Pittsburgh Compound-B and Alzheimers Disease ...

1 downloads 21 Views 284KB Size Report
Mar 20, 2010 - 12 Scheinin NM, Aalto S, Koikkalainen J, ... tanen M, NÃ¥gren K, Helin S, Scheinin M, ... 48 Koopman K, Bastard N, Martin J-J, Nagels G,.

Original Research Article Accepted: January 26, 2010 Published online: March 20, 2010

Dement Geriatr Cogn Disord 2010;29:204–212 DOI: 10.1159/000281832

Pittsburgh Compound-B and Alzheimer’s Disease Biomarkers in CSF, Plasma and Urine: An Exploratory Study M. Degerman Gunnarsson a M. Lindau a, f A. Wall c K. Blennow d T. Darreh-Shori e S. Basu b A. Nordberg e A. Larsson a L. Lannfelt a H. Basun g L. Kilander a   

 

 

 

 

 

 

 

 

 

 

Departments of a Public Health/Geriatrics and b Public Health/Oxidative Stress and Inflammation, Uppsala University, and c GE Healthcare Uppsala, Imanet PET Center, Uppsala, d Sahlgrenska University Hospital, Göteborg, e Karolinska Institutet, Division of Alzheimer Neurobiology, Karolinska University Hospital Huddinge, f Department of Psychology, Stockholm University, and g BioArctic Neuroscience, Stockholm, Sweden  

 

 

 

 

 

 

Key Words Pittsburgh Compound-B ⴢ PET FDG ⴢ Alzheimer’s disease, follow-up ⴢ Biomarkers ⴢ CSF ⴢ A␤1–42 ⴢ A␤x-42 APOE ⴢ Cystatin C

Abstract Background: The positron emission tomography (PET) radiotracer Pittsburgh Compound-B (PIB) is an in vivo ligand for measuring ␤-amyloid (A␤) load. Associations between PET PIB and cerebrospinal fluid (CSF) A␤1–42 and apolipoprotein E ␧4 (APOE ␧4) have been observed in several studies, but the relations between PIB uptake and other biomarkers of Alzheimer’s disease (AD) are less investigated. Method: PET PIB, PET 18Fluoro-2-deoxy- D -glucose and different AD biomarkers were measured twice in CSF, plasma and urine 12 months apart in 10 patients with a clinical diagnosis of mild to moderate AD. Results: PIB retention was constant over 1 year, inversely related to low CSF A␤1–42 (p = 0.01) and correlated positively to the numbers of the APOE ␧4 allele (0, 1 or 2) (p = 0.02). There was a relation between mean PIB retention and CSF ApoE protein (r = –0.59, p = 0.07), and plasma cystatin C (r = –0.56, p = 0.09). Conclusion: PIB retention is strongly related to CSF A␤1–42, and to the numbers of the APOE ␧4 allele. Copyright © 2010 S. Karger AG, Basel

© 2010 S. Karger AG, Basel 1420–8008/10/0293–0204$26.00/0 Fax +41 61 306 12 34 E-Mail [email protected] www.karger.com

Accessible online at: www.karger.com/dem

Introduction

Alzheimer’s disease (AD) is the main cause of dementia and is a neurodegenerative disorder that is histopathologically characteried by extracellular deposition of ␤-amyloid (A␤) in senile plaques and intraneuronal accumulation of neurofibrillary tangles. AD is a slowly progressive disease that remains asymptomatic for many years after the A␤ accumulation resulting in neurodegeneration has started [1]. AD is typically characterized by a progressive deterioration of episodic memory, language and spatial abilities over several years, with eventually severe loss of function and death. According to current diagnostic criteria, a diagnosis of AD can only be established if the cognitive impairment is severe enough to interfere with activities in daily life, i.e. the patient has dementia [2, 3]. Numerous studies have shown that the cerebrospinal fluid (CSF) concentrations of ␤-amyloid 1–42 (A␤1–42) are decreased, and/or the total tau (t-tau) and phosphorylated tau (p-tau) concentrations are increased in AD compared to normal controls and to patients with other dementia disorders [4, 5]. The presence of the APOE ␧4 allele is a well-established major risk factor for AD [6] with a gene dose effect.

M. Degerman Gunnarsson Department of Public Health and Caring Sciences/Geriatrics Uppsala University Hospital, Box 609, SE–751 25 Uppsala (Sweden) Tel. +46 18 611 0000, Fax +46 18 12 5304 E-Mail malin.degerman.gunnarsson @ akademiska.se

N-methyl [11C]2-(40-methylaminophenyl)-6-hydroxybenzothiazole (PIB) is an amyloid-binding PET tracer used to detect amyloid depositions in vivo in the human brain. Previous studies report a 2-fold higher PIB retention in AD compared to healthy controls, with a higher uptake in the frontal, parietal, temporal, posterior cingulum, occipital cortex and striatum areas [7]. Further, postmortem correlates of in vivo PET PIB amyloid imaging in AD show a strong association with A␤ plaque burden [8]. However, some patients with clinically diagnosed AD have low PIB retention [7, 9], but the reason is so far not explained, since postmortem correlates are lacking. Older nondemented individuals who decline in cognitive tests are more likely to show cortical PIB retention than stable subjects, indicating that PIB retention is an early event in AD [10]. Two 2-year follow-up studies suggest that PIB retention may reach an equilibrium early in the course of AD [11, 12]. Previous studies have described an inverse relation between A␤1–42 in CSF and PIB retention [13–15], and an association between PIB retention and the APOE ␧4 allele. Regarding other possible markers of AD pathology, their relations to PIB retention are less investigated. These are markers of inflammation, such as interleukins in CSF and plasma [16–18], neuronal damage like CSF t-tau and p-tau [19, 20], markers of astrocytic activation as S100B [21] and glial fibrillary acidic protein (GFAP) [22], markers of oxidative stress as F2isoprostanes [23], factors involved in amyloid processing and aggregation such as CSF ␤-secretase-cleaved soluble amyloid precursor protein (sAPP-␤) and ␣-secretasecleaved soluble APP (sAPP-␣) [24], CSF ApoE protein [25] and cystatin C in CSF and serum [26]. The aim of the present study was to further explore the relations between PET PIB and different CSF, plasma and urine biomarkers in AD patients, who were characterized regarding neuropsychological test performance and regional cerebral glucose metabolism.

