CEREBROSPINAL FLUID MARKERS
FOR THE EARLY AND DIFFERENTIAL
DIAGNOSIS OF
ALZHEIMER’S DISEASE
Niki Schoonenboom
© SNM Schoonenboom, 2006, Amsterdam, the Netherlands. All rights reserved.
ISBN-10: 90-9020990-5
ISBN-13: 978-90-9020990-6
Financial support for this thesis was kindly provided by:
- Stichting Alzheimer Nederland, Bunnik
- Stichting Alzheimer & Neuropsychiatrie Foundation, Amsterdam
The patients described in this thesis were recruited from and investigated at the
Alzheimer Center/Department of Neurology of the VU University Medical Center
(VUMC), Amsterdam.
Laboratory analyses were done at: Department of Clinical Chemistry, VUMC;
Innogenetics, Ghent, Belgium; Department of Developmental Neurobiology,
Division of Immunology, Institute for Basic Research in Developmental
Disabilities, Staten Island, NY, US.
Cover: M.C. Escher’s “Rind” © 2006 The M.C. Escher Company B.V. –Baarn- the
Netherlands. All rights reserved. www.mcescher.com.
Printed by: PrintPartners Ipskamp BV, Enschede.
VRIJE UNIVERSITEIT
Cerebrospinal fluid markers
for the early and differential
diagnosis of
Alzheimer’s disease
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad Doctor aan
de Vrije Universiteit Amsterdam,
op gezag van de rector magnificus
prof.dr. L.M. Bouter,
in het openbaar te verdedigen
ten overstaan van de promotiecommissie
van de faculteit der Geneeskunde
op vrijdag 10 november 2006 om 13.45 uur
in het auditorium van de universiteit,
De Boelelaan 1105
door
Saskia Niki Marijke Schoonenboom
geboren te Woerden
promotoren:
copromotor:
prof.dr. Ph. Scheltens
prof.dr. M.A. Blankenstein
dr. G.J. van Kamp
CONTENTS
List of abbreviations
1
General introduction
1.1
Alzheimer’s disease, mild cognitive impairment and neuropathological
2
changes
1.2
Cerebrospinal fluid markers for the diagnosis of Alzheimer’s disease
6
2
Aim of the thesis
26
3
Reliability of the assays
32
3.1
Description of ELISA’s
3.2
Effects of processing and storage conditions on CSF amyloid β (1-42)
35
and tau concentrations in cerebrospinal fluid: implications for use in
clinical practice
3.3
Differences and similarities between two frequently used assays for
53
Aβ42 in cerebrospinal fluid
4
Amyloid β 38, 40, and 42 species in cerebrospinal fluid: more of the
65
same?
5
CSF Aβ42, tau and phosphorylated tau in Alzheimer’s disease versus
frontotemporal lobar degeneration
5.1
Amyloid β 42 (1-42) and phosphorylated tau in CSF as markers for
77
early onset Alzheimer’s disease
5.2
CSF tau and Abeta42 are not useful in the diagnosis of frontotemporal
lobar degeneration.
96
6
Biomarker profiles and their relation to clinical variables in mild
101
cognitive impairment
7
Cerebrospinal fluid and magnetic resonance imaging markers
117
independently contribute to the diagnosis Alzheimer’s disease
8
General discussion
8.1
Comments on chapters 3-7
136
8.2
Conclusions
143
8.3
Future perspectives
147
References
152
Appendix
162
Summary/samenvatting
Curriculum vitae
Dankwoord
Publications
LIST OF ABBREVIATIONS
Aβ
Amyloid β
Aβ 1-42
Full length Aβ42 peptide
Aβ N-42
Full length Aβ42 and Aβ peptides truncated at the N-terminus
Aβ38
Amyloid β 40
Aβ40
Amyloid β 38
Amyloid β 42
Aβ42
α1-ACT
α1-antichymotrypsin
AD
Alzheimer’s disease
Apo E
Apolipoprotein E
APP
Amyloid precursor protein
AUC
Area under the curve
CDR
Clinical dementia rating scale
CI
Confidence interval
CJD
Creutzfeldt-Jakob disease
CSF
Cerebrospinal fluid
DLB
Diffuse lewy body disease
EAD
Early-onset Alzheimer’s disease
EC
Entorhinal cortex
ELISA
Enzyme-linked immunosorbent assay
FTLD
Frontotemporal lobar degeneration
FTD
Frontotemporal dementia
IL
Interleukin
IP-10
Interferon-γ-inducible protein-10
LAD
Late-onset Alzheimer’s disease
LP
Lumbar puncture
LR
Likelihood ratio
MCI
Mild Cognitive Impairment
MCP-1
Monocyte chemotactic protein-1
MMSE
Mini-mental state examination
LIST OF ABBREVIATIONS
MRI
Magnetic resonance imaging
MTA
Medial temporal lobe atrophy
NFT
Neurofibrillary tangles
NINCDS-
National Institute of Neurological and Communicative Disorders and Stroke-
ADRDA
the Alzheimer’s disease and Related Disorders Association
NP
Neuritic plaques
OR
Odds ratio
PAS
Preclinical Alzheimer’s disease scale
PET
Positron Emission Tomography
PIB
Pittsburgh Compound-B
PSEN
Presenilin
Ptau
Phosphorylated tau
Ptau-181
Tau phosphorylated at threonine 181
Ptau-231
Tau phosphorylated at threonine 231
Ptau-199
Tau phosphorylated at serine 199
ROC
Receiver operating curves
SD
Standard deviation
SP
Senile plaques
Tau
Total tau protein
TMT
Trailmaking test
VAD
Vascular Dementia
VAT
Visual association test
CHAPTER 1
GENERAL INTRODUCTION
1.1 Alzheimer’s disease, mild cognitive impairment and neuropathological changes
The diagnosis ‘possible and probable’ AD is based on clinical criteria (see Appendix for
description of the NINCDS-ADRDA criteria1) supported by neuropsychological tests,
neuroimaging and follow up. A person is demented when he suffers from dysfunction in at least
two cognitive domains as well as in daily activities, under the condition that the patient has a
clear conscience. AD is defined as ‘early onset’ AD (EAD), when the symptoms start before the
age of 65 years.2 This definition is arbitrary, and based on historic decisions regarding the
pension age only. Alois Alzheimer in 1907 described the first AD patient, being a 51-year old
woman, and considered AD as a presenile type of dementia, while there existed already another
poorly defined senile type of dementia in elderly persons. Almost sixty years later, it was found
that this senile type of dementia exhibited the same neuropathological findings as in presenile
AD.3 The arbitrary distinction between the two types of AD still exists, but more and more
evidence is gathered that distinguishes subtypes of AD based on other findings than age.4,5,83
Still, EAD is considered to be a rare condition, although the frequency of EAD in a presenile
dementia population is rather high.6 Some autosomal dominant cases are associated with
mutations in the amyloid precursor protein (APP) and presenilin (PSEN) genes.7 However, in the
majority of sporadic EAD no mutation was found.8 The presence of one or more ε4-alleles of the
Apolipoprotein E (Apo E) genotype is a risk factor for sporadic AD and is associated with an
earlier age-at-onset. 84-86 Yet, Apo E gene polymorphism is not used in the diagnostic process of
AD, as it has low specificity and sensitivity and little predictive value in an individual patient. 88
A definite diagnosis AD can only be obtained at autopsy, which holds true for most other types of
dementia too. The clinicopathological correlation differs between centers and is around 70-80%
overall.9 On microscopic examination AD is characterized by a combination of abnormalities:
diffuse and neuritic plaques (NP), containing extracellular non-fibrillar amyloid β (Aβ),
predominantly Aβ42, and fibrillar Aβ42 respectively; intraneuronal neurofibrillary tangles (NFT)
composed of abnormally phosphorylated tau (Ptau); and loss of synaptic proteins and neurons.10
Aβ42 is formed by proteolytic processing of APP (see also Appendix). The pattern of distribution
of NP and NFT throughout the brain differs with development of disease; in early preclinical
stages NFT are found in the entorhinal cortex (EC) and hippocampus, and with progression of
disease they spread via the medial temporal neocortex to other cortical areas. On the other hand,
2
NP deposition starts in the neocortical frontal/temporal areas and they spread in later stages to the
hippocampal areas. The staging system developed by Braak and Braak describe the extent of
tangle related abnormalities in AD, which correlates well with severity of dementia11. NP
correlate less with cognitive dysfunction in AD patients.12
Plaques and, to a lesser extent, tangles are also found in brains of elderly non-demented controls
and patients with mild cognitive impairment (MCI).13,14 MCI is a clinical entity15, describing
patients with subjective and/or objective cognitive complaints and mild functional disabilities,
but no dementia. A variety of definitions exist for the concept MCI in literature. In our studies we
included patients with ‘amnestic MCI’, conceptualized according to the criteria of Petersen et
al.16 According to these criteria patients have MCI when they have subjective and objective
problems with short term memory compared to persons with the same age, with no interference
in daily activities thus no dementia (see also Appendix). These amnestic MCI patients have a
high chance of developing AD in the future, especially when they are over 70 years of age.15 A
few autopsy studies investigated whether NFT and NP are related to memory function in MCI
patients13,14, NFT in the medial temporal lobe seem to have a relation with memory function in
amnestic MCI. However, all these studies must be interpreted with caution as there might be a
selection bias. The results might depend on the definition used for the concept MCI. In the next
chapter (1.2) an overview is presented of studies describing the most promising biochemical
markers in cerebrospinal fluid (CSF) for the (early) diagnosis AD which are supposed to reflect
the neuropathological changes in AD. Chapter 2 describes the aim of the present thesis in detail.
3
CHAPTER 1.2
Cerebrospinal fluid markers for the diagnosis of Alzheimer’s disease
Niki Schoonenboom, Harald Hampel, Philip Scheltens, and Mony de Leon
In: Gauthier S, Scheltens P, Cummings JL, ed; Alzheimer’s disease and related disorders Annual
2005; 2:17-33. London: Taylor & Francis, 2005.
4
Introduction
Alzheimer’s disease (AD) is considered to be the most common type of dementia. 1 Due to the
aging of the population, the number of persons affected by AD is expected to increase 3-fold by
2050. 2 The diagnosis AD is made by exclusion and based on clinical criteria3, supported by
neuropsychological tests, neuroimaging and extended follow-up. In the early stage, it is difficult
to differentiate AD from other types of dementia, as the clinical symptoms are subtle and the
diagnostic methods may be normal. Furthermore, clinical overlap exists between the different
types of dementias, while volume changes of the hippocampus and medial temporal lobe on
magnetic resonance imaging (MRI) are not specific for AD. 4 With the advent of novel
therapeutic strategies5, it became important to diagnose AD as early as possible, as
pharmacological treatment needs to be started before extensive and irreversible brain damage has
occurred. Over the last decade, many studies have been set out to find an appropriate biomarker
for the diagnosis of AD. 6 This chapter starts with an overview as regards the most promising
cerebrospinal fluid (CSF) biomarkers for the early and differential diagnosis of AD. Next, the
relation of the biomarkers with atrophy on MRI will be discussed. Finally, limitations and topics
for future research will be presented.
Neuropathology
The basis for the research on biochemical markers are the neuropathological changes present in
the various types of dementias. 7 Neuropathological hallmarks of AD -accumulation of
extracellularly senile plaques (SP) and neurofibrillary tangles (NFT), synaptic reductions and
neuron loss- gradually accumulate in time, and start long before the clinical picture of AD
becomes overt. 8 SP are divided into two types: diffuse and neuritic plaques (NP). NP are
composed of the highly insoluble fibrillar protein amyloid β 42 (Aβ42). Aβ depositions tend do
accumulate with age. NFT are intraneuronal accumulations of abnormally (hyper)phosphorylated
tau protein. NFT can be found already in non-demented subjects in the hippocampus and EC, the
regions affected earliest in AD. NP initially are found in the neocortex, but in later stages they
also affect the EC and the hippocampus. 9,10 Patients with frontotemporal dementia (FTD) show
heterogeneity in underlying pathology11, with tau deposits in some of them. Creutzfeldt Jakob
disease (CJD) is characterized by spongiform changes, neuronal loss, gliosis and immunostaining
of the protease-resistant prion protein. 12 Dementia with Lewy Bodies (DLB) is part of the α-
6
synucleïnopathies, in which α-synucleïn accumulates in the intraneuronal Lewy Bodies. 13
Vascular dementia (VAD) is characterized by ischemic lesions, lacunes and extensive white
matter changes. 14 Between the different types of clinically diagnosed dementias significant
neuropathological overlap exists. 15 Lewy bodies are present in AD, whereas in DLB, FTD and
VAD plaques and tangles can be found. White matter changes are found in all types of dementia,
especially in AD. 16
CSF amyloid β 42 and tau in AD versus controls
According to criteria established in 1998, a good biomarker has to have a sensitivity of at least
85% for AD and a specificity of ≥ 75% to differentiate AD from other types of dementia. 7 The
most promising CSF markers to differentiate AD from non-demented elderly are Aβ42 and tau.
Below, each biomarker will be discussed separately. Next, the most valid studies will be
summarized for the combination of CSF Aβ42 and tau.
Aβ42
In numerous studies it has been shown that Aβ42 is decreased in CSF of AD patients compared
to non-demented controls. 6,17 The decrease of Aβ42 concentration in CSF is thought to be the
result of several mechanisms:
1. Deposition of insoluble Aβ42 in the SP of the brain, which might be in part the result of
disturbance of the clearance of Aβ42
2. Decrease of production of Aβ42 by less (active) neurons, inevitably a result of
neurodegeneration
3. Altered binding to Aβ42-specific proteins (e.g. Apo E), resulting in masking of the epitope, to
which the antibodies of the assays are directed.
The concentration of CSF Aβ42 in AD is about 50% of that recorded in controls. 17 The most
commonly used assay is the commercial ELISA of Innogenetics (Table 1). The median values of
Aβ42, as measured in two large case-control studies, are:
AD: 487 (394-622) pg/mL, controls: 849 (682-1063) pg/mL.18
AD: 394 (326-504) pg/mL, controls: 1076 (941-1231) pg/mL.19
7
Reference value for CSF Aβ42 obtained from a control population is set above 500 pg/mL. 20
Sensitivity ranged from 69-100%, while specificity ranged from 56-85% in a subset of studies.
19,21-25
Considerable variability in absolute levels of Aβ42 exists among centers, even when using
the same commercial assay. Cross-sectional studies show little evidence of a relationship between
CSF Aβ42 and age, except for one study showing a U-shaped natural course in normal aging,
with an increase of CSF Aβ42 until 29 and over 60 years old. 26 No18,23 or only a weak22 crosssectional relation has been found between CSF Aβ42 and disease duration or mini-mental state
examination (MMSE). Only one study investigated and found an association between the number
of SP and the CSF Aβ42 concentration.27
Tau
Many studies have demonstrated that tau is increased in CSF of AD patients; concentrations are
about three times higher in AD than in non-demented controls. However, there is a large variation
in the range of CSF tau concentration in AD. Median and mean concentrations of CSF are:
AD: 425 (274-713) pg/mL and 587 (365) pg/mL. 6,18
Controls:195 (121-294) pg/mL and 224 (156) pg/mL.
The increase of tau in CSF is supposed to be the result of release from dying neurons containing a
large number of NFT. One study demonstrated that CSF tau concentration was related to the
number of NFT in the brain.28
Again, the most common used assay for tau is the ELISA from Innogenetics (Table1). Mean
sensitivity ranged from 55 to 81% at a mean specificity value of 90% comparing AD with
controls17. Important is that CSF tau increases with age19,29, which stresses the need to compare
only groups from the same age category. 30 Furthermore, CSF tau tends to be increased in several
other neurological disorders, such as acute stroke31, and trauma32, indicating that the marker is
not very specific. Reference values for tau in healthy individuals are defined as:
< 300 pg/mL (21-50 years)
< 450 pg/mL (51-70 years)
< 500 pg/mL (71-93 years). 19
No correlation was found between CSF tau and MMSE or disease duration.
8
Combination of CSF Aβ42 and tau
Diagnostic accuracy, especially the specificity, increases when using the combination of CSF
Aβ42 and tau comparing AD with controls, including patients with depression or memory
problems due to alcohol abuse. 17 In Table 1 an overview is given of class IA and 1A case-control
studies, with neuropathological (IA) or clinical diagnosis (1A) as gold standard, and patient and
control groups included with a minimum of thirty individuals. 33
Isoprostanes
Oxidative stress is thought to play an important role in the cascade resulting in cell death in AD.
36
A few studies have demonstrated that isoprostanes are increased in CSF of AD patients, even
already at an early stage of disease. 37,38 Further studies are needed how these proteins can be
used in the diagnostic work up for AD, especially to clarify the specificity of these markers.
CSF markers in AD versus other dementias
Combination of CSF Aβ42 and tau
How good is the diagnostic accuracy when using the combination of Aβ42 and tau in AD
compared to other types of dementias? Although this topic is much more relevant for clinical
practice, only a few studies investigated these two markers in large groups of patients. Most
studies found a lower specificity as compared to the studies mentioned in Table 1. There is
substantial overlap in CSF Aβ42 and tau concentrations between different types of dementias. A
decreased concentration of CSF Aβ42 can be found in DLB, FTD, and VAD. 18,20,30,39 A high
CSF tau is also not specific for AD: CSF tau is found to be increased in a subset of FTD and
VAD patients. 18,30 In most cases of DLB CSF tau concentration is normal. 39 In CJD, CSF Aβ42
is decreased and CSF tau is found to be very high, even higher than in AD. 40 The specificity of
the combined CSF Aβ42/tau analysis varies from 85% comparing AD with FTD to 67% in AD
versus DLB and 48% in AD versus VAD (Table 2).
Phosphorylated tau
Several investigators have developed assays to detect phosphorylated tau (Ptau) in CSF. As NFT
are abundant of abnormally phosphorylated tau, it is to be expected that Ptau is increased in CSF
from AD patients. Several immunoassays have been developed that are specific for the
9
Table 1 Diagnostic accuracy of CSF Aβ42 and tau combined in AD versus controls
Study
Population
Gold standard
Criteria
Result
Cut off
Method
Galasko, 199822
82 probable AD
60 controls
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 77%
Specificity 93%
Aβ42: 1032 pg/mL
Tau: 503 pg/mL
Aβ42 and tau: In house
methods
Multi-center study
Kanai, 199834
93 probable AD
41 controls
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 40%
Specificity 90%
Aβ42: 256 fmol/mL
Tau: 474 pg/mL
Aβ42: In house method
Tau: Innogenetics
Hulstaert, 199918
150 probable AD
100 controls = 42 HC + 58
OND
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 85%
Specificity 86%
Aβ42: 643 pg/mL
Tau: 252 pg/mL
Aβ42 and tau: Innogenetics
Multi-center study
Tapiola, 200023
80 probable AD
41 definite AD
39 OND
Clinical (1A) and
neuropathological
diagnosis (IA)
NINCDS-ADRDA
CERAD
Sensitivity 46-53%*
Specificity 95%
Aβ42 : 340 pg/mL
Tau : 380 pg/mL
Aβ42: In house method
Tau: Innogenetics
Andreasen, 200135
105 probable AD
100 controls of Hulstaert
et al. 1999
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 94%
Specificity 89%
Aβ42: 643 pg/mL
Tau: 252 pg/mL
Aβ42 and tau: Innogenetics
Riemenschneider, 200220
74 probable AD
40 controls
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 92%
Specificity 95%
Aβ42: 738 pg/mL
Tau: 255 pg/mL
Aβ42 and tau:
Innogenetics
Kapaki, 200324
49 probable AD
49 controls
Clinical diagnosis (1A)
3 year follow-up
NINCDS-ADRDA
Sensitivity 96%
Specificity 86%
Aβ42: 490 pg/mL
Tau : 317 pg/mL
Aβ42 and tau: Innogenetics
Sunderland, 20036
131 probable AD
72 controls
Clinical diagnosis (1A)
DSM-IV
NINCDS-ADRDA
Sensitivity 92%
Specificity 89%
Aβ42 : 444 pg/mL
Tau: 195 pg/mL
Aβ42: In house method
Tau: Innogenetics
* Definite and probable AD vs OND. Probable AD = AD according to the clinical NINCDS-ADRDA criteria; definite AD = AD confirmed at neuropathological examination; OND = other neurological
diseases. 1A = clinical diagnosis is gold standard, prospective collected materials, including groups of patients and controls with a minimum of 30 individuals; IA neuropathological diagnosis is gold
standard, rest conform class 1A.
10
Table 2 Diagnostic accuracy of CSF Aβ42 and tau combined in AD versus other types of dementia
Study
Population
Gold standard
Criteria
Result
Cut off
82 probable AD
74 NAD
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 77%
Specificity 65%
Aβ42: 1032 pg/mL
Tau: 503 pg/mL
Hulstaert, 199918
150 probable AD
79 NAD
Clinical diagnosis (1A)
NINCDS-ADRDA
Sensitivity 85%
Specificity 58%
Aβ42: 643 pg/mL
Tau: 252 pg/mL
Tapiola, 200023
80 probable AD
41 definite AD
27 NAD
Clinical (1A) and
neuropathological
diagnosis (IA)
NINCDS-ADRDA
CERAD
Sensitivity 50%
Specificity 85%
Aβ42 : 340 pg/mL
Tau : 380 pg/mL
Andreasen, 200135
105 probable AD
23 VAD
9 DLB
Clinical diagnosis (1A)
NINCDS-ADRDA
VAD: NINDS-AIREN
DLB: McKeith
Sensitivity 94%
Specificity VAD 48%
Specificity DLB 67%
Aβ42: 643 pg/mL
Tau: 252 pg/mL
Riemenschneider, 200220
74 probable AD
34 FTLD
Clinical diagnosis (1A)
NINCDS-ADRDA
FTLD: Neary
Sensitivity 85%
Specificity 85%
Aβ42: 528 pg/mL
Tau: 432 pg/mL
Kapaki, 200324
49 probable AD
15 NAD
6 VAD
Clinical diagnosis (1A)
NINCDS-ADRDA
VAD: NINDS-AIREN
AD vs NAD/VAD:
Sensitivity: 71-90%
Specificity: 83-100%
AD vs NAD:
Aβ42 : 435 pg/ml
Tau : 437 pg/ml
Schoonenboom, 200430
47 probable EAD
28 FTLD
Clinical diagnosis (1A)
NINCDS-ADRDA
FTLD: Neary
Sensitivity 72%
Specificity 89%
Aβ42 : 413 pg/mL
Tau: 377 pg/mL
Galasko, 1998
22
Probable AD = AD according to the clinical NINCDS-ADRDA criteria; definite AD = AD confirmed at neuropathological examination; EAD = early onset AD, disease starting before 65 years old;
VAD = vascular dementia; DLB = diffuse lewy body disease; FTLD = frontotemporal lobar degeneration; NAD = non-Alzheimer-dementia. 1A = clinical diagnosis is gold standard, prospective
collected materials, including groups of patients and controls with a minimum of 30 individuals; IA neuropathological diagnosis is gold standard, rest conform class 1A.
