Similar amyloid-β burden in posterior cortical atrophy and Alzheimer's disease.

Abstract

While the clinical presentation of posterior cortical atrophy is clearly distinct from typical Alzheimer's disease, neuropathological studies have suggested that most patients with posterior cortical atrophy have Alzheimer's disease with an atypical visual presentation. We analysed in vivo pathophysiological markers of Alzheimer's disease such as cerebrospinal fluid biomarkers and positron emission tomography imaging with ¹¹C-labelled Pittsburgh compound-B in posterior cortical atrophy to determine whether biochemical profile and fibrillar amyloid-β burden topography are associated with the clinical presentation. Nine patients with posterior cortical atrophy and nine with typical Alzheimer's disease individually matched for age, duration and severity of the disease and 10 cognitively normal age-matched controls were included. ¹¹C-labelled Pittsburgh compound-B images were analysed both using volumes of interest and on a voxel-wise basis using statistical parametric mapping, taking into account the individual regional cortical atrophy. Cerebrospinal fluid biomarkers did not differ between posterior cortical atrophy and patients with Alzheimer's disease. Compared with normal controls, both posterior cortical atrophy and Alzheimer's disease groups showed increased ¹¹C-labelled Pittsburgh compound-B uptake. No significant difference was found in regional or global ¹¹C-labelled Pittsburgh compound-B binding between posterior cortical atrophy and Alzheimer's disease groups with both volumes of interest and voxel-wise basis using statistical parametric mapping methods. Our findings demonstrate that cerebrospinal fluid biomarkers and positron emission tomography imaging with ¹¹C-labelled Pittsburgh compound-B may be useful in identifying an atypical visual form of Alzheimer's disease. The similar topography of fibrillar amyloid-β deposition between typical Alzheimer's disease and posterior cortical atrophy groups suggests that, although amyloid-β accumulation plays a critical role in the pathogenesis of Alzheimer's disease, other factors such as neurofibrillary tangles may contribute to the different clinical features observed in posterior cortical atrophy.

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BRAIN
A JOURNAL OF NEUROLOGY
Similar amyloid-b burden in posterior cortical
atrophy and Alzheimer’s disease
Leonardo Cruz de Souza,1,2,3,4,5,* Fabian Corlier,1,2,3,4,5,* Marie-Odile Habert,6,7
Olga Uspenskaya,1,2,3,4,5Renaud Maroy,8Foudil Lamari,9Marie Chupin,1,2,3,4
Ste ´phane Lehe ´ricy,1,2,3,4,10Olivier Colliot,1,2,3,4Vale ´rie Hahn-Barma,1,5Dalila Samri,1,5
Bruno Dubois,1,2,3,4,5Michel Bottlaender8and Marie Sarazin1,2,3,4,5
1 Universite ´ Pierre et Marie Curie-Paris 6, Centre de Recherche de l’Institut du Cerveau et de la Moelle E´pinie `re, UMR-S975, 47-83 bd de l’Ho ˆpital,
75013 Paris, France
2 Inserm, U975, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
3 CNRS, UMR 7225, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
4 Institut du Cerveau et de la Moelle E´pinie `re, ICM, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
5 Alzheimer Institute; Research and Resource Memory Centre; Centre de Re ´fe ´rence de De ´mences Rares, Centre de re ´fe ´rence maladie d’Alzheimer
jeune, AP-HP, Pitie ´-Salpe ˆtrie `re Hospital, 47-83 boulevard de l’Ho ˆpital, 75013 Paris, France
6 AP-HP, Groupe hospitalier Pitie ´-Salpe ˆtrie `re, Service de Me ´decine Nucle ´aire, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
7 Universite ´ Pierre et Marie Curie-Paris 6, INSERM, UMR-S 678, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
8 CEA, DSV, I2BM, Service Hospitalier Fre ´de ´ric Joliot, 4, place du Ge ´ne ´ral Leclerc, 91401 Orsay, France
9 Department of Metabolic Biochemistry, AP-HP, Pitie ´-Salpe ˆtrie `re Hospital, 47-83 bd de l’Ho ˆpital, 75013 Paris, France
10 Centre de Neuroimagerie de Recherche – CENIR and Department of Neuroradiology, Pitie ´-Salpe ˆtrie `re Hospital, 47-83 Boulevard de l’Ho ˆpital,
75013 Paris, France
*These authors contributed equally to this work.
