some clinical assessments correlated with striatal dopamine D₂ receptor binding, including severity of chorea and cognitive test performance. Hence, the present study demonstrates that dopamine D₂ receptors extrinsic to the striatum are well preserved in early to mid stage patients with HD. This observation may have implication for the development of therapy for HD. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.

INTRODUCTION

Huntington's disease (HD) is an autosomal‐dominant, progressive neurodegenerative disorder characterized by movement disorder, cognitive impairment, and psychiatric symptoms [Walker, 2007]. The diagnosis is made clinically and can be confirmed by genetic testing. The disease is caused by an abnormal expansion of the trinucleotide CAG repeat coding for glutamine at the N‐terminal of a protein called huntingtin (htt). The mutant gene, HTT, is located on the short arm of chromosome 4. Currently, there is no cure for HD and no effective symptomatic treatment [Bonelli and Wenning, 2006]. Despite being caused by mutation of a single gene, the phenotypic expression of HD is diverse and varies between individuals. Though chorea may be regarded as a clinical hallmark of the disease, parkinsonian symptoms such as impairment of voluntary movement, motor impersistence, apraxia and dystonia are other recognized features of HD [van Vugt et al., 1996]. In addition, cognitive deficits encompass multiple domains [Craufurd and Snowden, 2002; Folstein, 1989], and psychiatric manifestations are common in patients with HD [Anderson and Marder, 2001]. Recent studies have implicated that the cerebral cortex may contribute to the phenotypic expression in HD [Rosas et al., 2008; Squitieri et al., 2003]. At present, the variability in the phenotypic expression of HD is however not fully understood at a pathophysiological level.

The mutant htt protein is homogeneously expressed throughout the brain [Strong et al., 1993], yet the classical anatomical observation in postmortem brains of patients with HD is a strikingly selective degeneration of medium spiny neurones in the striatum [Folstein, 1989]. Apart from striatal cell loss, neuronal cell loss has been identified in many other regions of the brain, including the cerebral cortex [Gutekunst et al., 2002]. Recent structural magnetic resonance (MR) studies have shown that cortical loss of volume occurs early in the disease [Rosas et al., 2005], and there are also evidences for early cortical dysfunction, including changes in synaptic function, cytoskeletal integrity, and axonal transport. Taken together, these observations suggest an important role for cortical dysfunction in the pathogenesis of the disorder [DiProspero et al., 2004; Modregger et al., 2002].

A role of the dopamine system has been implicated in the pathogenesis of HD [Benchoua et al., 2008; Tang et al., 2007; van Oostrom et al., 2009]. Dopamine D₂ receptors are highly expressed in medium spiny neurones and may thus serve as a biomarker for the degeneration. Albeit at low density, these receptors are also present in the cerebral cortex and several subcortical regions [Kessler et al., 1993].

Changes in striatal dopamine D₂ receptor density has so far been extensively studied in patients with HD. Using the dopamine D₂ receptor antagonist radioligand [¹¹C]raclopride and positron emission tomography (PET), a progressive loss of D₂ receptors in the striatum has consistently been demonstrated [Andrews et al., 1999; Brandt et al., 1990; Feigin et al., 2007; Ginovart et al., 1997]. This decline has also been shown in asymptomatic carriers of the genetic mutation for HD [van Oostrom et al., 2009; Weeks et al., 1996]. Few studies have addressed dopamine D₂ receptor binding outside the striatum. In an early postmortem study including three patients with HD, a slight decrease in dopamine D₂ receptor concentration, as measured by [³H]spiroperidol, was reported in the frontal cortex [Reisine et al., 1977]. Moreover, statistical parametric mapping of [¹¹C]raclopride binding in patients with HD suggest a loss of cortical dopamine D₂ receptors in symptomatic HD patients [Pavese et al., 2003, 2010]. The aim of this PET study was to examine extrastriatal dopamine D₂ receptors in detail in control subjects and patients with HD. For this purpose, the high‐affinity radioligand [¹¹C]FLB 457 was used [Farde et al., 1997; Halldin et al., 1995; Suhara et al., 1999] with a ROI based analysis approach applying a method for atrophy correction. Furthermore, the study aimed at exploring relationships between the phenotypic expression of the disease and densities of striatal and extrastriatal dopamine D₂ receptors.