Methods Study Design Ten outpatients with a clinical AD diagnosis of mild to moderate severity according to the NINCDS-ADRDA [2] and DSM-IV criteria [3] were recruited from the Memory Clinic at the Department of Geriatrics, Uppsala University Hospital. All patients had MRI or CT scans consistent with the diagnosis of probable AD. They were examined at baseline and after 12 months (819 days) with PET PIB and fluorodeoxyglucose (FDG), MMSE, CSF and plasma samples and interviews of caregivers including daily functioning measured by Alzheimer’s Disease Cooperative Study Activites of Daily Living (ADCS-ADL) [27]. An experienced neuro-

Pittsburgh Compound-B and AD Biomarkers in CSF, Plasma and Urine

psychologist carried out neuropsychological investigations. In each sampling 8 ml of CSF, 1 ml of plasma and 1 ml of urine (all samples stored at –70 ° C) were taken. APOE genotyping was performed at baseline. Two CSF samples and 1 PET PIB scan from the 1-year follow-up are missing.  

 

CSF and Blood Samples The CSF A␤1–42 levels were determined using a sandwich ELISA (Innotest쏐 ␤-Amyloid(1–42); Innogenetics, Gent, Belgium), binding to amino acids in positions 1 and 42 of A␤ [28]. The CSF A␤-38 and A␤-40 levels were analyzed by electrochemiluminescence technology (Meso Scale Discovery, Gaithersburg, Md., USA), using the MS6000 Human Abeta 3-Plex Ultra-Sensitive Kit, following the recommendations by the manufacturer. CSF A␤x-42 was analyzed using an in-house research sandwich ELISA, in which the detector antibody 3D6 had been replaced by the 4G8 monoclonal antibody, which has the epitope A␤18–22, and thus measures all N-terminally truncated A␤42 species. Quantification of A␤1–40 and A␤1–42 in plasma was performed by the multiplex Luminex xMAP technique using the INNO-BIA plasma A␤ form assay (Innogenetics) [29]. The A␤x-40 and A␤x42 levels in plasma were determined using a sandwich ELISA (The Genetics Company, Schlieren, Switzerland), as described previously in detail [30]. The CSF t-tau concentration was determined with a sandwich ELISA (Innotest hTAU-Ag; Innogenetics) specifically constructed to measure all tau isoforms irrespectively of phosphorylation status [31]. Tau phosphorylated at threonine 181 (p-tau181) was measured using a sandwich ELISA method [Innotest쏐 PhosphoTau(181P); Innogenetics] [32]. Apo E protein was measured in CSF and in plasma [33]. Measurements of cystatin C in plasma and CSF were performed with a latex-enhanced reagent (Gentian, Moss, Norway) using an Architect ci8200 analyzer (Abbott Laboratories, Abbott Park, Ill., USA). The IL-6 and IL-1B levels in CSF and plasma were determined using the commercial ELISA kits according to the manufacturer’s instruction (high-sensitivity cytokine kits purchased from R&D Systems, UK). Measurement of sAPP-␤ and sAPP- ␣ in CSF was performed by electrochemiluminescence technology (Meso Scale Discovery), using the MS6000 Human sAPP␣/sAPP␤ Kit, following the recommendations by the manufacturer. In advance, all CSF samples were diluted with TBS-T-BSA [10 mM Tris-HCl, pH 7.4, 0.9% NaCl, 0.05% Triton X-100, 6 mM EDTA, 0.1% bovine serum albumin (BSA), and 0.01% sodium azide; all from Sigma]. For measuring S100␤ and GFAP, the CSF samples were diluted 5 times. For sIL-1Rii (soluble interleukin-1 receptor type II), the samples were diluted twice. The capturing, detecting and the secondary antibodies for the GFAP ELISA were the monoclonal mouse antibody, SMI26 from Covance, which was diluted 1/3,000 in a coating buffer (sodium carbonate buffer, pH 9.6, containing 0.02% w/v sodium azide), the polyclonal rabbit antibody, Z0334 from Dako Cytomation (diluted 1/3,000 in TBS-T-BSA) and the AP-conjugated bovine antirabbit IgG, sc-2376 from Santa Cruz Biotech (diluted 1/3,000 in TBS-T-BSA), respectively. Purified normal human brain GFAP protein (A86823H, from Biodesign International) was used as the standard protein, which was diluted in the TBS-T-BSA buffer ranging from 5.0 to 0.04 ng/ml (by 2 times serial dilution). The capturing, detecting and the secondary antibodies for the S100B ELISA were the monoclonal mouse antibody, S2532, from Sigma (diluted 1/3,000 in the coating buffer), the polyclonal rabbit anti-

Dement Geriatr Cogn Disord 2010;29:204–212

205

S100 antibody, Z0311, from Dako Cytomation (diluted 1/3,000 in TBS-T-BSA), and the AP-conjugated swine anti-rabbit IgG, D0306, from Dako Cytomation (diluted 1/3,000 in TBS-T-BSA), respectively. Recombinant full-length protein corresponding to human S100␤ (ab54050, from Abcam) was used as the standard protein, which was diluted in the TBS-T-BSA buffer ranging from 25.0 to 0.20 ng/ml (by 2 times serial dilution). The capturing and detecting antibodies for the sIL-1Rii ELISA were the monoclonal mouse antibody MAB663 from R&D Systems (diluted 1/500 in the coating buffer) and the biotinylated polyclonal goat anti-sIL1Rii antibody, BAF263, from R&D Systems (diluted 1/500 in TBST-BSA), respectively, and the AP-conjugated streptavidin (No. 11089161001 from Roche, diluted 1/5,000 in TBS-T-BSA). Recombinant human sIL-1Rii protein (No. 263-2R/CF, from R&D Systems) was used as the standard protein, which was diluted in the TBS-T-BSA buffer ranging from 62.5 to 0.24 pg/ml (by 2 times serial dilution). Briefly, Nunc Maxisorb ELISA plates were coated overnight at 4 ° C by adding 100 ␮l/well of the appropriate capturing antibody. The plates were then washed 3 ! 5 min with TBS (300 ␮l/well) and incubated for 30–60 min at room temperature (RT, 22.5 ° C) with 250 ␮l/well of a blocking solution (4% BSA, w/v, in TBS). The plates were washed 3 ! 5 min with TBS-T (300 ␮l/ well) and incubated with 100 ␮l/well of the standards and the diluted CSF samples (all in triplicates) at 4 ° C overnight. After washing as before, the plates were incubated for 2 h at RT with 100 ␮l/ well of the corresponding detecting antibodies. The plates were washed as before and incubated at RT for 2 h with working solution of the appropriate AP-secondary antibody or the AP-streptavidin. The plates were washed 4 times with TBS-T, once with dietanolamine buffer (1.0 M, pH 9.8, Sigma) and then incubated with 150 ␮l/well of the substrate (disodium-4-nitrophenyl phosphate, 10 mM, No. 73724, Sigma) in the dietanolamine buffer at RT. The endpoint reaction was monitored using a microplate spectrophotometer reader (SpectramaxTM 250; Molecular Devices Corporation) at 405 nm wavelength at RT, using Softmax쏐Pro software (version 2.6.1 for PC; Molecular Devices Corporation). Urinary samples were analyzed for free 8-iso-PGF2␣ (an F2-isoprostane), a reliable marker of oxidative stress in vivo, validated by a radioimmunoassay developed by Basu [34]. The levels of 8-iso-PGF2␣ were adjusted for the urinary creatinine concentrations and thus given as picomol/millimol creatinine.  