Correspondence to: Dr Marie Sarazin,
Fe ´de ´ration des maladies du Syste `me Nerveux,
Research and Resource Memory Centre,
Pavillon Jean Lhermitte,
Ho ˆpital de la Salpe ˆtrie `re,
47 Boulevard de l’Ho ˆpital,
75013 Paris,
France
E-mail: marie.sarazin@psl.aphp.fr
While the clinical presentation of posterior cortical atrophy is clearly distinct from typical Alzheimer’s disease, neuropathological
studies have suggested that most patients with posterior cortical atrophy have Alzheimer’s disease with an atypical visual
presentation. We analysed in vivo pathophysiological markers of Alzheimer’s disease such as cerebrospinal fluid biomarkers and
positron emission tomography imaging with
whether biochemical profile and fibrillar amyloid-b burden topography are associated with the clinical presentation. Nine pa-
tients with posterior cortical atrophy and nine with typical Alzheimer’s disease individually matched for age, duration and
severity of the disease and 10 cognitively normal age-matched controls were included.
images were analysed both using volumes of interest and on a voxel-wise basis using statistical parametric mapping, taking into
account the individual regional cortical atrophy. Cerebrospinal fluid biomarkers did not differ between posterior cortical atrophy
and patients with Alzheimer’s disease. Compared with normal controls, both posterior cortical atrophy and Alzheimer’s disease
11C-labelled Pittsburgh compound-B in posterior cortical atrophy to determine
11C-labelled Pittsburgh compound-B
doi:10.1093/brain/awr130Brain 2011: 134; 2036–2043 |
2036
Received February 16, 2011. Revised April 7, 2011. Accepted April 18, 2011
? The Author (2011). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
For Permissions, please email: journals.permissions@oup.com
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groups showed increased11C-labelled Pittsburgh compound-B uptake. No significant difference was found in regional or global
11C-labelled Pittsburgh compound-B binding between posterior cortical atrophy and Alzheimer’s disease groups with both
volumes of interest and voxel-wise basis using statistical parametric mapping methods. Our findings demonstrate that cere-
brospinal fluid biomarkers and positron emission tomography imaging with11C-labelled Pittsburgh compound-B may be useful
in identifying an atypical visual form of Alzheimer’s disease. The similar topography of fibrillar amyloid-b deposition between
typical Alzheimer’s disease and posterior cortical atrophy groups suggests that, although amyloid-b accumulation plays a critical
role in the pathogenesis of Alzheimer’s disease, other factors such as neurofibrillary tangles may contribute to the different
clinical features observed in posterior cortical atrophy.
Keywords: Alzheimer’s disease; posterior cortical atrophy; Pittsburgh compound-B
Abbreviations:11C-PIB =11C-labelled Pittsburgh compound-B; PCA = posterior cortical atrophy
Introduction
Posterior cortical atrophy (PCA) can be defined as an atypical form
of Alzheimer’s disease, as shown by neuropathological studies
(Renner et al., 2004; Tang-Wai et al., 2004; Alladi et al., 2007).
However, the clinical presentation of PCA is clearly distinct from
typical Alzheimer’s disease (Dubois et al., 2010). In PCA, disease
onset is characterized by visual disturbances, followed by an im-
pairment of visuospatial skills, while episodic memory is relatively
spared (McMonagle et al., 2006). Neuroimaging shows atrophy
and hypoperfusion/hypometabolism that predominates in the
parieto-occipital cortex regions (Lehmann et al., 2009), with a rela-
tive sparing of the temporal regions (Aharon-Peretz et al., 1999;
Nestor et al., 2003). This clinical presentation contrasts with typ-
ical Alzheimer’s disease, which is characterized by an early episodic
memory deficit associated with prominent medial temporal lobe
atrophy.
Pathophysiological markers can help identify the underlying aeti-
ology of PCA (Dubois et al., 2010). CSF biomarker levels are con-
sidered to reflect Alzheimer pathology and can be useful in
isolating patients with an atypical Alzheimer’s disease phenotype
(Baumann et al., 2010; de Souza et al., 2011).
Pittsburgh compound-B (11C-PIB)-PET scanning measures the fi-
brillar amyloid-b deposition (Ikonomovic et al., 2008). Only two
cases of PCA have been published with details of11C-PIB binding
showing a high amyloid-b burden in the occipital cortex (Ng et al.,
2007; Migliaccio et al., 2009), which is not the most affected re-
gion in Alzheimer’s disease (Kemppainen et al., 2006). Better char-
acterization of CSF and PET amyloid deposition profiles in patients
with PCA would improve diagnosis and facilitate inclusion in
clinical trials of Alzheimer’s disease-modifying drugs.
We aimed to analyse both CSF biomarkers and
profiles in subjects with PCA. Because PCA and Alzheimer’s
disease are likely to have the same underlying neuropathological
process, we hypothesize that the two groups would present
similar CSF and PIB binding patterns. Therefore, we studied the
topographyof amyloid deposition
Alzheimer’s disease to examine whether the different clinical pres-
entations of PCA and typical Alzheimer’s disease were associated
with a distinct distribution and burden of fibrillar amyloid-b
deposition.