Abbreviations

BP

binding potential

CSF

cerebrospinal fluid

FOV

field of view

HD

Huntington's disease

mMS

modified motor score

MRI

magnetic resonance imaging

PCA

principal component analysis

PET

positron emission tomography

PSF

point spread function

PVE

partial volume effect

ROI

region of interest

SPM

statistical parametric mapping (software)

SRTM

simplified reference tissue model

TE

echo time

Th

thickness

TR

repetition time

UHDRS

Unified Huntington's Disease Rating Scale

METHODS

Subjects

The study was performed in accordance with the Declaration of Helsinki and with the approval of the Ethics and Radiation Safety Committees of the Karolinska University Hospital, Stockholm, Sweden. Nine patients with mild to moderate HD (five male and four female) and nine age‐matched control subjects (five male and four female) were recruited from a neurological clinic in Stockholm, Sweden. To be enrolled in the study, all participants had to provide written informed consent and be in the age range 20–70 years. The exclusion criteria were: previous or current treatment with a dopamine D₂ receptor antagonist (e.g. an antipsychotic drug) or tetrabenazine; participation in any other clinical study in the 3 months prior to the screening visit; drug or alcohol abuse; implanted magnetic metal device; or claustrophobia.

Clinical Assessments

The average age was 54 years (range: 39–70) for the patients with HD and 53 years (range: 29–70) for the control subjects. Patients were assessed using the Unified Huntington's Disease Rating Scale (UHDRS), which includes motor, cognitive, behavioral, and functional assessments [Huntington Study Group, 1996]. Table I presents individual UHDRS scores of the patients included in the study. The cognitive assessment included the verbal fluency test, the symbol digit modalities test, and the three Stroop tests. The results of these five tests were summed to provide a total cognitive score.

Table I.

Patient demographics and Unified Huntington's Disease Rating Scale (UHDRS) assessments

Gender	Age (years)	Duration of symptoms (years)	CAG repeat length	TMS	mMS	Chorea	TFC
F	39	2	43	9	7	0	11
M	46	4	47	47	20	11	11
M	46	3	45	3	3	0	9
F	50	2	42	11	5	6	12
M	52	6	41	16	13	3	11
M	60	10	42	31	10	11	6
F	62	3	42	33	17	4	12
M	63	4	41	9	7	6	11
F	70	3	39	27	13	10	12
Mean (SD)	54 (10)	4 (2.5)	42 (2)	22.5 (14)	11.6 (6)	5.7 (4)	10.5 (2)

Shown are the modified motor score (mMS; UHDRS items 4–10, 13–15), total motor score (TMS), chorea score, and total functional capacity (TFC).

MRI Examination

Magnetic resonance imaging (MRI) was performed using a 1.5 Tesla Signa MRI system (General Electric, Milwaukee, WI, USA). Two examinations were carried out in one session, with duration of about 15 min, consisting of a T2‐weighted scan for clinical evaluation of pathology, and a T1‐weighted scan for coregistration with PET and delineation of anatomical brain regions or regions of interest (ROI).

The T2‐weighted sequence was a fast spin echo with the following parameters: repetition time (TR) 6,000 ms, echo time (TE) 90 ms, 47 slices, slice thickness (Th)/gap 3 mm/0.125 mm, matrix 256 × 256, field of view (FOV) 260 × 195, and imaging time 2 min. The T1‐weighted sequence was a three‐dimensional (3D) spoiled gradient recalled protocol with the following settings: TR 21 ms, TE 6 ms, flip angle 35°, 156 slices, Th/Gap 1 mm/0 mm, matrix 256 × 256, FOV 260 × 195, and imaging time 10 min 49 s.

PET Experimental Procedure

All PET examinations were performed using a high‐resolution research tomograph (HRRT, Siemens Molecular Imaging). This PET system has: an axial FOV of 25.2 cm, corresponding to 207 planes in the reconstructed images; and a slice thickness of 1.218 mm and thus a pixel size of 1.218 × 1.218 × 1.218 mm³. The resolution has been improved by implementation of point spread function (PSF) modeling. Using resolution modeling (OP‐3D‐OSEM‐PSF), the in‐plane resolution is 1.5 mm full‐width half‐maximum in the centre of the FOV and 2.4 mm at 10 cm off‐centre directions [Varrone et al., 2009].