 

 

 

 

 

Positron Emission Tomography The patients were examined with radiotracers in the order PIB and FDG on the same day after at least a 4-hour fasting period before PET. The PET scans were performed using Siemens ECAT EXACT HR+ scanners (CTI PET Systems Inc.), with an axial field of view of 155 mm, providing 63 contiguous 2.46-mm slices with 5.6-mm transaxial and 5.4-mm axial resolution. The orbitomeatal line was used to centre the subject’s head. The scanner protocol for transmission, emission and reconstructions as well as tracer doses were the same as used in previous studies at Uppsala Imanet [7, 11]. The subjects were given 239 8 24 (mean 8 standard deviation) MBq of FDG at baseline and 232 8 33 at the 12-month follow-up. They received 288 8 23 (mean 8 standard deviation) MBq of PIB at baseline and 273 8 30 MBq of PIB at the 12-month follow-up. Production of FDG and PIB was carried out according to the standard good manufacturing process at Uppsala Imanet. Synthesis of PIB was performed by means of the method described previously [7].

206

Dement Geriatr Cogn Disord 2010;29:204–212

All PET investigations were analyzed using identical standardized regions of interest (ROIs) in the brain and each subject had an individual set of ROIs delineated. The set of ROIs applied for statistical analyses is described in detail in earlier studies [35]. The posterior cingulum was added [11] to the other included areas in the analyses: the frontal, parietal, temporal, occipital and cerebellar cortices, pons, white matter and striatum. A computerized reorientation procedure was used to align consecutive PET images for accurate intra- and interindividual comparisons [36] so that all PET images within each subject were realigned to the same position as FDG baseline scan. For each patient all images were realigned to the FDG baseline image. In this clinical study it was not possible to obtain MR images for all patients included. For that reason the ROIs were delineated on a late summation over the last 15 min of the FDG baseline scan and according to the standardized method routinely used at our site [37]. Furthermore all ROIs were delineated well within the anatomical structures to avoid partial volume effects. The ROIs delineated on the baseline FDG late summation were applied on the follow-up FDG late summation image and adjusted for brain atrophy between baseline and follow-up if necessary. Data Management For the FDG examinations, parametric maps of cerebral glucose metabolism were generated by means of the Patlak method using the time course of the tracer from arterialized venous plasma samples as an input function [38]. The cerebral glucose metabolism values were normalized to the pons value (ROI/ref.) [7, 14]. For PIB the mean uptake values of the ROIs obtained in the late time interval (40–60 min) were normalized to the corresponding uptake in the cerebellar cortex, which was chosen as reference region (ROI/ref.) [13]. Scans were characterized as ‘PIB positive’ both on visual inspection and by a mean ratio 11.6, obtained by calculating a mean value of the following areas: the frontal, parietal, temporal and posterior cingulum (ROI/ref.). PIB retention ‘negative’ scans were also characterized both on visual inspection and by a ratio mean !1.6 of the same areas (ROI/ref.). This threshold value is based on the results from healthy controls (mean value + 1 standard deviation) in previous studies [11, 13]. The mean PIB retention was also calculated as a mean value of the frontal, parietal, temporal and posterior cingulum areas (ROI/ref.). Cognitive Assessment The neuropsychological evaluation comprised 12 psychometric tests with 13 measurements. The following cognitive functions were investigated: verbal, spatial, psychomotor function, verbal and spatial short-term memory as well as verbal and spatial episodic memory. Verbal thinking was measured with the word fluency test FAS [39], abstract thinking with similiarites and knowledge with information [40]. Visuospatial and executive functions were examined with a Clock Drawing task with predrawn clock faces according to Luria [41], visuoconstructive ability with Block Design (WAIS III) and perceptual organization and visual episodic memory with Rey-Osterrieth Complex Figure [42]. Trail Making test parts A and B were used to probe psychomotor speed, cognitive flexibility and set shifting [43]. Verbal short-term memory was scrutinized by digit span, a subtest of WAIS III, and shortterm visuospatial memory with the Corsi Block-Tapping Test [42]. Verbal episodic memory was analyzed with the Claeson-Dahl

Degerman Gunnarsson et al.

Table 1. Demographic, clinical, APOE genotype, imaging data and baseline and 1-year follow-up CSF samples of individual patients Pa- Age at Age at PET FDG: tient onset base- hypometabolic regions years line years

MMSE

APOE

baseline

followup

CSF A␤42, ng/l

t-tau, ng/l

p-tau, ng/l

baseline

followup

baseline

followup

base- followline up

PIB retention

1

71

73

left temporal, parietal and occipital cortex, right temporal cortex

23

23

␧3/␧4

288a

330a

190

195

33

39

pos.

2

63

69

right parietal cortex, temporal cortex and bilateral anterior cingulate

24

25

␧3/␧4

369a

428a

207

204

67

111c

pos.

3

63

66

frontoparietal cortex bilaterally, right temporal cortex, left anterior cingulate

27

24

␧3/␧4

285a

279a

716b

530b

120c

109c

pos.

4

68

70

bilateral parietal, right frontotemporal cortex

22

18

␧4/␧4

314a

NA

1,039b

NA

174c

NA

pos.

5

66

69

left thalamus

28

30

␧4/␧4

386a

391a

327

431b

102c

59

pos.

345a

552b

509b

83c

91c

pos.

6

70

74

parietotemporal cortex and cerebellum bilaterally, right occipital cortex and anterior cingulate

28

29

␧4/␧4

328a

7

56

67

bilateral parietal cortex, right temporal cortex, bilateral occipital cortex

30

30

␧3/␧3

751

797

206

204

46

44

neg.

8

63

65

frontoparietal and bilateral occipital cortex

28

25

␧2/␧4

839

752

281

234

58

51

neg.

9

68

71

right frontotemporal and parietal cortex, left frontotemporal cortex

28

24

␧3/␧3

904

NA

409

NA

83c

NA

neg.

10

73

78

left anterior cingulate and bilateral thalami

23

22

␧3/␧3

1,050

1,021

557b

652b

87c

91c

neg.

a

Below reference (400 ng/l); c above reference (>80 ng/l). NA = Not available.

