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The Journal of Neuroscience, May 1, 2002, 22(9):3708-3719
Prefrontal Dopamine D1 Receptors and Working
Memory in Schizophrenia
Anissa
Abi-Dargham1, 2,
Osama
Mawlawi1, 2,
Ilise
Lombardo1,
Roberto
Gil1,
Diana
Martinez1,
Yiyun
Huang1,
Dah-Ren
Hwang1, 2,
John
Keilp1,
Lisa
Kochan1,
Ronald
Van
Heertum2,
Jack M.
Gorman1, 2, and
Marc
Laruelle1, 2
Departments of 1 Psychiatry and
2 Radiology, Columbia University College of Physicians and
Surgeons and New York State Psychiatric Institute, New York, New York
10032
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ABSTRACT |
Studies in nonhuman primates documented that appropriate
stimulation of dopamine (DA) D1 receptors in the
dorsolateral prefrontal cortex (DLPFC) is critical for working memory
processing. The defective ability of patients with schizophrenia at
working memory tasks is a core feature of this illness. It has been
postulated that this impairment relates to a deficiency in mesocortical
DA function. In this study, D1 receptor availability was
measured with positron emission tomography and the selective
D1 receptor antagonist [11C]NNC 112 in
16 patients with schizophrenia (seven drug-naive and nine drug-free
patients) and 16 matched healthy controls. [11C]NNC 112 binding potential (BP) was
significantly elevated in the DLPFC of patients with schizophrenia
(1.63 ± 0.39 ml/gm) compared with control subjects (1.27 ± 0.44 ml/gm; p = 0.02). In patients with
schizophrenia, increased DLPFC [11C]NNC 112 BP was
a strong predictor of poor performance at the n-back task, a test of
working memory. These findings confirm that alteration of DLPFC
D1 receptor transmission is involved in working memory
deficits presented by patients with schizophrenia. Increased
D1 receptor availability observed in patients with
schizophrenia might represent a compensatory (but ineffective)
upregulation secondary to sustained deficiency in mesocortical DA function.
Key words:
dopamine; D1 receptors; schizophrenia; prefrontal cortex; working memory; positron emission tomography
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INTRODUCTION |
Impairment in higher cognitive
functions is one of the most enduring symptoms of schizophrenia and a
strong predictor of poor clinical outcome (Green, 1996 ). Among these
deficits, defective performance at tasks involving working memory,
i.e., the ability to retain and manipulate information over a brief
period of time, has been reliably observed in these patients (Park and
Holzman, 1992 ; Fleming et al., 1995 ; Morice and Delahunty, 1996 ; Gold
et al., 1997 ; Keefe et al., 1997 ; Park, 1997 ; Conklin et al., 2000 ). Functional brain imaging studies documented the engagement of the
dorsolateral prefrontal cortex (DLPFC) in the execution of working
memory tasks in humans (Cohen et al., 1994 ; McCarthy et al., 1994 ;
Courtney et al., 1996 ; Braver et al., 1997 ; Carlson et al., 1998 ;
D'Esposito et al., 1998 ; Callicott et al., 1999 ; Jansma et al., 2000 ).
Alterations in DLPFC activation during completion of working memory
tasks has been reported in patients with schizophrenia by numerous
investigators, suggesting that pathology of the DLPFC or its
connectivity is implicated in working memory deficits in schizophrenia
(Callicott et al., 1998 , 2000 ; Stevens et al., 1998 ; Honey et al.,
1999 ; Manoach et al., 1999 , 2000 ; Barch et al., 2001 ; Perlstein et al.,
2001 ).
The mesocortical DA system, ascending form the ventral tegmental area,
provides a widespread innervation to the neocortical areas (Levitt et
al., 1984 ; Lewis et al., 1987 ; Oades and Halliday, 1987 ).
D1 receptors are the most expressed DA receptors
in the neocortex (Lidow et al., 1991 ; Hall et al., 1994 ; Hurd et al., 2001 ). Studies in nonhuman primates have shown that working memory, studied during delayed response paradigms, is critically dependent on
prefrontal DA function and appropriate stimulation of
D1 receptors in the DLPFC (Brozoski et al., 1979 ;
Sawaguchi and Goldman-Rakic, 1991 , 1994 ; Arnsten et al., 1994 ; Arnsten
and Goldman-Rakic, 1998 ). These observations led to the suggestion that
altered DA transmission at D1 receptors in DLPFC
might be involved in the pathophysiology of working memory in
schizophrenia (Weinberger, 1987 ; Davis et al., 1991 ; Goldman-Rakic,
1994 ; Goldman-Rakic et al., 2000 ).
The aim of the study reported here was to measure DLPFC
D1 receptor availability in untreated patients
with schizophrenia and matched healthy controls and to assess the
relationship between DLPFC D1 receptor
availability and working memory performance. (+)-5-(7-Benzofuranyl)-8-chloro-7-hydroxy-3-methyl-2,3,4,5-tetrahydro-1H-3-benzazepine (NNC 112) is a potent and selective D1 receptor
antagonist (Andersen et al., 1992 ).
[11C]NNC 112 was recently introduced as
a new and superior radiotracer to image D1
receptors (Halldin et al., 1998 ). Because of its high specific to
nonspecific binding ratio, [11C]NNC 112 is well suited for quantification of D1 receptors
in extrastriatal areas such as the neocortex (Halldin et al., 1998 ), where the density of these receptors is much lower than in the striatum
(Hall et al., 1994 ). We recently demonstrated that
[11C]NNC 112 provides a reproducible
measurement of D1 receptor parameters in several
regions of the PFC, including the DLPFC (Abi-Dargham et al., 2000 ).
Working memory was assessed in both patients and controls, using a
verbal n-back paradigm and three working memory load levels (1-back,
2-back, 3-back).
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MATERIALS AND METHODS |
Subjects
The protocol was approved by the Institutional Review Boards of
the New York State Psychiatric Institute and Columbia Presbyterian Medical Center. Patients were recruited after voluntary admission to a
research ward (Schizophrenia Research Unit, New York State Psychiatric
Institute) or from the affiliated outpatient research clinic. Capacity
to provide informed consent was evaluated by a psychiatrist not
associated with the study. Subjects provided written informed consent
after detailed explanation of the nature and risks of the study.
According to the recommendations of the National Alliance for the
Mentally Ill (Arlington, VA), assent from involved family members was
also obtained when appropriate.