11
phosphorylated epitopes threonine 181 (Ptau-181)41, serine 199 (Ptau-199)42, and threonine
231 (Ptau-231). 43 Good results have been obtained comparing AD with other types of
dementia; in the majority of patients Ptau is found to be normal in DLB44, VAD45, FTD30, and
CJD. 46 One study demonstrated an increase in diagnostic accuracy of Ptau-231 and Ptau-181
compared to Ptau-199 in differentiating AD from other types of dementia. 47 The same authors
found a decline of CSF Ptau-231 during the course of AD in 17 patients. 48 These data need to
be confirmed in another independent study, preferably with post-mortem confirmation of
diagnoses. A greater diagnostic accuracy of Ptau compared to total tau is obtained in most
studies. 30,49 In one study it has been shown that the combination of CSF Aβ42 with Ptau-181
differentiated best (early onset) AD (EAD) from FTD with a high specificity (93%) and a low
negative predictive value (negative likelihood ratio: 0.03). 30 As there still exists overlap
between the different types of dementia, either clinically or biochemically, a combination of
the three markers seems best for routine clinical practice, with at least two of the three
biomarkers positive as indicator for AD. 50
14-3-3 protein
The 14-3-3 protein gives, like tau, a reflection of (fast progressive) neuron loss. It can be
detected in CSF by the semi-quantitative method Western Blot analysis. When used in the
proper context, with a high clinical suspicion and in combination with EEG, MRI scan and
routine CSF analysis, the measurement of 14-3-3 protein in CSF supports the diagnose CJD
with high diagnostic accuracy. 51 False-positive results can be obtained in acute stroke, brain
tumor, encephalitis, or even (fast progressive) AD. Sensitivity and specificity values of CSF
14-3-3 and tau have been reported to be the same in one study (cut off level for tau = 1300
pg/mL). 52 Recently it has been shown that the combination of 14-3-3 protein and Aβ42 gives
the highest diagnostic accuracy for CJD (sensitivity 100%, specificity 98%, positive
predictive value 93%, negative predictive value 100%).40
Gold standard
The majority of above-mentioned studies have been obtained in groups of patients where the
diagnosis has been obtained clinically. Accuracy of the clinical diagnosis in specialized
settings is estimated around 85%.53 By use of clinical criteria there is risk of circular
reasoning -ie, the diagnostic performance of CSF markers cannot be higher than the accuracy
of the clinical criteria. 17 The NINCDS/ADRDA criteria for AD have a high sensitivity but a
moderately high specificity. Illustrative is the specificity of only 23% of the
NINCDS/ADRDA criteria for the differentiation of AD from FTD in one retrospective
neuropathological study. 54 Furthermore, 40-80% of the clinically diagnosed VAD patients
have concomitant AD pathology. 55 Only two studies were published in which (in part) the
neuropathological diagnosis was used as gold standard. 23,56 For the differentiation of AD
from controls similar sensitivity and specificity was obtained for CSF tau and Aβ42 as
compared to clinical studies (Table 123). However, specificity of FTD and DLB as compared
to AD was not optimal, 69%.56
Most published studies were done in specialized tertiary referral settings with selected patient
groups. Only a few studies were done with consecutively recruited patients from a memory
clinic; sensitivity was high, but specificity was lower in this setting with ‘unselected’ patients.
35,57
More studies are needed in large primary and secondary referral centers to get insight
how to use CSF Aβ42, tau and Ptau in an elderly population in clinical practice. Populationbased studies are under way to establish CSF markers as potential biomarkers for routine
diagnostic use.
Mild cognitive impairment
Mild cognitive impairment (MCI) is considered to be a transitional state between normal
aging and dementia. Around 10-15% of the MCI patients progress to Alzheimer type
dementia each year.58 Several studies have shown that a subgroup of MCI patients has low
CSF Aβ42 levels and/or high CSF tau levels at baseline, that are indicative for AD.17
Furthermore, there is evidence that these markers can be used as predictors for the conversion
of MCI to AD.50,59 It is not clear yet which marker is changing first in the disease process, as
contradictory findings are reported by various studies describing either an increased CSF
tau50,60 or a decreased CSF Aβ42 at baseline.61,62 In two independent studies a relation
between CSF tau with memory impairment was found, while this was not the case for CSF
Aβ42.63,64 Good results have been obtained for CSF Ptau as indicator of AD-related changes
in the MCI stage.4,59,65 In one study it has been demonstrated that high CSF levels of Ptau at
baseline, but not CSF tau levels, correlated with cognitive decline and conversion of MCI to
AD.66 A very recent study, following 78 MCI patients, shows the best prediction for the
development of AD using the combination of CSF Aβ42 with Ptau.67 Most of the studies
mentioned have been conducted retrospectively in research settings, and limited data are
available about the frequency of a biomarker profile typical for AD in a prospective setting
that reflects clinical practice. But overall, the use of biomarkers in combination with other
13
diagnostic tools is very promising in recognizing MCI patients who will develop AD in the
future.
Neuroimaging and CSF biomarker studies
Cross-sectional studies
Hippocampal size reduction, atrophy of the medial temporal lobe (MTL) and the entorhinal
cortex are sensitive markers for AD. Moreover, atrophy of the hippocampus is found to be a
good predictor in MCI for the development of AD. However, these markers are not diseasespecific and cannot be used as primary evidence for AD.4 By combining CSF and MRI
markers one could get a better diagnostic accuracy. In addition, by investigating the relation
between the two markers a better understanding of the agreement between the two disease
markers could be obtained: do they reflect the same pathological substrate at the same time?
Only a few studies investigated the cross-sectional relation between CSF biomarkers and
atrophy on MRI in small groups of patients. One study showed a correlation between CSF
Aβ42 and the volume of the temporal lobes. 68 We were unable to find a relationship between
medial temporal lobe atrophy (MTA), and CSF Aβ42, tau and Ptau in 62 mild-moderate AD
patients and 32 controls when considered as separate groups.69 Moreover, both disease
markers contributed independently to the diagnose AD. In MCI patients, we found a relation
between CSF Aβ42 and MTA, while CSF tau did not relate to MTA. 63 These data
corresponded to a larger study reporting lower baseline CSF Aβ42 levels with lower brain
volume and larger ventricular volume in the spectrum of normal aging, MCI and AD. 70 In
contrast, higher CSF tau and Ptau were found with an increase in ventricular widening during
follow up. In this light, CSF Aβ42 can be more considered as a stage marker, indicating the
presence of disease at a certain time, while CSF tau is more a state marker, indicating the
intensity of the neuronal damage and degeneration.17,70 However, these data give only
information about one time-point in disease, and until yet it was not possible to show
progressive changes in CSF Aβ42 or (P)-tau concentrations, except for one study.71 On the
other hand, atrophy rates on MRI are good indicators of disease progression in MCI and AD.
The question is therefore: can one or both disease markers be used as markers of progression?
14
Longitudinal studies
The few studies investigating the change in CSF biomarkers were done in AD patients. Little
is known about the change of CSF Aβ42, tau and Ptau in MCI, while one would expect that in
this early stage of disease the biomarkers are more prone to change than in later stages. One
study investigated whether there was a longitudinal relationship between the change in
biomarkers with the change in hippocampal volume on MRI in a small group of aged
individuals with and without memory problems.4 In a 2 time-point longitudinal design, the
MCI group, N=8, showed an inverse relationship between hippocampal volume reductions
and elevations in CSF Ptau, while CSF Aβ42 levels showed a positive relation with
hippocampal volume reductions. However, there are several limitations of this study: a very
small group was investigated; it is not known whether these MCI patients will develop AD;
and the change in biomarkers could also be due to the intra-assay variability, as very small
changes are detected. The authors did not find a significant change in CSF Aβ42, tau and Ptau
between two time points, only if they corrected for dilution of Ptau due to ventricular
enlargement; this ‘Ptau-231 load’ was increased in MCI at follow-up.65 These findings need
to be replicated in larger groups of patients, while additional studies are warranted for a better
understanding of CSF flow and clearance dynamics of biomarkers.
Additive value of CSF markers over other diagnostic tools
In a recent review the position of CSF markers in the clinical assessment of patients with MCI
and early AD has been discussed.17 The authors suggest that only after intensive screening of
the patients by history, neurological examination, routine laboratory tests (blood and CSF),
and neuroimaging (CT, MRI or SPECT) there is place for CSF markers for the (early)
diagnosis of AD. The clinical diagnosis of AD should be based on cumulative information of
all the different diagnostic tools, as in other areas of medicine. For the differential diagnosis
of AD, we state that the biomarkers are especially important for the early onset dementias, as
there is clinical and radiological overlap, especially between EAD and FTD. In the older age
group, the prevalence of AD is much higher, and the usefulness of biomarkers to distinguish
AD from other types of dementia becomes less relevant. However, since the currently
available medications to enhance cognition are approved for mild to moderate AD, every hint
to the correct diagnosis should be taken into account irrespective of age. The additive value of
CSF markers to other diagnostic tools has not yet been investigated systematically, and is an
aim for future studies.
15
Limitations in research on CSF markers
For the differentiation of AD from normal aging, depression or other types of dementia
overlap is seen in CSF Aβ42, tau and Ptau concentrations between the groups. One
explanation is that the control or demented groups could have neuropathological findings
indicative for AD, resulting in an AD biomarker profile. Other explanations are the use of
different processing and storage conditions of CSF71, the use of different reagent antibodies,
differences in the definition of cut off values, and intra- and inter-assay variability of the
assays used.17 Standardization of the (pre-) analytical methods will increase the reliability of
the results and it will improve collaboration with other neurological/biochemical research
centers or memory clinics. Although it is not difficult to obtain CSF by lumbar puncture, this
method is considered to be somewhat invasive for an outpatient clinic, especially in the US.
Therefore, a sensitive serum or plasma marker for AD would be very valuable for the use in
clinical practice.
Conclusion
For the differentiation of AD from normal aging, depression, or alcoholic dementia the
combination of CSF Aβ42 with tau gives a high sensitivity and specificity of ≥ 85%, with
minimal overlap in individual cases. In the pre-clinical (MCI) stage of disease CSF Aβ42, tau
and Ptau could be used as predictors for the development of AD. For the differentiation of AD
from other types of dementia the combination of CSF Aβ42, tau and Ptau gives a good
sensitivity and a reasonable specificity, especially for the differentiation of AD from FTD and
less for AD versus DLB or VAD. For clinical practice a high positive predictive value, and a
low negative predictive value are important. With at least two markers positive, the diagnosis
AD is very likely, while two markers negative can practically rule out the diagnosis AD. The
CSF biomarkers must be only used in combination with other diagnostic tools, including
clinical investigation, imaging and neuropsychological work up.
16
Guide lines for the use of CSF Aβ42, tau and Ptau in clinical practice
1. When there is doubt about the diagnosis AD, with non-conclusive MRI and
neuropsychological findings.
2. In patients with early onset dementias (disease onset before 65 years old), as the
differential diagnosis here is wider and more complicated; especially the
differentiation of EAD from FTD is relevant.
3. In patients suspected for AD, and for whom treatment is being considered.
4. In patients suspected for CJD, in combination with CSF 14-3-3 protein, MRI scan and
EEG.
Topics for future research
- Investigate the additional value of the biomarkers CSF Aβ42, tau and Ptau to other
diagnostic methods, i.e. MRI parameters, and/or neuropsychological examinations.
- Investigate the diagnostic value of the biomarkers in primary and secondary referral settings,
preferably with neuropathological or prolonged clinical follow-up.
- Investigate which markers could be used for tracking the progression of the disease,
especially in the MCI stage of disease. Promising markers are: C-and N-terminally truncated
Aβ peptides, oxidative stress markers or inflammatory markers.
- Develop new tests for a sensitive marker, which can be determined in blood or urine.
- Standardize (pre-analytical) laboratory methods between research centers.
17
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23
CHAPTER 2
AIM OF THE THESIS
24
25
In chapter 1.2 an overview was given of studies on CSF markers published in the past 10
years. The number of centers investigating biomarkers in AD is increasing, and one would
expect that CSF Aβ42, tau and Ptau will soon be accepted as established diagnostic markers
in clinical practice. However, several issues still need thorough attention before this can be
done. First, CSF data with neuropathological confirmation of clinically diagnosed AD patients
as well as patients with other types of dementia are merely lacking. One must also bear in
mind that the exact etiology of AD is still not known. Plaques and tangles are classical in AD,
but what triggers the development of senile plaques containing insoluble Aβ42? Are Aβ
peptides indeed the first manifestation of AD –described in the amyloid beta cascade
hypothesis17- or do they need neurofibrillary tangles at a very early stage of disease to become
neuropathogenic, leading to neuron loss and thus clinical symptoms? Recent insights show
that various truncated forms and oligomers of Aβ play an important role in disease
development18, as well as inflammation and oxidative stress.19 The emerging knowledge from
basic science is a must for research on biomarkers, especially for how and when to use them
properly in clinical practice.
General aim of the thesis
The aim of studies described in the current thesis was to investigate whether the CSF markers
Aβ42, tau and Ptau can be used for an early and differential diagnosis of AD in clinical
practice.
Reliability of the assays
First we had to define whether the assays we (and most centers in Europe) used were reliable
with regard to (pre-) analytical factors involved. Among centers there is a large variation of
CSF concentrations of Aβ42 and tau, even when using the same assays in clinically well
defined control groups and patients. The manufacturers of the commercial available assays
reported that repeated freeze/thaw cycles and tube type may influence concentrations of CSF
Aβ42.20 Little is known about the stability of the samples when stored for a longer period.
We, therefore, addressed the following questions.
Are CSF samples stable as far as Aβ42 and tau are concerned?
We conducted an independent study to investigate the effects of storage temperature, repeated
freeze/thaw cycles and centrifugation on CSF concentrations of Aβ42 and tau (chapter 3.2).
26
This study should shed some light to the influence of pre-analytical factors and their
physicochemical mechanisms on CSF concentrations of both markers. Final aim was to
formulate standardized conditions, which are crucial for the implementation of the CSF
markers as a diagnostic tool in clinical practice.
Are CSF concentrations of Aβ42 comparable when measured by two different ELISAs?
CSF concentrations of Aβ42 also varied between assays, from decreased levels in AD to no
change (two studies) or even increased (one study) levels as compared to controls.21,22 This
might be due to the use of different antibodies directed against distinct epitopes of the Aβ
peptide. To address this, we compared CSF concentrations of Aβ42 as measured by two
different Aβ42 assays in the same CSF samples (chapter 3.3).
In addition to N-terminally truncated Aβ42 peptides various C-terminally truncated Aβ
peptides can be found in brain tissue and CSF.23
Is there a relation between various C-terminally truncated Aβ peptides in CSF?
We wondered whether there was a relation between the three C-terminally truncated Aβ
species, Aβ38, 40 and 42, measured by ELISA in CSF from AD patients and controls
(chapter 4). By studying the relation between Aβ42 to other Aβ peptides, we hoped to get a
better understanding of the specific decrease of concentration of Aβ42 in CSF from AD
patients, for which the exact mechanism is not known.
CSF Aβ42, tau and Ptau in early and differential diagnosis
After these more fundamentally orientated studies, we conducted three case-control studies in
order to approach the main question: can these CSF biomarkers be used for early and
differential diagnosis in clinical practice? To this end several subquestions were formulated,
i.e.:
What is the diagnostic value of CSF Aβ42, tau and Ptau in early onset AD versus
frontotemporal dementia?
This study (chapter 5.1) is particularly relevant as these two types of presenile dementia
syndromes show clinical, neuropsychological and radiological overlap. Most previous studies
compared older AD patients with younger patients with frontotemporal lobar degeneration
27
(FTD), or older FTD patients with age-matched AD patients, but in this older age group FTD
is less prevalent.24,25 The combination of CSF Aβ42, tau and Ptau had not yet been studied in
these two types of presenile dementia (see also chapter 5.2).
Are CSF Aβ42 and tau independent predictors of AD?
Patients with mild cognitive impairment (MCI) have an increased risk of developing AD, and
several studies have shown that CSF Aβ42 is decreased while CSF tau is increased in
MCI.26,27 We investigated whether MCI patients at different risk for AD according to their
biomarker profile differed from each other with respect to other clinical markers or risk
factors (chapter 6). Furthermore, the relation between CSF Aβ42 and tau with other clinical
markers –medial temporal lobe atrophy (MTA) on MRI scan and memory disturbance- was
investigated. To date, cognitive and intellectual impairment with the support of MRI markers
are the clinical indicators of AD.28 CSF biomarkers might well add to this panel of disease
markers.
What is the relation between CSF markers and medial temporal lobe atrophy?
The final study as reported in this thesis focused on the relation between CSF Aβ42, tau and
Ptau with MTA in a cohort of AD patients and controls (chapter 7). The aim of this study was
two-fold: first, to get insight whether both CSF and MRI markers reflect the same
neuropathological substrate simultaneously. Second aim was to investigate whether both
disease markers contribute equally to the diagnosis AD. The comparison with other diagnostic
methods becomes more and more important, because neuropathological ante-mortem data as
gold standard are missing and none of the disease markers can be 100 percent accurate.
With the abovementioned cross-sectional studies we might well get more insight in whether,
how, and when to use the currently most specific biomarkers for AD in clinical practice. Of
course much more research is needed, and fortunately enough the topic of biomarkers is an
expanding area, especially considering the development of novel biomarkers for diagnosis as
well as for tracking progression of the disease.
28
29
CHAPTER 3
RELIABILITY OF THE ASSAYS
30
31
3.1 Description of ELISA’s for Aβ 1-42, Aβ N-42, Aβ38, Aβ40, total tau and tau
phosphorylated at threonine 181
- INNOTESTTM β-amyloid [1-42] (Innogenetics, Ghent, Belgium)
The monoclonal antibody (mAb) 21 F12 binds the COOH terminus of the Aβ42 peptide
(amino acids 36-40) and is used as capture antibody. Biotinylated mAb 3D6, which binds the
NH2 terminus (amino acids 1-6) , is used as detector antibody. Synthetic Aβ (1-42) peptides
from Bachem were used as calibrators.
- Sandwich ELISA for Aβ N-42 (P. Mehta, Staten Island, NY, US)
Monoclonal antibody 6E10 (Signet Labs) is used as capture antibody, and is specific to an
epitope covering N-terminal amino acid residues 1-17. The polyclonal antibody R165 is used
as detector antibody. R165 is made by immunizing rabbits with conjugated 33-42 Aβ peptides
(Ana Spec). Aβ (1-42) peptides from Bachem were used as calibrators.
- Sandwich ELISA for Aβ38 (P. Mehta, Staten Island, NY, US)
Monoclonal antibody 6E10 (Signet Labs) is used as capture antibody. Antisera to Aβ38
peptide were produced in rabbits by immunization of peptide “hCys-aminohexoanoyl-Ala-IleIle-Gly-Leu-Met-Val-Gly-GlyOH”. The antibody lacked reactivity against Aβ40 or Aβ42
peptides as examined by sandwich ELISA and Western blot analysis. This antibody is used as
detector antibody. Aβ (1-42) peptides from Bachem were used as calibrators.
- Sandwich ELISA for Aβ40 (P. Mehta, Staten Island, NY, US)
Monoclonal antibody 6E10 (Signet Labs) is used as capture antibody. The polyclonal
antibody R208 is used as detector antibody. R208 is made by immunizing rabbits with
conjugated 33-40 Aβ peptides (Ana Spec). Aβ (1-42) peptides from Bachem were used as
calibrators.
- INNOTESTTM hTAU-Ag (Innogenetics, Ghent, Belgium)
Monoclonal antibody AT120 is used as capture antibody, while two mAbs are used as
detection antibodies: HT7 and BT2, recognizing different epitopes on the tau protein.
32
- INNOTESTTM Phosphotau (181P (Innogenetics, Ghent, Belgium)
Monoclonal antibody HT7 is used as capture antibody, and biotinylated mAb AT270 is used
as detector antibody, which is specific for the phosphotau-Thr181 epitope.
33
CHAPTER 3.2
Effects of processing and storage conditions on CSF amyloid β (1-42) and tau
concentrations in cerebrospinal fluid: implications for use in clinical practice
Niki SM Schoonenboom, Cees Mulder, Hugo Vanderstichele, Evert-Jan Van Elk, Astrid Kok,
Gerard J Van Kamp, Philip Scheltens, Marinus A Blankenstein
Clin Chem 2005;51:189-195.
34
Abstract
Background: Reported concentrations of Aβ42 and tau in cerebrospinal fluid (CSF) differ
among reports. We investigated the effects of storage temperature, repeated freeze/thaw
cycles, and centrifugation on the CSF Aβ42 and tau concentrations.
Methods: Stability of samples stored at -80°C was determined by use of an accelerated
stability testing protocol according to the Arrhenius equation. CSF Aβ42 and tau
concentrations were measured in CSF samples stored at 4°C, 18°C, 37°C and -80°C. Relative
CSF concentrations (%) of the biomarkers after 1 freeze/thaw cycle were compared with those
after 2, 3, 4, 5, and 6 freeze/thaw cycles. In addition, relative Aβ42 and tau concentrations in
samples not centrifuged were compared to samples centrifuged after 1, 4, 48, and 72 hours.
Results: Aβ42 and tau concentrations were stable in CSF when stored for a long period at
-80°C. CSF Aβ42 decreased by 20% during the first two days at 4°C, 18°C, and 37°C
compared with -80°C. CSF tau decreased after storage for 12 days at 37°C. After 3
freeze/thaw cycles CSF Aβ42 decreased with 20%. CSF tau was stable up to 6 freeze/thaw
cycles. Centrifugation did not influence the biomarker concentrations.