11C-labelled
11C-PIB-PET
in PCA comparedwith
Materials and methods
Subjects
Nine patients with PCA were enrolled on the basis of following diagnostic
criteria (McMonagle et al., 2006; Alladi et al., 2007): (i) insidious onset
and gradual progression of cognitive impairment beginning with visual
complaints; (ii) presentation with visuospatial deficits with intact pri-
mary visual function; (iii) features suggestive of Ba ´lint’s syndrome
(optic ataxia, ocular apraxia and simultagnosia) associated or not
with Gerstmann’s (acalculia, agraphia, left–right disorientation and
finger agnosia) syndrome; (iv) proportionally less episodic memory im-
pairment; (v) relatively preserved insight; and (vi) glucose hypometa-
bolism on
cortical atrophy in the posterior cortical region on MRI. A complete
Ba ´lint’s syndrome was observed in seven of nine patients with PCA,
while incomplete Ba ´lint’s syndrome was present in two of nine subjects
(isolated simultagnosia for one patient, and simultagnosia with oculo-
motor apraxia for the other). In addition, complete Gerstmann’s syn-
drome was observed in three of nine patients with PCA; incomplete
Gerstmann’s syndrome was present in six of nine patients. Ideomotor
apraxia, acalculia, agraphia and environmental disorientation were
observed for eight of nine patients, visual agnosia, hemineglect and
finger agnosia were present in seven of nine patients and dressing
apraxia in five of nine patients with PCA (refer to Supplementary
Table 1 for details).
Nine typical patients with Alzheimer’s disease were individually
matched with subjects with PCA for age, duration of disease and dis-
ease severity assessed by the Clinical Dementia Rating scale score.
Individual matching was used to avoid a selection bias caused by
these parameters. All subjects with Alzheimer’s disease were selected
according to the New Research Criteria (Dubois et al., 2007, 2010),
which include (i) progressive episodic memory impairment, character-
ized by a low free recall not normalized with cueing; (ii) CSF
Alzheimer’s disease profile, defined as score below 0.8 for the ratio
of amyloid-b42:tau,calculated
[240 + (1.18 ? T-tau)] (Visser et al., 2009); and (iii) clinical dementia
rating scale50.5.
Ten healthy elderly controls were recruited for the study according to
the following criteria: (i) Mini-Mental State Examination score 528/30
and clinical dementia rating scale = 0; (ii) no history of neurological or
psychiatric disorders; and (iii) no memory complaint or cognitive
deficit.
Subjects were not included in the study if they presented any of the
following criteria: (i) systemic illnesses that could interfere with
18F-fluorodeoxyglucose-PET examination and prominent
withtheformula amyloid-b42/
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cognitive functioning; (ii) extrapyramidal signs or neurological history
suggestive of Parkinson’s disease with dementia, progressive supra-
nuclear palsy, corticobasal degeneration or dementia with Lewy
bodies; (iii) vascular lesions on MRI or neurological history suggestive
of vascular dementia; or (iv) depression assessed with a score 420 on
the Montgomery-Asberg Depression
Montgomery and Asberg, 1979).
Blood samples were drawn to characterize APOE genotypes. The
controls underwent the same procedures as did the patients with
PCA and Alzheimer’s disease, except for lumbar puncture, which
was not proposed due to ethical reasons.
The study was conducted by the French National Institute of Health
and Medical Research (INSERM; ANR-07-LVIE-002-01) and was
approved by the Ethics Committee of Pitie ´-Salpe ˆtrie `re Hospital. All
subjects provided written informed consent before participating.
Rating Scale(MADRS;
Clinical, functional and cognitive
assessment
All subjects (healthy controls, Alzheimer’s disease and PCA) underwent
a clinical and neuropsychological examination that included the Mini-
Mental State Examination (Folstein et al., 1975), the clinical dementia
rating scale (Morris, 1993) and tests for assessing verbal episodic
memory, executive functions, working memory, gesture praxis and
visuoconstructive function. In addition, subjects with PCA underwent
a specific ‘posterior neuropsychological battery’ assessing hemineglect,
spatial disorientation, body schema distortion, Ba ´lint’s and Gerstmann’s
syndromes (Kas et al., 2011).
Cerebrospinal fluid biomarker analysis
CSF samples obtained by lumbar puncture were processed with the
same procedures described previously (de Souza et al., 2011) to obtain
CSF levels of total tau (T-tau), phosphorylated tau at threonine 181
(P-Tau) and amyloid-b peptide 1-42 (amyloid-b42) by using enzyme-
linked immunosorbent assay kits (Innogenetics), according to the
manufacturer’s instructions. All operators were blind to clinical
information.