Test for Learning and Memory [44]. Only 5 of the 10 trials on the Claeson-Dahls were administered in order not to exhaust the patients. The z-scores were calculated on the basis of reference material used at the Karolinska University Hospital, Huddinge, Stockholm [45]. The average is z = 0 on the normal distribution scale. All zvalues below –0.75 are lower than normal. Inversely, all z-scores from –0.74 to positive z-scores are normal. Statistical Analyses The analyses of correlations between PIB retention and biomarkers in CSF and plasma, and PET FDG data, respectively, were conducted using the Spearman coefficient of correlation. Wilcoxon Matched Paired tests were used to assess changes in PIB retention from baseline to the 1-year follow-up. Comparisons of CSF and plasma data between PIB-positive and -negative patients were made by Mann-Whitney U test. Comparisons between numbers of copies of the APOE ␧4 allele and PIB retention were performed by Kendall ␶ correlations. The ␣ level was set to 0.05. Adjustments for multiple comparisons were not made, since this was an exploratory study with a small number of patients.

Pittsburgh Compound-B and AD Biomarkers in CSF, Plasma and Urine

Results

All patients (8 men and 2 women) were on stable doses with cholinesterase inhibitors, and 1 (patient 6) was on additional treatment with memantine. Demographics, APOE genotype, PET FDG and CSF data at baseline and 1-year follow-up are presented in table  1. As expected there was a high frequency of the APOE ␧4 allele. PET FDG showed a hypometabolic pattern in accordance with AD, i.e. temporoparietal hypometabolism in all patients except 2 (patients 5 and 10). At the 1-year followup patient 5 showed a slight decline in glucose metabolism in the temporoparietal regions, but the values were still within the normal variation. Patient 10 had a pronounced thalamic hypometabolism but a relatively intact cortical glucose metabolism at both measurements. At the 1-year follow-up regional cerebral glucose metabolism was mainly stable in all patients, except for patient 3, who had a marked deterioration in both glucose metabolism and cognition. Similarly, the CSF concentraDement Geriatr Cogn Disord 2010;29:204–212

207

Table 2. Length of education (years) and results of neuropsychological tests Patient: 1 Education: 14 Cognitive functions: RV

z

2 14.5 RV z

3 15 RV 18 19 21

z

4 7 RV

z

5 16 RV

–2.6 0.0 0.7

z

6 15 RV

30 1 10

–1.7 –2.7 –1.0 –2.6 –1.3 –3.0

7 12.5 RV

z

26 29 21

–2.0 1.7 0.7

56 18 17

0.3 –0.3 0.0

31 11 21

4 51 35

–0.1 1.7 0.3

2.5 26 9.5

–1.3 –0.3 –6.9

3.5 33 34

8 10.5 RV z

9 7 RV

z

–1.6 –1.3 0.7

25 2 19

–2.1 –2.7 0.3

28 22 15

–1.8 0.3 –0.3

27 –1.9 27 1.3 19 0.7

–0.8 0.3 –0.1

1 20 30

–3.4 –0.7 –1.4

1.5 –2.5 11 –1.7 33 –0.3

1 –2.6 25 –0.3 25 –2.3

z

10 12 RV

z

Verbal Fluency Abstract Knowledge

38 14 21

–1.1 –1.0 0.7

44 25 22

Spatial Clock draw Block design Complex drawing

4 22 32

–0.1 –0.7 –0.5

2.5 –1.7 38 0.7 30 –1.3

4 –0.3 25 –0.3 29.5 –1.5

1.5 14 24

Processing speed, s TMT A TMT B

105 –4.2 243 –4.8

61 –1.3 158 –2.4

95 –3.7 389 –10

104 –4.2 – –

32 0.7 102 –1.0

69 –1.7 126 –1.5

81 –2.8 332 –6.7

95 95

–3.8 –0.0

42 0.1 208 –2.5

40 72

12 6.3

–0.7 1.6

9 –1.3 4.2 –1.9

18 –0.7 4.9 –1.0

10 4.9

–1.3 –0.6

11 4.7

–1.0 1.1

17 5.2

0.3 –0.2

12 4.9

–1.0 –0.8

15 –0.3 4.1 –2.1

13 –0.7 4.8 –0.7

15 0.0 4.6 –1.0

12 0 3

– – –2.1

21 0 0

25 – 2 – 4.5 –2.1

10 0 0

– – –2.6

24 – 0 – 11.5 –1.0

30 1 0

– – –2.5

19 1 16

– – –0.4

21 3 0

24 1 2

22 – 0 – 0 –2.4

Memory Short-term visual Short-term spatial Verbal episodic 5 trials, total 30 min Spatial episodic

–0.6 0.7 1.0

– – –2.6

– – –2.7

– – –2.3

0.4 0.6

The z-scores were calculated on the basis of reference material used at the Karolinska University Hospital, Huddinge, Stockholm [45]. The average is z = 0 on the normal distribution scale. All z-values below –0.75 are lower than normal. Inversely, all z-scores from –0.74 to positive z-scores are normal. RV = Raw value; z = z-score; TMT = Trail Making Test.

Table 3. PIB retention and mean ratio at baseline and 1-year follow-up

Patient

1 2 3 4 5 6 7 8 9 10

Posterior cingulum

Frontal cortex

Parietal cortex

Temporal cortex

Mean ratio neg. < 1.6 < pos.

baseline

follow-up

baseline

follow-up

baseline

follow-up

baseline

follow-up

baseline

follow-up PIB pos./neg.

2.42 2.55 2.27 3.42 1.90 2.53 1.18 1.09 1.03 1.66

2.52 2.52 2.30 3.38 2.47 NA 1.21 1.07 1.07 1.28

2.90 2.41 1.88 3.29 1.62 2.69 1.22 1.00 1.00 1.32

2.65 2.28 2.07 3.34 2.11 NA 1.27 1.18 0.96 1.06

2.41 2.33 2.25 3.35 1.79 2.65 1.41 1.21 1.21 1.25

2.34 2.37 2.25 3.29 2.16 NA 1.46 1.14 1.20 1.30

1.84 1.90 1.71 2.59 1.41 2.00 1.31 1.13 1.13 1.49

1.81 1.81 1.76 2.73 1.59 NA 1.34 1.28 1.18 1.32

2.39 2.30 2.03 3.16 1.68 2.47 1.28 1.11 1.09 1.43

2.33 2.25 2.10 3.19 2.08 NA 1.32 1.17 1.10 1.24

tions of A␤1–42 were constant over time. The baseline neuropsychological performances of the individual patients are shown in table 2. All patients had impaired episodic memory and impairment in at least 1 other cognitive domain. PET PIB scans were positive in 6 patients and negative in 4. PIB retention was constant between baseline and follow-up in all brain regions in all 4 of the PIB-negative 208

Dement Geriatr Cogn Disord 2010;29:204–212

pos. pos. pos. pos. pos. pos. neg. neg. neg. neg.

patients and in 5 out of the 6 PIB-positive patients (table  3). One PIB-positive patient (No. 5) with mild AD showed an increased PIB retention from baseline to the 1-year follow-up. PIB uptake was not related to dementia severity according to clinical assessments, ADL status or MMSE, nor with PET FDG data. There were differences in CSF A␤1–42 (p = 0.01) and CSF A␤x-42 (p = 0.01) levels between the PIB-positive Degerman Gunnarsson et al.