Conclusions: Repeated freeze/thaw cycles and storage at 4°C, 18°C, and 37°C influence the
quantitative result of the Aβ42 test. Preferably, samples should be stored immediately at 80°C after collection.
35
Introduction
In the last decade many studies have set out to find an appropriate biochemical marker for the
diagnosis of Alzheimer’s disease (AD). Several authors have shown that the sensitivity and
specificity of amyloid β (1-42) (Aβ42) and total tau (tau) in cerebrospinal fluid (CSF) are
high when comparing AD patients with controls. 1,2 However, upon comparing AD with other
types of dementia3, overlap in each biomarker occurs, hampering clinical utility. Ideally, the
diagnostic value of biomarkers needs to be validated in neuropathologically confirmed cases,
but most studies use the clinical criteria as the gold standard, with risk of circular reasoning.
Furthermore, the use of the markers in clinical practice still needs to be established, as most
studies have been carried out in research settings with selected patient samples. 4 A recent
meta-analysis5 demonstrated considerable variability in absolute levels of both markers
among centres, even when using the same commercial assay. This variability could be
attributed to differences in patient groups or to a difference in processing and storage methods
among centres. Few published studies have investigated which factors produce a major
influence on the quantitative outcome of the INNOTESTTM β-amyloid (1-42) ELISA. 6,7 An
important confounding factor is the tendency of both Aβ42 and tau to adhere to glass or hard
plastic tubes4, reducing the concentration. Furthermore, repeated freeze/thaw cycles seem to
play a role in the decrease of CSF Aβ42, although different methods are used to investigate
this phenomenon. One study6 showed a large decrease of CSF Aβ42 between the first and
second freeze/thaw cycle, while no difference was found between Aβ42 concentrations in
fresh CSF and CSF that had been frozen and thawed once. 7 No studies have been published
regarding the stability of both Aβ42 and tau in CSF when stored frozen at -20°C or -80°C for
many years. Knowing sample stability at freezing temperature is especially important for
longitudinal studies in which samples are stored for long periods and analyzed simultaneously
with samples stored for short periods to minimize inter-assay variability.
In this study we sought to answer the following questions: What are the stabilities of Aβ42
and tau in CSF samples stored at -80°C for several years? What are the stabilities of Aβ42 and
tau in samples stored at 4°C, 18°C (room temperature), and 37°C up to three weeks, in order
to investigate the effect of mailing? What is the effect of repeated freeze/thaw cycles on the
concentration of Aβ42 and tau in CSF? What is the effect of centrifugation on CSF Aβ42 and
tau concentrations? Awareness of pre-analytical factors that may influence the concentration
of the markers could improve collaboration with other neurological research centers or
36
memory clinics and provide more reliable results. Our final aim is to formulate standardized
conditions, which will be crucial when the use of Aβ42 and tau become standard practice for
the (early) diagnosis of AD.
Materials and Methods
Participants
Twenty-three individuals provided CSF for the entire study: 3 AD patients, 5 patients with
mild cognitive impairment (MCI), 5 patients with frontotemporal dementia (FTD), 1 patient
with mixed-type dementia (MD), and 9 controls with no dementia. All individuals gave
informed consent to participate in the study. Four patients entered the accelerated stability
testing protocol. For the analysis of tau in this experiment, one sample was excluded because
the results were higher than the values for the highest calibrator. Two of the four individuals
used in the accelerated stability testing protocol also participated in the freeze/thaw
experiment. Thirteen other individuals provided CSF for the freeze/thaw experiments: 5 for
the comparison of unfrozen CSF versus CSF frozen and thawed once, plus 8 for the
comparison of samples frozen and thawed once with samples subjected to several freeze/thaw
cycles. Six individuals provided CSF for the centrifugation experiment, including one who
provided a haemolytic CSF specimen, which was not centrifuged and was compared with the
baseline centrifuged specimen.
Lumbar puncture
CSF was obtained by lumbar puncture in the L3/L4 or L4/L5 intervertebral space, using a 25gauge needle, and was collected in 12 mL polypropylene tubes. A small amount of CSF was
used for routine analysis, including total cells, total protein, and erytrocytes. Within two hours
after collection CSF samples were centrifuged at 2100g for 10 minutes at 4°C. Samples were
kept at room temperature until centrifugation. After centrifugation, CSF was pipetted into
polypropylene tubes in 0.11-, 0.2- or 0.5-mL aliquots, depending on the experiment for which
the CSF was to be used.
Accelerated stability testing protocol
For studying the stability at -80°C we used an accelerated stability testing protocol based on
the principle of the Arrhenius equation8, describing a linear relationship between the
logarithm of the reaction rate constant (e.g. the degradation rate) and the inverse of the
37
absolute temperature. Three temperatures 4°C, 18°C and 37°C were used for calculation of
the rate constant.
The principle and calculations of this protocol applying the Arrhenius method are provided in
the APPENDIX at the end of this article.
Participants
Two patients and two controls participated in the accelerated stability testing protocol.
One patient was a 73-year-old male with MD, and the other a 54-year-old female with
probable AD according to the clinical criteria. 9 The controls were two non-demented spouses
of patients, a male and a female of 77 and 58 years old.
Samples
After centrifugation, CSF samples were divided into 0.2 and 0.5 mL aliquots. The 0.5 mL
aliquot was stored immediately at -80°C (193K) to determine the baseline values for Aβ42
and tau. The other thirty aliquots of 0.2 mL from each patient were stored at 4°C (277K),
room temperature (18°C (291K)) and 37°C (310K), 10 (polypropylene) tubes at each
temperature. After 1, 2, and 3 days up to 22 days one tube stored at each of the three different
temperatures was removed and frozen at –80°C until analysis. All 30 samples from each
patient were thawed and analyzed, in duplicate, simultaneously in one run.
Freeze/thaw cycles
To compare unfrozen CSF with CSF frozen and thawed once, we stored two polypropylene
aliquots of 0.2 mL CSF from five individuals for two days either at 4°C or at -80°C until
analysis. The concentrations of Aβ42 and tau in the aliquots that had not been frozen and
thawed (stored at 4°C) were compared with the concentrations in the aliquots that had been
thawed once (stored at -80°C). All aliquots were tested in duplicate.
As most samples are stored at -80°C until analysis, the best way to simulate daily practice is
to compare samples subjected to one freeze/thaw cycle with samples that have undergone
several freeze/thaw cycles. Therefore, CSF of 10 individuals was centrifuged and aliquoted
into six portions of 0.11 mL. One (polypropylene) tube from each patient was kept at -80°C
until analysis and the concentration of Aβ42 and tau in this aliquot was used as baseline value
(100%). The other five (polypropylene) tubes from each patient were stored at -80°C and
thawed 2, 3, 4, 5, or 6 times at room temperature for 2 hours and stored again at -80°C until
38
analysis. The relative Aβ42 and tau concentrations of the 10 patients (%) were compared with
the baseline value (100%) and plotted against the number of freeze/thaw cycles.
Influence of centrifugation
CSF from five individuals was aliquoted in five 0.5 mL polypropylene tubes. Tube 1 was
centrifuged at 2100g for 10 minutes at 4°C within 2h after CSF collection and stored
immediately at -80°C. The concentrations of Aβ42 and tau determined in tube 1 were used as
baseline value. Tubes 2, 3, and 4 were stored at 4°C and centrifuged after 4, 48, and 72 hours.
After centrifugation the supernatant was pipetted into polypropylene tubes and stored frozen
for maximal 1 month until analysis. Tubes 5 were not centrifuged at all and kept for 4 days at
4°C before storage at freezing temperature. Relative Aβ42 and tau concentrations (%) in
samples not centrifuged were compared to samples centrifuged after 1, 4, 48 and 72 hours. In
addition, we compared a haemolytic CSF sample obtained after a traumatic lumbar puncture
(28,800 erythrocytes/µL, equivalent to approximately 0.5% whole-blood contamination), that
was not centrifuged but had been stored at -80°C, with a sample from the same patient
centrifuged within 2 hours and stored at 4°C until analysis.
Analysis of Aβ42 and tau
Aβ42 concentrations for all experiments were determined with the sandwich ELISA
INNOTEST β-amyloid (1-42) (Innogenetics, Ghent, Belgium). Monoclonal antibody (Mab)
21F12, which is highly specific for the C-terminus of the Aβ42 peptide, was used as capturing
antibody, and the biotinylated Mab 3D6, specific for the N-terminus, was used as detector
antibody. 6 For quantification of tau we used the sandwich ELISA INNOTESTTM hTau
Antigen (Innogenetics) constructed to measure both total tau and phosphorylated tau with
Mab AT120 as capturing antibody and HT7 and BT2 as detection antibodies. 10 For the
stability experiment, performed at Innogenetics, the mean intra-assay coefficients of variation
(CVs) were calculated from the difference between duplicate measurements. The mean CVs
for Aβ42 were 6.2% at an Aβ42 level of ≤ 500 pg/ml (N=61) and 7.2% at an Aβ42 level of >
500 pg/ml (N=59). For tau the mean intra-assay CV’s were 8.7% (tau ≤ 300 pg/ml, N=61) and
13.3% (tau > 300 pg/ml, N=26). The mean CV’s at the VUMC laboratory were calculated by
the precision from the difference between duplicate measurements (SDx100/mean) of 60
routine samples. For Aβ42 mean CV was 4.0% at concentrations in the low range (125-300
pg/ml), 2.9% at concentrations in the middle range (600-800 pg/ml), and 3.4% at
39
concentrations in the high range (1000-2000 pg/ml). For tau the CVs were 6.5% at low
concentrations (75-200 pg/ml), 4.7% at concentrations in the middle range (500-700 pg/ml)
and 4.6% at a high concentration (900-1200 pg/ml). The mean inter-assay CVs of 3 different
pools, evaluated in advance and tested in the stability, centrifugation and freeze/thaw
experiments, were 12.1% for Aβ42 (N=7) and 8.1% for tau (N=7). Mean recoveries from four
samples to which 1:1 dilutions of the highest calibrators for Aβ42 or tau were added were
77% (range 73%-81%) for Aβ42 and 109% (range 108%-112%) for tau.
Results
Stability at -80°C according to the Arrhenius equation
The relative concentrations (%) of Aβ42 and tau in CSF from the four and three patients on
the consecutive days were calculated at 4°C, 18°C and 37°C, with the baseline value (-80°C)
set at 100%. Plotting the relative concentrations (%) versus the days of heat stress, the rate
constants at each investigated temperature (k(T)) were calculated (Table 1). The calculated
k(T) values, determined at the three temperatures, were not different from zero, indicating that
Aβ42 and tau are stable in CSF when stored at -80°C.
Table 1 Rate constants (k(T)) for Aβ42 and tau
Temperature (K)
k(T) of Aβ42
k(T) of tau
277
-0.0043 (±0.04)
0.0018 (0.03)
291
-0.0032 (0.03)
-0.0016 (0.03)
310
0.050 (0.03)
-0.039 (0.03)
Percentages of remaining measurable protein were plotted versus days of heat stress at each temperature. Mean
(SD) k values were determined for the three temperatures at the slope of the best-fit line.
Stability during mailing conditions
When we plotted the mean CSF Aβ42 values for samples from four patients stored at the
three different temperatures against time, the protein concentrations were highest at baseline
(–80°C) and during the first two days, the concentrations decreased by 20% in samples stored
at 4°C, 18°C and 37°C (Figure 1A). Thereafter, the concentration of CSF Aβ42 remained
40
Figure 1 Relative concentrations of Aβ42 in CSF samples stored at 4°C, 18°C and 37°C
Figure 1A
110
100
Relative concentration (%)
90
80
4 ºC
70
60
18 ºC
50
37 ºC
40
30
20
10
0
0
5
10
15
20
25
Days
Mean percentages of Aβ42 plotted vs time, in samples collected from four subjects, and stored at 4°C, 18°C and
37°C compared with the baseline sample, stored at -80°C and stated as 100%.
Figure 1B
Subject 1:
Subject 2:
120
120
100
100
80
80
60
60
Temperature
40
Temperature
40
4 celsius
20
18 celsius
0
37 celsius
0
1
2
5
7
9
12 14 16 20 22
Time (days)
AB42 (%)
AB42 (%)
4 celsius
20
18 celsius
37 celsius
0
0
2
3
5
7
9
13 15 17 20 22
Time (days)
Percentages of Aβ42 plotted vs time in CSF samples from subject 1 (mixed type dementia) and subject 2
(control) and stored at 4°C, 18°C and 37°C
41
relatively stable up to 22 days, although we observed considerable variability between
aliquots from the same individual (Figure 1B). Tau plots showed that the protein was stable in
CSF at 4°C and 18°C, whereas the concentration decreased at 37°C after approximately 12
days (Figure 2).
Figure 2 Relative concentrations of tau in CSF samples stored at 4°C, 18°C and 37°C
150
140
130
Relative cooncentration (%)
120
110
4 ºC
100
90
80
18 ºC
70
60
37 ºC
50
40
30
20
10
0
0
5
10
15
20
25
Days
Mean percentages of tau, plotted vs time, in CSF samples collected from three patients and stored at 4°C, 18°C
and 37°C compared with baseline sample, stored at -80°C and stated as 100%.
Freeze/thaw cycles
No difference could be demonstrated between concentrations of Aβ42 and tau in CSF that had
not been thawed and CSF that had undergone one freeze/thaw cycle (visualized for Aβ42 in
Figure 3A). In Figure 3B the mean (SD) relative concentrations (%) for Aβ42 vs the number
of freeze/thaw cycles are shown. A decrease of 20% after 3 freeze/thaw cycles was observed.
Thereafter, no decline could be demonstrated and the values remained constant at 80% of the
baseline concentration during 6 freeze/thaw cycles. The change in concentration varied
among individuals, ranging from no change in the samples from one patient to a large
decrease in samples from another. We could not demonstrate a difference between samples
with high concentrations of Aβ42 (≥ 550 pg/ml, n=5) and low concentrations of Aβ42 (<550
pg/ml, n=5). In Figure 3C the mean (SD) relative concentrations (%) of tau vs the number of
freeze/thaw cycles are shown. No change during 6 freeze/thaw cycles could be demonstrated.
42
Figure 3 Effect of freezing/thawing on Aβ42 and tau concentrations
Figure 3A
1250
Abeta42 (pg/ml)
1000
750
500
250
0
0
1
Plot of CSF Aβ42 concentration in five samples that had not been subjected to a freeze/thaw cycle compared
with samples that had been subjected to one freeze/thaw cycle.
Figure 3B
Abeta(1-42) (%)
100
90
80
70
1
2
3
4
5
6
Number of freeze/thaw cycles
Mean (SD, error bars) relative CSF Aβ42 concentrations (%) in samples of ten patients versus numbers of
freeze/thaw cycles. The values of Aβ42 after 1 freeze/thaw cycle of each subject were used as baseline value and
stated as 100%.
43
Figure 3C
120
Tau (%)
110
100
90
80
1
2
3
4
5
6
Number of freeze/thaw cycles
Mean (SD, error bars) relative CSF tau concentrations (%) in samples of nine patients versus numbers of
freeze/thaw cycles. The values of tau of each subject after 1 freeze/thaw cycle were used as baseline value and
stated as 100%.
Influence of centrifugation
No difference was found between CSF concentrations of Aβ42 and tau in samples that were
stored at 4°C and centrifuged after 1, 4, 48, or 72 hours. Furthermore, there was no difference
in concentrations of the markers in samples stored frozen after centrifugation, and samples
that were not centrifuged and stored for 4 days at 4°C. In addition, no difference in Aβ42 and
tau concentrations could be shown in the haemolytic sample not centrifuged and stored at 80°C (Aβ42 662 ng/L; tau 232 ng/L) and the sample centrifuged and stored at 4°C (Aβ42 =
596 ng/L; tau = 230 ng/L).
Discussion
Using the Arrhenius approach, we showed that the Aβ42 and tau concentrations are stable in
CSF samples when frozen immediately and stored for a longer period at -80°C. Furthermore,
the concentration of Aβ42 in CSF decreased by approximately 20% during the first two days
when stored at 4°C, 18°C and 37°C compared to the baseline value, and then remained
constant for up to 22 days, although with considerable variability between aliquots from the
same individual. CSF tau concentration was stable at 4°C and 18°C, but showed a decrease
44
after 12 days when stored at 37°C. After 4 freeze/thaw cycles the concentration of Aβ42 in
CSF decreased by 20%, while tau remained stable during 6 freeze/thaw cycles. Centrifugation
did not influence the outcome of either biomarker.
To the best of our knowledge, the stability of Aβ42 and tau in CSF samples stored at -80°C
for many years has never been systematically investigated. Two previous studies found that
CSF Aβ42 2,5 and tau5 concentrations remained stable when stored for > 6 months at –70°C or
-80°C. The first study showed that the correlation between CSF Aβ42 measured at different
times during 1 year and reanalysis at one time was high (correlation coefficient = 0.96). 2
Unfortunately, the regression coefficient (or slope of the line) is not mentioned in that study,
while this could give more accurate information about degradation of the protein. The second
study did not find a relation between CSF Aβ42 or tau and shelf life. 5 In our study we
investigated the long-term stability at -80°C with an accelerated stability testing protocol
according to the Arrhenius method. No significant decline in Aβ42 and tau concentration at
4°C, 18°C, and 37°C was found, except for tau at 37°C, and only after 12 days. Therefore, the
degradation constant was not different from zero, and no Arrhenius-plot or projected stability
time could be calculated. From this we conclude that both proteins are very stable in CSF and
that the samples can be stored for a very long period at -80°C. However, a real-time stability
experiment performed in the future is needed to confirm our data.
The stability of various forms of Aβ in CSF samples stored at different temperatures has been
described in two studies11,12 using in-house ELISAs. In the first study11, the immunoreactivity
of CSF Aβ40 and Aβ42 decreased by 8% and 10% when kept for 24 hours at 20°C, but
remained stable the first 24 hours at 4°C. In the second study12, CSF total Aβ levels were
measured and found to be unstable if samples were stored at –20°C, 4°C, and room
temperature, with the largest decrease during the first day and plateauing after the third day.
Although different assay formats were used, measuring different types of Aβ,
abovementioned findings support our results of a decrease in concentration of CSF Aβ42
during the first two days for samples stored at 4°C, 18°C and 37°C. Although incubation at
higher temperatures could have an effect on the binding capacity of Aβ42 6, 13,14, storage of
CSF at different temperatures does not seem to affect the Aβ42 concentration6, which is
supported by our findings showing comparable Aβ42 concentrations in CSF samples stored at
4°C or 37°C. There was a difference in Aβ42 concentration only between samples stored at 80°C immediately after collection or stored at higher temperatures after collection. An
45
interesting finding in one study11 was that the antibody-binding capacity of synthetic Aβ42
was lower in CSF than in water. In addition, Aβ42 levels were lower in artificial CSF with
physiological concentrations of albumin than without albumin. An explanation for this finding
could be that binding of Aβ42 to albumin masks the epitope recognized by Aβ42-specific
antibodies. 15,16 This binding of Aβ42 to other proteins might also cause the low recovery rate
of the Aβ42 ELISA, although Vanderstichele et al.6 and others17 could not find interference
with Aβ by other proteins, including human albumin. However, interference experiments are
largely dependent on the protocol being used, and whether pre-incubation is needed.
Furthermore, results are also dependent on which medium is used, either artificial CSF,
human CSF or another medium such as sample diluent. 6 The difference in concentrations of
Aβ42 between samples stored at –80°C and at higher temperatures could also be the result of
binding of Aβ42 to other proteins, but conformational changes, aggregation18 or degradation
may be involved as well. The variability in Aβ42 concentrations among centers5 might very
well be attributable to the procedure for sample treatment the first hours after collection, with
one center immediately freezing samples on dry ice and another center storing samples at
room temperature until further processing (our center). This is an important factor to be
considered and investigated in future multicenter studies.
Our finding of decreased concentrations of Aβ42 in CSF after repeated freeze/thaw cycles
corresponds with the outcome of several other studies6,11,12, and stresses again the importance
of avoiding freeze/thaw cycles in order to minimize the risk of falsely low Aβ42 values. The
decrease of CSF Aβ42 after repeated freeze/thaw cycles might also be explained by the same
physicochemical mechanisms –i.e. conformational change of the fibrillary β-sheeted Aβ42
protein or masking of the epitope by binding to other proteins- that led to a decrease of Aβ42
concentration during the first two days when stored at 4°C. This is sustained by our finding of
comparable CSF Aβ42 concentrations between samples that had not been been subjected to a
freeze/thaw cycle (stored for two days at 4°C) versus samples that had been subjected to 1
freeze/thaw cycle.
Tau protein is considered to be very stable, and also repeated freeze/thaw cycles do not seem
to influence the concentration of this protein. Therefore, it is remarkable that tau decreases
after 12 days storage at 37°C. At this temperature, the protein may be degraded by proteases,
form aggregates or undergo conformational changes, producing a form that is not detectable
by one or both anti-tau antibodies used in the ELISA.10 Little is known about the relationship
46
between CSF tau and temperature. The pathological core protein of paired helical filaments
(PHF), consisting of a portion of tau, is found to be protease and heat resistant.19 However,
the aggregation of tau into PHF has been demonstrated to increase at temperatures above
30°C.20 The tau protein is generally highly soluble, but the aggregated pathological form
found in the neurofibrillary tangles in the brain might not be released in CSF. The nature of
tau in CSF is not well documented, but previous studies have revealed different molecular
masses of tau in lumbar CSF ranging from 25-80 kDa. 21 The low molecular weight of 25 kDa
is not found in the brain, suggesting that CSF tau is truncated when released into CSF,
probably as a result of degradation processes occurring in the brain. The truncated forms of
tau in CSF should be well recognized by the anti-tau antibodies as they cover only a small
part of the large full-length tau. We speculate that the 12 days storage of CSF at 37°C might
lead to a change of the truncated form of tau into a more aggregated form, which is
undetectable by the antibodies incorporated in the ELISA. 10
In conclusion, both Aβ42 and tau are stable in CSF at -80°C for a long period. However, CSF
Aβ42, when stored at 4°C, 18°C and 37°C, decreased by 20% during the first two days
compared with the baseline value (-80°C). Furthermore, the concentration of Aβ42 in CSF is
influenced by the number of freeze/thaw cycles. To avoid these difficulties it is best to
process CSF as soon as possible after collection and store it at –80°C for long storage.