Inclusion criteria for patients were as follows: (1) diagnosis of
schizophrenia or schizophreniform disorder (provisional) according to
the Diagnostic and Statistical Manual (DSM-IV); (2) no other DSM-IV
axis I diagnosis; (3) no lifetime history of alcohol or substance abuse
or dependence; (4) absence of any psychotropic medication for at least
14 d before the study (with the exception of lorazepam, which was
allowed at a maximal dose of 3 mg per day up to 24 hr before the
study); (5) no concomitant or past severe medical conditions; (6) no
pregnancy; (7) no current suicidal or homicidal ideation; and (8)
capacity to provide informed consent. Subjects with schizophreniform
disorder (provisional) were included in the study only if the diagnosis
of schizophrenia was confirmed after 6 months.
Inclusion criteria for the control group were (1) absence of past or
present neurological or psychiatric illnesses, including substance
abuse; (2) no concomitant or past severe medical conditions; (3) no
pregnancy; and (4) informed consent. Groups were matched for age,
gender, race, parental socioeconomic level (Hollingshead, 1975 ), and
nicotine smoking.
A total of 17 patients with schizophrenia and 20 controls were enrolled
in the study. All sequentially enrolled subjects were included in the
study sample, with the following exceptions. One patient with
schizophrenia was excluded because of failure of arterial sampling
during the scan. Three controls subjects were excluded for the
following reasons: failure to obtain magnetic resonance image (MRI)
(n = 1), discovery of a meningioma at the MRI
(n = 1), and technical failure of the PET scanner
during the experiment (n = 2). Thus, the final sample
includes 16 patients with schizophrenia and 16 healthy controls.
Patients and controls were studied over a 2 year period (June 1999 to
June 2001).
Clinical assessment
Diagnosis was assessed with the Structured Clinical Interview
for DSM-IV (SCID) (Spitzer et al., 1992 ), followed by consensus diagnosis conference. For controls, a trained rater administered the
SCID nonpatient version (SCID-NP). Medical evaluation included a
detailed medical and neurological history, complete physical and
neurological examination, EKG, and routine laboratory tests. Severity
of symptoms was assessed with the Positive and Negative Symptoms Scale
(PANSS) (Kay et al., 1987 ), obtained on the day of the PET study, i.e.,
after at least 14 d without antipsychotic medications.
Working memory assessment
A large number of tasks involving working memory have been used
in schizophrenia research (Goldman-Rakic, 1994 ). These tasks might vary
in complexity, from pure maintenance tasks (allowing to vary the delay
and the extent of information to be maintained) to tasks involving
increasing levels of information manipulation (ranging from simple
matching to more elaborate decision making processes, such as set
shifting in the Wisconsin card sorting task). We selected the n-back
paradigm because: (1) it is a reliable method to activate DLPFC,
irrespective of the presentation modality or the nature of the
information, (2) it allows to vary the working memory load of the task,
and (3) DLPFC activation during n-back tasks has been demonstrated to
be load-sensitive by several investigators (Cohen et al., 1994 ; Barch
et al., 1997 ; Braver et al., 1997 ; Carlson et al., 1998 ; Carter et al.,
1998 ; Callicott et al., 1999 ; Rama et al., 2001 ).
The n-back task used here required subjects to monitor a series of
letters presented sequentially on a computer screen and to respond when
a letter is identical to the one that immediately preceded it (1-back
condition), the one presented two trials back (2-back), or three trials
back (3-back) (Cohen et al., 1994 ). Sixty letters were presented in
each condition. Each presentation lasted 500 msec, with 2500 msec
intervals (blank screen). A total of 12, 10, and 10 targets were
presented for the 1-, 2-, and 3-back conditions, respectively. The hit
rate (HR) was calculated as the number of correct responses divided by
the number of targets (maximum is 1, minimum is 0). The error rate (ER)
was calculated as the number of errors divided by the number of
nontargets (maximum is 1, minimum is 0). The adjusted HR (AHR) was
calculated as HR ER. AHR ranges from 1 (if the subject provides
all the correct responses and no incorrect response) to 1 (if the
subject provides no correct response and all the incorrect responses).
Operating at chance level corresponds to an AHR of 0. d' was calculated for 2 and 3 back as inv(HR) inv(ER), where inv is the inverse of the standard normal cumulative distribution.
D1 receptor measurement
Radiochemistry. The desmethyl precursor
(+)-5-(7-benzofuranyl)-8-chloro-7-hydroxy-3-methyl-2,3,4,5-tetrahydro-1H-3-benzazepine was kindly provided by Christer Halldin (Karolinska Institute, Stockholm, Sweden). [11C]NNC 112 was
prepared by N-methylation of the precursor using [11C]methyl triflate as previously
described (Halldin et al., 1998 ). Specific radioactivity at the time of
injection was 949 ± 533 Ci/mmol (mean ± SD;
n = 32). Injected dose was 12.5 ± 4.8 mCi, and
injected mass was 4.8 ± 1.3 µg (range from 1.8 to 6.5 µg).
PET protocol. PET imaging sessions were conducted as
previously described (Abi-Dargham et al., 2000 ). An arterial catheter was inserted in the radial artery after completion of the Allen test
and infiltration of the skin with 2% lidocaine. A venous catheter was
inserted in a forearm vein on the opposite side. A polyurethane head
immobilizer system (Soule Medical, Tampa, FL) was used to minimize head
movement (Mawlawi et al., 1999 ). PET imaging was performed with the
ECAT EXACT HR+ (Siemens, Knoxville, TN) [63 slices covering an axial
field of view of 15.5 cm, axial sampling of 2.46 mm, in-plane and
axial resolution of 4.4 and 4.1 mm full width half-maximum at the
center of the field of view in the three-dimensional mode (3-D),
respectively]. A 10 min transmission scan was obtained before
radiotracer injection. [11C]NNC 112 was
injected intravenously over a 45 sec period. Emission data were
collected in the 3-D mode for 90 min as 18 successive frames of
increasing duration (3 × 20 sec, 3 × 1 min, 3 × 2 min, 2 × 5 min, 7 × 10 min). Images were reconstructed
with attenuation correction using the transmission data and a Sheppe
0.5 filter (cutoff 0.5 cycles per projection rays).
Input function measurement. After radiotracer injection,
arterial samples were collected every 10 sec with an automated sampling system for the first 2 min, and manually thereafter at longer intervals. A total of 30 samples was obtained per experiment. After
centrifugation (10 min at 1800 × g), a 200 µl
aliquot of plasma was collected, and activity was measured in a gamma
counter (1480 Wizard 3M automatic gamma counter; LKB-Wallac,
Gaithersburg, MD). Gamma counter efficiency was calibrated at
regular intervals with the PET camera using an
18F solution. In addition, a long-lived
source (22Na) was counted with each set of
samples, to control for between run variance in counting efficiency.