Discussion

In this study on 10 patients with clinically diagnosed AD, PIB retention was constant in 2 measurements with a 12-month interval. There were no correlations between PIB retention and disease severity measured by PET FDG. This is in accordance with previous observations indicating that PIB retention reaches a plateau early in the course of AD and remains stable when cognition deteriorates and brain atrophy advances [12]. Further, there was a positive correlation between the numbers of the APOE ␧4 allele and PIB retention. Four out of the 10 AD patients were classified as PIB negative. They did not differ from PIB-positive patients except for higher concentrations of CSF A␤1–42 and A␤x-42 and that the APOE ␧4 allele was less frequent. Pittsburgh Compound-B and AD Biomarkers in CSF, Plasma and Urine

1,100 1,000 900 A␤1–42 (ng/l)

and -negative patients. All PIB-positive patients had low concentrations of A␤1–42, and all PIB-negative patients had normal A␤1–42 (fig. 1). The numbers of the APOE ␧4 allele were positively correlated to mean PIB retention (p = 0.02). There were moderately strong, although not statistically significant, correlations between mean PIB retention and CSF ApoE protein (r = –0.59, p = 0.07) and plasma cystatin C (r = –0.56, p = 0.09). No correlations were seen between mean PIB retention and CSF concentrations of cystatin C, p-tau 181, t-tau, A␤1–40, A␤1–38, IL-6, IL-1B, sIL-1Rii, GFAP, sAPP-␣, sAPP-␤ and A␤40, concentrations of A␤1–42, A␤1–40, A␤x-42, A␤x-40, IL6, IL-1B, sIL-1Rii, S100B and ApoE protein in plasma or F2-isoprostane/creatinine in urine. Four out of the 6 PIB-positive patients and 2 PIB-negative patients had deteriorated at the follow-up, having a reduced MMSE score of 63 points and/or a reduction of 65 points on the ADCS-ADL scale. We have followed the PIB-negative patients with clinical assessments up to 3 years after the end of the study. More than 10 years after the first signs of cognitive decline, patient 7 developed parkinsonism. Although he lacks 2 of 3 core features, i.e. hallucinations and fluctuations in cognition, he fulfils the diagnosis of probable dementia with Lewy bodies (DLB) due to a positive DaTSCAN indicating low dopamin transporter uptake. After inclusion in the study, patient 8 developed typical signs of Lewy body dementia, with visual hallucinations and extrapyramidal symptoms. Patients 9 and 10 both have had a slow deterioration of memory and loss of executive functions. Twenty-nine months after the 1-year follow-up patient 1 died and autopsy confirmed the AD diagnosis.

800 700 600 500 400 300 200 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 PIB (ROI/ref.)

Fig. 1. CSF A␤1–42 concentrations and PIB retention [mean val-

ues of the frontal, parietal, temporal and posterior cingulum areas (ROI/ref.)] of individual patients at baseline. There was a difference in CSF A␤1–42 levels between PIB-positive and PIB-negative patients (p = 0.01).

Although this was a study with a small number of patients, a strong relation between CSF A␤1–42 and PIB retention was seen, with all patients with AD-like PIB retention having low CSF A␤1–42. This inverse relation between cerebral amyloid plaque load and CSF A␤1–42 levels was described earlier [14]. However, the congruence between A␤42 in CSF and PIB retention in the brain is not total and in a recent study only 54% of the MCI PIBpositive subjects showed AD-type CSF A␤1–42 values [46]. In a large study with 50 nondemented older individuals all the subjects with low levels of CSF A␤1–42 were PIB positive, and all with high levels were PIB negative [47]. There are only a few studies with autopsy-confirmed AD and correlated antemortem CSF biomarkers. In 95 patients with autopsy-confirmed AD approximately one fourth had normal CSF A␤1–42 values [48]. Also in another large study (n = 123) with antemortem CSF and neuropathological examinations a significant relationship between high numbers of senile plaques and low CSF A␤1–42 levels was observed [49]. Further, an optimum CSF A␤1–42 cutoff for pathologic senile plaque load was 515 ng/l, which is slightly higher than in clinical use. Another study could not find any association of CSF A␤1–42 with APOE ␧4 or senile plaques in definite AD [50]. However, a long time of storage of the CSF samples of up to 15 years [48], CSF samples stored at high temDement Geriatr Cogn Disord 2010;29:204–212

209

perature (–20°) [50] and differences in (pre)analytical procedures of CSF A␤1–42 [51] may influence the results. In this study no correlations between PIB retention and t-tau or p-tau were detected. CSF t-tau has been suggested to be a marker of neuronal damage, AD disease intensity [52] and a predictor for conversion from MCI to AD [53]. The 2 patients (3 and 4) with the highest t-tau levels were the only ones who had disease progression measured with both MMSE and ADCS-ADL. All patients with PIB-positive scans in this study had at least 1 APOE ␧4 allele. Each additional copy of the ␧4 allele is associated with a higher risk of AD and an earlier mean onset of dementia [54]. In a large study, 65% of those with neuropathologically confirmed AD had at least 1 APOE ␧4 allele [55]. Three other studies observed a correlation between PIB retention and the APOE ␧4 allele, with higher levels of A␤ plaque deposition in ␧4positive patients, in AD [56] as well as in patients with mild cognitive impairment, i.e. a possible state of early AD [57]. This relationship extends into cognitively normal older people, where the APOE ␧4 allele seems to be associated with higher PIB retention, with highest values in homozygotes [58]. In other PET PIB studies there is an overlap and some of the APOE-␧4-negative patients are PIB positive [7]. Three out of 10 patients in the present study were APOE ␧4/␧4 homozygotes. Although not statistically significant, high PIB uptake was linked to low concentrations in CSF of the ApoE protein. A genotypedependent decrease in both plasma and CSF ApoE levels, ␧2 1 ␧3 1 ␧4, was described earlier in transgenic mice [25]. The authors concluded that low levels of ApoE exhibited by ␧4 carriers might contribute to the AD progression, perhaps by reducing the capacity of ApoE to promote synaptic repair and/or A␤ clearance. We also found that high PIB uptake was linked to low plasma levels of cystatin C. Although less studied, low serum cystatin C has recently been associated with higher risk of AD in a population-based study with long follow-up [26]. Previous investigations suggest that cystatin C may protect against the development of AD by inhibition of A␤ aggregation [59]. This was an exploratory study with a limited number of patients. Larger trials are needed to identify more subtle correlations between PIB retention and biomarkers in CSF/plasma. The proportion of PIB-negative patients in our sample is higher than in previous AD studies. Different analysis methods of PET PIB data, different definitions of PIB-positive/negative patients and varying threshold values make direct comparisons between studies difficult. Our characterization of PIB-positive/nega210