Preferably, CSF samples should be sent on dry ice when stored frozen.
Acknowledgements
Niki SM Schoonenboom was partly funded through a grant from Alzheimer Nederland,
Bunnik (V2001-023). Additional funding was received from the Stichting Alzheimer and
Neuropsychiatry Foundation, Amsterdam.
47
APPENDIX Estimation of stability by the Arrhenius method
The best way to determine the stability of analytes in body fluids is to perform a real time stability experiment. This can be done by storing
paired aliquots of a sample and determining the concentrations of the proteins after certain time points, varying from some months to many
years, taking into account that the sample is thawed once. However, this approach requires long experimental periods. Moreover, in real
stability time studies, the determination of the protein must be performed at the beginning, during and at the end of the study. These
measurements can often not be performed using the same batch of reagents. An increased inter-assay coefficient of variation may be the
result.
Therefore, estimation of protein stability should rather be performed using an accelerated stability testing protocol. The kinetics of protein
denaturation are comparable with that of a first order reaction, which means that the degradation rate is proportional to the concentration of
the respective analyte. The equation for the accelerated stability testing protocol is:
-d[C]/dt = k[C] or ln C(t)/C(0) = -k.t
where C(0) is the initial protein concentration, C(t) is the concentration after time t, and k is the rate constant. The rate constant, which is
dependent of the temperature, is determined at the three fixed temperatures 4ºC, 18ºC and 37ºC, assuming that at -80ºC the concentrations
remain constant during the time of this storage experiment. Afterwards the Arrhenius equation is applied, using this formula:
Ln k(T) = A + E/RT
in which A = the pre-exponential factor and E/R = the slope of the equation. Using the equation of the best-fit line, it is possible to calculate
the degradation rate constant at each desired temperature:
Ln k(T) = A + B/T
or
y =A + Bx
A and B have fixed values. By substituting the temperature of interest, e.g. -80º C = 193ºK Æ k(193) is calculated. We can calculate the time
after which 90% or 95% of Aβ42 or tau can be recovered, by substituting Ct)/C(0) = 0.90 or 0.95 in the equation:
Ln(0.90) = -k(193).t
-0.105 = -k(193).t
t = 0.105/k(193)
or
Ln(0.95) = -k(193).t
-0.0513 = -k(193).t
t = 0.0513/k(193)
48
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Cras P. Detection of tau proteins in normal and Alzheimer’s disease cerebrospinal
fluid with a sensitive sandwich enzyme-linked immunosorbent assay. J Neurochem
1993;61:1828-34.
11. Jensen M, Hartmann T, Engvall B, Wang R, Uljon SN, Sennvik K, et al.
Quantification of Alzheimer amyloid beta peptides ending at residues 40 and 42 by
novel ELISA systems. Mol Med 2000;6:291-302.
12. Southwick PC, Yamagata SK, Echols CL Jr, Higson GJ, Neynaber SA, Parson RE,
Munroe WA. Assessment of amyloid beta protein in cerebrospinal fluid as an aid in
the diagnosis of Alzheimer’s disease. J Neurochem 1996;66:259-65.
13. Motter R, Vigo-Pelfrey C, Kholodenko D, Barbour R, Johnson-Wood K, Galasko D,
et al. Reduction of β-Amyloid peptide42 in the cerebrospinal fluid of patients with
Alzheimer’s disease. Ann Neurol 1995;38:643-48.
14. Wiltfang J, Esselman H, Bibl M, Smirnov A, Otto M, Paul S, et al. Highly conserved
and disease-specific patterns of carboxyterminally truncated Aβ peptides 1-37/38/39
in addition to 1-40/42 in Alzheimer’s disease and in patients with chronic
neuroinflammation. J Neurochem 2002;81:481-96.
15. Golabek A, Marques MA, Lalowski M, Wisniewski T. Amyloid beta binding proteins
in vitro and in normal human cerebrospinal fluid. Neurosci Lett 1995;191:79-82.
16. Bibl M, Esselmann H, Otto M, Lewczuk P, Cepek L, Ruther E, et al. Cerebrospinal
fluid amyloid β peptide patterns in Alzheimer’s disease and nondemented controls
50
depend on samples pretreatment; indication of carrier-mediated epitope masking of
amyloid β peptides. Electrophoresis 2004;25:2912-8.
17. Takeda M, Tanaka T, Arai H, Sasaki H, Shoji M, Okamoto K, et al. Basic and Clinical
Studies on the Measurement of β-amyloid (1-42) in Cerebrospinal Fluid as a
Diagnostic Marker for Alzheimer's Disease and Related Disorders: Multi Center Study
in Japan. Psychogeriatrics 2001;1:56-63.
18. Stine WB Jr, Dahlgren KN, Krafft GA, LaDu MJ. In vitro characterization of
conditions for amyloid-beta peptide oligomerization and fibrillogenesis. J Biol Chem
2003;278:11612-22.
19. Sadqi M, Hernandez F, Pan U, Perez M, Schaeberle MD, Avila J, Munoz V. Alphahelix structure in Alzheimer’s disease aggregates of tau-protein. Biochemistry
2002;41:7150-5.
20. Friedhoff P, Schneider A, Mandelkow EM, Mandelkow E. Rapid assembly of
Alzheimer-like paired helical filaments from microtubule-associated protein tau
monitored by fluorescence in solution. Biochemistry 1998;37:10223-30.
21. Sjögren M, Davidsson P, Tullberg M, Minthon L, Wallin A, Wikkelso C, et al. Both
total and phosphorylated tau are increased in Alzheimer’s disease. J Neurol Neurosurg
Psychiatry 2001;70:624-30.
51
CHAPTER 3.3
Differences and similarities between two frequently used assays for Aβ42 in
cerebrospinal fluid
Niki SM Schoonenboom, Cees Mulder, Hugo Vanderstichele, Yolande AL Pijnenburg,
Gerard J Van Kamp, Philip Scheltens, Pankaj D Mehta, Marinus A Blankenstein
Clin Chem 2005;51:1057-1060.
52
Abstract
Background: Differences in absolute concentrations and clinical performance of cerebrospinal
fluid (CSF) amyloid β 42 (Aβ42) between laboratories is partly attributable to the antibodies
selected for the assay. We compared Aβ42 levels and diagnostic accuracy of two Aβ42 assays
in the same CSF samples.
Methods: Aβ42 levels were measured in CSF of 39 Alzheimer’s disease (AD) patients, 24
patients with frontotemporal lobar degeneration (FTLD) and 30 controls. One ELISA used the
monoclonal antibodies 3D6 and 21F12 directed against amino acids 1-6 of the N-terminal part
and amino acids 36-42 of the C-terminal part of Aβ42 (Aβ 1-42). The other ELISA used the
monoclonal antibody 6E10 specific to an epitope present on 1-17 amino acid residues of the
N-terminal part and the polyclonal antibody R165 directed against amino acids 33-42 of the
C-terminal part of Aβ42 (Aβ N-42).
Results: Absolute concentrations of CSF Aβ 1-42 and Aβ N-42 were comparable in all CSF
samples. In AD versus controls sensitivity and specificity values for CSF Aβ 1-42 and Aβ N42 were equal; Aβ 1-42: sensitivity 90% and specificity 93%; Aβ N-42: sensitivity 90% and
specificity 87%. A slightly better differentiation of AD from FTLD was obtained with CSF
Aβ N-42 than CSF Aβ 1-42 (area under the ROC curve Aβ 1-42= 0.77, 95%CI 0.64-0.90 and
Aβ N-42= 0.87, 95%CI 0.76-0.97, P=0.045).
Conclusions: Both Aβ42 assays provided equal diagnostic accuracy comparing AD with
controls. Further studies are needed to investigate the involvement of the different forms of
Aβ42 in AD and FTLD patients.
53
Amyloid β 42 (Aβ42) concentrations in cerebrospinal fluid (CSF) are used to identify
Alzheimer disease (AD)1, but reported concentrations differ among studies as does diagnostic
accuracy. 2 These differences may relate to the patient and control groups (3) studied,
processing and storage methods4, intra- and inter-assay variation of the assays, or to the
reagent antibodies used. A recent meta-analysis2 stressed the importance of standardizing
assays for Aβ42 in CSF. In most studies CSF Aβ42 was reported to be decreased, but in two
studies, CSF Aβ42 was not significantly changed in AD2, and in one study even increased in
the early stages of AD.5 These dissimilarities might reflect the specificities of the antibodies
incorporated in the assays.
The first aim of our study was to compare levels of Aβ42, as measured by two different
assays in the same CSF samples. The first assay, widely used in Europe6, uses two
monoclonal antibodies (Mabs) and detects full length Aβ42 peptide, Aβ 1-42. 7 The second
assay [Aβ (N-42)], used mainly in the United States8, detects both full length Aβ42 and Aβ
peptides truncated at the N-terminus. 9
The second aim of the study was to compare diagnostic accuracies of the assays for patients
with AD compared with non-demented controls and patients with frontotemporal lobar
degeneration (FTLD).
Finally, we investigated the relationship between CSF Aβ 1-42 and Aβ N-42 concentrations
and albumin ratio, age, disease duration, and disease severity.
Between October 2000 and December 2002 39 AD patients, 24 FTLD patients and 30 nondemented controls were recruited at the Alzheimer Center of the VU University Medical
Center (VUMC). All patients underwent a standardized investigative protocol. 3 A diagnosis
of ‘probable’ AD was made according to the NINCDS-ADRDA criteria10; the clinical picture
of FTLD (including frontotemporal dementia, semantic dementia, and progressive aphasia)
was based on international clinical diagnostic criteria. 11 Disease duration in AD and FTLD
patients was defined as the time in years between the first symptoms by history and the
lumbar puncture.
The control group (n = 30) consisted of 20 persons with subjective memory complaints, who
had undergone the same protocol of examinations as the patients; five healthy spouses of
patients without memory complaints; three individuals with a positive family history for AD,
all without memory complaints; one patient with a suspicion of benigne intracranial
54
hypertension and one patient with a possible neuritis vestibularis. No controls developed
dementia or mild cognitive impairment within 1 year. The Mini Mental State Examination
(MMSE) score12 was used as a measure of global cognitive impairment.The study was
approved by the ethics review board of the VUMC. All patients and controls gave written
informed consent.
CSF was collected and stored as described previously. 4 The albumin ratio (serum
albumin/CSF albumin) was used as a measurement of the intactness of the blood-brain
barrier. Except for one FTLD patient and 2 controls, the blood-brain barriers of the patients
were intact (Table 2).
The INNOTESTTM β-AMYLOID(1-42) (Innogenetics) uses Mab 21F12, which binds the Cterminus of the Aβ42 peptide (amino acids 36-42), as capture antibody, and biotinylated Mab
3D6, which binds the N-terminus (amino acids 1-6), as detector antibody (6). Aβ (1-42)
peptides from Bachem were used for calibration. To minimize aggregates in the peptide
stocks used to prepare calibrators, we obtained three different batches of Aβ1-42 (Bachem)
and processed them together. Peptides were pre-treated to eliminate the occurrence of small
oligomers/aggregates. This test was performed at the Department of Clinical Chemistry of the
VUMC.
The sandwich ELISA for Aβ N-42 uses the commercially available Mab 6E10, specific to an
epitope covering N-terminal amino acid residues 1-17 of Aβ42 (Signet Labs) as capture
antibody, and the polyclonal antibody R165 as detector antibody. R165 was made by
immunizing rabbits with conjugated Aβ33-42 peptides (Ana Spec). Aβ1-42 from Bachem
was used for calibration, although production procedures for the calibrators were slightly
different between the two laboratories. This test was performed at the New York site
according to an in-house protocol.
For statistical analysis, SPSS version 11.0 was used. Non-parametric statistics were used, as
the distribution of the variables was not normal. Passing and Bablok regression 13 was
calculated with Medcalc, V 4.30 (Medcalc Software), and we also prepared a Bland and
Altman plot. 14 For group differences we applied the Kruskall-Wallis test, followed by the
Mann Whitney U test applying the Bonferroni correction. The Chi-square test with continuity
correction was used to test group differences within genders.
The sensitivities and specificities for CSF Aβ 1-42 and Aβ N-42 were also calculated by
Medcalc. Cut points corresponded to a sensitivity ≥ 85% (15), but if a higher sensitivity was
55
obtained for a reasonable specificity, it was used. Receiver operating characteristic (ROC)
curves were constructed and compared. 16 Spearman correlations were calculated. A test was
considered significant at P < 0.05. All reported tests are two-tailed unless stated otherwise.
The CSF Aβ 1-42 and Aβ N-42 concentrations were not statistically significantly different
(Table 1, Figures 1 and 2, see also Appendix and the online version of this Technical Brief at
http://www.clinchem.org/content/vol51/issue 6/).
Table 1 Passing and Bablok regression equation
N
Equation
Slope 95% CI
Intercept 95% CI
AD
39
Y=0.71X+35
0.51-1.01
-39 - +106
FTLD
24
Y=1.17X-39
0.89-1.59
-230 - +99
Controls
30
Y=1.36X-245
0.81-2.44
-947 - +89
All subjects
93
Y=1.12X-67
0.95-1.3
-140 - -3
AD = Alzheimer’s disease; FTLD = frontotemporal lobar degeneration. CI = confidence interval. Variable X =
Aβ 1-42, variable Y = Aβ N-42.
Concentrations of both CSF Aβ 1-42 and Aβ N-42 levels were significantly lower in AD
patients than in FTLD patients and controls (Table 2).
CSF Aβ 1-42 concentrations differed significantly between FTLD patients and controls,
whereas CSF Aβ N-42 concentrations did not differ significantly between the two groups
(Table 2). The ratio of Aβ 1-42 to Aβ N-42 differed significantly only between the AD and
FTLD patient groups.
ROC curves for CSF Aβ 1-42 and Aβ N-42 are shown in Figure 3. In AD versus controls
sensitivity and specificity for CSF Aβ 1-42 were 90% and 93% at 473 ng/L, and for CSF Aβ
N-42 90% and 87%, respectively, at 383 ng/L. No difference was present in diagnostic
accuracy of CSF Aβ 1-42 compared to CSF Aβ N-42 (Figure 3A); AUC Aβ 1-42 = 0.94,
95%CI 0.86 - 0.99 versus AUC Aβ Ν−42 = 0.92, 95% CI 0.83 - 0.97, P = 0.47.
56
Table 2 Demographic data and CSF analyses for each diagnostic category
AD
(N=39)
FTLD
(N=24)
Co + OND
(N=30)
AD vs FTLD
(P-value)
AD vs controls
(P-value)
FTLD vs controls
(P-value)
Age (yrs)
62 (52-79)
63 (49-85)
64 (32-79)
0.58
0.14
0.66
Sex (M/F)
20/19
16/8
14/16
0.26
0.90
0.41
Duration (yrs)
4 (1-11)
3 (1-11)
--
0.054
--
--
MMSE
20 (3-28)
24 (3-29)
30 (25-30)
0.02
<0.001
<0.001
Albumin ratio
4.8 (2.0-10.6)
5.3 (1.5-17.3)
5.2 (2.8-18.5)
0.6
0.47
0.99
Aβ 1-42 (pg/mL)
315 (140-626)
495 (202-1087)
651 (337-1224)
<0.001
<0.001
0.02
Aβ N-42 (pg/mL)
288 (116-674)
588 (150-1324)
629 (218-1075)
<0.001
<0.001
0.66
Aβ 1-42/Aβ N-42
1.1 (0.5-1.7)
0.9 (0.4-1.3)
1.0 (0.6-2.6)
0.001
0.24
0.07
AD = Alzheimer’s disease; FTLD = frontotemporal lobar degeneration; Co = controls; yrs = years; M/F = Male/Female; MMSE = Mini Mental State Examination; ≥ 1 ε4
alleles = one or two ε4 alleles. Values are expressed as medians (minimum-maximum). P-values refer to statistical difference between AD vs FTLD, AD vs controls or FTLD
vs controls.
When comparing AD with FTLD, a specificity of 67% was obtained for CSF Aβ 1-42 at a
sensitivity of 85% (448 ng/L). For CSF Aβ N-42 specificity was 75% at a sensitivity of 87% (373
pg/mL). The AUCs for CSF Aβ N-42 and CSF Aβ 1-42 tended to be different (Figure 3B); AUC
Aβ 1-42= 0.77 (0.64-0.90) and AUC Aβ N-42= 0.87 (0.76-0.97), P =0.045. The AUCs for CSF
Aβ 1-42 and CSF Aβ N-42 (Figure 3C) in distinguishing FTLD patients from controls were
significantly different [AUC Aβ 1-42= 0.69 (0.55-0.81) and AUC Aβ N-42= 0.54 (0.39-0.67),
P=0.007], but the discriminatory value was small for Aβ 1-42 and negligible for Aβ N-42, with
the confidence interval for the AUC including 0.5.
We found no significant correlation of either CSF Aβ 1-42 or Aβ N-42 with albumin ratio,
MMSE, age or disease duration (AD and FTLD) in either group.
The absolute concentrations of CSF Aβ 1-42 and Aβ N-42 were comparable. However, in earlier
studies concentrations of CSF Aβ N-42 ranged from 36 pg/mL to 623 pg/mL in AD and 111
pg/mL to 629 pg/mL in controls. 8,17,18 The reason for the low CSF Aβ N-42 concentrations
measured in these studies could be a difference in the affinity of the Aβ N-42 polyclonal
antiserum samples or the purity and solubility of the peptides used as calibrator. 8 The sensitivity
of an ELISA depends largely on the binding characteristics of the antigen, which may vary with
temperature and buffer solutions, or among different reagent lots. 6 In addition, the affinity of the
antibodies used in the assays might vary for the various Aβ42 peptides involved in the AD
pathogenesis, including oligomers of the Aβ42 peptide. A future study exchanging calibrators
and antibodies among various ELISAs is necessary for harmonization. ROC curve analysis
revealed no difference in the ability of the two assays to differentiate between AD patients from
controls. Next to the C-terminal heterogeneity, various N-terminal truncated peptides are found in
the Aβ pools of AD brains. 19,20 These peptides are considered to play a role in the increased
Aβ42 production in developing AD. We speculate that Aβ 1-42 and Aβ N-42 concentrations go
hand in hand at a certain stage of disease, in mild to moderate AD as well as in controls. Because
the N-terminally truncated Aβ42 peptides can be demonstrated early in the disease process9, they
might be promising markers for the preclinical diagnosis of AD, when used simultaneously with
Aβ 1-42. 21
58
Figure 3 ROC curve Aβ 1-42 versus Aβ N-42
3A. AD vs controls
Abeta 1-42
Abeta N-42
100
Sensitivity
80
60
40
20
0
0
20
40
60
80
100
100-Specificity
ROC curve comparing Aβ 1-42 (straight line) with Aβ N-42 (dotted line) in AD versus controls
3B. AD vs FTLD
Abeta 1-42
Abeta N-42
100
Sensitivity
80
60
40
20
0
0
20
40
60
80
100
100-Specificity
ROC curve comparing Aβ 1-42 (straight line) with Aβ N-42 (dotted line) in AD versus FTLD
3C. FTLD vs controls
Abeta 1-42
Abeta N-42
100
Sensitivity
80
60
40
20
0
0
20
40
60
80
100
100-Specificity
ROC curve comparing Aβ 1-42 (straight line) with Aβ N-42 (dotted line) in FTLD versus controls
59
The difference in diagnostic accuracy of CSF Aβ 1-42 and Aβ N-42 comparing AD with FTLD
is remarkable. Several authors found a decrease of Aβ 1-42 in CSF in a subset of FTLD patients.
3,22
Hardly any information is available about the CSF Aβ N-42 concentration in FTLD. 17 The
reason for a decrease of CSF Aβ 1-42 in FTLD is unknown, although there might be a relation
with the presence of an Apo E ε4 allele or with age. 23 Interestingly, a few studies have shown the
involvement of three mutations in the presenilin 1 gene (PSEN1) mutations in familiar forms of
FTLD. 24-26 These possible ‘loss of function’ PSEN1 mutations might act as inhibitors of the γ-
secretase cleavage of APP27, leading to a decrease of Aβ 1-42 in the brain. Although most FTLD
patients included in our study have the sporadic form of FTLD, we cannot exclude the possibility
of a mutation in the PSEN1 gene in some of them.
60
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13. Passing H and Bablok W. A new biometrical procedure for testing the equality of
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16. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating
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17. Tapiola T, Pirttila T, Mehta PD, Alafuzoff I, Lehtovirta M, Soininen H. Relationship
between Apo E genotype and CSF β-amyloid (1-42) and tau in patients with probable and
definite Alzheimer’s disease. Neurobiol Aging 2000;21:735-40.
18. Mehta PD, Pirttila T, Patrick BA, Barshatzky M, Mehta SP. Amyloid beta protein 1-40
and 1-42 levels in matched cerebrospinal fluid and plasma from patients with Alzheimer
disease. Neurosci Lett 2001;304:102-06.
19. Li R, Lindholm K, Yang LB, Yue X, Citron M, Yan R, et al. Amyloid beta peptide load is
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generation of truncated Abeta in beta-site amyloid-beta Precursor protein-cleaving
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21. Sergeant N, Kostanjevecki V, Casas K, Gesthem A, Grognet P, Drobecq H, et al. Aminotruncated Abeta42 species as early diagnostic and etiological biomarkers of Alzheimer’s
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23. Mann DM, McDonagh AM, Pickering-Brown SM, Kowa H, Iwatsubo T. Amyloid beta
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24. Dermaut B, Kumar-Singh S, Engelborghs S, Theuns J, Rademakers R, Saerens J, et al. A
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63
CHAPTER 4
AMYLOID β 38, 40, AND 42 SPECIES IN CEREBROSPINAL FLUID: MORE OF THE
SAME?
Niki SM Schoonenboom, Cees Mulder, Gerard J Van Kamp, Sangita P Mehta, Philip Scheltens,
Marinus A Blankenstein, Pankaj D Mehta
Ann Neurol 2005;58:139-142.
64
Abstract
Various C-terminally truncated amyloid β peptides (Aβ) are linked to Alzheimer’s disease (AD)
pathogenesis. Cerebrospinal fluid (CSF) concentrations of Aβ38, Aβ40, and Aβ42 were
measured by enzyme-linked immunosorbent assay in 30 AD patients and 26 controls. CSF Aβ42
levels were decreased in AD, while CSF Aβ38 and Aβ40 levels were similar in AD and controls.