Magentic resonance imaging procedure
In each participant, the imaging data were collected using a 3T
Siemens 32-channel TRIO TIM system using 12-channel head coil
for signal reception. The MRI examination included a 3D T1-weighted
volumetric magnetization-prepared rapid-gradient echo sequence with
repetition time = 2300ms, echo time = 3.43ms, inversion time = 900,
256 ? 256 matrix, axial field of view and slice thickness 1mm. This
sequence provided a high grey/white matter contrast-to-noise ratio
and allowed for excellent segmentation and accurate coregistration
with the PET images.
Positron emission tomography imaging
procedure
Data acquisition
PET examinations were performed with a High Resolution Research
Tomograph (HRRT, Siemens Medical Solution), the camera with the
highest available spatial resolution for brain imaging. The spatial reso-
lution for the HRRT scanner was 2.5mm with an absolute sensitivity of
6% for a point source in the centre of the field of view. The HRRT had
an axial field of view of 25cm and a transaxial field of view of
31.2cm. It allowed the reconstruction of 207 slices of 1.1mm thick-
ness. Subjects were positioned in the tomograph with the head
maintained using an individually moulded head holder. A 6-min
brain transmission scan was performed before injection of each
radioligand using a
for tissue attenuations.
intravenously, and PET acquisitions lasted 90min. Twenty-five images
were reconstructed with a scan duration starting from 1min and
increasing up to 10min during the experiment. All images were recon-
structed with anaccelerated
ordered-subset expectationmaximization
including an experimental stationary model of the scanner spatial reso-
lution that allowed for a lowering or the statistical noise at the voxel
level in the reconstructed images without degrading spatial resolution
(Sureau et al., 2008). This method improved quantitative accuracy by
reducing the partial volume effects.
137Cs point source to correct the emission scan
11C-PIB (mean 364 ? 47 MBq) was injected
list-mode,ordinaryPoisson
algorithm,(OP-OSEM)
Volume of interest analysis
Parametric images were created using Brainvisa software (http://brainvisa
.info). The cerebellum was used as a reference region in the analysis
because this region has been found to be spared from amyloid plaque
accumulation (Joachim et al., 1989). Standard uptake value parametric
images were constructed on late images over 50–70min because this
time schedule has been shown to be more accurate (Lopresti et al.,
2005). Standard uptake value-ratio parametric images were con-
structed by dividing each pixel by the corresponding value obtained
in the cerebellum. The parametric images were coregistered individu-
ally with the corresponding 3D magnetic resonance T1images using
the Brainvisa software.
All volumes of interests were delineated on the individual MRI scans
for each subject as described below.
Segmentation: the T1weighted images were segmented with the
Brainvisa software. The cortical and sub-cortical grey matter, white
matter and cerebellum were delineated using histogram analysis, thresh-
old methods and morphological operators. A parcellation of the cortex
into 76 structures was then performed in three steps: (i) non-linear
registration of the subject’s segmented cortex on the Montreal
Neurological Institute grey matter template and application of the
inverse transformation to the Automated Anatomic Labeling atlas;
(ii) masking of this resampled volume of labels by the segmented
cortex structure and filling of the cortex mask using a Voronoi diagram;
and (iii) minimization of the gyri interface distance to the nearest sulci
bottoms extracted using a regional deformable model. The amygdala
and hippocampi were automatically segmented in each individual using
the T1-weighted MRIs and the SACHA software (Chupin et al., 2009).
Automated Anatomic Labeling segmentation provided values of
11C-PIB fixation in 76 anatomical regions. The volumes of interest
were defined separately for the left and right hemispheres and were
pooled into greater anatomical regions based on anatomical relation-
ships to obtain a mean11C-PIB-standard uptake value-ratio for each
region, as described in the legend of Fig. 1. As a measure of global
amyloid burden, we calculated a
the subject’s mean standard uptake value-ratio in all the defined re-
gions (Fig. 1).
11C-PIB global index, representing
Voxel-based analysis and preprocessing
MRI data were spatially normalized using SPM5 (Wellcome Trust
Centre for Neuroimaging) and the Montreal Neurological Institute
template, and then segmented to isolate the grey matter partition.
In an effort to avoid a bias group effect resulting from spatial normal-
ization, the procedure included the creation of a customized template
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of the grey matter using the MRI data from the whole combined
patient and control samples (n = 28). Grey matter data were then
renormalized using this customized template. A whole grey matter
mask was obtained by thresholding the grey matter density average
image above a value of 0.2, corresponding to a 20% chance that the
voxel belongs to the grey matter (Chetelat et al., 2008).