Dement Geriatr Cogn Disord 2010;29:204–212

tive is based on previous studies with the same scanner protocol for transmission, emission and reconstructions at Uppsala Imanet and the same analysis methods of data [17, 11, 13]. Two out of 4 PIB-negative AD patients (7 and 8) later developed symptoms consistent with probable DLB [60]. Even if senile plaques with A␤ are present in most DLB cases, at least 10–15% is pure DLB without A␤ burden [9, 61, 62]. Both patients 9 and 10 have mainly preserved personalities and absence of disinhibition, hence, they do not fulfil the criteria of the FTD diagnosis [63]. At the time of inclusion, all 10 patients fulfilled the diagnostic criteria of AD (NINCDS-ADRDA and DSM-IV), but 2 of them later turned out to have DLB. Only postmortem examinations will clarify if PET PIB has failed to prove A␤ burden in the 4 PIB-negative patients. The present study confirms previous findings that PIB retention is stable over time, a strong inverse relation between A␤1–42 in CSF and PIB retention exists and there is a correlation between PIB retention and numbers of the APOE ␧4 allele. Acknowledgment This study was supported by grants from the Alzheimer’s Association and Amersham Foundation.

References

1 Nelson PT, Braak H, Markesbery WR: Neuropathology and cognitive impairment in Alzheimer disease: a complex but coherent relationship. J Neuropathol Exp Neurol 2009;68:1–14. 2 McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM: Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–944. 3 American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, ed 4: DSM-IV. Washington, APA, 1994. 4 Blennow K, Vanmechelen E: CSF markers for pathogenic processes in Alzheimer’s disease: diagnostic implications and use in clinical neurochemistry. Brain Res Bull 2003; 61: 235–242. 5 Hampel H, Mitchell A, Blennow K, Frank RA, Brettschneider S, Weller L: Core biological marker candidates of Alzheimer’s disease – perspectives for diagnosis, prediction of outcome and reflection of biological activity. J Neural Transm 2004;111:247–272.

Degerman Gunnarsson et al.

6 Farrer LA, Cupples LA, Haines JL, Hyman B, Kukull WA, Mayeux R, Myers RH, PericakVance MA, Risch N, van Duijn CM, APOE and Alzheimer Disease Meta Analysis Consortium: Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer’s disease: a metaanalysis. JAMA 1997;278:1349–1356. 7 Klunk WE, Engler H, Nordberg A, Wang Y, Blomquist G, Holt DP, Bergström M, Savitcheva I, Huang GF, Estrada S, Ausén B, Debnath ML, Baretta J, Price JC, Sandell J, Lopresti BJ, Wall A, Koivisto P, Antoni G, Mathis CA, Långström B: Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol 2004; 55: 306– 319. 8 Ikonomovic MD, Kunk WE, Abrahamson EE, Mathis CA, Price JC, Tsoplas WE, Lopresti BJ, Ziolko S, Bi W, Paljug WR, Debnath ML, Hope CE, Isanski BA, Hamilton RL, DeKosky ST: Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain 2008; 131:1630–1645. 9 Edison P, Rowe CC, Rinne JO, Hg S, Ahmed I, Kemppainen N, Villmage VL, O’Keefe G, Någren K, Chaudhuri R, Master CL, Brooks DJ: Amyloid load in Parkinson’s disease dementia and Lewy body dementia measured with [11C]PIB-PET. J Neurol Neurosurg Psychiatry 2008;79:1331–1338. 10 Villemage VL, Pike KE, Darby D, Maruff P, Savage G, Ng S, Ackermann U, Cowie TF, Currie J, Chan SG, Jones G, Tochon-Danguy H, O’Keefe G, Master CL, Rowe CC: A␤ deposits in older non-demented individuals with cognitive decline are indicative of preclinical Alzheimer’s disease. Neuropsychologia 2008;46:1688–1697. 11 Engler H, Forsberg A, Almkvist O, Blomquist G, Larsson E, Savitcheva I, Wall A, Ringheim A, Långström B, Nordberg A: Two-year follow-up of amyloid deposition in patients with Alzheimer’s disease. Brain 2006; 129: 2856–2866. 12 Scheinin NM, Aalto S, Koikkalainen J, Lötjönen J, Karrasch M, Kemppainen N, Viitanen M, Någren K, Helin S, Scheinin M, Rinne JO: Follow-up of [11C]PIB uptake and brain volume in patients with Alzheimer disease and controls. Neurology 2009; 73:1186– 1192. 13 Forsberg A, Engler H, Almquist O, Blomquist G, Hagman G, Wall A, Ringheim A, Långström B, Nordberg A: PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging 2008; 29: 1456–1465. 14 Grimmer T, Riemenschneider M, Förstl H, Henriksen G, Klunk W, Mathis C, Shiga T, Wester HJ, Kurz A, Drzezga A: Beta amyloid in Alzheimer’s disease: increased deposition in brain is reflected in reduced concentrations in cerebrospinal fluid. Biol Psychiatry 2009;65:927–939.