All three Aβ peptides were inter-related, particularly CSF Aβ38 and Aβ40. Diagnostic accuracy
of CSF Aβ42 was not improved by applying the ratios of CSF Aβ42 to Aβ38 or Aβ40.
65
Introduction
The amyloid β (Aβ) peptides comprise a heterogeneous set of N-and C-terminally truncated
peptides as has been demonstrated in cell culture supernatants, brain tissue and cerebrospinal
fluid (CSF). 1-3 The three best known C-terminally truncated Aβ peptides are Aβ38, Aβ40 and
Aβ42. Aβ38 has been found to be the second prominent soluble Aβ peptide species in CSF after
Aβ40.3 Aβ42 is decreased in CSF of Alzheimer’s disease (AD) patients compared with control
subjects.4,5 There is evidence that soluble Aβ peptides are more related to disease severity in AD
than the insoluble Aβ42 peptide.3,6 Furthermore, the ratio of Aβ42 to Aβ40 is stated to classify
more AD patients correctly compared with CSF Aβ42 alone.7
With the emerging strategies for disease modification in AD8,9, quantification of other Aβ
species, in addition to Aβ42, linked to AD pathology may gain importance. To evaluate this, we
measured CSF concentrations of Aβ38, Aβ40, and Aβ42 by enzyme-linked immunosorbent
assays in AD and control subjects. The relations between the Aβ species and their correlations to
clinical variables were also investigated. Finally, the diagnostic accuracy of CSF Aβ42 in AD
versus controls subjects was compared with that of the ratios of CSF Aβ42 to Aβ40 and CSF
Aβ42 to Aβ38.
Subjects and methods
Subjects
Thirty AD patients and 26 controls were recruited at the Alzheimer Center of the VUMC. All AD
patients underwent a standardized investigative protocol as described in detail previously .5
Diagnosis of probable AD was made according to the NINCDS-ADRDA criteria.10 The control
group consisted of 20 subjects with subjective memory complaints, two subjects with a positive
family history and four healthy spouses without memory complaints. None of the controls
experienced development of dementia within a follow-up period of one year. The Mini Mental
State Examination (MMSE) score11 was used as a measure of global cognitive impairment.
Disease duration in AD patients was defined as the time in years between the first symptoms and
the lumbar puncture. The study was approved by the Ethical Review Board of the VU University
Medical Center. Patients and controls gave written informed consent to participate in the study.
66
CSF analyses
Antisera to Aβ40 and Aβ42 were produced in rabbits by immunizing Aβ32-40 and Aβ35-42
peptides.12 Antisera to Aβ38 peptide were produced in rabbits by immunization of peptide
“hCys-aminohexoanoyl-Ala-Ile-Ile-Gly-Leu-Met-Val-Gly-GlyOH” as described previously.12
The antisera were made specific for Aβ38 by passing through the affinity column, and eluting the
specific antibody at low pH. The antibody lacked reactivity against Aβ40 or Aβ42 peptides as
examined by sandwich enzyme-linked immunosorbent assay and Western blot analysis (data not
shown). Levels of Aβ38, Aβ40, and Aβ42 were quantified in CSF using a combination of mouse
monoclonal antibody (6E10), and antibodies specific for Aβ38, Aβ40 and Aβ42 in a double
antibody sandwich sandwich enzyme-linked immunosorbent assay as described13. The detection
limit for the assay was 10 pg/ml for all Aβ peptides. The mean of the coefficient of variation
within assay was 5.0% for Aβ38, 4.6% for Aβ40, and 9.3% for Aβ42.
Statistical analysis
For statistical analysis, SPSS version 11.0 was used. Mann Whitney U or Chi-square tests were
used to test group and frequency differences. Spearman correlation coefficient was used for
calculation of correlations. Statistical significance was set at p < 0.05. To determine the relation
between Aβ38 and Aβ40 the Passing and Bablok regression method14 was used, calculated by
Medcalc V 4.30 Software (Medcalc Software, Mariakerke, Belgium). Applying a sensitivity of ≥
85% or greater5, the corresponding specificities for Aβ42, and Aβ42/Aβ40 and Aβ42/Aβ38 ratios
were calculated. Receiver operating curves (ROC) curves were drawn by plotting the truepositive rate (sensitivity) against the false-positive rate (100-specificity). The area under the
curve (AUC) and the confidence interval of 95% (95%CI) were calculated. To assess the
statistical difference of the diagnostic performance between Aβ42 and the Aβ42/Aβ40 and
Aβ42/Aβ38 ratios the Hanley and McNeil method15 was applied.
67
Results
Subject characteristics and CSF levels of Aβ38, Aβ40, and Aβ42
AD patients and controls were comparable regarding age and gender (Table). Median disease
duration in AD was 4 years, ranging from 1 to 11 years. Median MMSE was 21 (range 3-28) in
AD and 29 (range 25-30) in control subjects. CSF Aβ42 and the ratios of Aβ42 to Aβ40
(Aβ42/Aβ40) and Aβ42 to Aβ38 (Aβ42/Aβ38) were significantly lower in AD compared with
control subjects. CSF levels of Aβ38 and Aβ40 in patients with AD and control subjects were
comparable.
Table Subject characteristics and CSF levels of Aβ38, Aβ40, and Aβ42
AD
Controls
P-value
Age
60 (52-79)
65 (45-79)
0.79
Sex (M/F)
15/15
12/14
0.32
Aβ38 (ng/mL)
2.7 (1.3-6.4)
3.2 (1.4-5.1)
0.22
Aβ40 (ng/mL)
16.9 (7.4-42.7)
19.2 (7.6-33.3)
0.90
Aβ42 (ng/mL)
0.29 (0.12-0.67)
0.63 (0.22-1.07)
<0.001
Aβ42/Aβ40
0.017 (0.006-0.048)
0.034 (0.016-0.069)
<0.001
Aβ42/Aβ38
0.11 (0.04-0.26)
0.24 (0.07-0.37)
<0.001
AD = Alzheimer’s disease. Aβ42/Aβ40 = ratio of Aβ42 to Aβ40; Aβ42/Aβ38 = ratio of Aβ42 to Aβ38. Values are
expressed as medians (minimum-maximum).
Relations of CSF levels of Aβ38, Aβ40, and Aβ42
In the whole group, a significant correlation could be shown between CSF Aβ38 and Aβ40
(R=0.89, P<0.001). The relation between Aβ38 and Aβ40 is shown in the Figure. Correlation
coefficients per diagnostic group of Aβ42 versus Aβ38 are 0.46 for AD (P=0.01) and 0.58 for
control subjects (P=0.02). For Aβ42 versus Aβ40 we found for AD R=0.43 (P=0.02) and R=0.65
(P<0.001) for control subjects. In the whole group, positive correlations were found between CSF
Aβ38 and Aβ40 and age (R=0.30, P=0.023 and R=0.28, P=0.037, respectively). There was no
68
Figure Plot of CSF Aβ38 and Aβ40 in AD and Controls
AD patients
Controls
10
9
Abeta38 (ng/ml)
8
7
6
5
4
3
2
1
0
0
10
20
30
40
50
Abeta40 (ng/ml)
The line represents the regression line Y = 0.66 + 0.115X correlation among CSF levels of Aβ38, Aβ40, Aβ42, and
age, disease duration or MMSE in either group.
69
correlation among CSF levels of Aβ38, Aβ40, Aβ42, and age, disease duration or MMSE in
either group.
Diagnostic performance of Aβ42 and the Aβ42/Aβ40 and Aβ42/Aβ38 ratios
Comparing AD patients with control subjects specificity for CSF Aβ42 was 88% at a sensitivity
of 87% using a cut off value of 0.37 ng/mL. For the Aβ42/Aβ40 and Aβ42/Aβ38 ratios
specificities were 81% and 77% at a sensitivity of 87%. Calculation of ratios did not improve the
diagnostic accuracy of CSF Aβ42 (AUC Aβ42 = 0.91, 95% CI 0.80 - 0.97, AUC Aβ42/Aβ40
ratio = 0.92, 95% CI 0.81 - 0.97, and AUC Aβ42/Aβ38 ratio = 0.90, 95% CI 0.79-0.96; Aβ42
versus Aβ42/Aβ40 ratio, P= 0.88, Aβ42 versus Aβ42/Aβ38 ratio, P= 0.80).
Discussion
Our data showed that CSF concentration of Aβ42 was decreased in AD, whereas CSF Aβ38 and
Aβ40 levels were similar in patients with AD compared with control subjects. All three Aβ
peptides were related to each other, with the strongest correlation between CSF Aβ38 and Aβ40.
Diagnostic accuracy of CSF Aβ42 alone was not different from the Aβ42/Aβ40 and Aβ42/Aβ38
ratios.
To our knowledge, no other study has been published, in which Aβ38, Aβ40 and Aβ42 have been
estimated by a quantitative method in the same CSF samples. By employing SDS-page gel
electrophoresis3 it was reported that the absolute amount of CSF Aβ42 was decreased in AD,
while CSF Aβ38 and Aβ40 concentrations were similar between AD and control subjects. When
the amount of the single Aβ peptide species was calculated relative to total Aβ, an increase of
CSF Aβ38 and Aβ40 was found. However, it is unclear how the total amount of Aβ was
measured in this study. Using the surface-enhanced laser desorption/ionization time-of-flight
(SELDI-TOF) technique 16 they found an increased peak of Aβ38 in pooled CSF from AD
patients, whereas CSF Aβ40 remained unchanged. The unchanged CSF concentration of Aβ40 is
consistent with previous studies.4,7,17 The discrepancy of the Aβ38 findings could be attributed to
the use of different methods. Furthermore, as both Aβ38 and Aβ40 are soluble peptides, they are
70
supposed to be released easily into the CSF, which might result in comparable concentrations in
AD and controls.
The correlation between CSF Aβ42 and CSF Aβ38 or Aβ40 was most prominent in control
subjects. Our findings are in line with the other study3, in which a close correlation was found
among the quintet Aβ37, Aβ38, Aβ39, Aβ40 and Aβ42 in control subjects. The various C-
terminally truncated Aβ peptides are formed by (alternative) γ-secretase cleavage of APP. Aβ42
is deposited in the plaques as a result of fibrillation. In all stages of plaque formation Aβ42 is
abundant, while Aβ40 and to a lesser extent Aβ38 are found in later stages of plaques
maturation.18,19 In some control subjects, Aβ38, Aβ40 and Aβ42 can be found in the brain, but to
a much lower extent.19 Analysis of CSF rests upon the assumption that CSF reflects the
biochemical processes taking place in the brain. The decrease of Aβ42 in CSF thus can be
explained by deposition of this peptide in the brain of patients with AD. Our findings further
support this hypothesis, since we found only Aβ42 to be decreased in CSF, which correlated
poorly to Aβ38 and Aβ40 in AD.
We found no difference in diagnostic accuracy of CSF Aβ42 compared to the Aβ42/Aβ40 and
Aβ42/Aβ38 ratios for the differentiation of AD from control subjects. The Aβ42/Aβ40 and
Aβ42/Aβ38 ratios are considered to give information about the disease progression, typically in
the early stage of disease, as the cerebral deposition of Aβ42 probably starts already before the
disease becomes clinically overt.20 This is in line with an earlier report showing an increased ratio
of Aβ40/Aβ42 before the clinical onset of AD.17 CSF Aβ42 alone is considered to be a stage
marker, reflecting the presence of the disease at a certain stage.20 It would be of interest to
investigate the ratio of Aβ42 to Aβ40 and Aβ38 in a group of patients with mild cognitive
impairment, observed longitudinally, to be informed when Aβ42 starts to decrease in CSF as
compared to Aβ38 and Aβ40, in relation with clinical progression.
71
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phosphorylated tau in CSF as markers for early-onset Alzheimer disease. Neurology
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6. McLean CA, Cherny RA, Fraser FW, et al. Soluble pool of Abeta amyloid as a
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7. Lewczuk P, Esselmann H, Otto M, et al. Neurochemical diagnosis of Alzheimer’s
dementia by CSF Aβ42, Aβ42/Aβ40 ratio and total tau. Neurobiol of Aging 2004;25:27381.
8. Weggen S, Eriksen JL, Das P, et al. A subset of NSAIDs lower amyloidogenic Abeta42
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Abeta(42) and change presenilin 1 conformation. Nat Med 2004;10:1065-6.
10. McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease:
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12. Potempska A, Mack K, Mehta PD, et al. Quantitation of sub-femtomole amounts of
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13. Mehta PD, Mehta SP, Fedor B, et al. Plasma amyloid beta protein1-42 levels are
increased in old Down syndrome but not in young Down syndrome. Neurosci Lett
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14. Passing H and Bablok W. A new biometrical procedure for testing the equality of
measurements from two different analytical methods. Application of linear regression
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Biochem 1983;21:709-20.
15. Hanley JA and McNeil BJ. A method of comparing the areas under receiver operating
characteristic curves derived from the same cases. Radiology 1983;148:839-43.
16. Lewczuk P, Esselmann H, Meyer M, et al. The amyloid-beta (Abeta) peptide pattern in
cerebrospinal fluid in Alzheimer's disease: evidence of a novel carboxyterminally
elongated Abeta peptide. Rapid Commun Mass Spectrom 2003;17:1291-6.
17. Kanai M, Matsubara E, Isoe K, et al. Longitudinal study of cerebrospinal fluid levels of
tau, A beta1-40, and A beta1-42(43) in Alzheimer's disease: a study in Japan. Ann Neurol
1998;44:17-26.
18. Wiltfang J, Esselmann H, Cupers P, et al. Elevation of β-amyloid peptide 2-42 in sporadic
and familial Alzheimer’s disease and its generation in PS1 knockout cells. J Biol Chem
2001:276;42645-57.
19. Pype S, Moechars D, Dillen L, Mercken M. Characterization of amyloid β peptides from
brain extracts of transgenic mice overexpressing the London mutant of human amyloid
precursor protein. J Neurochem 2003;84:602-9.
20. Blennow K and Hampel H. CSF markers for incipient Alzheimer’s disease. Lancet Neurol
2003;2:605-13.
73
CHAPTER 5
CSF Aβ42, TAU AND PHOSPHORYLATED TAU IN ALZHEIMER’S DISEASE
VERSUS FRONTOTEMPORAL DEMENTIA
74
.
75
CHAPTER 5.1
Amyloid β 42 (1-42) and phosphorylated tau in CSF as markers for early
onset Alzheimer’s disease
Niki SM Schoonenboom, Yolande AL Pijnenburg, Cees Mulder, Sonia M Rosso,
Evert-Jan Van Elk, Gerard J Van Kamp, John C Van Swieten, Philip Scheltens
Neurology 2004;62:1580-1584.
76
Abstract
Objective: To determine the diagnostic value of CSF amyloid β 1-42 (Aβ42), CSF total tau and
CSF tau phosphorylated at threonine 181 (Ptau-181) in early onset AD (EAD) vs frontotemporal
lobar degeneration (FTLD).
Methods: Levels of Aβ42, total tau and Ptau-181 in CSF were measured using commercially
available ELISAs in 47 EAD patients, 28 FTLD patients and 21 non-demented controls.
Results: CSF Aβ42 was significantly lower, and CSF total tau and CSF Ptau-181 significantly
higher in EAD patients compared to FTLD patients and controls. There was an increase in
diagnostic accuracy for CSF Ptau-181 vs CSF total tau (P=0.067). Combining low CSF Aβ42 and
high CSF Ptau-181 allowed EAD patients to be separated from FTLD patients with a sensitivity
of 72% and a specificity of 93%. Logistic regression analysis with CSF Aβ42 and CSF Ptau-181
as independent continuous variables resulted in correct classification of 46/47 (98%) EAD
patients and 23/28 (82%) FTLD patients. The diagnostic accuracy for EAD was independent of
gender, disease duration or disease severity.
Conclusion: The combination of CSF Αβ42 and CSF Ptau-181 may help differentiating EAD
from FTLD.
77
Introduction
In early onset AD (EAD), disorders of language, praxis or executive functions are more common
than memory problems.1,2 Compared to the other major types of early onset dementia2 EAD is
most difficult to distinguish from frontotemporal lobar degeneration (FTLD) on clinical and
radiological grounds, especially in the early phase of disease. The clinical and radiological
overlap calls for more specific diagnostic tools.
The combination of decreased CSF levels of amyloid β 1-42 (Aβ42) and increased levels of total
tau has been found to be a highly sensitive discriminator of AD from normal aging.3,4 In FTLD,
levels of CSF Aβ42 have been found to be normal or moderately low5, while CSF total tau was
either normal6 or increased.7-9 The few studies that investigated CSF phosphorylated tau10-12 all
showed better separation between AD and FTLD compared to total tau. However, in two studies
patients were not matched for age10,11, corrected for by analysis of variance with age as covariate10. A third study included an older AD and FTLD population of comparable age12, but the
prevalence of AD in late onset dementia is considerably higher than FTLD. When a priori
chances of dementia syndromes differ according to age, the usefulness of biomarkers to
distinguish them becomes less relevant. A recent study13 demonstrated that the prevalence of AD
and FTLD may be comparable in an early onset dementia population. To date, only one study has
described the value of two biomarkers -neurofilament protein and total tau- for the differential
diagnosis of EAD and FTLD.14 We investigate the diagnostic value of the currently most specific
commercially available biomarkers CSF Aβ42, CSF total tau and CSF Ptau-181 in a large group
of EAD patients, FTLD patients and non-demented age-matched controls.
Materials and methods
Subjects
Between October 2000 and June 2003 47 EAD patients and 22 FTLD patients (12 with FTD,
seven SD and three PA) were consecutively investigated at the Alzheimer Center of the VU
University Medical Center (VUMC), Amsterdam. An additional six FTLD patients were recruited
from the Erasmus Medical Center, Rotterdam (four FTLD and two SD). In all EAD and FTLD
patients symptoms started before the age of 65. All patients underwent a standardized
investigative battery, including medical history, physical and neurological examination, screening
78
laboratory tests, psychometric evaluation, EEG, and brain MRI or CT. In two EAD and five
FTLD patients with normal or inconclusive findings on structural imaging, Single Photon
Emission Computed Tomography (SPECT) with 99mTc-hexamethyl propyleneamine oxime was
performed. Dementia severity was assessed by the clinical dementia rating scale (CDR, all EAD
and FTLD patients) 15 and Mini Mental State Examination (MMSE) score (all EAD patients and
controls, 21 out of 28 FTLD patients).16 Disease duration was defined as the time in years
between the first symptoms (by history) and the first clinical diagnosis. At that time all patients
underwent a lumbar puncture. The initial diagnoses were made in conference by a team of
neurologists, neuropsychologists, a neurophysiologist, a psychiatrist and a radiologist. Diagnosis
of probable AD was made by exclusion according to the NINCDS-ADRDA criteria17; for FTLD
we used the clinical diagnostic criteria of Neary et al.18
The team involved in the diagnostic work-up was blinded to the results of the CSF analyses. For
most of the EAD and FTLD patients, clinical diagnoses were revisited and confirmed after a
minimum follow up period of six months and used in the analysis as the golden standard. The
diagnoses of the six FTLD cases from the Erasmus Medical Center were confirmed after a follow
up period of at least one year. In the 22 FTLD cases from the VUMC diagnoses were revisited
and confirmed by an independent neurologist. The three EAD patients, from whom CSF was
collected in June 2003 had been referred for a second opinion, and had been extensively
evaluated elsewhere. They underwent the same diagnostic procedure as all the other patients. In
19 EAD patients disease started with memory problems, while in the rest of the patients, aphasia,
apraxia or executive problems were initial features. Two EAD patients had first-degree family
members with confirmed AD starting before the age of 65, while the other EAD patients with a
positive family history for dementia had family members with late-onset type of AD. No further
genetic analysis took place in these patients. There were two FTLD patients with a positive
family history for early onset dementia; in one FTLD patient the P301L tau mutation was present.
The control group consisted of 21 non-demented subjects with a maximum age of 70. The group
included 13 subjects with subjective memory complaints, who were seen at the Alzheimer Center
of the VU University Medical Center and had undergone the same examinations as the patients;
five healthy spouses of patients with no memory complaints; two subjects with a positive family
history for AD and one patient with intracranial hypertension. None of the control subjects had
developed dementia after a follow up period of at least 6 months. The study was approved by the
79
ethical review boards of both the VU and Erasmus Medical Centers. All patients and controls
gave written informed consent to participate in the study.
CSF analysis
CSF was obtained by lumbar puncture between the L3/L4 or L4/L5 intervertebral space, and 12
ml was collected in polypropylene tubes. At the same time a serum sample was taken. Within an
hour, CSF and serum samples were centrifuged at 3000 rpm for 10 minutes at 4°C. A small
amount of CSF was used for routine analysis, including total cells, total protein, and erythrocytes.
CSF was aliquoted in polypropylene tubes of 0.5 or 1 ml, and stored at -80°C until analysis. CSF
Aβ42, CSF total tau and CSF Ptau-181 were measured by commercially available sandwich
ELISAs (Innotest β-amyloid (1-42) 19, Innotest hTAU-Ag20 and Innotest Phosphotau (181P);
Innogenetics, Ghent, Belgium).21 All CSF analyses were performed at the department of Clinical
Chemistry of the VUMC.
Statistical analysis
For statistical analysis, SPSS version 11.0 was used. In the study population none of the
variables, except age, were normally distributed. Non-parametric analyses (Kruskall Wallis
followed by the Mann Whitney U test) were used to compare medians of age, disease duration,
disease severity (CDR and MMSE), CSF Aβ42, CSF total tau and CSF Ptau-181. Statistical
significance was set at p<0.05. To calculate correlations between sex, age, disease duration,
disease severity and CSF Aβ42, CSF total tau and CSF Ptau-181 Spearman correlation
coefficient was used. Receiver Operating Characteristic (ROC) curves were drawn by plotting the
true-positive rate (sensitivity) against the false-positive rate (100-specificity). Based on the
assumption that the clinical criteria for AD provide a sensitivity of approximately 85%22, we
applied a sensitivity of ≥ 85% for each individual biomarker in accordance with the Reagan
Consensus report.23 We calculated the corresponding specificities and cut-off values, using EAD
as positive cases and FTLD or controls as negative cases. The areas under the ROC curves
(AUC) and standard errors (SE) were calculated by Medcalc V 4.30 Software (Medcalc Software,
Mariakerke, Belgium). To assess the statistical difference of the discriminating power of CSF
total tau and CSF Ptau-181 as well as CSF Αβ42 and CSF Ptau-181 from ROC curves the Hanley
80
and McNeil method was applied using the same statistical program.24 To differentiate EAD and
FTLD a logistic regression analysis with backward stepwise selection method was used as a
statistical modeling technique to estimate the simultaneous impact of the variables sex, disease
duration, disease severity (CDR), CSF Aβ42, and CSF Ptau-181.