Six selected samples (collected at 2, 8, 16, 30, 50, and 70 min) were
further processed by protein precipitation using acetonitrile followed
by HPLC to measure the fraction of plasma activity representing
unmetabolized parent compound, as previously described (Abi-Dargham et
al., 2000 ).
A biexponential function was fitted to the six measured fractions
parent and used to interpolate values between and after the
measurements. The smallest exponential of the fraction parent curve,
par, was constrained to the difference between
cer, the terminal rate of washout of
cerebellar activity, and tot, the smallest
elimination rate constant of the total plasma (Abi-Dargham et al.,
1999 ). The input function was calculated by the product of total counts
and interpolated fraction parent at each time. The measured input
function values (Ca(t),
µCi/ml) were fitted to a sum of three exponentials, and the fitted
values were used as input to the kinetic analysis of the regional brain
uptake. The clearance of the parent compound
(CL, l/hr) was calculated as the ratio
of the injected dose to the area under the curve of the input function
(Abi-Dargham et al., 1994 ).
For the determination of the plasma-free fraction
(f1), triplicate 200 µl
aliquots of plasma collected before injection were mixed with
radiotracer, pipetted into ultrafiltration units (Centrifree; Amicon,
Danvers, MA), and centrifuged at room temperature (20 min at 4000 rpm).
At end of centrifugation, plasma and ultrafiltrate activities were
counted, and f1 was calculated as the ratio of ultrafiltrate to total activity concentrations (Gandelman et al., 1994 ).
MRI acquisition and segmentation procedures. MRIs were
acquired on a GE 1.5 T Signa Advantage system. After a sagittal scout (1 min), performed to identify the anterior commissure (AC)-posterior commissure (PC) plane, a transaxial T1-weighted sequence with 1.5 mm
slice thickness was acquired in a coronal plane orthogonal to the
AC-PC plane over the whole brain with the following parameters: three-dimensional spoiled gradient recalled acquisition in the steady
state; repetition time, 34 msec; echo time, 5 msec; flip angle of
45°; slice thickness 1.5 mm and zero gap; 124 slices; field of view,
22 × 16 cm; with 256 × 192 matrix, reformatted to 256 × 256, yielding a voxel size of 1.5 × 0.9 × 0.9 mm; and time of acquisition, 11 min. MRI segmentation was performed
within MEDx (Sensor Systems, Inc., Sterling, VA), with original
subroutines implemented in MATLAB (Math Works, Natick, MA). Steps for
MRI segmentation included correction for field inhomogeneities, fitting of the voxel distribution to a combination of three Gaussian functions, voxel classification, and post filtering (Abi-Dargham et al., 2000 ).
Image analysis. Image analysis was performed blind to the
subject diagnosis with MEDx (Sensor Systems, Inc., Sterling, VA). To
correct for head movement during the acquisition, all frames were
coregistered to a frame of reference, using a least-square algorithm
for within modalities coregistration [automated image registration
(AIR)] (Woods et al., 1992 ). After frame-to-frame registration, the 18 frames were summed, and the summed PET image was coregistered and
resampled to the MRI, using AIR (Woods et al., 1993 ). The summed PET
image was used for the coregistration because it contains counts from
the initial, flow-dependent, activity distribution, which enhances
detection of boundaries of regions with low receptor density, such as
the cerebellum. The parameters of the spatial transformation matrix of
the summed PET data set were then applied to each individual frame.
Thus, each PET frame was resampled in the coronal plane to a voxel
volume of 1.5 × 0.9 × 0.9 mm3.
The boundaries for 14 regions of interest (ROIs) and one region of
reference were drawn on the MRI according to criteria based on brain
atlases (Talairach and Tournoux, 1988 ; Duvernoy, 1991 ) and on published
reports (Pani et al., 1990 ; Kates et al., 1997 ; Killiany et al., 1997 ).
Cortical regions (n = 8) included DLPFC, medial
prefrontal cortex (MPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), parietal cortex (PC), temporal cortex (TC),
parahippocampal gyrus (PHG), and occipital cortex (OC).
The prefrontal cortex was sampled from the most rostral plane to the
plane corresponding to the rostral boundary of the genu of the corpus
callosum. Prefrontal area ventral to the AC-PC plane was labeled OFC
and included the inferior rostral gyrus, the gyrus rectus, the orbital
gyrus, and the inferior frontal gyrus (orbital part). Prefrontal area
dorsal to the AC-PC plane was divided into a lateral and medial
section (medial section defined as cortex adjacent to the
interhemispheric fissure). The lateral section (dorsal part of superior
frontal gyrus, middle frontal gyrus and inferior frontal gyrus,
triangular part) was labeled DLPFC. This region includes Brodmann areas
9 and 46 (Rajkowska and Goldman-Rakic, 1995 ). The medial section
excluded the anterior cingulate and corresponded to the MPFC (areas 8 and 9, medial part of the superior frontal gyrus).
Subcortical regions (n = 6) included dorsal caudate
(DCA), dorsal putamen (DPU), ventral striatum (VST), thalamus (THA),
amygdala (AMY), and hippocampus (HIP). Criteria used to delineate
striatal subregions (DCA, DPU, and VST) are found in Mawlawi et al.
(2001) , and criteria used for other regions are available on request. Right and left regions for bilateral ROIs were averaged. The cerebellum (CER), a region with negligible density of D1
receptors, was used as region of reference to define the distribution
volume of the nonspecific compartment.
Two methods were used for final ROI definition. A segmentation-based
method was used for cortical regions, and a direct identification method was used for subcortical regions. For cortical regions, "large" regions were first drawn to delineate the boundaries of the
ROIs. Within these regions, only the voxels classified as gray matter
voxels by the MRI segmentation procedure were sampled to measure
activity distribution (see details in Abi-Dargham et al., 2000 ). The
steps involved in this method are illustrated in Figure
1. Because of the mixture of gray and
white matter in central gray structures (especially thalamus), the
segmentation-based approach was not used to define subcortical ROIs,
and the boundaries of these regions were identified by anatomical
criteria. The CER region included the whole structure (both gray and
white matter).

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Figure 1.