Pittsburgh Compound-B and AD Biomarkers in CSF, Plasma and Urine

15 Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, LaRossa GN, Spinner ML, Klunk WE, Mathis CA, DeKosky ST, Morris JC, Holtzman DM: Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid A␤42 in humans. Ann Neurol 2006;59:512–519. 16 Blum-Degena D, Müller T, Kuhn W, Gerlach M, Przuntek H, Riederer P: Interleukin-1␤ and interleukin-6 are elevated in the cerebrospinal fluid of Alzheimer’s and de novo Parkinson’s disease patients. Neurosci Lett 1995;202:17–20. 17 Cacabelos R, Barquero M, Garcia P, Alvarez XA, Varela de Seijas E: Cerebrospinal fluid interleukin-1 ␤ (IL-1 ␤) in Alzheimer’s disease and neurological disorders. Methods Find Exp Clin Pharmacol 1991;13:455–458. 18 Garlind A, Brauner A, Höjeberg B, Basun H, Schultzberg M: Soluble interleukin-1 receptor type II levels are elevated in cerebrospinal fluid in Alzheimer’s disease patients. Brain Res 1999;826:112–116. 19 Andreasen N, Sjögren M, Blennow K: CSF markers for Alzheimer’s disease: total tau, phospho-tau and A␤42. World J Biol Psychiatry 2003;4:147–155. 20 Frankfort SV, Tulner LR, van Campen JP, Verbeek MM, Jansen RW, Beijnen JH: Amyloid ␤ protein and tau in cerebrospinal fluid and plasma as biomarkers for dementia: a review of recent literature. Curr Clin Pharmacol 2008;3:123–131. 21 Peskind ER, Griffin WS, Akama KT, Raskind MA, Van Eldik LJ: Cerebrospinal fluid S100B is elevated in the earlier stages of Alzheimer’s disease. Neurochem Int 2001; 39: 409–413. 22 Jesse S, Steinacker P, Cepek L, von Arnim CA, Tumani H, Lehnert S, Kretzschmar HA, Baier M, Otto M: Glial fibrillary acidic protein and protein S-100B: different concentration pattern of glial proteins in cerebrospinal fluid of patients with Alzheimer’s disease and Creutzfeldt-Jakob disease. J Alzheimers Dis 2009;17:541–551. 23 Sundelöf J, Kilander L, Helmersson J, Larsson A, Rönnemaa E, Degerman Gunnarsson M, Sjögren P, Basun H, Lannfelt L, Basu S: Systemic tocopherols and FS-isoprostanes and the risk of Alzheimer’s disease and dementia: a prospective population-based study. J Alzheimers Dis 2009;18:71–78. 24 Lewczuk P, Kamrowski-Kruck H, Peters O, Heuser I, Jessen F, Popp J, Bürger K, Hampel H, Frölich L, Wolf S, Prinz B, Jahn H, Luckhaus C, Perneczky R, Hüll M, Schröder J, Kessler H, Pantel J, Gertz HJ, Klafki HW, Kölsch H, Reulbach U, Esselmann H, Maler JM, Bibl M, Kornhuber J, Wiltfang J: Soluble amyloid precursor proteins in the cerebrospinal fluid as novel potential biomarkers of Alzheimer’s disease: a multicenter study. Mol Psychiatry DOI:10.1038/2008.84.

25 Riddell D, Zhou H, Atchison K, Warwick H, Atkinson P, Jefferson J, Xu L, Aschmies S, Kirksey Y, Hu Y, Wagner E, Parratt A, Xu J, Li Z, Zaleska M, Jacobsen S, Pangalos M, Reinhart P: Impact of apolipoprotein E (ApoE) polymorphism on brain ApoE levels. J Neurosci 2008;28:11445–11453. 26 Sundelöf J, Arnlöv J, Ingelsson E, Sundström J, Basu S, Zethelius B, Larsson A, Irizarry MC, Giedraitis V, Rönnemaa E, DegermanGunnarsson M, Hyman BT, Basun H, Kilander L, Lannfelt L: Serum cystatin C and the risk of Alzheimer disease in elderly men. Neurology 2008;71:1072–1079. 27 Galasko D, Bennett D, Sano M: An inventory to assess activities of daily living for the clinical trials in Alzheimer’s disease. Alzheimer Dis Assoc Disord 1997;11:S33–S39. 28 Andreasen N, Hesse C, Davidsson P, Wallin A, Minthon L, Winblad B, Vanderstichele H, Vanmechelen E, Blennow K: Cerebrospinal fluid ␤-amyloid(1–42) in Alzheimer’s disease: differences between early- and late-onset Alzheimer disease and stability during the course of disease. Arch Neurol 1999;56:673– 680. 29 Hansson O, Zetterberg H, Vanmechelen E, Vanderstichele H, Andreasson U, Londos E, Wallin A, Minthon L, Blennow K: Evaluation of plasma A␤40 and A␤42 as predictors of conversion to Alzheimer’s disease in patients with mild cognitive impairment. Neurobiol Aging 2008 DOI:10.10016/2008.09.006. 30 Hansson O, Zetterberg H, Buchhave P, Andreasson U, Londos E, Minthon L, Blennow K: Prediction of Alzheimer’s disease using the CSF A␤42/A␤40 ratio in patients with mild cognitive impairment. Dement Geriatr Cogn Disord 2007;23:316–320. 31 Blennow K, Wallin A, Ågren H, Spenger C, Siegfried J, Vanmechelen E: Tau protein in cerebrospinal fluid: a biochemical diagnostic marker for axonal degeneration in Alzheimer’s disease? Mol Chem Neuropathol 1995;26:231–245. 32 Vanmechelen E, Vanderstichele H, Davidsson P, Van Kerschaver E, Van der Perre B, Sjögren M, Andreasen N, Blennow K: Quantification of tau phosphorylated at threonine 181 in human cerebrospinal fluid: a sandwich ELISA with a synthetic phosphopeptide for standardization. Neurosci Lett 2000;285: 49–52. 33 Darreh-Shori T, Modiri N, Blennow K, Baza S, Kamil C, Ahmed H, Andreasen N, Nordberg A: The apolipoprotein E var␧4 allele plays pathological roles in AD through high protein expression and interaction with butyrylcholinesterase. Neurobiol Aging DOI: 10.1016/200907015. 34 Basu S: Radioimmunoassay of 8-iso-prostaglandin F2␣: an index for oxidative injury via free radical catalysed lipid peroxidation. Prostaglandins Leukot Essent Fatty Acids 1998;68:319–325.

Dement Geriatr Cogn Disord 2010;29:204–212

211

35 Engler H, Lundberg PO, Ekbom K, Nennesmo I, Nilsson A, Bergström M, Tsukada H, Hartvig P, Långström B: Multitracer study with positron emission tomography in Creutzfeldt-Jakob disease. Eur J Nucl Med Mol Imaging 2003;30:186. 36 Andersson JL, Thurfjell L: Implementation and validation of a fully automatic system for intra- and interindividual registration of PET brain scans. J Comput Assist Tomogr 1997;21:136–144. 37 Engler H, Lundberg PO, Ekbom K, Nennesmo I, Nilsson A, Bergström M, Tsukada H, Hartvig P, Långström B: Multitracer study with positron emission tomography in Creutzfeldt-Jakob disease. Eur J Nucl Med Mol Imaging 2003;30:85–95. 38 Patlak CS, Blasberg RG, Fenstermacher JD: Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 1983;3: 1–7. 39 Benton AL, Hamsher K de S: Multilingual Aphasia Examination. Iowa City, University of Iowa, 1976. 40 Wechsler D: WAIS-III. Swedish Version Manual. Stockholm, Harcourt Assessment, 2003. 41 Christensen AL: Luria’s Neuropsychological Investigation, ed 2, rev. Risskov, Munksgaard, 1984. 42 Lezak MD, Howieson DB, Loring DW: Neuropsychological Assessment, ed 4. New York, Oxford University Press, 2004. 43 Reitan RM, Wolfson D: The Halstead-Reitan Neuropsychological Test Battery: Theory and Clinical Interpretation. Tucson, Neuropsychology Press, 1993. 44 Claeson LE, Esbjörnsson E, Tännérus BM, Wahlbin M: Claeson-Dahls test för inlärning och minne, rev. Halmstad, The Halmstad Printer, 2003. 45 Bergman I, Blomberg M, Almkvist O: The importance of impaired health and age in normal cognitive aging. Scand J Psychol 2007;48:115–125. 46 Koivunen J, Pirttilä T, Kemppainen N, Aalto S, Herukka SK, Jauhianen AM, Hänninen T, Hallikainen M, Någren K, Rinne JO, Soininen H: PET amyloid ligand [11C]PIB uptake and cerebrospinal fluid ␤-amyloid in mild cognitive impairment. Dement Geriatr Cogn Disord 2008;26:378–383.