Results
EAD patients were well matched for age with FTLD patients (Table 1). Furthermore, age at onset
of disease was comparable between the two patient groups. In EAD and control subjects women
were overrepresented, while in FTLD there was a surplus of men. There was a tendency towards
a longer disease duration in EAD patients compared to FTLD patients. EAD patients were more
functionally impaired than FTLD patients as measured by the CDR and MMSE.
CSF Aβ42 was significantly lower, and CSF total tau and Ptau-181 were significantly higher in
EAD patients than FTLD patients and control subjects. Total tau was increased in FTLD patients
compared with control subjects (P=0.03), while no difference in CSF Aβ42 and CSF Ptau-181
could be demonstrated (P=0.2 and P=0.7). There was a trend of increased CSF Ptau-181 in
patients with the temporal variant of FTLD (P=0.06).
No significant associations were found between the three biomarkers and gender, disease
duration or disease severity in EAD, FTLD and controls. In FTLD, a negative correlation
between CSF Aβ42 and age could be demonstrated (r=-0.39, P=0.04). Furthermore, there was a
trend towards a positive correlation between age and CSF Ptau-181 in control subjects (r=0.39,
P=0.08). Positive correlations were found between CSF total tau and CSF Ptau-181 in each group
(EAD: r=0.95, P<0.001; FTLD: r=0.8, P<0.001; controls: r=0.85, P<0.001)
Sensitivity and specificity for each biomarker were calculated using ROC analyses. Using a cut
off value of 413 pg/mL for CSF Aβ42, EAD patients could be separated from FTLD patients
with a sensitivity of 85% and a specificity of 75%. Sensitivity and specificity values for CSF total
tau were 85% and 74% at a cut off value of 377 pg/mL. For CSF Ptau-181 sensitivity was 85%
and specificity 82% at a cut off value of 54 pg /mL. There was a tendency towards a significant
increase in diagnostic accuracy for CSF Ptau-181 compared with CSF total tau (CSF total tau:
AUC = 0.813, 95% CI 0.706-0.894; CSF Ptau-181: AUC = 0.866, 95% CI 0.767-0.933 P=0.067).
81
Table 1: Demographic data and CSF analyses per diagnostic category
EAD (n=47)
FTLD (n=28)
Controls (n=21)
P-value*
P-value**
Age (yrs)
59 (52-68)
60 (43-68)
62 (39-70)
0.7
0.9
Sex (F:M)
29:18
10 :18
14 :7
0.03
0.7
Disease duration
4 (1-11)
3 (1-11)
--
0.08
--
CDR
1 (1-3)
1 (0.5-2)
--
0.002
--
MMSE
20 (3-28)
25 (3-29)
29 (27-30)
0.01
< 0.001
Aβ42 (pg/ml)
307 (124-525)
603 (245-1072)
604 (337-1224)
< 0.001
< 0.001
Total tau (pg/ml)
642 (75-2692)
330 (65-1527)
191 (95-587)
<0.001
<0.001
Ptau-181 (pg/ml)
79 (18-279)
41 (18-141)
35 (18-87)
< 0.001
< 0.001
EAD = early onset Alzheimer’s disease; FTLD = Frontotemporal Lobar Degeneration; CDR = Clinical Dementia Rating; MMSE = Mini Mental State Examination; M = male, F = female; yrs = years;
Ptau-181 = tau protein phosphorylated at threonine 181; Aβ42 = amyloid β 1−42. Disease duration is defined as the time in years between the first symptoms (by history) and the first clinical diagnosis.
Values are expressed as medians (minimum-maximum). P-values refer to statistical difference between EAD vs FTLD (*) and EAD vs controls (**).
82
Figure 1 Plot CSF amyloid β 1-42 and CSF tau phosphorylated at threonine 181 in EAD vs
FTLD
1400
1200
1000
Amyloid B 1-42 (pg/mL)
800
600
GROUP
400
controls
200
FTD
EAD
0
0
100
200
300
Ptau-181 (pg/mL)
EAD=early onset Alzheimer’s disease, FTLD= frontotemporal lobar degeneration. Ptau-181 = tau phosphorylated at
threonine 181. Dotted lines represent the cut-off values for EAD vs FTLD
83
Table 2 Cross tabulation of CSF amyloid β 1-42 and CSF tau phosphorylated at threonine 181 in
EAD, FTLD and controls
Two markers positive
EAD
FTLD
Controls
(N=47)
(N=28)
(N=21)
34
2
0
6
5
1
6
3
5
1
18
15
Aβ42 ≤ 413 pg/mL and Ptau-181 > 54 pg/mL
One marker positive: Aβ42
Aβ42 ≤ 413 pg/mL and Ptau-181 ≤ 54 pg/mL
One marker positive: Ptau-181
Ptau-181 > 54 pg/mL and Aβ42 > 413 pg/mL
Two markers negative
Aβ42 > 413 pg/mL and Ptau-181 ≤ 54 pg/mL
EAD = early onset Alzheimer’s disease; FTLD = Frontotemporal Lobar Degeneration.
Ptau-181 = tau protein phosphorylated at threonine 181; Aβ42 = amyloid β 1−42
No difference was present in diagnostic accuracy for CSF Aβ42 and CSF Ptau-181 as
demonstrated by the AUC values (CSF Aβ42: AUC = 0.860, 95% CI 0.760-0.929; CSF Ptau181: AUC = 0.866, 95% CI 0.767-0.933; P=0.92).
In EAD versus control subjects sensitivity for CSF Aβ42 was 96% at a specificity of 95% using a
cut off value of 471 pg/mL. Specificity for CSF total tau was 90% at a sensitivity of 85% with a
cut off value of 369 pg/mL. For CSF Ptau-181 sensitivity was 85% and specificity 76% at a cut
off value of 54 pg/mL. Diagnostic accuracy of CSF Aβ42 was better than CSF Ptau-181 (CSF
Aβ42: AUC = 0.981, 95% CI 0.918-0.998; CSF Ptau-181: AUC = 0.879, 95% CI 0.783-0.943;
P=0.01). No difference was present in diagnostic accuracy of CSF total tau versus CSF Ptau-181
(P=0.27).
In Table 2 the number of EAD patients, FTLD patients and control subjects are depicted with at
least one marker being positive or negative, or with the combination of CSF Aβ42 and CSF Ptau181 being positive or negative, using abovementioned cut off values for EAD vs FTLD. These
findings are visualised in Figure 1. For EAD vs FTLD, sensitivity and specificity for the
combination of Aβ42 and Ptau in the AD range is 72% and 93%. For EAD vs controls, the
84
combination of Aβ42 and total tau gives a sensitivity of 81% and a specificity of 100% using the
cut off values for EAD vs controls.
Positive and negative likelihood ratios (+LR and -LR) for the differentiation between EAD vs
FTLD are calculated using the data depicted in table 2. The combination of two markers being
positive compared with at least one marker negative gives a +LR of 10 and a -LR of 0.30. A
negative value of both biomarkers compared with at least one positive gives a +LR of 2.72 and a
-LR of 0.03.
When using parametric statistics (univariate analysis of variance) after log-transformation of the
variables no influence of the covariates MMSE and disease duration on the primary variables
Aβ42, total tau and Ptau-181 could be demonstrated. Logistic regression analysis with diagnosis
(EAD or FTLD) as dependent variable and CDR, CSF Aβ42 and Ptau-181 as independent
variables resulted in correct classification of 44/47 (94%) EAD patients and 24/28 (86%) FTLD
patients. Removing CDR from the model correctly classified 46/47 (98%) EAD patients and
23/28 (82%) FTLD patients. Disease duration or gender did not affect the outcome of the model.
Discussion
In this study, we found a high diagnostic accuracy for the combination of low CSF Aβ42 and
high CSF Ptau-181 in differentiating EAD from FTLD. The diagnostic accuracy for EAD
achieved by this combination of markers was independent of gender, disease duration and disease
severity. Furthermore, we confirmed the results of other studies describing an increase in
diagnostic accuracy for CSF Ptau-181 compared with CSF total tau in differentiating AD from
FTLD.
Our observation of decreased CSF levels of Aβ42 in EAD patients is consistent with two
previous studies in which early onset AD and sporadic (or late onset) AD (LAD) were compared.
6,25
Although levels of CSF Aβ42 in EAD and LAD were comparable in one of these studies 6,
the significantly lower CSF Αβ42 values in EAD compared with LAD in the second study25 are
suggestive of pathophysiological heterogeneity. It could be argued that EAD is a more ‘pure’
form of AD, in which the formation of neuritic plaques by overproduction of Aβ42 is a relatively
early and prominent phenomenon, whereas in LAD multiple (vascular) pathogenic factors are
thought to play a role.26 The heterogeneity of AD could also explain the discordance of CSF
85
markers between different studies27, and support the notion of separating EAD from LAD
patients in research on diagnostic markers.
Our findings of an increase of CSF Ptau-181 in five of the 28 FTLD patients do not correspond
with those from two previous studies10,21, in which Ptau-181 was found to be significantly lower
in FTLD patients compared to AD patients and controls. A possible explanation for this
discrepancy could be that the authors compared younger FTLD patients (mean age of 65 years) to
older AD patients (mean age of 74 years) and controls (mean age of 72 years). In our study we
found a trend towards a positive correlation between age and Ptau-181 in controls, which might
have been stronger if subjects with a broader age range had been included. An age-related
increase of CSF total tau in healthy individuals has previously been demonstrated28,29, and may
reflect age related neuronal or axonal degeneration. Recently, a positive correlation between CSF
Ptau-231 and age was found in a population of depressed subjects.30 These consistent
correlations between age and total tau and Ptau stress the importance of comparing only groups
that are strictly matched for age.
Another explanation for the discrepant results between our study and the aforementioned
studies10,21 could be the heterogeneity in underlying pathology of FTLD.31 Although the extent of
abnormal phosphorylation of tau is supposed to be higher in tau deposits in the brain of AD
patients compared with FTLD patients, phosphorylation of tau at threonine 181 itself is a normal
phenomenon32, which could either be decreased10 or increased, as in some of our FTLD patients.
Two of the FTLD patients had an increase of CSF total tau without an increase of CSF Ptau-181
resulting in a better diagnostic accuracy of CSF Ptau-181. Overall, the increase of CSF total tau
in a subset of FTLD patients could be a reflection of tau deposits, which are found in a minority
of FTLD patients.31 However, the hypothesis of a direct association between tau pathology and
an increase of CSF total tau remains unproven as demonstrated recently by normal CSF total tau
levels in FTLD patients with tau mutations that cause intracerebral tau-deposition.33
It could be argued that our results lack biological validity in the absence of post-mortem
verification. This applies to many of the studies published in the field of diagnostic markers and
in our opinion does not invalidate the results. We tried to achieve the highest diagnostic certainty
by means of the same rigorous diagnostic work up in every patient, use of all available imaging
information, including a high resolution MRI protocol in all patients, and ensuring clinical follow
86
up of at least 6 months. From class I studies (prospective studies with neuropathological
confirmation) it is known that the NINCDS-ADRDA for probable AD have a high sensitivity but
a moderately high specificity.22,34 Although none of the other diagnostic measurements
(neuropsychological tests, MRI scan) have neuropathological validation, serial tests should
increase the overall specificity of the diagnosis.34
The difference in diagnostic value of the single biomarkers for EAD and FTLD on the one hand
and EAD and controls on the other hand is noteworthy. For the differentiation of EAD from
FTLD, CSF Ptau-181 seems to be a slightly more specific marker than CSF Αβ42; seven out of
28 FTLD patients had a CSF level of Aβ42 below the cut off value. Although plaques are not a
common feature in the sporadic form of FTLD, several authors found decreased CSF levels of
Αβ42 in a subset of FTLD patients5, which may be related to the presence of an Apo E ε4 allel or
older age35 as in our patients. For the differentiation of EAD from age-matched elderly controls
CSF Αβ42 alone is found to be the most sensitive and specific marker, followed by CSF total tau,
whereas CSF Ptau-181 was increased in five out of 21 controls. This increase of CSF Ptau-181
could be related to aging, but there remains the possibility that these five subjects may develop
AD in the future, particularly as four of the five had subjective memory complaints. This
hypothesis is supported by a recent study showing that high CSF levels of Ptau-231 at baseline,
but not total tau levels, correlated with cognitive decline and conversion from mild cognitive
impairment (MCI) to AD.36
According to the Reagan Consensus Report23 an ideal biomarker needs to have a specificity of
75-85% and a sensitivity of ≥ 85% to be clinically useful. To date, no single marker has been
found to be specific enough to differentiate AD from other dementias, and the use of a
combination of markers has been advocated to increase specificity.37 Indeed, in our study only
two FTLD patients (both with PA) had a value of both markers in the AD range (specificity
93%), an increased specificity of more than 10% compared with the use of CSF Aβ42 or CSF
Ptau-181 alone. It would be informative to collect further autopsy data from these two PA
patients. Although the majority of PA cases presented in the literature have non-AD pathology,
several case reports of patients with non-fluent aphasic syndromes have been described, who
revealed typical AD pathological features at autopsy.2
87
For the use of the markers to assist with the differential diagnosis of EAD and FTLD in clinical
practice, a low negative likelihood ratio may be even more important.23 A test to exclude EAD
will be of great benefit to the patient and would provide the clinician the opportunity to direct the
diagnostic effort elsewhere. Furthermore, it has been demonstrated by retrospective
neuropathological studies that the specificity of the NINCDS-ADRDA criteria for the differential
diagnosis of AD vs FTLD is only 23%.38 A negative laboratory test may be more informative to
the clinician regarding the neuropathological nature of the underlying type of dementia, when
clinical and radiological criteria fail to do so. Our findings of a very low -LR (0.03) when both
markers are negative make this combination of markers quite robust.
88
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3. Hulstaert F, Blennow K, Ivanoiu A, et al. Improved discrimination of AD patients using
beta amyloid 1-42 and tau levels in CSF. Neurology 1999;52:1555-62.
4. Galasko D, Chang L, Motter R, et al. High cerebrospinal fluid tau and low amyloid beta
42 levels in the clinical diagnosis of Alzheimer disease and relation to apolipoprotein E
genotype. Arch Neurol 1998;55:937-45.
5. Riemenschneider M, Wagenpfeil S, Diehl J, et al. Tau and Abeta42 protein in CSF of
patients with frontotemporal degeneration. Neurology 2002;58:1622-8.
6. Sjögren M, Minthon L, Davidsson P, et al. CSF levels of tau, beta amyloid 1-42
and GAP-43 in frontotemporal dementia, other types of dementia and normal
aging. J Neural Transm 2000;107:563-79.
7. Green AJE, Harvey RJ, Thompson EJ, Rossor MN. Increased tau in the cerebrospinal
fluid of patients with frontotemporal dementia and Alzheimer’s disease. Neurosci Lett
1999;259:133-5.
8. Arai H, Morikawa Y, Higuchi M, et al. Cerebrospinal fluid tau levels in
neurodegenerative diseases with distinct tau-related pathology. Biochem Biophys Res
Commun 1997;236:262-4.
9. Fabre SF, Forsell C, Viitanen M, et al. Clinic-based cases with frontotemporal dementia
show increased cerebrospinal fluid tau and high apolipoprotein E epsilon 4 frequency, but
no tau gene mutations. Exp Neurol 2001;168:413-8.
10. Sjögren M, Davidsson P, Tullberg M, et al. Both total and phosphorylated tau are
increased in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2001;70:624-30.
11. Itoh N, Arai H, Urakami K, et al. Large-scale, multicenter study of cerebrospinal fluid tau
protein phosphorylated at serine 199 for the antemortem diagnosis of Alzheimer’s
disease. Ann Neurol 2001;50:150-6.
89
12. Buerger K, Zinkowski R, Teipel SJ, et al. Differential diagnosis of Alzheimer disease
with cerebrospinal fluid levels of tau protein phosphorylated at threonine 231. Arch
Neurol 2002;59:1267-72.
13. Ratnavalli E, Brayne C, Dawson K, Hodges JR. The prevalence of frontotemporal
dementia. Neurology 2002;58:1615-21.
14. Sjögren M, Rosengren L, Minthon L, Davidsson P, Blennow K, Wallin A. Cytoskeleton
proteins in CSF distinguish frontotemporal dementia from AD. Neurology 2000;54:19604.
15. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules.
Neurology 1993;43:2412-4.
16. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for
grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-98.
17. 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;34:939-44.
18. Neary D, Snowden JS, Gustafson L, et al. Frontotemporal lobar degeneration: a consensus
on clinical diagnostic criteria. Neurology 1998;51:1546-54.
19. Vanderstichele H, Van Kerschaver E, Hesse C, et al. Standardization of measurement of
beta amyloid 1-42 in cerebrospinal fluid and plasma. Amyloid 2000;7:245-58.
20. Vandermeeren M, Mercken M, Vanmechelen E, et al. Detection of tau proteins in normal
and Alzheimer’s disease cerebrospinal fluid with a sensitive sandwich enzyme-linked
immunosorbent assay. J Neurochem 1993;61:1828-34.
21. Vanmechelen E, Vanderstichele H, Davidsson P, et al. Quantification of tau
phosphorylated at threonine 181 in human cerebrospinal fluid: a sandwich ELISA with a
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22. Galasko D, Hansen LA, Katzman R, et al. Clinical-neuropathological correlations in
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23. The Ronald and Nancy Reagan Research Institute of the Alzheimer’s Association.
Consensus report of the working group on: “Molecular and biochemical markers of
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24. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating
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27. Sunderland T, Linker G, Mirza N, et al. Decreased β-Amyloid 1-42 and increased tau
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28. Sjögren M, Vanderstichele H, Ågren H, et al. Tau and Aβ42 in cerebrospinal fluid from
healthy adults 21-93 years of age: establishment of reference values. Clin Chem
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29. Blomberg M, Jensen M, Basun H, Lannfelt L, Wahlund LO. Cerebrospinal fluid tau
levels increase with age in healthy individuals. Dement Geriatr Cogn Disord
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30. Buerger K, Zinkowski R, Teipel S, et al. Differentiation of geriatric major depression
from Alzheimer’s disease with CSF tau protein phosphorylated at threonine 231. Am J
Psychiatry 2003;160:376-9.
31. Buée L, Bussière T, Buée-Scherrer V, Delacourte A, Hof PR. Tau protein isoforms,
phosphorylation and role in neurodegenerative disorders. Brain Res Rev 2000;33:95-130.
32. Morishima-Kawashima M, Hasegawa M, Takio K, et al. Hyperphosphorylation of tau in
PHF. Neurobiol Aging 1995;16:365–71.
33. Rosso SM, Van Herpen E, Pijnenburg YAL, et al. Total tau and phosphorylated tau 181
levels in the cerebrospinal fluid of patients with frontotemporal dementia due to P301L
and G272V tau mutations. Arch Neurol 2003;60:1209-13.
34. Qizilbash N, ed. Evidence-based Dementia Practice. Oxford: Blackwell Science Ltd,
2002.
35. Mann DM, McDonagh AM, Pickering-Brown SM, Kawaa H, Iwatsubo T. Amyloid beta
protein deposition in patients with frontotemporal lobar degeneration: relationship to age
and apolipoprotein E genotype. Neurosci Lett 2001;304:161-4.
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36. Buerger K, Teipel SJ, Zinkowski R, et al. CSF tau protein phosphorylated at threonine
231 correlates with cognitive decline in MCI subjects. Neurology 2002;59:627-9.
37. Blennow K, Vanmechelen E, Hampel H. CSF total tau, Abeta42 and phosphorylated tau
protein as biomarkers for Alzheimer’s disease. Mol Neurobiol 2001;24:87-97.
38. Varma AR, Snowden JS, Lloyd JJ, et al. Evaluation of the NINCDS-ADRDA criteria in
the differentiation of Alzheimer's disease and frontotemporal dementia. J Neurol
Neurosurg Psychiatry 1999;66:184-8.
Acknowledgements
We thank Peggy Verelst, Innogenetics NV, Ghent, Belgium, for supplying ELISAs. Silla
Notten is thanked for technical assistance at the Department of Clinical Chemistry, VUMC.
Bernard MJ Uitdehaag (MD, PhD) is gratefully acknowledged for his unbiased critique and
helpful discussion.
Niki SM Schoonenboom was partly funded through a grant from Alzheimer Nederland,
Bunnik (V2001-023). Additional funding was received from the Stichting Alzheimer and
Neuropsychiatry Foundation, Amsterdam.
92
93
CHAPTER 5.2
CSF tau and Abeta42 are not useful in the diagnosis of frontotemporal
lobar degeneration
Yolande AL Pijnenburg, Niki Schoonenboom, Sonia M Rosso, Cees Mulder,
Gerard J Van Kamp, John C Van Swieten, Philip Scheltens
Neurology 2004;62:1649.
94
95
Frontotemporal lobar degeneration (FTLD),1 a neurodegenerative disorder presenting with a
spectrum of behavior changes, executive disturbances, or aphasia, is often unrecognized. Patients
with FTLD are many times considered to have a psychiatric disorder or Alzheimer disease (AD).
Imaging studies and psychometric testing can be normal at an early stage.2 CSF biomarkers have
been considered in the diagnosis of FTLD. One study found that the combination of CSF tau and
amyloid β (1–42) (Aβ42) provided assistance in the diagnosis of FTLD.4 We investigated CSF
tau and Aβ42 in FTLD compared with age-matched AD patients and cognitively healthy control
subjects.
Methods Thirty-five patients with FTLD (18 frontotemporal dementia, 11 semantic dementia, and
6 progressive nonfluent aphasia) were compared with 51 patients with probable AD3 and 27
nondemented control subjects. All patients underwent a standard medical history, physical and
neurologic examination, screening laboratory tests, psychometric tests, EEG, MRI, or CT.