To standardize head positioning during the PET examination, a plaster helmet was made individually for each participant, and used with a head fixation system [Bergstrom et al., 1981]. All participants underwent one PET measurement with the radioligand [¹¹C]FLB 457. The radioligand was prepared from [¹¹C]methyl triflate as previously described and according to standardized procedure at the PET Centre at the Karolinska University Hospital [Langer et al., 1999]. On average, 406 MBq, prepared in a 10 mL saline solution, was injected as a bolus for 3 s via a venous canula positioned in the left arm, followed by a flush of 10 mL of saline solution. The specific radioactivity of the injected radioligand was on average 12 414 Ci/mmol, corresponding to a mean injected mass of 0.49 μg (range: 0.16–1.28 μg). There were no differences in the injected mass between control subjects and patients with HD. Data were acquired in list mode. Images were reconstructed for 19 time frames, equating to the total measurement duration of 87 min following injection of the radiotracer.

Image Processing

After acquisition and reconstruction, the T1 MRI and PET images were transferred to statistical parametric mapping 5 (SPM5) software for spatial normalization and coregistration (Wellcome Trust Centre for Neuroimaging). For each subject, the MRI images were spatially normalized to position the anterior–posterior commissural line in the horizontal plane, and the inter‐hemispheric plane orthogonal to the anterior–posterior commissural plane. The reoriented T1 images were then resliced to 1 mm voxels in a matrix of 220 × 220 × 170.

Regions of Interest

The delineation of ROIs was made manually on the spatially normalized MRI images in three orthogonal projections using the Human Brain Atlas software [Roland and Zilles, 1994]. All ROIs were delineated for each hemisphere and for the entire anatomical definition. For the striatum (caudate nucleus and putamen), hippocampus, and temporal, parietal and occipital cortices, the ROIs were delineated on sagittal projections, while for the frontal regions (dorsolateral and dorsomedial prefrontal cortices, orbitofrontal cortex) and amygdala, the ROIs were delineated on coronal sections. For the anterior cingulate, insula and subregions of thalamus, the ROIs were delineated on horizontal projections. The thalamic subregions (centromedial, centrolateral, anteromedial, anterolateral, and posterior) were delineated using a procedure described previously [Gilbert et al., 2001]. Finally, the cerebellum was delineated below the appearance of the petrosal bone in the horizontal projections.

For cortical regions the initial delineation was schematic, also including surrounding cerebrospinal fluid (CSF) and white matter. To define grey matter boundaries accurately, the MRI images were coregistered with the PET images and segmented into grey and white matter and CSF. The initial crude cortical ROIs were then segmented using the grey matter mask to include with precision only pixels belonging to grey matter.

All ROIs were superimposed on the PET images using predefined coregistration parameters. Radioactivity concentrations (nCi/mL) in each ROI were calculated for each sequential frame, corrected for ¹¹C decay, and plotted versus time.

Partial Volume Effect Correction

The accuracy of neuroreceptor quantification by PET is influenced by the partial volume effect (PVE). The radioactivity concentration in an anatomical region is under or overestimated by “spill‐over” or “spill‐in” effects of radioactivity to or from neighboring brain regions with lower or higher receptor density [Varrone et al., 2009]. Size of an anatomical region less than three to four times the PET resolution reduces the recovery of radioactivity exponentially. This effect is increased in the presence of cortical atrophy, as in patients with HD.

To compensate for the underestimation of the activity concentration in the PET images, several approaches for PVE correction have been developed, thus improving the quantitative accuracy. Here, a previously described PVE‐correction method, based on segmentation of the MRI into grey matter, white matter and CSF, was used [Meltzer et al., 1990]. In this method, the segmented grey matter and white matter masks are summed to obtain a brain tissue mask. The tissue mask is then convolved with the resolution of the PET system, resulting in a correction map for the PET images. The original PET image is divided by the correction map, resulting in a PVE‐corrected PET image in which the count density represents activity per volume of brain tissue. The MRI segmentation procedure was performed with SPM5 and the PVE correction algorithm was implemented in Matlab 7.5.