Four
injection were realigned with SPM5, and a mean volume was calcu-
lated from these four frames for each subject. The mean11C-PIB-PET
volumes were then coregistered to their corresponding MRI and spa-
tially normalized, applying the transformation parameters obtained
from MRI normalization. A partial volume effect was minimized by
(i) the reconstruction algorithm described above (Sureau et al.,
2008); and (ii) by multiplying each normalized mean
by its corresponding whole grey matter mask. Each partial volume
11C-PIB PET frames of 5min each from 50 to 70min post-
11C-PIB image
effect corrected11C-PIB image was then divided by its corresponding
mean cerebellum PIB standard uptake value, resulting in parametric
standard uptake value-ratio images. The mean cerebellum activity
was obtainedfroma custom
Neurological Institute single subject MRI provided by SPM. The
PIB-standard uptake value-ratio images were then smoothed (full
width at half maximum = 10mm).
mask drawnonthe Montreal
Statistical analysis
The clinical data, CSF biomarker levels, mean11C-PIB-standard uptake
value-ratio in each volume of interest and global PIB index group were
compared between the PCA, Alzheimer’s disease and healthy controls
groups using a non-parametric Kruskal–Wallis one-way analysis of vari-
ance. The homogeneity of variances was assessed with the Levene and
Figure 1 Scatter plots showing11C-PIB-standard uptake value-ratio in anatomical regions across groups [healthy controls (diamonds),
Alzheimer’s disease (circles), PCA (triangles)]. Anatomical regions were pooled from volumes of interests provided by Automated
Anatomic Labeling segmentation and were defined as the following: (i) frontal cortex by grouping orbitofrontal, polar prefrontal and
dorsolateral cortex; (ii) anterior cingulate; (iii) medium cingulated; (iv) posterior cingulate; (v) precuneus; (vi) occipital cortex by grouping
calcarine cortex, occipital cortex and cuneus; (vii) temporal cortex by grouping anterior and lateral temporal cortex; (viii) hippocampus;
and (ix) parietal cortex by grouping inferior and superior parietal cortex and the parietotemporal junction. The11C-PIB global index
representing the subject’s mean standard uptake value-ratio in the regions is described above. AD = Alzheimer’s disease.
Table 1 Demographic and clinical data of studied groups
PCA Alzheimer’s diseaseControls
Number of subjects
Female/male
Age (years)
Education (years)
Disease duration (years)
Mini-Mental State Examination
Clinical dementia rating scale
9
7/2*
62.9 ? 3.5 (59.5–69)
12.6 ? 2.6§(9–15)
2.1 ? 1.8 (1–6)
17.1 ? 5.9** (9–27)
0.5, n = 3
1, n = 3
2, n = 3
303 ? 73 (209–400)
511 ? 290 (319–1183)
76 ? 34 (45–143)
0.4 ? 0.1 (0.2–0.6)
9
6/3
62.0 ? 2.7 (58–65.5)
14.7 ? 1.0 (12–15)
2.6 ? 1.3 (1–5)
19.4 ? 3.8** (15–25)
0.5, n = 4
1, n = 3
2, n = 2
236 ? 92 (125–386)
540 ? 266 (175–1106)
86 ? 28 (29–123)
0.3 ? 0.1 (0.1–0.4)
10
2/8
65.8 ? 6.8 (59–75.5)
13.3 ? 2.35 (9–15)
–
29.2 ? 1.0 (27–30)
0 for all subjects
Amyloid-b42 (pg/ml)
T-tau (pg/ml)
P-tau (pg/ml)
Ratio of amyloid-b42:Tau
NA
NA
NA
NA
Data are presented as mean ? standard deviation (min–max).
§P50.05 versus Alzheimer’s disease subjects; *P50.05 versus controls; **P50.001 versus controls. NA = not applicable.
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Brown-Forsythe tests. The Bonferroni correction for multiple compari-
sons was applied. The chi-square test was used to compare gender
ratios. An alpha (significance) level of 0.05 was chosen. All statistical
analyses were performed using PASW Statistics 18 (? SPSS Inc). For
SPM analyses, the statistical threshold was set at P50.001, and false
discovery rate corrected.
Results
Subjects characteristics
Clinical characteristics of subjects with PCA, Alzheimer’s disease
and healthy controls are presented in Table 1. The Mini-Mental
State Examination score did not differ between the PCA and
Alzheimer’s disease groups, whereas both groups significantly
differed from the healthy control group (P50.001).