99mTc-Hexamethylpropyleneamine oxide SPECT was performed in seven cases with normal or
inconclusive findings on structural neuroimaging. Only patients whose clinical diagnoses were
evaluated by a multidisciplinary team and supported by either structural or functional
neuroimaging were included. All but two of the FTLD cases were sporadic. Genetic screening
took place in one of the familial cases, yielding a P301L mutation. The clinical diagnosis was
confirmed pathologically in one case, showing neuronal degeneration without tau pathology. The
Clinical Dementia Rating Scale (CDR)5 was used to assess dementia severity.
The control group consisted of 16 subjects with subjective memory complaints, who underwent
the same examinations as the patients, 5 cognitively healthy subjects with a positive family
history, as well as 6 healthy spouses of patients with no memory complaints.
CSF was obtained by lumbar puncture between the L3 to L4 or L4 to L5 intervertebral space after
informed consent. Within an hour, CSF samples were centrifuged at 3,000 rpm for 10 minutes at
4 °C followed by storage in polypropylene tubes at _80 °C until analysis. CSF tau and Aβ42 were
determined by sandwich ELISA (Innotest β-amyloid(1—42) and Innotest hTAU-Ag;
Innogenetics, Ghent, Belgium).
Results Clinical, demographic, as well as CSF tau and Aβ42 data are displayed in the table. No
significant differences in CSF tau between the FTLD subgroups were found. In progressive
96
nonfluent aphasia, Aβ42 was lower than in frontotemporal dementia (p = 0.033) and semantic
dementia (p = 0.015).
A cut-off value of 908 pg/mL for CSF tau distinguished FTLD from AD at a sensitivity of 86%
and a specificity of 26%. To distinguish FTLD from controls, a CSF tau cut-off of 193 pg/mL
yielded a sensitivity of 86% at a specificity of 41%. For CSF Aβ42, a cut-off value of 315 pg/mL
distinguished FTLD from AD at a sensitivity of 86% and a specificity of 59%. The number of
FTLD patients that was correctly classified by a CSF tau range between 193 and 908 pg/mL and
a CSF Aβ42 value higher than 315 pg/mL was 21 (60%).
Discussion Even though significant differences were found, there was extensive overlap of CSF
tau and Aβ42 values between FTLD, AD, and control subjects. In a relatively young population
where the a priori chance of FTLD is at best 50%,6 the positive predictive value of a CSF tau
value between 193 and 908 pg/mL combined with a CSF Aβ42 value higher than 315 pg/mL
would be 51% with a negative predictive value of 52%, which is not above chance level.
Therefore, we conclude that measurement of tau and Aβ42 in CSF is not useful for the diagnosis
of FTLD.
97
References
1. Neary D, Snowden JS, Gustafson L, et al. Frontotemporal lobar degeneration: a consensus on
clinical diagnostic criteria. Neurology 1998;51:1546–54.
2. Gregory CA, Serra–Mestres J, Hodges JR. Early diagnosis of the frontal variant of
frontotemporal dementia: how sensitive are standard neuroimaging and neuropsychologic
tests? Neuropsychiatry Neuropsychol Behav Neurol 1999;12:128–35.
3. 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;34:939–44.
4. Riemenschneider M, Wagenpfeil S, Diehl J, et al. Tau and Abeta42 protein in CSF of patients
with frontotemporal degeneration. Neurology 2002;58:1622–8.
5. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology
1993;43:2412–4.
6. Ratnavalli E, Brayne C, Dawson K, Hodges JR. The prevalence of frontotemporal dementia.
Neurology 2002;58:1615–21.
98
Table Clinical and demographic data and values of CSF biomarkers
Data
FTLD, N = 35
AD, N = 51
Controls, N = 27
Statistical significance
Age, y
61 (51–85)
63 (53–78)
66 (39–76)
P = 0.50
Sex, M:F
23:12
22:29
11:16
P < 0.001
CDR
1 (0.5–2)
1 (1–3)
—
P = 0.009
Disease duration, y 3 (1–11)
4 (1–11)
—
P = 0.014
CSF tau, pg/mL
632 (195–1,822)
298 (95–993)
FTLD vs AD, P = 0.002
353 (49–1,740)
FTLD vs controls, P = 0.03
CSF Aβ42, pg/mL
565 (178–1,225)
298 (124–592)
634 (232–1,243)
FTLD vs AD, P < 0.001
FTLD vs controls, P = 0.13
Values are medians (range). For statistical analysis, nonparametric tests were used (Kruskal–Wallis, Mann–
Whitney); differences in male/female distribution were analyzed using the χ2 test. FTLD = frontotemporal lobar
degeneration; AD = Alzheimer disease; CDR = Clinical Dementia Rating Scale; Aβ42 = amyloid β (1–42), y =
years
99
CHAPTER 6
BIOMARKER PROFILES AND THEIR RELATION TO CLINICAL VARIABLES IN
MILD COGNITIVE IMPAIRMENT
Niki SM Schoonenboom, Pieter Jelle Visser, Mulder Cees, Jaap Lindeboom, Evert-Jan Van Elk,
Gerard J Van Kamp, Philip Scheltens
Neurocase 2005;11:8-13.
100
Abstract
The aim of the study was to compare clinical variables between MCI patients at different risk for
Alzheimer’s disease (AD) according to their biomarker profile. Fifty-four % out of 39 MCI
patients had a low Aβ42 and high tau in cerebrospinal fluid (CSF) (high-risk), 26% either a low
CSF Aβ42 or high CSF tau (intermediate-risk) and 20% a normal CSF Aβ42 and tau (low-risk).
Both high- and intermediate-risk subjects differed from the low-risk group in episodic memory,
executive functions and the preclinical AD scale (PAS), which combines a set of clinical
parameters. Subjects at high-risk did not differ from subjects with an intermediate-risk. Aβ42
levels correlated with the MTA and PAS scores, tau levels with episodic memory. These
correlations suggest that the biomarkers are not independent when compared to the other AD
markers. Longitudinal studies are necessary to interpret the correlations between biomarkers,
imaging, and neuropsychological markers.
101
Introduction
Mild cognitive impairment (MCI) is considered to be a transitional state between normal aging
and dementia16 and 10-15% of the patients with MCI progress to Alzheimer type dementia (AD)
each year. 17 Several studies have shown that a subgroup of MCI patients has low cerebrospinal
fluid (CSF) amyloid β 1-42 (Aβ42) and high total tau (tau) levels that are considered indicative
for AD. However, most of these studies have been performed in specific research settings.1,2,20
Little is known about how frequently such a typical AD biomarker profile is seen in MCI patients
selected from a setting that reflects daily clinical practice.32
No cross-sectional studies investigated to what extent MCI patients with an AD biomarker profile
differ from MCI patients with a normal biomarker profile with respect to other clinical markers or
risk factors of AD. This is important to know for two reasons. First, investigating the relation
between biomarkers and other markers of AD will show whether these markers are independent
predictors for AD at baseline. Second, it will yield information regarding the pathophysiology of
AD in the early stage.
The aim of the present study is threefold. First, we investigate how many subjects with amnestic
MCI from our Memory Clinic display high-risk (low CSF Aβ42 and high CSF tau), intermediate
risk (low CSF Aβ42 and normal CSF tau or normal CSF Aβ42 and high CSF tau), and low-risk
(normal CSF Aβ42 and normal CSF tau) biomarker profiles. Secondly, we compare age, disease
duration, MMSE, Apo E genotype, neuropsychological test performance, and medial temporal
lobe atrophy (MTA) score among these groups. In addition, we compare the score on the
preclinical Alzheimer’s disease Scale (PAS)29 between the groups with different biomarker risk
profiles. The PAS is a scale that applies a set of clinical parameters to estimate the risk for AD in
MCI patients. Finally, we investigate the correlation between the two biomarkers and the other
risk factors for AD.
Patients and methods
Patients
Thirty-nine patients younger than 85 years with amnestic MCI were consecutively recruited at the
Alzheimer Center of the VU University Medical Centre (VUMC), Amsterdam, between January
2001 and November 2003. Patients were referred to our memory clinic by general practitioners
(N=30) or by other neurologists/specialists as second opinions (N=9). Diagnosis of amnestic MCI
102
was made according to the criteria of Petersen et al.17, indicating that a patient had subjective and
objective memory impairment with no interference with daily activities, and no dysfunction in
other cognitive domains. The patients underwent a standardized clinical assessment, including
medical history, physical and neurological examination, laboratory tests, psychometric
evaluation, EEG, and brain MRI or CT. The initial diagnoses were made in conference by a team
of neurologists, neuropsychologists, a neurophysiologist, a psychiatrist, and a radiologist. The
team involved in the diagnostic work-up was blinded to the results of the CSF analyses. The Mini
Mental State Examination (MMSE) score7 was used as a measure of global cognitive impairment.
Disease duration was defined as the time in years between the first symptoms (by history) and the
lumbar puncture (LP) for CSF sampling. Median time between first assessment and LP was 2
months (range 0-23). All patients met criteria for amnestic MCI at the time of the LP. The ethical
review board of the VUMC approved the study and all subjects gave written informed consent.
CSF analysis
CSF was obtained by lumbar puncture (LP) between the L3/L4 or L4/L5 intervertebral space and
collected in polypropylene tubes. Within an hour, CSF samples were centrifuged at 3000 rpm for
10 minutes at 4°C. A small amount of CSF was used for routine analysis, including total cells,
total protein, and erythrocytes. CSF was aliquoted in polypropylene tubes of 0.5 or 1 ml, and
stored at -80°C until analysis. CSF Aβ42 and tau were measured by commercially available
sandwich ELISAs (Innotest β-amyloid (1-42)27 and Innotest hTAU-Ag26, Innogenetics, Ghent,
Belgium). All CSF analyses were performed at the department of Clinical Chemistry of the
VUMC.
Calculation of the cut off values
The optimal cut-off values for CSF Aβ42 and tau were set at data obtained from 92 probable AD
patients15 and 38 controls also recruited at the Alzheimer Centre, VUMC. After drawing Receiver
Operating Characteristics (ROC) curves, we applied a sensitivity of ≥ 85% for each individual
biomarker in accordance with the Ronald and Nancy Reagan Consensus report.25 The
corresponding specificities and cut-off values were calculated. Sensitivity and specificity values
for CSF Aβ42 were 86% and 89% using a cut off level of ≤ 494 pg/mL. For CSF tau sensitivity
and specificity were 89% and 74% at a cut off level of > 356 pg/mL.
103
Apo E genotype
DNA was isolated from 10 ml EDTA blood and was available from 36 out of 39 patients. ApoE
genotype was determined with the Light Cycler ApoE mutation detection method (Roche
diagnostics GmbH, Mannheim, Germany). Patients were dichotomized on the basis of no or ≥ 1
ε4 allele.
MRI analysis
MRI scans were made on a 1.0 (N=30) or 1.5 (N=4) Tesla scanner (Siemens), in coronal (mprage, slice thickness 1.5 mm) and axial direction (FLAIR, slice thickness 5 mm). In 3 MCI
patients no MRI was made because of claustrophobia (N=1) or the presence of a pacemaker
(N=2). Two other patients were also excluded from MRI analysis, one patient because the time
between LP and MRI scan was > 12 months and in another patient because no coronal scan was
available. Median time between LP and MRI scan was 2 months (range 0-10). The MTA score
was rated visually according to the method of Scheltens et al.30 The MTA score is based on a
visual estimation of the volume of the medial temporal lobe, including the hippocampus proper,
dentate gyrus, subiculum, and parahippocampal gyrus, and the volume of the surrounding CSF
spaces, in particular the temporal horn of the lateral ventricle and the choroid fissure, on both
sides. The MTA score ranges from 0 (no atrophy) to 4 (severe atrophy). MTA scores of the right
and left hippocampi were added up in each patient. Furthermore, the scores were dichotomised
into a normal value, with a grade 0 or 1 in each hippocampus, or an abnormal value with at least
grade 2 in one hippocampus. The MTA score was estimated as part of routine patient care by two
trained raters, who were blinded to the clinical information.
Neuropsychological measurements
From the neuropsychological evaluation we used the data of the visual association test (VAT)13 as
a measure of episodic memory. The VAT was administered in 33 out of 39 patients. The material
of the VAT consists of six association cards showing two interacting objects and six cue cards
showing only one of the objects. Recall is tested without delay. The maximum score of the VAT
is 6 points. An impaired score on the VAT was defined as a score < 5. The VAT was
104
dichotomised into a normal score (VAT ≥ 5) and an abnormal score (VAT < 5). The verbal
fluency (the ability to name as many animals as possible within 1 minute) was measured in 37
patients and used as a measure of language function. Furthermore, Trailmaking test A (TMT A,
32 patients) and Trailmaking test B (TMT B, 29 patients) were used as measures of executive
function. Fluency, TMT A, and TMT B were corrected for age, sex, and education and expressed
as z-scores on the basis of a reference population of cognitively normal subjects (Visser et al.,
2000). Impairment on the fluency, TMT A, and TMT B was defined as a z-score below -1.28
(corresponding with a score below the 10th percentile). The sign of the z-scores of the TMT A
and B was inverted such that a negative z-score indicated below average performance. Median
time between LP and neuropsychological evaluation was 1.5 months (range 0-10).
PAS scoring
The PAS consists of six markers of AD: age, MMSE score, functional impairment, cognitive test
performance, MTA score and Apo E genotype. Increasing PAS scores indicate a higher risk for
AD. The PAS item ‘functional impairment’ was scored with the Global Deterioration Scale
(GDS) (Reisberg et al., 1982). The PAS item ‘cognitive test performance’ was obtained with the
VAT, fluency, and TMT B measures using the cut-off scores described above. Medial temporal
lobe (MTL) atrophy was rated using the MTA scale as described above. Complete PAS scores
were available for 26 subjects. The PAS and scoring instructions can also be found at wwwnp.unimaas.nl/scales/pas/.29
Statistical analysis
For statistical analysis, SPSS version 11.0 was used. On the basis of abovementioned cut off
values for CSF Aβ42 and tau, MCI patients were divided into three groups at different risk for
AD: a high-risk biomarker profile (low CSF Aβ42 and high CSF tau), an intermediate risk
biomarker profile (low CSF Aβ42 and normal CSF tau or normal CSF Aβ42 and high CSF tau),
and a low-risk biomarker profile (normal CSF Aβ42 and CSF tau). Mann Whitney U test
(continuous variables) or Chi-square test with continuity correction (dichotomous variables) was
used to test group differences. Correlations between the biomarkers CSF Aβ42 and tau versus
gender, age, disease duration, MMSE, VAT, TMT A, TMT B, Fluency, MTA and PAS were
calculated using the Spearman correlation coefficient. Statistical significance was set at p < 0.05.
105
Results
Twenty-one (54%) of the 39 MCI subjects had a high-risk biomarker profile, 10 subjects (26%)
had an intermediate risk biomarker profile (low Aβ42 (n=4) or high tau (n=6)), and 8 (20%) had
a low-risk biomarker profile (Table 1, Figure 1). Median values of Aβ42 and tau in the high-risk
biomarker group were comparable with the values from AD patients (data not shown). Compared
to subjects with a low-risk biomarker profile, patients with a high-risk biomarker profile had
more impaired TMT A and higher PAS scores (Table 1). Furthermore, they tended to have more
impaired VAT and higher MTA scores. The intermediate biomarker profile group had higher
PAS scores and lower MMSE and more impaired VAT scores, and a tendency towards higher tau
levels and more impaired TMT A scores compared to the low-risk biomarker profile group
(Table 1). No differences in neuropsychological and imaging markers existed between the highrisk and the intermediate risk biomarker profile group (Table 1). Furthermore, there were no
differences in age, sex, disease duration, MMSE, and Apo E genotype between the three groups.
In the whole MCI sample, Aβ42 levels correlated with tau levels, with MTA score, and with the
PAS score. Tau levels correlated with the score on the VAT (Table 2). There were no correlations
between the levels of Aβ42 and tau with disease duration or MMSE. Furthermore, there was no
correlation between VAT and MTA score (R = -0.19, P=0.33).
Discussion
About half of the MCI patients included in this cross-sectional study had a high risk of
developing AD according to their biomarker profile at baseline. Twenty-six percent had either a
low CSF Aβ42 and normal CSF tau level or a normal CSF Aβ42 and a high CSF tau level, while
20% had both normal CSF Aβ42 and tau levels. Subjects with a high-risk biomarker profile did
not differ from subjects with an intermediate risk biomarker profile with respect to other markers
of AD, while both high-risk and intermediate risk subjects differed significantly from the lowrisk group in neuropsychological markers and PAS scores.
106
Table 1 Patient characteristics and clinical variables
High risk
(N=21)
(Group 1)
Intermediate risk
(N=10)
(Group 2)
Low Risk
(N=8)
(Group 3)
P-value
Group 1 vs
Group 2
P-value
Group 1 vs
Group 3
P-value
Group 2 vs
Group 3
Age
70 (53-81)
69 (58-80)
75 (56-78)
0.61
0.49
0.42
Sex (F/M)
11/10
6/4
2/6
0.99
0.31
0.31
Duration of
cognitive
complaints
(yrs)
3 (0-11)
3 (1-10)
2 (1-6)
0.64
0.37
0.22
MMSE
26 (23-30)
26 (24-28)
28 (23-29)
0.17
0.32
0.04
Aβ42
(pg/mL)
395 (142-479)
527 (241-1223)
767 (504-916)
0.03
<0.001
0.37
Tau
(pg/mL)
707 (379-1108) 410 (260-1545)
262 (145-355)
0.006
<0.001
0.07
78
40
43
0.11
0.23
0.99
MTA R+L
MTA score
abnormal (%)
3.5 (2-5)
61
3 (0-6)
56
2 (0-4)
29
0.48
0.99
0.09
0.31
0.42
0.57
VAT
< 5 (%)
2.5 (0-6)
82
1 (0-4)
100*
5 (1-6)
38
0.17
0.06
0.08
0.01
0.04
Fluency
z < -1.28 (%)
15 (11-33)
42
18 (11-23)
22
17 (10-24)
25
0.68
0.55
0.87
0.61
0.69
0.99
TMT A
z < -1.28 (%)
52 (34-97)
39
64 (34-82)
50
37 (27-55)
14
0.86
0.99
0.04
0.43
0.08
0.43
TMT B
z < -1.28 (%)
156 (70-486)
88
150 (75-300)
67
108 (65-249)
57
0.66
0.57
0.14
0.28
0.32
0.99
PAS
8.1 (3-11)
8.2 (7-11)
5.8 (4-7)
0.74
0.02
0.02
≥ 1 ε4 allele
(%)
MTA R+L = medial temporal lobe atrophy right and left, VAT = visual association test, TMT A = trail making test A, TMT B = trail making test
B, PAS = Preclinical Alzheimer’s disease Scale. Groups 1, 2 and 3 are defined on the basis of the optimal cut off values for Aβ42 and tau
comparing AD vs controls. Group 1: Aβ42 ≤ 494 and tau > 356; Group 2: Aβ42 ≤ 494 or tau > 356; Group 3: Aβ42>494 and tau ≤ 356. Disease
duration is defined as the time in years between the first symptoms (by history) and the lumbar puncture. Values are expressed as medians
(minimum-maximum) or percentages when dichotomised. MTA score was abnormal when at least one hippocampus had a score of ≥ 2. *: VAT
was available in only 7 out of 10 patients, all with a value of < 5. Impairment on the fluency, TMT A, and TMT B was defined as a z-score below
-1.28.
107
Furthermore, low CSF Aβ42 levels were associated with high MTA and high PAS scores, while
high CSF tau levels were associated with low memory scores.
The high percentage of subjects with a high-risk biomarker profile is consistent with the high
conversion percentage to AD in subjects with amnestic MCI.12,17 The increased risk for AD in
this group is further corroborated by the high frequency of other markers of AD such as the
ApoE-ε4 allele, memory impairment, and MTL atrophy. The findings in the group of patients
with an intermediate risk biomarker profile are intriguing. Since there were no differences in
clinical characteristics between the high-risk versus the intermediate risk group it seems likely
that these subjects also have an increased risk for AD, even though one of the biomarkers was
still in the normal range. Which biomarker is changed first in the disease process is not clear yet,
as contradictory findings were reported by various studies describing either an increased CSF
tau6,14,32 or decreased CSF Aβ4223 at baseline.
Another possible explanation for the intermediate risk could be that some of the patients will
develop another type of dementia, for example frontotemporal lobar degeneration, in which a
high CSF tau or a low CSF Aβ42 can be found. 21 Adding phosphorylated tau to the panel of
biomarkers might help in differentiating MCI patients at risk for AD or other types of dementia. 5
About 20% of the patients had a low-risk biomarker profile. These subjects also had less often
other AD markers compared to patients with a high or intermediate-risk biomarker profile. This
underlines the fact that these subjects indeed might have a low risk for the development of future
AD. Furthermore, the percentage of 20% fits well with the results of a long-term study showing
that about 20% of the MCI subjects do not progress to AD21, but clearly, longitudinal studies are
necessary to determine whether these subjects will remain non-demented. The PAS score was the
variable that was found to differentiate best between high/intermediate and low-risk biomarker
profile groups. Since MCI is a heterogeneous disorder it is not surprising that the PAS, which
combines a number of tests, differentiates better between MCI subjects at different risk for AD
according to their biomarker profile than a single test.
108
Figure 1 Plot Aβ42 and tau
1400
1200
1000
Amyloid B 1-42 (pg/mL)
800
600
400
200
0
0
200
400
600
800
1000
1200 1400
1600
Tau (pg/mL)
The dotted lines represent optimal cut off values obtained by comparing AD patients (N=92) with controls (N=38)
(cut off value for Aβ42 ≤ 494 pg/mL; cut off value for tau > 356 pg/mL). Squares indicate MCI patients.
Table 2 Correlations between biomarkers, VAT, MTA and PAS score
Aβ42
Tau
VAT
0.26
-0.44**
PAS
-0.43*
0.28
MTA
-0.39*
-0.03
Tau
-0.34*
--
MTA = atrophy score of medial temporal lobe; VAT = visual association test; PAS = Preclinical Alzheimer’s disease
Scale. *P < 0.05, **P < 0.01.