Quantification of Radioligand Binding

To quantify radioligand binding, the binding potential (BP) was calculated for each ROI. At tracer doses, BP is proportional to the ratio B _max/K _D, where B _max is the total concentration of specific receptor‐binding sites and K _D is the dissociation constant of the radioligand at equilibrium [Mintun et al., 1984]. The BP was calculated using the simplified reference tissue model (SRTM) [Lammertsma and Hume, 1996]. Cerebellum was used as reference tissue, serving as an indirect approximation of free and non‐ specifically bound radioligand concentration, due to its minute density of dopamine D₂ receptors [Hall et al., 1996]. All BPs were calculated using Matlab 7.4, where SRTM was implemented in a program designed by the author (ME), which has recently been validated [Rominger et al., 2009].

Statistical Analysis

Mean differences between patients with HD and controls were assessed by Student's t‐ test. No correction was made for multiple comparisons. Correlations between the clinical assessments and [¹¹C]FLB 457 binding were examined for all the investigated ROIs, using Pearson's correlation coefficient (r). The following clinical variables were included in the analysis: the occulomotor score (UHDRS motor items 1–3), the modified motor score (mMS, UHDRS motor items 4–10, 13–15), chorea (UHDRS motor item 12), the total cognitive score, and the behavioral score. Multivariate statistic analysis was carried out in the analysis of ROI data by means of Partial Least Squares (PLS) analysis [Clark and Cramer, 1993; Eriksson et al., 2006]. The statistical significance of the models was assessed using the cross‐validation procedure [Jackson, 1991; Wold, 1978]. All multivariate statistical analyses were carried out using the software SIMCA‐P+, version 12 (Umetrics AB, Umeå, Sweden) (CV Significance rule 1 and rule 2, see help section in software).

RESULTS

Volumetric Quantification of ROI

All subjects participated in the study according to the protocol. The entire anatomically defined structure was delineated for each cortical and subcortical ROI, thus allowing for a comparison of the volumetric information. In Table II, volumetric data are shown for a selection of ROIs. In patients with HD, there was marked atrophy in the striatum resulting in volumes that were about 45% of the control value. Cortical atrophy was not evident and volumes ranged from 86 to 116% of control volumes.

Table II.

Volumes for the putamen, caudate nucleus, and several cortical regions

Region	Volume, mL (SD)		HD patient value as a percentage of control
	Patients with HD	Controls
Putamen	3.1 (0.87)	7.1 (0.9)	44*
Caudate nucleus	3.2 (1.0)	6.9 (0.9)	46*
Prefrontal cortex	28.0 (7.0)	31.0 (6.9)	90
Occipital cortex	47.7 (10)	53.9 (6.6)	88
Temporal cortex	76.0 (8.8)	88.0 (7.8)	86*
Anterior Cingulate	4.3 (0.8)	3.7 (1.2)	116

^* P < 0.05, Student's t‐test.

Radioligand Binding in Patients With HD and Controls

Representative parametric PET images of a control subject and a patient with HD are illustrated in Figure 1. The corresponding time‐activity curves for the putamen and temporal cortex are shown in Figure 2, as well as a representative fit of the SRTM algorithm to experimental data. Significant reductions in BP values were observed in the striatum in patients with HD (Table III). There were numerically lower BP values in most extrastriatal regions in patients with HD compared with controls, but the difference was not statistically significant for any of the regions.

Figure 1.

PET images overlaid on MR images showing [11C]FLB 457 BP in the brain of a patient with HD (left) and a control subject (right).

Figure 2.

Time‐activity curves following [11C]FLB 457 injection, in a patient with HD (a) and an age‐matched control (b). The green, blue, and red curves in the upper panels correspond to the putamen, temporal cortex and cerebellum, respectively. Lower panels show the SRTM fit and the estimated parameters R, k2 and BP for putamen and temporal cortex.

Table III.