Cerebrospinal fluid biomarker analysis
CSF biomarker levels in the PCA and Alzheimer’s disease groups
are presented in Table 1. No statistical differences were found
between the PCA and Alzheimer’s disease groups for amyloid-b42,
T-tau, P-tau levels or for the amyloid-b42:Tau ratio. In accordance
with the inclusion criteria, individual analysis showed that all pa-
tients with Alzheimer’s disease had abnormal ratios of amyloid-
b42:Tau. All patients with PCA had a CSF Alzheimer’s disease
profile, and the highest amyloid-b42:Tau ratio observed in this
group was 0.6.
Pittsburgh compound-B: region of
interest analysis
The Alzheimer’s disease and PCA groups showed higher global
11C-PIB index and higher11C-PIB uptake values in all regions of
interest when compared with normal controls, except for the hip-
pocampal region (Table 2). The mean PIB indices were identical in
the PCA and Alzheimer’s disease groups, and no significant differ-
ences in regional PIB uptake were detected between both groups
in any region of interest.
Individual analysis showed that one patient with Alzheimer’s
disease had no significant11C-PIB uptake regardless of the region
studied. This 65-year-old female had a typical clinical history of
Alzheimer’s disease, with onset of memory deficit 2 years before
inclusion in the study. The Mini-Mental State Examination was
19/30, and the clinical dementia rating scale was 0.5. The CSF
analysis revealed a biological profile of Alzheimer’s disease with
a low amyloid-b42 level (125pg/ml) and an unusually high
increase of T-tau (1016pg/ml) and P-tau (123pg/ml) levels. The
EEG was normal. The clinical follow-up (18 months) was in
agreement with the diagnosis. There was no argument for a
frontotemporal dementia on clinical and neuroimaging investiga-
tions (MRI and fluorodeoxyglucose-PET). A 60-year-old female
with PCA (Mini-Mental State Examination = 14; clinical dementia
rating scale = 1) had a global11C-PIB index overlapping with the
highest score measured in controls, although regional analysis
showed a high11C-PIB uptake in the anterior and medium cingu-
late and occipital cortices. The CSF biomarkers showed a low
amyloid-b42 level (246pg/ml) with normal T-tau (336pg/ml)
and high P-tau levels (67pg/ml) and an abnormal ratio of amy-
loid-b42:Tau (0.38).
Pittsburgh compound-B: voxel-wise
comparisons
Compared with normal controls, patients with Alzheimer’s disease
showed significant symmetrical
frontal and parietal cortices, precuneus and cingulate regions
(Fig. 2A), and patients with PCA showed diffuse and symmetric
11C-PIB binding in the frontal, parietal, temporal cortices, cingulate
and precuneus (Fig. 2B). Direct SPM comparison of the two pa-
tient groups showed no voxel in which PIB uptake was greater in
one or another group, even at a lower threshold of P50.001
uncorrected for multiple comparisons.
11C-PIB binding throughout the
Discussion
In our study, we used CSF biomarkers and
binding, which are markers of Alzheimer’s disease lesions, to
11C-PIB-PET amyloid
Table 2 Neocortical mean (?SD)11C-PIB standard uptake value-ratio in anatomical regions
Healthy controls
(n = 10)
Alzheimer’s
disease (n = 9)
PCA (n = 9)
Frontal
Anterior cingulate
Medium cingulate
Posterior cingulate
Precuneus
Occipital
Temporal
Hippocampus
Parietal
Global index
1.30 (?0.17)
1.23 (?0.19)
1.32 (?0.17)
1.29 (?0.29)
1.24 (?0.18)
1.26 (?0.16)
1.11 (?0.13)
1.24 (?0.20)
1.26 (?0.15)
1.22 (?0.15)
2.66 (?0.97)*
2.69 (?0.73)*
2.79 (?0.86)*
2.53 (?0.84)*
2.79 (?0.88)*
2.23 (?0.72)*
1.88 (?0.63)*
1.22 (?0.31)
2.66 (?0.83)*
2.37 (?0.71)*
2.57 (?0.86)* NS
2.85 (?0.55)* NS
2.89 (?0.61)* NS
2.47 (?0.64)* NS
2.79 (?0.80)* NS
2.12 (?0.54)* NS
1.95 (?0.48)* NS
1.36 (?0.16) NS
2.57 (?0.84)* NS
2.35 (?0.57)* NS
*Significant (P50.001) when compared with healthy group; NS = non-significant (P40.05) when compared with Alzheimer’s disease group.
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investigate in vivo the neuropathological process of patients with
PCA. The positivity of both pathophysiological markers indicated
the presence of Alzheimer pathology in favour of the diagnosis of
atypical Alzheimer’s disease. In addition, using two different meth-
ods of analysis, no difference in the load and topography of
amyloid-b deposition assessed by
tween the PCA and Alzheimer’s disease groups, suggesting that
amyloidosis cannot explain the differences in the Alzheimer’s dis-
ease/PCA clinical presentations.