Illustration of the steps involved in the sampling
of activity from cortical regions. A coronal section 0.5 mm anterior to
the rostral part of the corpus callosum is displayed. The MRI
(A) is segmented into white matter, gray matter,
and CSF voxels. Gray matter voxels are assigned a value of 1, and all
other pixels are assigned a value of 0 to form a gray inverted mask
image (B). The coregistered PET image
(C) is multiplied by the mask
(B) to form a gray matter PET image
(D). Regional activities are sampled on
D in nonzero voxels. Region boundaries (white
lines) are illustrated on the right. The
yellow line corresponds to the AC-PC plane. The region
ventral to this plane is the OFC. Regions dorsal to the AC-PC plane
are divided into a lateral region (DLPFC) and medial regions, which, at
this level, include the MPFC and ACC, dorsal and ventral to the
cingulate gyrus, respectively.
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Derivation of regional total distribution volumes.
Derivation of [11C]NNC 112 regional
distribution volumes was performed using kinetic analysis and a three
compartment model in the ROIs and a two compartment model in the
cerebellum (Mintun et al., 1984 ; Abi-Dargham et al., 2000 ). The three
compartment configuration included the arterial plasma compartment
(Ca), the intracerebral free and
nonspecifically bound compartment (nondisplaceable compartment,
C2), and the specifically bound
compartment (C3). Brain activity was
corrected for the contribution of plasma activity assuming a 5% blood
volume (Mintun et al., 1984 ).
The total regional distribution volume
(VT, milliliters of plasma per gram of
tissue) was defined as the ratio of the tracer concentration in this
region (CT) to the
metabolite-corrected plasma concentration at equilibrium:
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(1)
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VT is equal to the sum of the
distribution volumes for the second (nondisplaceable,
V2) and third (specific,
V3) compartments. VT was derived from the kinetic rate
constants as:
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(2)
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where K1 (in milliliters per
gram per minute) and k2
(min 1) are the unidirectional fractional
rate constants for the transfer between
Ca and
C2, and
k3
(min 1) and
k4
(min 1) are the unidirectional fractional
rate constants for the transfer between
C2 and
C3. The terms
K1 and
k2 include the regional blood flow:
K1 = F(1 expPS/F) where F is regional
blood flow, and PS is the permeability surface area product
of the tracer; k2 = K1/V2f1.
Thus, distribution volumes (V2,
V3, and
VT) are flow independent (the flow is
present in both numerator and denominator and cancels out).
Kinetic parameters were derived by nonlinear regression using a
Levenberg-Marquardt least-squares minimization procedure (Levenberg, 1944 ) implemented in MATLAB (Math Works) as previously described (Laruelle et al., 1994b ). Given the unequal sampling over time (increasing frame acquisition time from beginning to end of the study),
the least squares minimization procedure was weighed by the square root
of the frame acquisition time.
Derivation of binding potential. The binding potential (BP,
milliliters per gram) was derived as the difference between total (VT) and nonspecific
(V2) distribution volumes, with
cerebellum VT used as a measure of
V2:
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(3)
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Under these conditions, BP is equal to (Laruelle et al., 1994a ):
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(4)
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where Bmax is the regional
concentration of D1 receptors,
KD is the affinity of
[11C]NNC 112 for
D1 receptors, and
f1 is the free fraction of
[11C]NNC 112 in the plasma. Although
f1 was measured in this study, the
derivation of BP was not corrected for
f1, given the low free fraction of
[11C]NNC 112 in the plasma (<1%) and
the lack of reliability of f1 measurement when f1 is <10%
(Abi-Dargham et al., 2000 ).
A second outcome measure of interest was the BP normalized to
cerebellum distribution volume, termed
V3".
V3" is equal to the ratio of BP to
V2 (Laruelle et al., 1994a ):
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(5)
|
where f2 is the free fraction
in the nondisplaceable compartment
(f2 = f1/V2).
Comparing Equations 4 and 5 informs on the nature of BP and
V3", respectively. Both outcome
measures are related to receptor parameters
Bmax and
KD plus a term unrelated to receptor
parameters, f1 and
f2, respectively. Thus, BP corrects for between-subject differences in nonspecific binding in the brain,
but is affected by between-subject differences in nonspecific binding
in the plasma. V3" corrects for
between-subject differences in nonspecific binding in the plasma, but
is affected by between-subject differences in nonspecific binding in
the brain. [11C]NNC 112 test-retest
studies demonstrated that BP and V3"
are affected by similar test-retest variability, but that the
intraclass correlation coefficient of BP was superior to
V3" (Abi-Dargham et al., 2000 ). Thus,
BP as defined by Equation 4 was a priori selected as the
primary outcome measure for this study.
Statistical analysis
Between-group comparisons were performed using two-tailed
unpaired t tests. Relationships between continuous variables
were analyzed with the Pearson product moment correlation coefficient. A probability value of 0.05 was selected as significance level.
The primary hypothesis of this study related to DLPFC
D1 receptor, and no correction for multiple
testing was applied to this region. Other regions were analyzed and
compared between groups, to test the regional specificity of the
finding in DLPFC. To correct for multiple testing and explore the
covariance structure among regions, principal component analysis with
varimax transformation was performed on the complete sample. Individual
regional BP values were transformed into z scores and
reduced to an appropriate number of factors using the factor weights
derived by the principal component analysis. Repeated measure ANOVA was
performed with factors as repeated measure and diagnosis as grouping
variable to test the existence of a factor by diagnosis interaction,
followed by unpaired t test on each factor.
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RESULTS |
Sample composition
Table 1 lists the demographic and
clinical variables of the samples. Groups were matched for age, gender,
race, socioeconomic status of the family of origin, and nicotine
smoking. The socioeconomic status of patients was lower than controls.
In the patient group, seven subjects were experiencing a first episode
of illness and had never been treated with antipsychotic medications at
the time of the scan. Nine subjects were chronic patients who had been previously treated with antipsychotic drugs. At the time of the scan,
these patients were off antipsychotics for 164 ± 173 d
(range from 15 to 360 d, with the latter value used for patients
off antipsychotic drugs for >1 year). Twelve patients were studied as
inpatients, and four patients were studied as outpatients. Duration of
illness was 6.8 ± 7.1 years (range from 4 weeks to 26 years).
Patients displayed a moderate level of symptom severity. PANSS-positive
symptoms subscale (seven positive symptoms rated from 1 to 7) score was
18.6 ± 7.5 (range from 7 to 33). PANSS-negative symptoms subscale
(seven negative symptoms rated from 1 to 7) was 18.4 ± 5.7 (range
from 11 to 30). PANSS general psychopathology subscale (16 symptoms
rated from 1 to 7) was 33.6 ± 7.6 (18-48).
Working memory assessment
The n-back task was administered to 14 patients and 15 controls
(three subjects were not available for testing). Twelve patients completed the n-back during the drug-free interval preceding the PET
study, and two completed it after the PET study, while on antipsychotic
medications (for scheduling reasons, not for clinical reasons).