[11C]FLB 457 binding potential (BP) in examined brain regions of interest for nine patients with Huntington's disease and age matched control subjects

	BP not corrected for partial volume effect					BP corrected for partial volume effect
	HD patients		Controls		HD patient value as a percentage of control	HD patients		Controls		HD patient value as a percentage of control
	Mean	SD	Mean	SD		Mean	SD	Mean	SD
Cortex
Insula	1.25	0.36	1.43	0.15	88	1.47	0.40	1.62	0.15	90
Dorsomedial prefrontal	0.53	0.24	0.64	0.16	83	0.83	0.25	0.86	0.18	97
Dorsolateral prefrontal	0.42	0.23	0.57	0.14	75	0.69	0.27	0.77	0.15	90
Anterior Cingulate	0.72	0.31	0.79	0.15	92	1.01	0.25	0.99	0.19	102
Occipital	0.30	0.19	0.33	0.19	91	0.49	0.25	0.51	0.18	96
Orbitofrontal	0.58	0.22	0.62	0.18	93	0.81	0.27	0.85	0.20	95
Prefrontal	0.46	0.23	0.59	0.14	78	0.73	0.26	0.80	0.15	91
Parietal	0.36	0.25	0.52	0.17	69	0.65	0.27	0.74	0.20	88
Temporal	0.89	0.35	1.01	0.29	89	1.16	0.41	1.23	0.30	94
Subcortex
Hippocampus	0.85	0.27	0.98	0.27	87	0.88	0.28	0.99	0.27	89
Amygdala	2.73	0.67	2.72	0.36	100	2.80	0.69	2.77	0.38	101
Striatum
Caudate nucleus	8.76	2.83	11.44	2.53	77*	9.26	3.01	11.92	2.77	78
Putamen	9.77	2.17	14.54	2.29	67**	9.85	2.15	14.58	2.30	67**
Thalamus
Posterior	2.42	0.66	2.92	1.16	83	2.52	0.68	2.98	1.12	85
Centromedial	3.79	1.04	3.97	0.78	95	4.09	0.91	4.12	0.76	99
Centrolateral	1.99	0.45	2.16	0.49	92	2.01	0.43	2.17	0.51	92
Anteromedial	3.42	0.84	4.07	0.69	84	3.50	0.86	4.15	0.75	84
Anterolateral	2.26	0.59	2.72	2.01	83	2.28	0.59	2.77	2.18	83

Data are shown without and with correction for partial volume effects.

^* P < 0.05;

^** P < 0.001.

Radioligand Binding Corrected for Partial Volume Effect

In addition to the BP values described above, BP values were calculated from time‐activity curves obtained from PVE‐corrected PET imaging data (Table III). The numerical but not statistically significant difference between the values calculated for patients with HD and controls became even smaller.

Correlation Between Clinical Assessment and Radioligand Binding

Correlations between UHDRS assessments and [¹¹C]FLB 457 BPs for striatal regions are shown in Table IV. There was a statistically significant correlation between maximal chorea and [¹¹C]FLB 457 BP in the putamen as well as for the modified motor score (mMS) in the caudate, whereas no statistically significant correlation was found between chorea or mMS and radioligand binding in any extrastriatal region. The total cognitive score correlated with [¹¹C]FLB 457 BP in the putamen whereas no correlation was found between this assessment and radioligand binding in any extrastriatal region. There were no statistically significant correlations between striatal or extrastriatal radioligand BPs for the behavioral and occulomotor assessments.

Table IV.

Correlation analysis for striatal [11C]FLB 457 binding potential and UHDRS assessments

Clinical domain	Pearson's correlation coefficient (r)
	Caudate nucleus	Putamen
mMS	−0.68*	−0.51
Oculomotor score	−0.46	−0.40
Maximal chorea	−0.55	−0.75*
Total cognitive score	0.59	0.69*
Behavioural score	−0.40	−0.22

mMS = modified motor score.

^* P < 0.05.