PCA is a rare disease, and we included a small number of pa-
tients in our analysis. To avoid selection bias, we individually
matched each patient with PCA with a patient with Alzheimer’s
disease for age, duration of disease and disease severity. Patients
with PCA had a similar profile of CSF biomarkers as compared
with patients with Alzheimer’s disease. Neuropathological studies
demonstrated that the combination of amyloid-b42, T-tau and
P-tau levels in ante-mortem CSF predicted the presence of
Alzheimer’s disease-associated pathological changes with high
accuracy, supporting the idea that these CSF changes are a sur-
rogate marker for the diagnosis of Alzheimer’s disease (Bian et al.,
2008; Tapiola et al., 2009). Previous studies have also suggested
that CSF biomarkers may be useful to identify in vivo atypical
focal forms of Alzheimer’s disease such as PCA (Baumann et al.,
2010; de Souza et al., 2011), although these observations
were not supported by11C-PIB-PET or autopsy data. The present
study extends these results by providing molecular imaging
support.
PIB binding is highly selective for insoluble fibrillar amyloid-b
deposits. Direct correlation of in vivo11C-PIB retention with quan-
titative analyses of amyloid-b plaques was demonstrated in a
post-mortem study (Ikonomovic et al., 2008) and supports the
11C-PIB-PET was observed be-
validity of11C-PIB-PET imaging as a method for the in vivo evalu-
ation of amyloid-b plaque burden. High PIB uptake was observed
in 80–100% of patients with Alzheimer’s disease (Rowe et al.,
2007; Rabinovici et al., 2010). In the current study, the CSF diag-
nosis of Alzheimer’s disease in the PCA group was in accordance
with the11C-PIB-PET imaging showing higher11C-PIB binding in
subjects with PCA as compared with controls, and similar PIB bind-
ing as compared with patients with Alzheimer’s disease. One sub-
ject with PCA had a PIB index that overlapped with the control
values, although the subject had a biological CSF diagnosis of
Alzheimer’s disease. Interestingly, regional analysis showed high
PIB binding in the anterior and median cingulate regions and a
milderincreasein theoccipital
Alzheimer’s disease did not show evidence of elevated
binding, despite having the typical Alzheimer’s disease clinical
presentation and CSF biomarkers profile. Failure of
detect amyloid-b pathology in Alzheimer’s disease has already
been reported (Rabinovici et al., 2010.), even in one patient
with a pathological confirmation of Alzheimer’s disease (Cairns
et al., 2009).
Taken together, CSF biomarkers and11C-PIB-PET provided ar-
guments to establish in vivo the diagnosis of atypical Alzheimer’s
disease in patients with PCA. Clinicopathological investigations
have demonstrated that Alzheimer’s pathology is the most fre-
quent cause of PCA, accounting for 80–100% of all cases
(Renner et al., 2004; Tang-Wai et al., 2004; Alladi et al., 2007).
Other diagnoses such as Lewy-body dementia, corticobasal
degeneration and Creutzfeldt–Jakob (Renner et al., 2004) are
rare. The fact that all patients with PCA in our study had no
parkinsonism and had a disease onset characterized by visual
disturbance could explain the homogeneity of our data. Future
cortex. Onepatientwith
11C-PIB
11C-PIB to
Figure 2 Topography of11C-PIB standard uptake value-ratio in the grey matter of nine patients with Alzheimer’s disease (A) and in the
grey matter of nine patients with PCA (B) compared with 10 normal healthy controls. In both the Alzheimer’s disease and PCA group,
increased11C-PIB standard uptake value-ratio involves widespread areas in the frontal, parietal, temporal and posterior cingulate cortices
(significance threshold set at P50.001 corrected for false discovery rate).
Amyloid-b burden in PCA Brain 2011: 134; 2036–2043 |
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studies including autopsy diagnoses are needed to confirm our
findings.
An unresolved challenge remains how to explain the differences
in clinical presentation between PCA and Alzheimer’s disease des-
pite a similar burden of amyloidosis. PCA is characterized by early
higher order visual deficits (Benson et al., 1988). Patients develop
features of Ba ´lint’s syndrome (ocular apraxia, optic ataxia and
simultanagnosia), Gerstmann’s syndrome (acalculia, agraphia,
finger agnosia, and left–right disorientation), visual agnosia and
transcortical sensory aphasia, whereas episodic memory is pre-
served or only mildly impaired. Structural and functional neuroi-
maging has also demonstrated parieto-occipital atrophy and
hypoperfusion/hypometabolism in a focal pattern that is clearly
differentfrom Alzheimer’sdisease
Schmidtke et al., 2005; Lehmann et al., 2009; Kas et al., 2011).