Figure 2 presents the AHR for the 1-, 2-, and 3-back conditions for controls and patients with schizophrenia.
Controls performed almost perfectly at the 1- back with an AHR of
0.99 ± 0.03. The AHR in controls decreased to 0.86 ± 0.10 at 2-back and 0.72 ± 0.18 at 3-back. The AHR in patients with
schizophrenia was 0.88 ± 0.16 at 1-back, 0.61 ± 0.30 at
2-back, and 0.50 ± 0.28 at 3-back. Each of these distributions
had a mean significantly different from zero (one sample t
test; p < 0.001), indicating that patients performed
significantly above chance levels.

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Figure 2.
Adjusted hit rate (mean ± SD) for the 1-, 2-, and 3-back conditions in controls (CTR;
n = 15) and patients with schizophrenia
(SCH; n = 14). The adjusted hit rate
is the hit rate (number of correct responses divided by number of
targets) corrected for the error rate (number of incorrect responses
divided by number of nontargets) and ranges from +1 to 1. Patients
performed significantly worse than controls at each level of the task,
but above chance level (score of zero). Increasing task difficulty
results in similar relative decrements in performance in patients and
controls (repeated measures ANOVA, task level, p < 0.0001; diagnosis factor, p = 0.0017; diagnosis by
task level interaction, p = 0.27).
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The effect of working memory load (1- vs 2- vs 3-back) and diagnosis on
the AHR was evaluated with repeated measure ANOVA, with load level as
repeated factor. This test indicated a significant effect of task level
(p < 0.0001), diagnosis
(p = 0.001), but no task level by diagnosis
interaction (p = 0.23). Patients performed worse
than controls at each level of the task (1-back, p = 0.011; 2-back, p = 0.005; 3-back, p = 0.015). AHR variance was larger in patients compared with controls at
the 1-back (p < 0.0001), the 2-back
(p = 0.003), but not the 3-back
(p = 0.10). d' was calculated for
2-back and 3-back. For both conditions, d' in the patient group (2-back
d', 2.07 ± 1.04; 3-back d', 1.75 ± 1.01) was significantly
lower than d' in the control group (2-back d', 3.10 ± 0.60, p = 0.005; 3-back d', 2.57 ± 0.75, p = 0.003). AHR at 1-, 2-, and 3-back conditions were
not associated with age (r2 < 0.01 for all three correlations).
Among patients with schizophrenia, no differences were noted in AHR at
any level of the test between first episode patients never previously
exposed to antipsychotics (n = 7; AHR at 1-, 2-, and
3-back of 0.90 ± 0.10, 0.64 ± 0.28, and 0.49 ± 0.31, respectively) and chronic patients previously treated with
antipsychotics (n = 7; AHR at 1-, 2-, and 3-back of
0.85 ± 0.20, 0.57 ± 0.33, and 0.52 ± 0.26, respectively). Severity of positive, negative, or general symptoms
measured with the PANSS subscales were not predictive of performance at
1-back, 2-back, or 3-back conditions
(r2 < 0.15, p > 0.05 for all correlations).
D1 receptor measurements
[11C]NNC 112 injection parameters
No significant between-group differences were observed in the
[11C]NNC 112-injected dose (controls:
13.0 ± 4.4 mCi; patients with schizophrenia: 11.9 ± 5.2 mCi; p = 0.53), specific activity at time of injection
(controls: 1022 ± 545 Ci/mmol; patients with schizophrenia:
876 ± 528 Ci/mmol; p = 0.44), or injected mass (controls: 4.7 ± 1.3 µg; patients with schizophrenia: 5.0 ± 1.2 µg; p = 0.47).
[11C]NNC 112 input function
No significant between-group differences were observed in the
clearance rate of [11C]NNC 112 from the
plasma compartment (controls: 83 ± 21 l/hr; patients with
schizophrenia: 85 ± 32 l/hr; p = 0.81). The
plasma-free fraction (f1) was
similar in control subjects (0.81 ± 0.34%) and patients with
schizophrenia (0.83 ± 0.38%; p = 0.88),
supporting the use of BP as outcome measure (Eq. 4) for between-group comparisons.
[11C]NNC 112 cerebellum
distribution volume
The cerebellum distribution volume
(V2) was derived using a two
compartment model and was not significantly different between control
subjects (1.92 ± 0.43 ml/gm) and patients with schizophrenia (1.81 ± 0.46 ml/gm; n = 0.51). The free fraction
of the nonspecific distribution volume
(f2) was not different between
groups (controls, 0.43 ± 0.18%; patients, 0.47 ± 0.21%;
p = 0.55).
ROI volumes
Table 2 lists the ROI volumes in
healthy controls and patients with schizophrenia. No significant
between-group differences were found in DLPFC volumes, nor in volumes
of the other regions. A trend was observed for the hippocampus
(p = 0.05) and parahippocampal gyrus
(p = 0.07) volumes to be smaller in patients
with schizophrenia compared with controls, by 13 and 9%,
respectively.
[11C]NNC 112 delivery to the brain
No significant between-group differences were observed in the
regional rates of tracer delivery to the brain, as measured by the
parameter K1. For example, DLPFC
K1 was 0.14 ± 0.03 ml · gm 1 · min 1
in control subjects and 0.15 ± 0.04 ml ·gm 1 · min 1
in patients with schizophrenia (p = 0.46).
Assuming that patients and controls have similar permeability-surface
area product for [11C]NNC 112, this
result indicates no significant between-group difference in regional
blood flow.
[11C]NNC 112 regional BP
The regional uptake of [11C]NNC 112 was consistent with the known distribution of D1
receptors in the human brain. Representative images and regional time-activity curves
are presented in Figures 3 and 4,
respectively.

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Figure 3.
MRI and coregistered [11C]NNC
112 PET images. The PET image represents the activity recorded from 30 to 60 min after injection of 13.3 mCi in a 37-year-old healthy female
volunteer. A, B, Sagittal view,
illustrating the contrast between cortical and cerebellar activities.
C, D, Transaxial view, at the level of the head of
caudate, putamen, and thalamus. E, F,
Coronal view, at the level of the anterior striatum, illustrating the
lower level of activity in the ventral striatum compared with the
caudate and putamen. G, H, Coronal view
at the level of the hippocampus, illustrating low levels of activity in
thalamus, hippocampus, and parahippocampal gyrus. Putamen and caudate
activities are still visualized.
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Figure 4.