Partial Least Squares Regression Discriminating Patients With HD From Controls

The partial least square (PLS) model discriminating patients with HD from controls had three significant components (R2X = 0.15, R2Y = 0.56, Q2cum = 0.23) (see Fig. 3). In this plot, each dot represents one patient, and the position of each dot represents the underlying variables, i.e., the binding potential in different ROIs. Hence, dots located close to each other are generally similar across these variables, whereas dots far apart are dissimilar. It can be seen that the control subjects and patients with HD are fairly well separated, with controls in the lower left quadrant and patients with HD tending to cluster apart from them. The variables underlying this separation are shown in Figure 4, showing the PLS regression coefficients with 95% confidence limits. Large negative coefficients indicated decrease in HD vs. controls. Hence, caudate and putamen BPs are decreased in HD, whereas there were no evident trends among the BP values in other regions. Removing striatal regions from the data set yielded no significant PLS model.

Figure 3.

Object score plot (t1 vs. t2) from a PLS model discriminating patients with HD from control subjects. Each marker corresponds to one subject; squares: HD, circles: controls. The score on each PLS component (x‐axis: component 1, Y‐axis: component 2) represents a composite of all striatal and extrastriatal BP data which is used in the model. Patients with HD and control subjects are separated with minor overlap, reflecting differences in BP values.

Figure 4.

Regression coefficients obtained from the PLS model discriminating regional BP values between HD patients and healthy subjects. The coefficients shown were scaled and centered with 95% confidence limits estimated by the jack‐knife method (Simca‐P+ 12.0, Umetrics, Inc.). Large negative coefficients indicate decreased BP of the ROIs in HD vs. healthy controls. The differentiation of HD vs. healthy controls in this model is mainly driven by decreased BP in the caudate nucleus and putamen of patients with HD. Abbreviations: Caud, caudate nucleus; Put, putamen; INS, insular cortex; DLPC, dorsolateral prefrontal cortex; HIP, hippocampus; AMG, amygdala; OC, occipital cortex; OFC, orbitofrontal cortex; PFC, prefreontal cortex; TC, temporal cortex; THA, thalamus.

DISCUSSION

The primary objective of this study was to examine the density of dopamine D₂ receptors in extrastriatal brain regions in patients with HD. The radioligand [¹¹C]FLB 457 has high affinity for the dopamine D₂ receptor and is thus suitable for examination of low‐density receptor populations [Farde et al. 1997]. [¹¹C]FLB 457 is however less suitable for reliable quantification of the high density of dopamine D₂ receptors in the striatum since binding equilibrium in this region is not reached within the time frame of a PET measurement [Olsson and Farde, 2001]. In this study, [¹¹C]FLB 457 binding in the striatum was anyhow analyzed to obtain a confirmation of loss of striatal D₂ receptors in the actual patient sample. The markedly lower binding potential values obtained for the striatum is consistent with previous literature [Ginovart et al., 1997; Lawrence et al., 1998].

There was no statistically significant difference in extrastriatal dopamine D₂ receptor binding between patients with HD and the control subjects. Few studies have addressed extrastriatal dopamine D₂ receptor distribution in HD. An early study performed on postmortem tissue from three patients treated with antipsychotic drugs has shown a marked reduction in [³H]‐spiroperidol binding in the striatum and frontal cortex [Reisine et al., 1977]. Another study including six patients with HD used SPM and showed a longitudinal decline in [¹¹C]raclopride binding in several extrastriatal regions, [Pavese et al., 2003]. A recent study from the same laboratory found clusters of cortical [¹¹C]raclopride BP reductions in 62% of symptomatic HD patients [Pavese et al., 2010]. However, [¹¹C]raclopride is a less suitable radioligand for the low density extrastriatal dopamine D₂ receptor populations due to the low signal to noise ratio [Farde et al., 1998]. Moreover, it could be argued that the reductions in regional cortical [¹¹C]raclopride binding reported in symptomatic HD, might be related to atrophy. In this study, PVE correction resulted in a mean increase of 43% in cortical ROIs in patients with HD and a 29% increase in healthy controls, suggesting that cortical radiotracer binding is relatively underestimated in degenerative disorders like HD. Contrary to these reports, this study, using a high‐affinity radioligand, a high‐resolution PET system, and including an atrophy correction method, showed that dopamine D₂ receptor density is relatively preserved in extrastriatal regions of patients with mild to moderate HD.