One way to understand this singular clinical presentation of PCA
is to assess the amyloid topography between both diseases in
order to evaluate whether amyloidosis is related to the atypical
visual form of Alzheimer’s disease. Descriptive data about11C-PIB
binding in PCA are scarce. In two PCA cases,11C-PIB uptake was
increased in the occipital (Ng et al., 2007) and right calcarine
cortices (Kambe et al., 2010). We did not confirm higher
11C-PIB uptake in the posterior cortical regions with our larger
sample of nine patients with PCA who fulfilled strict inclusion
criteria. No significant differences in11C-PIB burden and distribu-
tion between patients with PCA and Alzheimer’s disease were
observed either using a region of interest method or a voxel-based
approach. The absence of a relationship between the clinical
symptoms of Alzheimer’s disease and amyloid deposition is sup-
ported by several arguments: (i) PIB binding in Alzheimer’s disease
was not correlated with the severity of dementia assessed by the
Mini-Mental State Examination (Engler et al., 2006) or the clinical
dementia rating scale (Jack et al., 2009); (ii) amyloid deposition
remains stable during Alzheimer’s disease follow-up (2 years) des-
pite further decreases in cognitive function and cortical glucose
metabolism (Engler et al., 2006); (iii) the differences in clinical
presentation between the early and late onset Alzheimer’s disease
groups was not related to amyloid burden (Rabinovici et al.,
2010); and (iv) the progression of the amyloid deposition in the
human brain (from neocortical regions to cerebellum) does not
correspond tothe clinical
Alzheimer’s disease (Thal et al., 2002).
The similar topography of fibrillar amyloid-b deposition between
typical Alzheimer’s disease and PCA groups provides support for
the model in which amyloidosis plays a critical role in Alzheimer’s
disease pathogenesis. Other factors such as neurofibrillary tangles
may contribute to the atypical visual clinical presentation (Jack
et al., 2002; Csernansky et al., 2004). Indeed, autopsies have
reported a greater density of neurofibrillary tangles in PCA than
in Alzheimer’s disease; these are most notable in the primary visual
and visual associative cortex. Autopsies have also found a smaller
density of tangles in the hippocampus and subiculum, with a simi-
lar density of senile plaques in cortical areas (Tang-Wai et al.,
2004).
To conclude, we hypothesize that amyloid-b pathology in PCA
occurs at an early phase of the disease, similar to the timing seen
in typical Alzheimer’s disease, and that the clinical presentation of
(Nestor
et al.,2003;
progressionofsymptomsin
PCA may result from an interaction with tau-pathology. Because
PCA is similar to Alzheimer’s disease in terms of amyloid-b path-
ology but differs in its tau-pathology progression, PCA provides a
model to study in vivo the interaction between amyloid and tau
pathology, an interaction that is still poorly understood.
11C-PIB-PET and CSF biomarkers have the potential to identify
candidate patients with PCA who may benefit from specific thera-
peutic strategies targeting amyloid-b metabolism. The therapeutic
windows during which treatment should be initiated should be
discussed with regard to the present data, which provide support
for early therapeutic interventions.
Acknowledgements
We are greatly indebted to the chemical/radiopharmaceutical and
nursing staff of Service Hospitalier Fre ´de ´ric Joliot for the synthesis
of the11C-PIB and patient management, respectively.
Funding
French
reference ANR-07-LVIE-002-01, French Fondation Nationale de
Gerontologie and MEDIAPART; ‘Fondation pour la Recherche
Me ´dicale’ (to L.C.dS.). During the two last years, Dr L.C.dS.
has collaborated with the pharmaceutical company Lundbeck;
European Federationof Neurological
Dr O.U.). Mr F.C., Dr M.-O.H., Dr O.U., Dr R.M., Dr F.L.,
Dr O.C., Ms D.S. and Mrs V.H.-B. report no conflict of interest.
During the two last years, Dr M.C. and Pr S.L. have collaborated
with the pharmaceutical company EISAI. During the two last
years, Pr B.D. has collaborated with the pharmaceutical companies
EISAI, Novartis, Roche, Bristol-Mayer-Squib, Servier. During the
two last years, Dr M.B. has collaborated with the pharmaceutical
company IPSEN-BEAUFOUR. During the two last years, Dr M.S.
has collaborated with the pharmaceutical companies EISAI,
Novartis, Pfizer, Lundbeck.
agenceNationalede la Recherche (ANR) under
Societies(EFNS to
Supplementary material
Supplementary material is available at Brain online.
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