Regional time-activity curves after injection of
16.6 mCi [11C]NNC 112 in a 42-year-old male
healthy volunteer. Only a subset of regions are represented: dorsal
caudate (closed squares), ventral striatum (open
squares), dorsolateral prefrontal cortex (closed
circles), hippocampus (closed triangles), and
cerebellum (open circles). Points are
measured values for each frame, and lines are values fitted
to a three compartment model.
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DLPFC [11C]NNC 112 BP was significantly
higher in patients with schizophrenia compared with control subjects
(p = 0.02) (Table 3). The distribution of DLPFC
[11C]NNC 112 BP values in each group is
presented in Figure 5. The variance was
not different between groups (F test; p = 0.70). One value in the patients group was an outlier, with
z score of 2.26. No rationale was identified to exclude this
observation a posteriori. Nonetheless, the analysis was
repeated without this value, and provided similar results
(p = 0.038). The absence of significant
between-group differences in DLPFC volume indicates that the
between-group difference in DLPFC
[11C]NNC 112 BP was not attributable to
partial voluming effects.

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Figure 5.
Distribution of [11C]NNC 112 BP in DLPFC of healthy controls (n = 16; open
circles) and patients with schizophrenia (n = 16;
antipsychotic-naive patients, open squares; patients
antipsychotic-free for >1 year, closed circles;
patients with 2-3 weeks of antipsychotic-free interval, closed
triangles). Patients with schizophrenia displayed increased
D1 receptor availability compared with controls
(p = 0.02).
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Table 3 also lists [11C]NNC 112 BP
values in other regions. A trend was observed for higher
[11C]NNC 112 BP in the MPFC
(p = 0.08) and temporal cortex
(p = 0.08; values not corrected for multiple
testing). Other regions did not show significant between-group
differences in [11C]NNC 112 BP.
Principal component analysis was applied to
[11C]NNC 112 BP values from the 14 regions included in Table 3. This analysis returned three significant
factors (eigenvalues higher than 1) that accounted for 87% of the
variance. The regional weights associated with each factor are
presented in Table 4. Factor 1 accounted
for 54% of the variance, showed high loads for anterior neocortical
regions, and was termed frontocortical factor. Factor 2 accounted for
19% of the variance and was essentially contributed to by the striatal
regions. A third factor was extracted, accounting for 10% of the
variance and showing high loads in hippocampus and thalamus only.
Individual values on each factor were computed by multiplying the
z score matrix of regional
[11C]NNC 112 BP value by the factor
weight matrix. Repeated measure ANOVA with factors as repeated measure
and diagnosis as factor showed no diagnosis effect
(p = 0.62), but a significant factor by
diagnosis interaction (p = 0.036). Post
hoc analysis revealed that patients with schizophrenia had
significantly higher values on factor 1 compared with controls
(p = 0.016). No significant differences were
observed in factors 2 (p = 0.38) and 3 (p = 0.21). Together, these data indicated a
relatively diffuse and significant increase in neocortical
D1 receptor availability in patients with schizophrenia, most pronounced in DLPFC.
[11C]NNC 112 regional V3"
Results obtained with V3"
(=BP/V2) were essentially similar to results
obtained with BP, which was expected from the absence of between-group
differences in V2. Thus, DLPFC was the only
region showing a significant difference in
[11C]NNC 112 V3"
(higher in patients compared with controls; p = 0.03).
DLPFC D1 receptors BP and clinical variables
A significant age-related decline in DLPFC
[11C]NNC 112 BP was observed in the
entire sample (r2 = 0.13;
p = 0.02) (Fig. 6). This
relationship was present in both groups,
but failed to reach significance when groups were analyzed separately
(control subjects: r2 = 0.11, p = 0.08; patients with schizophrenia,
r2 = 0.17, p = 0.11). No age by diagnosis interaction was observed for DLPFC
[11C]NNC 112 BP
(p = 0.62), suggesting that age affected both
groups similarly.

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Figure 6.
Effect of aging on [11C]NNC
112 BP in DLPFC of healthy controls (open circles) and
patients with schizophrenia (closed circles). A
significant age-related decline in DLPFC [11C]NNC
112 BP was observed in the entire sample
(r2 = 0.13;
p = 0.02). No age by diagnosis interaction was
observed for DLPFC [11C]NNC 112 BP
(p = 0.62), suggesting that age affected
both groups similarly.
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In the patient group, DLPFC [11C]NNC 112 BP was not significantly different between first episode-antipsychotic
drug-naive patients (n = 7; age = 30 ± 13 years; DLPFC [11C]NNC 112 BP = 1.64 ± 0.23 ml/gm) and chronic patients previously exposed to
antipsychotic medications (n = 9; age = 35 ± 12 years; DLPFC [11C]NNC 112 BP = 1.62 ± 0.50 ml/gm; p = 0.94). Among the
previously treated patients, five underwent inpatient washout and had a
relatively brief drug-free interval before the PET scan (19 ± 3 d), and four were not taking antipsychotic drugs for at least 1 year before the PET scan. DLPFC [11C]NNC
112 BP was not different between previously treated patients with short
(1.70 ± 0.55 ml/gm) or long drug-free interval (1.52 ± 0.40 ml/gm; p = 0.62). In previously treated patients, no
relationship was observed between duration of the drug-free interval
and DLPFC [11C]NNC 112 BP
(r2 = 0.03; p = 0.66). Together, these data indicate that the upregulation of
D1 receptors in the DLPFC in patients with
schizophrenia was not related to previous exposure to antipsychotic medications.
In the patient group, DLPFC [11C]NNC 112 BP was not significantly associated with severity of positive symptoms
as assessed by the PANSS-positive subscale
(r2 = 0.02; p = 0.65), nor with severity of negative symptoms (PANSS-negative subscale;
r2 = 0.04; p = 0.21), nor with general psychopathology (PANSS general psychopathology
scale; r2 = 0.04;
p = 0.46). DLPFC
[11C]NNC 112 BP was not associated with
duration of illness (r2 = 0.03;
p = 0.49).
DLPFC D1 receptors BP and working
memory performance
The hypothesis of an association between D1
receptor availability in DLPFC and n-back performance was tested in the
entire sample and in each group separately (Table
5). When analyzing both groups together,
an association was observed between low working memory
performance at 1-, 2-, and 3-back and high DLPFC [11C]NNC 112 BP. This effect was
accounted for by the patients with schizophrenia. Within the control
group, there was no relationship between performance on the n-back and
D1 receptor availability. In patients with
schizophrenia, high DLPFC D1 receptor
availability was associated with low AHR at 2-back
(r2 = 0.31; p = 0.04) and at 3-back (r2 = 0.45;
p = 0.008). Similar results were observed with d'
(2-back, r2 = 0.29, p = 0.04; 3-back,
r2 = 0.43, p = 0.01). The relationship between DLPFC
[11C]NNC 112 BP and AHR at the 3-back
condition is presented in Figure 7.