The secondary objective was to explore potential correlations between regional dopamine D₂ receptor binding and the phenotypic expression in the examined patients. There was a correlation between striatal [¹¹C]FLB 457 BP and cognitive test performance. This observation is in accordance with previous studies in HD, where a relationship between the dopamine D₂ receptor density in the striatum and cognitive test performance has been shown [Backman et al., 2000; Lawrence et al., 1998; Volkow et al., 1998]. We also found a statistically significant correlation between striatal [¹¹C]FLB 457 BP and chorea. Results from an fMRI study as well as a peripheral receptor binding study have previously proposed that increasing chorea (but not other motor features) strictly depends on striatal dysfunction [Maglione, 2006; Reading et al., 2004]. To our knowledge, this is the first study showing a significant correlation between the striatal binding of a dopamine D₂ receptor radioligand and chorea in HD.

To further explore any latent covariance structure in the data set, PLS analysis was used. This analysis demonstrated a separation between patients with HD and controls, a separation that was entirely driven by changes in striatal BPs. The PLS model thus also confirms that the HD phenotype is not to a significant extent driven by extrastriatal dopamine D₂ receptor density or distribution. The results give further support for the view that the striatal receptor density is most important for basic motor and cognitive abilities. There is support in literature that dopaminergic neurotransmission in extrastriatal regions, such as the amygdala, hippocampus, anterior cingulate, ventrolateral frontal cortex, and thalamus, are important for higher order functions and may thus be influencing the phenotypic expression of HD [Aalto et al., 2005; Christian et al., 2006]. However, in the present investigation there was no statistically significant correlation between extrastriatal D₂ dopamine receptor density and the investigated clinical variables, indicating that the phenotypic heterogeneity in HD may be influenced by other aspects of dopaminergic transmission. A recent study has investigated dopamine D₂ receptor loss in the hypothalamus, potentially explaining some symptoms related to HD such as progressive weight loss, alternations in sexual behavior and disturbance in the wake‐sleep‐cycle [Politis et al., 2008]. It might be of interest for a further study to investigate dopamine D₂ receptor binding in hypothalamus using [¹¹C]FLB 457.

[¹¹C]FLB 457 is a suitable radioligand for measuring low tissue concentrations of dopamine D₂ receptors, such as in the cerebral cortex. The binding potential, which is generated from the analysis, is a composite value representing the ratio between receptor density (B _max) and affinity (K _D). However, the affinity is not likely to differ across brain regions, and moreover, the extrastriatal binding of [¹¹C]FLB 457 is not particularly sensitive to competition with endogenous dopamine [Okauchi et al., 2001; Suhara et al., 1999]. This means that the BP in extrastriatal regions most likely can be attributed to receptor density. Owing to its high affinity [¹¹C]FLB 457 is considered less suitable for high‐density regions such as the striatum, having a density of about 30 nM [Farde et al., 1995]. A receptor density above 7 nM causes time of equilibrium to occur beyond the time of data acquisition [Olsson and Farde, 2001]. Nevertheless, we chose to include the striatum in our analysis. The time‐activity curve at pre‐equilibrium conditions is influenced to a greater extent by the blood flow than in equilibrium conditions. It has previously been described that striatal blood flow decreases with progression of HD, and that blood flow correlates with some clinical assessments in patients with HD [Young et al., 1986]. It is thus likely that the measured BP in the striatum in this study represents a composite measure of true dopamine D₂ receptor binding and blood flow, both of which are known to correlate with clinical variables. However, this is the first experimental study investigating [¹¹C]FLB 457 binding in the striatum. In a study of five patients with HD, a BP of about 60% of control mean was measured with [¹¹C]raclopride in the putamen [Ginovart et al., 1997]. Our results showing a [¹¹C]FLB 457 BP decrease to about 67% of control mean in the putamen for patients with HD, is thus in line with previous reports using a validated radioligand such as [¹¹C]raclopride.

In summary, there was no significant decline in dopamine D₂ receptors outside the striatum in patients with mild to moderate HD. Given the importance of the dopaminergic system in the pathophysiology of HD, our finding of unexpected selectivity in the preservation of cortical dopamine D₂ receptors suggests that these receptors may be a potential therapeutic target in HD.