212

47 Fagan AM, Roe C, Xiong C, Mintun M, Morris J, Holtzman D: Cerebrospinal fluid tau/␤amyloid 42 ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol 2007;64:343–349. 48 Koopman K, Bastard N, Martin J-J, Nagels G, De Deyn P, Engelborghs S: Improved discrimination of autopsy-confirmed Alzheimer’s disease (AD) from non-AD dementia using CSF P-tau 181. Neurochem Int 2009; 55:214–218. 49 Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H, Pirttilä T: Cerebrospinal fluid ␤-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol 2009;66:382–389. 50 Engelborghs S, De Vreese K, Van de Casteele T, Vanderstichele H, Van Everbroeck B, Cras P, Martin JJ, Vanmechelen E, De Deyn PP: Diagnostic performance of a CSF-biomarker panel in autopsy-confirmed dementia. Neurobiol Aging 2008;29:1143–1159. 51 Verwey NA, van der Flier WM, Blennow K, Clark C, Sokolow S, De Deyn PP, Galasko D, Hampel H, Hartmann T, Kapaki E, Lannfelt L, Mehta PD, Parnetti L, Petzold A, Pirttila T, Saleh L, Skinningsrud A, Swieten JC, Verbeek MM, Wiltfang J, Younkin S, Scheltens P, Blankenstein MA: A worldwide multicentre comparison of assays for cerebrospinal fluid biomarkers in Alzheimer’s disease. Ann Clin Biochem 2009;46:235–240. 52 Sämgård K, Zetterberg H, Blennow K, Hansson O, Minthon L, Londos E: Cerebrospinal fluid total tau as a marker of Alzheimer’s disease intensity. Int J Geriatr Psychiatry DOI: 10/1002/2353. 53 Schönknecht P, Pantel J, Kaiser E, Thomann P, Schröder J: Increased tau protein differentiates mild cognitive impairment from geriatric depression and predicts conversion to dementia. Neurosci Lett 2007;416:39–42. 54 Corder EH, Saunders AM, Stritmatter WJ, Schmechel DE, Gaskell PC, Small GW, Roses AD, Haines JL, Pericak-Vance MA: Gene dose apolipoprotein E type 4 allele and risk of Alzheimer’s disease in late-onset families. Science 1993;26:921–923 55 Mayeux R, Saunders A, Shea S, Mirra S, Evans D, Roses A, Hyman B, Crain B, Tang M-X, Phelps C: Utility of the apolipoprotein E genotype in the diagnosis of Alzheimer’s disease. N Eng J Med 1998;19:506–511. 56 Drzezga A, Grimmer T, Henriksen G, Muhlau M, Perneczky R, Miederer I, Praus C, Sorg C, Wohlschläger A, Riemenschneider M, Wester HJ, Foersti H, Schwaiger M, Kurz A: Effect of APOE geneotype on amyloid plaque load and gray matter volume in Alzheimer’s disease. Neurology 2009; 72: 1487–1494.

Dement Geriatr Cogn Disord 2010;29:204–212

57 Kemppainen NM, Aalto S, Wilson IA, Någren K, Helin S, Brück A, Oikonen V, Kailajärvi M, Scheinin M, Viitanen M, Parkkola R, Rinne JO: PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology 2007;68:1603–1606. 58 Reiman EM, Chen K, Liu X, Bandy D, Yu M, Lee W, Ayutyanont N, Keppler J, Reeder SA, Langbaum JB, Alexander GE, Klunk We, Mathis CA, Price JC, Aizenstein HJ, DeKosky ST, Caselli RJ: Fibrillar amyloid-␤ burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci USA 2009;106:6820–6825. 59 Levy E, Sastre M, Kumar A, et al: Code position of cystatin C with amyloid-␤ protein in the brain of Alzheimer disease patients. J Neuropathol Exp Neurol 2001;60:94–104. 60 McKeith IG, Dickson DW, Lowe J, Emre M, O’Brien JT, Feldman H, Cummings J, Duda JE, Lippa C, Perry EK, Aarsland D, Arai H, Ballard CG, Boeve B, Burn DJ, Costa D, Del Ser T, Dubois B, Galasko D, Gauthier S, Goetz CG, Gomez-Tortosa E, Halliday G, Hansen LA, Hardy J, Iwatsubo T, Kalaria RN, Kaufer D, Kenny RA, Korczyn A, Kosaka K, Lee VM, Lees A, Litvan I, Londos E, Lopez OL, Minoshima S, Mizuno Y, Molina JA, Mukaetova-Ladinska EB, Pasquier F, Perry RH, Schulz JB, Trojanowski JQ, Yamada M, Consortium on DLB: Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 2005; 65:1863–1872. 61 Gomperts SN, Rentz DM, Moran E, Becker JA, Locascio JJ, Klunk WE, Mathis CA, Elmaleh DR, Shoup T, Fischman AJ, Hyman BT, Grow JH, Johnson KA: Imaging amyloid deposition in Lewy body diseases. Neurology 2008;71:903–910. 62 Merdes AR, Hansen LA, Jeste DV, Galasko D, Hofstetter CR, Ho GJ, Thal LJ, CoreyBloom J: Influence of Alzheimer pathology on clinical diagnostic accuracy in dementia with Lewy bodies. Neurology 2003;60:1586– 1590. 63 McKhann GM, Albert MS, Grossman M, Miller B, Dickson D, Trojanowski JQ, Work Group on Frontotemporal Dementia and Pick’s Disease: Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick’s Disease. Arch Neurol 2001;58:1803–1809.

Degerman Gunnarsson et al.

Suggest Documents