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Figure 7.
Relationship between [11C]NNC
112 BP in DLPFC (x-axis) and performance
(AHR) at the 3-back test (y-axis)
in healthy controls (left) and in patients with
schizophrenia (right). The AHR ranges from 1 (best
performance) to 1 (worse performance), with a score of 0 corresponding to performance at chance level. In controls, DLPFC
D1 receptor availability was not associated with
performance at the task. In patients with schizophrenia, increased
DLPFC D1 receptor availability was associated with low
performance at the task (r2 = 0.45; p = 0.008). Note the difference in
x-axis scales between controls and patients with
schizophrenia. Similar findings were observed with the 2-back (Table
5).
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DISCUSSION |
The main findings of this study are that DLPFC
D1 receptor availability, measured by the
in vivo binding of [11C]NNC
112, is increased in never-treated and currently untreated patients
with schizophrenia, and that this increase is a strong predictor of
decreased performance at the n-back task.
Because of the evidence implicating DLPFC DA transmission in working
memory processes, evaluation of [11C]NNC
112 BP in the DLPFC was the primary focus of this study. Other regions
were also investigated to assess the regional specificity of the
results in the DLPFC. The DLPFC was the only region examined in which a
significant difference in [11C]NNC 112 BP was found between patients with schizophrenia and controls. However,
principal component analysis indicated that the alteration of DA
transmission associated with increased
[11C]NNC 112 BP might not be restricted
to the DLPFC, because other cortical regions such as MPFC showed high
covariance with DLPFC. Analysis of a larger sample is required to
further explore this issue. In contrast, there was no indication for
alterations in [11C]NNC 112 BP in
striatal, limbic, and thalamic regions.
The absence of change in striatal
[11C]NNC 112 BP observed in this study
is consistent with postmortem studies that reported unaltered striatal
binding of [3H]SCH 23390 in
schizophrenia (Pimoule et al., 1985 ; Seeman et al., 1987 ; Joyce et al.,
1988 ; Reynolds and Czudek, 1988 ), although one study reported decreased
striatal binding of [3H]SCH 23390 in
schizophrenia (Hess et al., 1987 ).
The significant increase in DLPFC
[11C]NNC 112 BP observed in patients
with schizophrenia contrasts with results of three previous postmortem
studies. Two studies evaluated the binding of
[3H]SCH 23390 in the PFC in
schizophrenia. One homogenate binding study reported no change
(Laruelle et al., 1990 ), and one autoradiography study reported a
nonsignificant increase (Knable et al., 1996 ). PFC
D1 receptor mRNA levels were also reported
unchanged (Meador-Woodruff et al., 1997 ). These postmortem results
might be affected by antemortem medications, because administration of
antipsychotic drugs downregulate PFC D1 receptor
mRNA and proteins (Lidow and Goldman-Rakic, 1994 ; Lidow et al.,
1997 ).
The results presented here contrast with the results of a previous PET
study that reported lower [11C]SCH 23390 k3/k4 ratio
(V3" in our notation) in the PFC in
patients with schizophrenia (Okubo et al., 1997 ). In addition to
potential clinical differences in clinical populations and symptoms
severity, several critical technical factors limit the comparability of these studies: (1) the PFC-cerebellum distribution volume ratio of
[11C]SCH 23390 is in the 1.2-1.4 range,
versus 1.7-2 for [11C]NNC 112, indicating that [11C]NNC 112 is a
superior ligand for the measurement of D1
receptors in the PFC; (2) the PET camera used by Okubo et al. (1997)
was a seven slices device, with limited field of view and limited resolution compared with the camera used in this study; (3)
[11C]SCH 23390 displays a relatively low
selectivity against 5HT2A/2C receptors (Laruelle
et al., 1991 ), whereas [11C]NNC 112 in vivo binding in the PFC is not affected by pretreatment with selective 5HT2A/2C antagonists (Halldin et
al., 1998 ); (4) several lines of evidence suggest that the cellular
localization of D1 receptors differentially
influence the in vivo binding of [11C]SCH 23390 and
[11C]NNC 112 (for review, see Laruelle,
2000 ). Acute DA depletion has no effect on the in vivo
binding of [11C]NNC 112, but decreases
the in vivo binding of
[3H]SCH 23390 (Guo et al., 2000 ), an
effect that might be attributable to receptor translocation from the
endosomial compartment to the cell surface and lower in vivo
affinity of SCH 23390 for externalized compared with internalized
receptors (Dumartin et al., 2000 ; Laruelle, 2000 ). In addition,
sustained DA depletion induced by chronic reserpine treatment (21 d) is
associated with increased in vivo [11C]NNC 112 binding in the rat PFC
(presumably reflecting increase in D1 receptor
expression) (Guo et al., 2001 ). However, the same treatment failed to
produce detectable changes in the in vivo binding of
[3H]SCH 23390 in the PFC (Guo et al.,
2001 ), maybe because the opposite effects of receptor upregulation and
externalization on [3H]SCH 23390 in vivo binding cancel each other. Further research is
warranted to elucidate the role of these factors in the discrepant findings between these two studies.
Patients enrolled in this study performed significantly worse than
controls at each working memory load, but, even at the challenging
3-back load, performed significantly above chance level. This
observation might reflect a selection bias toward patients with
moderate pathology, because of the rigor of the capacity to consent
evaluation. In these patients, increased DLPFC D1
receptor availability was a strong predictor of poor performance at the
2-back and 3-back conditions (approximately one-third of the variance
in 2- and 3-back AHR was accounted for by the variance in DLPFC
[11C]NNC 112 BP). This relationship
supports the involvement of altered DLPFC D1
receptor transmission in the working memory deficits presented by these
patients. Although it has been argued that working memory deficit might
be the fundamental cognitive impairment in schizophrenia
(Goldman-Rakic, 1994 ), patients with schizophrenia are impaired on
multiple cognitive dimensions such as attention, learning and memory,
executive function, and general intelligence (Braff et al., 1991 ;
Saykin et al., 1994 ). Studies in a larger sample of subjects
characterized with a comprehensive neuropsychological battery are
warranted to test the specificity of the association between increased
D1 receptor availability and working memory deficits.
The in vivo binding of
[11C]NNC 112 is not affected by acute
changes in endogenous DA (Abi-Dargham et al., 1999 ; Chou et al., 1999 ;
Guo et al., 2000 ). It is therefore reasonable to assume that the
increased [11C]NNC 112 binding observed
in this study reflects increased concentration of
D1 receptors in DLPFC of patients with
schizophrenia. This increased concentration might represent a primary
phenomenon or a compensatory upregulation secondary to chronic
deficiency in D1 receptor stimulation by DA. At
this point, both possibilities must be entertained, but the second
hypothesis is favored by several lines of evidence.
The first interpretation (increase in DLPFC D1
receptor is a primary phenomenon) might suggest that the alteration in
working memory performance seen in these patients results from
increased postsynaptic sensitivity to DA released in the DLPFC during
performance of the task (Watanabe et al., 1997 ). This view is
consistent with the evidence that excessive stimulation of
D1 receptors, either because of excessive DA
release or to high doses of DA agonists (Arnsten et al., 1994 ; Murphy
et al., 1996a ,b ; Cai and Arnsten, 1997 ; Zahrt et al., 1997 ), is
associated with a deterioration of working memory function in primates.
This interpretation would predict that administration of
D1 antagonists should improve working memory
function in patients with schizophrenia. While we are not aware of
studies that specifically evaluated the effect of
D1 receptor antagonists on working memory
function in schizophrenia, limited therapeutic trials with selective
D1 receptor antagonists in schizophrenia showed a
lack of efficacy or even worsening of clinical conditions (de
Beaurepaire et al., 1995 ; Den Boer et al., 1995 ; Karle et al., 1995 ;
Karlsson et al., 1995 ).
The second interpretation (increase in DLPFC D1
receptors is a compensatory response to deficit in presynaptic DA
function) is consistent with several indirect lines of evidence
suggesting that schizophrenia might be associated with a deficit in
prefrontal DA function. This hypothesis was proposed based on the
relationship between low CSF homovanillic acid and poor
performance at tasks involving the DLPFC in schizophrenia (Weinberger
et al., 1988 ; Kahn et al., 1994 ), and on the beneficial effect of DA
agonists on the pattern of DLPFC activation measured with PET during
these tasks (Daniel et al., 1989 , 1991 ; Dolan et al., 1995 ). More
direct evidence for such a deficit was recently provided by one
postmortem study suggesting a decrease in DA innervation in the DLPFC
(Akil et al., 1999 ). This interpretation is also consistent with the performance deficits at delayed-response tasks observed in nonhuman primate models of prefrontal DA deficiency (selective 6-OHDA-induced DA
depletion in the PFC, aged monkeys, and monkeys chronically treated
with haloperidol). These deficits are reversed by indirect DA agonists
and D1 agonists (Brozoski et al., 1979 ; Arnsten
et al., 1994 ; Cai and Arnsten, 1997 ; Castner et al., 2000 ). This view
is also supported by the observation that chronic phencyclidine exposure, which induces in humans symptoms reminiscent of schizophrenia (for review, see Javitt and Zukin, 1991 ), is associated with both impaired working memory performance and decreased DA turnover in the
PFC in rodents and primates (for review, see Jentsch and Roth,
1999 ).
The observation that chronic DA depletion is associated with increased
in vivo binding of [11C]NNC
112 in the PFC supports the plausibility of this interpretation of the
PET findings (Guo et al., 2001 ). If this hypothesis is correct, both
the increase in DLPFC [11C]NNC 112 BP
and the decrease in n-back performance would be related to a common
cause, i.e., a deficit in mesocortical presynaptic DA function. The
similarity in DLPFC [11C]NNC 112 BP
between first episode and chronic patients and the absence of
association between this parameter and duration of illness are
consistent with the hypothesis that this mesocortical DA function
deficiency might be of neurodevelopmental origin (Weinberger, 1987 ).
This interpretation suggests that working memory function in patients
with schizophrenia might be improved by DA agonists.
A third possible interpretation of the data that combines elements of
the first and second interpretations should also be discussed. A
persistent decrease in prefrontal DA activity might induce upregulation
of D1 receptors. This upregulation, which could
be associated with increased sensitivity to agonists, might create
conditions in which the increase in DA associated with stress or
cognitive demands would result in an overstimulation of these
upregulated D1 receptors. This model would
predict that acute administration of a D1
receptor agonist might be detrimental, although repeated administration
of a D1 agonist might lead to desensitization of
the receptors and thus have long term therapeutic effects. The
development of an effective D1 receptor agonist
suitable for human administration is critical to test these predictions.
Conclusions
In this study, D1 receptor availability was
measured in vivo with PET and
[11C]NNC 112 in untreated patients with
schizophrenia and controls. [11C]NNC 112 BP was significantly elevated in the DLPFC, as well as, to a lower
extent, in other anterior cortical regions. This increase was not
caused by previous antipsychotic medications and was not associated
with the severity of clinical symptomatology. However, excessive
expression of D1 receptor in the DLPFC was strongly associated with impaired performance at the n-back task, a
test of working memory function, confirming in humans the critical role
of prefrontal D1 receptor transmission in
delayed-response tasks observed in animal studies. We propose that both
D1 receptor upregulation and impaired working
memory performance might be caused by a chronic deficit in presynaptic
DA function in the DLPFC of patients with schizophrenia. Additional
imaging studies are warranted to confirm these data in an extended
sample, to study the specificity of the relationship between
cortical D1 receptor expression and working
memory relative to other cognitive impairments, and to evaluate the
relationship between prefrontal presynaptic DA function and
D1 receptor availability in patients with schizophrenia.
 |
FOOTNOTES |
Received Aug. 24, 2001; revised Jan. 28, 2002; accepted Feb. 4, 2002.
This work was supported by United States Public Health Service Grant
RO1 MH59144-01 from the National Institute of Mental Health, a
Charles A. Dana Foundation grant, and the Lieber Center for
Schizophrenia Research. We thank the subjects who participated in the
study, Christer Halldin (Karolinska Institute, Stockholm, Sweden), who
provided the desmethyl precursor of [11C]NNC 112, Drs. Janine Rodenhiser-Hill, Mark Slifstein, and Eric Zarahn, and the
expert technical assistance of Marcella Bonjovi, Nicole Eftychiou,
Ingrid Gelbard, David Amstel, Heather Lawson, Jennifer Bae, Mohamed
Ali, Julie Montoya, Kim Ngo, Norman Simpson, and Kris Wolff as well as
the staff of the Schizophrenia Research Center at the New York State
Psychiatric Institute.
Correspondence should be addressed to Dr. Anissa Abi-Dargham, New York
State Psychiatric Institute, 1051 Riverside Drive, Box 31, New York, NY
10032. E-mail: aa324{at}columbia.edu.
 |
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