109
The increase of CSF tau is supposed to be the result of release from dying neurons containing a
large number of neurofibrillary tangles (NFT), an important hallmark of AD. Our finding of a
correlation between CSF tau and episodic memory impairment, as measured by the VAT, is
consistent with clinicopathological studies 8,10 , in which a strong correlation between memory
impairment with NFT densities and neuron numbers in the entorhinal cortex and hippocampus
was found. As CSF tau is associated with neuronal loss one would also expect an association
with the MTA score, but we did not find such a correlation. This finding is consistent with
another study showing no association between CSF tau levels and global brain atrophy at
baseline.31 It is possible that the increase of CSF tau in our MCI population could be the result of
neuronal loss in the entorhinal cortex or hippocampus at the very early stage of the disease, which
may precede MTL atrophy as rated visually on MRI. A future study comparing CSF tau with the
size of the hippocampus or entorhinal cortex as measured by volumetry could provide additional
information about the cross-sectional relation between CSF tau and imaging markers of AD. It is
also possible that tau is more a ‘state marker’, reflecting the intensity of the neuronal damage and
degeneration .4 Evidence for this explanation comes from a recent study showing an association
between higher CSF tau levels at baseline and more rapid progression of atrophy after 1-year
follow-up. 31
Aβ42 is thought to be decreased in CSF as a result of deposition in senile plaques. In various
studies, only a weak or no correlation between amyloid burden in the brain and cognitive status
was found. 3,8 The absence of an association between decreased CSF Aβ42 and
neuropsychological measurements in the present study is in line with this. The observation that
lower CSF Aβ42 levels were associated with more atrophy in the medial temporal lobe is
consistent with two other studies22,31, showing a correlation between decreased CSF Aβ42 and
atrophy of the whole brain, ventricles or temporal lobe in patients with MCI and AD. CSF Aβ42
may thus be considered as a ‘stage marker 4,31, indicating the presence and severity of the disease
at a certain stage and reflecting the total brain damage that has occurred since the onset of the
disease. The correlation between CSF Aβ42 and the PAS score at baseline in MCI could be a
reflection of both markers being independent predictors of AD, which was confirmed for Aβ42 in
a recent study. 11
110
A limitation of our study was the small cohort we included with the risk of selection bias and
insufficient power to draw firm conclusions. Between January 2001 and November 2003 we
collected CSF from approximately one third of all amnestic MCI patients seen at the Alzheimer
Center, VUMC. The patients who underwent a LP were significantly younger compared to the
patients without a LP, which can be explained by the inclusion criteria since we included only
patients younger than 85 years. Cognition as measured by the MMSE was similar between the
two groups. In addition, the degree of memory impairment and hippocampal atrophy, as well as
the presence of ≥ 1 ε4 allele comparing the high-risk to the low-risk biomarker profile group
correspond very well with those found in a recent population study when comparing MCI
patients with controls and AD patients. 9 This makes us confident that no selection bias has
occurred and that our cohort is representative of a ‘normal’ MCI group.
The relative high percentage of one or more ε4 alleles in the three groups –even in the low-risk
group- may be explained by the fact that all MCI patients could have an increased risk of AD, as
was supported by the study of Smith et al.24, who also found a prevalence of 40% of the ε4 allele
in their MCI cohort. Both Apo E genotype and memory impairment are indicator markers for AD
in MCI.
Our study underscores the recognition that MCI is a heterogeneous group of patients containing
various biomarker profiles. MCI patients with a high- and intermediate-risk biomarker profile for
AD also differed in other indicator markers from patients with a low-risk biomarker profile,
adding to the biological validity of these markers. In addition, the relation between the
biomarkers and other AD markers suggests that the markers are not independent at baseline.
Longitudinal studies are necessary to interpret the correlations between biomarkers, imaging, and
neuropsychological markers as well as their contribution to the diagnosis or as predictor of the
severity of developing AD in the pre-dementia stage.
111
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115
CHAPTER 7
CEREBROSPINAL FLUID AND MAGNETIC RESONANCE IMAGING MARKERS
INDEPENDENTLY CONTRIBUTE TO THE DIAGNOSIS ALZHEIMER’S DISEASE
Niki SM Schoonenboom, Wiesje M van der Flier , Marinus A Blankenstein , Femke H
Bouwman, Gerard J Van Kamp, Frederik Barkhof, Philip Scheltens
Neurobiol Aging, 2006, in press.
116
Abstract
Background: Decreased amyloid β (1-42) (Aβ42) and increased (phosphorylated) tau in
cerebrospinal fluid (CSF) are considered to be a reflection of plaques, tangles, and neuronal
degeneration in Alzheimer’s disease (AD). Atrophy of the medial temporal lobe (MTA) on
magnetic resonance imaging (MRI) reflects neuronal loss in this area.
Objective: To compare diagnostic accuracy of CSF biomarkers and MTA in AD versus controls.
Methods: Aβ42, tau and tau phosphorylated at threonine 181 (Ptau-181) were measured in CSF
from 61 AD patients and 32 controls by sandwich enzyme-linked immunosorbent assay. A CSF
biomarker profile for AD was constructed. MTA was rated visually on MRI.
Results: When AD patients and controls were evaluated separately, no correlations were present
between the CSF markers and MTA score. Both MTA and CSF biomarker profile were
independently associated with the diagnosis AD (MTA: OR (95% CI) = 28 (3 – 239); CSF
biomarker profile: OR (95% CI) = 57 (13 – 262)). Among individuals younger than 65 years old
and without MTA 60% suffered AD, and the finding of an abnormal CSF biomarker profile was
limited to AD patients only.
Conclusions: MTA and CSF biomarkers seem to be of incremental value for the diagnosis AD.
CSF analysis is most sensitive in the absence of MTA, and especially among early-onset AD
patients.
117
Introduction
Decreased cerebrospinal fluid (CSF) amyloid β (1-42) (Aβ42) in Alzheimer’s disease (AD) is
associated with intracerebral deposition of neuritic plaques, mainly composed of Aβ42 [2,31].
Increased CSF tau protein (tau) is considered to be a reflection of neuronal degeneration, caused
by intraneuronal accumulation of neurofibrillary tangles containing (phosphorylated) tau. 2,6,7
Especially CSF phosphorylated tau (Ptau) is increased in AD compared to other types of
dementia. 2,27 Although the combination of CSF Aβ42, tau and Ptau provides reasonable accuracy
in the differentiation of AD from controls CSF concentrations of these biomarkers do overlap
between groups. 16,27
Atrophy of the medial temporal lobe (MTA) on magnetic resonance imaging (MRI) has been
found to be an early and sensitive marker for AD37 and is assumed to reflect underlying neuronal
loss of the hippocampus and the temporal lobe. However, MTA may also be present in other
types of dementia and absence of MTA does not exclude the diagnosis AD, especially in the early
stages. 37 The latter particularly applies to early-onset AD (EAD), where MTA is often not
prominently present. 13,20
Relatively little is known about the association between MTA and CSF markers, while both are
presumed to reflect Alzheimer pathology. From post mortem work it is known that hippocampal
volume is a good indicator of the amount of plaques and tangles deposition 8,14,30, which led us to
suspect an association with CSF Aβ42 and (P)tau. An association between MTA and (P)tau
would provide further evidence for the notion that both are measures of neuronal degradation or
neuronal loss. 3,9,18 In addition, while MTA has become a widely used marker in AD diagnosis,
CSF markers still have to be established as such. The aim of this study was twofold: first, to
study the association between CSF markers and MTA, to provide insight whether both types of
markers reflect the same neuropathological substrate. The second aim was to investigate whether
both disease markers are independent predictors for the diagnosis AD. Therefore, we studied the
relations between CSF Aβ42, tau, and Ptau with MTA in AD and controls. Furthermore,
diagnostic accuracy of MTA and the combination of CSF Aβ42, tau and Ptau was compared in
AD versus controls.
118
Methods
Participants
Sixty-one AD patients and 32 controls younger than 85 years old were recruited consecutively at
the memory clinic of the Alzheimer Center VU University Medical Center, Amsterdam. All
patients underwent a standardized diagnostic work-up, including medical history, informant
interview, physical and neurological examination, screening laboratory tests, EEG, and Magnetic
Resonance Imaging (MRI). The majority of patients underwent neuropsychological testing.
Diagnoses were made in conference by a team of neurologists, neuropsychologists, a
neurophysiologist, a psychiatrist and a radiologist. Diagnosis of probable AD was made
according to the NINCDS-ADRDA criteria. 23 Although brain MRI contributed to the diagnostic
process, it should be noted that MTA scores were not used. All clinicians participating in the
diagnostic conference meeting were blinded to CSF results. Clinical diagnoses were revisited and
confirmed after a minimum follow up period of 1 year and used in the analysis as gold standard.
Disease duration was defined as the time in years since the first symptoms by history. The MiniMental State Examination (MMSE) was used as a measure of global cognitive function. 11 In
addition, memory function was assessed using the visual association test. 22
The control group of 32 subjects included 25 subjects with subjective memory complaints and
three subjects with a positive family history for AD. These subjects presented at our memory
clinic and underwent exactly the same diagnostic work-up as the AD patients. Patients were
considered to have subjective memory complaints if all clinical investigations were normal.
Additionally, four healthy spouses of patients without memory complaints were included. None
of the controls had developed dementia after a follow up period of 1 year. The study was
approved by the ethical review board of the VUMC. All subjects gave written informed consent
to participate in the study.
Apo E genotype
DNA was isolated from 10 ml EDTA blood and was available from 57 AD patients, and 31
controls. Apolipoprotein E (Apo E) genotype was determined with the light cycler Apo E
mutation detection method (Roche diagnostics GmbH, Mannheim, Germany). Patients were
divided into two groups according to the absence or presence of ≥ 1 ApoE ε4 alleles.
119
CSF analysis
CSF was obtained by lumbar puncture (LP) between the L3/L4 or L4/L5 inter-vertebral space,
and collected in 12 mL polypropylene tubes. After centrifugation at 3000 rpm for 10 minutes at
4°C, CSF was aliquoted in polypropylene tubes of 0.5 or 1 mL, and stored at -80°C until analysis.
CSF Aβ42, tau and tau phosphorylated at threonine-181 (Ptau-181) were measured by
commercially available sandwich ELISAs (INNOTESTTM β-amyloid [1-42], INNOTESTTM,
hTAU-Ag and INNOTESTTM Phosphotau (181P)). 33-35 The optimal cut off values for CSF Aβ42
were set at data obtained in earlier studies, in which we applied a sensitivity of ≥ 85% for each
individual biomarker in accordance with the Ronald and Nancy Reagan Consensus report after
drawing Receiver Operating Characteristics curves. 7,27,28 The following cut off values were used:
CSF Aβ42 < 495 pg/mL, CSF tau > 356 pg/mL and Ptau-181 > 54 pg/mL. 27,28 Based on the three
markers, a CSF biomarker profile was constructed. The CSF profile was defined as abnormal
when in addition to abnormal CSF Aβ42, also tau and/or Ptau were abnormal. The CSF
biomarker profile was normal when CSF Aβ42, CSF tau and Ptau-181 were all in the normal
range.
MRI analysis
MRI scans were made on a 1.0 (N = 44 AD and 26 controls) or 1.5 (N = 17 AD and 6 controls)
Tesla scanner (Siemens), and included a coronal T1-weighted 3D inversion-prepared gradient
echo-sequence (168 slices, FOV 250mm, matrix 256x256; slice thickness 1.5 mm, in-plane
resolution 1 mm). Mean (SD) time between LP and MRI scan was 2 (2.8) months in both AD and
controls. The MTA score was rated visually according to the method described earlier. 37 The
MTA score is based on a visual estimation of the volume of the medial temporal lobe, including
the hippocampus proper, dentate gyrus, subiculum, and parahippocampal gyrus, and the volume
of the surrounding CSF spaces, in particular the temporal horn of the lateral ventricle and the
choroid fissure, on both sides. The MTA score ranges from 0 (no atrophy) to 4 (severe atrophy).
MTA scores of the left and right hippocampus were averaged. 21 MTA scores were dichotomized,
and an average MTA ≥ 1.5 was considered abnormal (requiring a score of 2 at least on one side).
One rater (FB), who was blinded to the clinical information, performed the MTA ratings, with
good intra-rater agreement for the MTA score. 36
120
Statistical analysis
SPSS version 11.0 was used. Mann Whitney U test was used to compare medians of clinical,
CSF and MRI variables between AD and controls. Chi-square test was used to compare
frequencies between groups. To determine associations between CSF biomarkers and MTA
Spearman correlation coefficient was used. To estimate the impact of the different variables on
diagnosis, logistic regression analysis was used, with diagnosis as dependent factor, CSF
biomarker profile and MTA as independent factors, and age and gender as covariates. Apo E
genotype was additionally corrected for in a separate model. Odds ratios (OR) with
accompanying 95% confidence intervals (CI) are presented. Statistical significance was set at p <
0.05.
Results
AD patients and controls were well matched for age and gender (Table 1). There were no
differences between groups in the prevalence of history of hypertension, diabetes mellitus, or
myocardial infarction (p > 0.10). Median disease duration in AD was 4 years (range 0.5-11
years), median MMSE was 20 (9-28) in AD and 29 (25-30) in controls (p<0.001). CSF Aβ42
levels were decreased and CSF tau and Ptau-181 levels were increased in AD patients compared
to controls. MTA score was significantly higher in AD patients compared to controls. The
prevalence of Apo E ε4 was higher among patients with AD than among controls. In 37 AD
patients, disease started before the age of 65 years (= early onset AD, EAD).
Table 2 shows characteristics of patients with early onset compared to patients with late onset
AD. Patients with EAD had comparable disease severity as measured using the MMSE. In
addition Apo E ε4 prevalence and level of CSF biomarkers were comparable among groups.
Patients with late onset AD had more MTA than patients with EAD.
121
Table 1 Subject characteristics and CSF and MRI analyses
AD (N=61)
Controls (N=32)
P-value
Age (years)
66 (53-82)
64 (45-83)
0.43
Gender (M/F)
28/33
16/16
0.71
≥ 1 Apo E ε4 (%)
44 (77%)
15 (48%)
0.006
CSF Aβ42 pg/mL
324 (124-590)
648 (232-1450)
<0.001
CSF tau (pg/mL)
632 (75-2615)
256 (100-993)
<0.001
CSF Ptau-181 (pg/mL)
78 (18-279)
48 (18-123)
<0.001
≥ 1 Apo E ε4 (%)
44 (77%)
15 (48%)
0.006
MTA score
1 (0-3.5)
0 (0-3)
<0.001
Values are expressed as medians (range).
M = male, F = female; CSF = cerebrospinal fluid; Aβ42 = amyloid β (1-42); Ptau-181 = tau phosphorylated at
threonine 181; MTA = medial temporal lobe atrophy.
In the whole group, there was a significant correlation between CSF Aβ42 and tau with MTA
(CSF Aβ42 and MTA: r = - 0.34, p = 0.001; CSF tau and MTA, r = 0.25, p = 0.02). CSF Ptau181 did not correlate with MTA (r = 0.13, p = 0.21). When AD patients and controls were
evaluated separately, no correlations were present between the CSF markers and MTA score
(Figure 1). In AD, CSF Aβ42 was low in most patients, while there was variability in MTA
score. CSF tau and Ptau-181 levels showed a large variation in AD patients. To assess whether
MTA and CSF markers contributed independently to the diagnosis of AD, logistic regression
analysis was performed. MTA as well as the CSF biomarker profile contributed to diagnosis
122
Table 2 Characteristics of AD patients according to age-at-onset
Early onset (N=37)
Late onset (N=24)
P-value
Age (years)
59 (53-68)
74 (69-82)
Gender (M/F)
17/20
11/13
0.99
MMSE
20 (9-28)
19.5 (10-28)
0.37
Visual association testa
3 (0 – 12)
3 (0 – 10)
0.77
≥ 1 Apo E ε4 (%)
74%
83%
0.42
CSF Aβ42 pg/mL
307 (124-525)
342 (197-590)
0.36
CSF tau (pg/mL)
697 (75-2615)
533 (304-2605)
0.64
CSF Ptau-181 (pg/mL)
79 (18-279)
78 (46-254)
0.57
MTA
1 (0-2.5)
1.5 (0-3.5)
0.01
Values are expressed as medians (range).
M = male, F = female; MMSE = mini-mental state examination, CSF = cerebrospinal fluid; Aβ42 = amyloid β (142); Ptau-181 = tau phosphorylated at threonine 181; MTA = medial temporal lobe atrophy.
a
available for 20
patients with early onset and 17 with late onset AD.
when entered separately in models with age and gender as covariates (MTA: OR (95% CI) = 14
(3 – 69); CSF biomarker profile: OR (95% CI) = 40 (11 – 143)). When both MTA and CSF
biomarker profile were added in a model with age and gender, each disease marker contributed
independently to AD diagnosis, with even higher odds ratios (MTA: OR (95% CI) = 28 (3 –
239); CSF biomarker profile: OR (95% CI) = 57 (13 – 262)). Additional correction for Apo E ε4
status only marginally affected the results (MTA: OR (95% CI) = 23 (3 – 193); CSF biomarker
profile: OR (95% CI) = 46 (10 – 217)).
123
Table 3 MTA and CSF biomarker profile in AD and controls according to age
≥65
<65
AD
MTA absent
MTA present
AD
controls
16 (100%)
1
(4%)
11 (69%)
Normal CSF profile
2
Abnormal CSF profile
22 (60%)
0
8 (33%)
3 (19%)
Normal CSF profile
2
(5%)
0
4 (17%)
1
(6%)
Abnormal CSF profile
11 (30%)
0
11 (46%)
1
(6%)
37 (100%)
16 (100%)
24 (100%)
16 (100%)
Total
(5%)
controls
MTA = medial temporal lobe atrophy, CSF = cerebrospinal fluid. MTA absent = MTA score 0 or 1; MTA present =
MTA score ≥ 2; normal CSF profile = Aβ42 > 494 pg/mL and tau < 357 pg/mL and Ptau-181 < 55 pg/mL; abnormal
CSF profile = Aβ42 < 495 pg/mL and either tau > 356 pg/mL or Ptau-181 > 54 pg/mL.
When the analysis was restricted to controls and patients with mild AD only (MMSE ≥20, n=65),
the contribution of MTA became less strong (OR (95% CI) = 10 (0.9 – 124)), while the CSF
biomarker profile remained a significant predictor (OR (95% CI) = 37 (8 – 178)).
Visual inspection of younger and older patients separately (table 3), revealed that the majority of
AD patients with early onset had no appreciable atrophy of the medial temporal lobe (65%;
24/37). Among individuals younger than 65 and without MTA, 60% (24/40) suffered AD (a
priori). The finding of an abnormal CSF biomarker profile was limited to AD patients only, and
therefore raised the a posteriori chance to 100%. Alternatively, among those younger than 65, all
individuals with MTA were patients with AD, and therefore there was no added value of CSF
analysis in the presence of MTA.
124
Figure 1
1600
1400
1200
1000
800
Abeta42 (pg/mL)
600
400
Group
200
AD
0
Controls
-1
0
1
2
3
4
Average MTA
3000
2000
Tau (pg/mL)
1000
Group
AD
0
Controls
-1
0
1
2
3
4
Average MTA
300
Ptau181 (pg/mL)
200
100
Group
AD
0
Controls
-1
0
1
2
3
4
Average MTA
Scatterplots of medial temporal atrophy (MTA) by (a) amyloid β (1-42) (Abeta42), (b) tau and (c) tau phosphorylated tau at threonine 181 (ptau
181), respectively. Patients with AD are depicted by empty squares, and controls by filled diamonds. Within diagnostic groups, Spearman’s
correlations are not significant.
125
For individuals over 65 years of age, and without atrophy of the medial temporal lobe, the a priori
chance to be an AD patient in our study was 39% (9/23). The additional finding of abnormal CSF
biomarker profile raised this to an a posteriori chance of 73% (8/11). If MTA was present, an
individual was likely to suffer AD (88%; 15/17). Additional finding of abnormal CSF raised this
to an a posteriori chance of 92% (11/12).
Discussion
In the present study, we could not demonstrate cross-sectional relations between CSF Aβ42, tau
and Ptau-181 with MTA in AD or controls. Both MTA and the combination of CSF Aβ42, tau
and Ptau-181 contributed independently to the diagnosis AD. Our data suggest that CSF analysis
is most sensitive in the absence of MTA, and especially among younger patients.
Only a few studies investigated the cross-sectional relation between CSF biomarkers and atrophy
on MRI in small groups of patients 4,9,10,15,26,29,38, with conflicting results: some observed no
relation between CSF tau and cerebral atrophy 26,38, while others found a significant inverse
relationship between CSF Ptau and hippocampal volume in subjects with mild cognitive
impairment 9,10, or, on the other hand, CSF tau levels corresponding to higher baseline
hippocampal volume in AD. 15 Two studies showed lower CSF Aβ42 levels corresponding to
lower brain volume 38 or volume of the temporal lobes. 29 The discrepancies between the different
studies could be attributed to the selection of different patient groups as well as to the use of
diverse methods to measure brain and hippocampal atrophy. The strength of our study is that we
included a larger group of subjects than in former studies, in which we were able to compare all
three biomarkers with MTA in subjects with AD and controls.
Our observation of higher CSF tau and Ptau concentrations in AD patients with relatively little
MTA is in line with higher CSF tau and Ptau levels in patients with larger baseline hippocampal
volumes mentioned in an earlier study. 15 Neuropathological studies have shown that
neurofibrillary tangles precede entorhinal cortex (EC) and hippocampal neuronal loss. 24 The
increase of CSF Ptau and tau might reflect the intensity of neuronal loss induced by the
neuropathological changes 38, which precedes volume loss as visualized on MRI.
126
Our finding of a relation between CSF Aβ42 and MTA in the whole group corresponds to the
results presented elsewhere 28,38, where the relation of CSF Aβ42 with cerebral atrophy in
patients with a wide variation of cognitive impairment is attributed to CSF Aβ42 as stage marker
of disease. 28,38
Both MTA and CSF biomarkers independently contributed to the diagnosis of AD. With the
abovementioned absence of direct cross-sectional correlations between the two disease markers
one could consider that imaging- and CSF biomarkers reflect different stages of disease and/or
another neuropathological substrate at one point in time. This might in part be due to the stable
character of CSF biomarkers; CSF Aβ42, tau and Ptau levels demonstrate little change over time.
1,9,19,32
By contrast, MTA progresses with disease advancement, and the rate of atrophy is
considered a valuable marker for disease progression. 25 Our data suggest that especially in the
early stage of the disease, when cognitive scores are still high and when MTA is not yet
prominently present, the value of CSF analysis is evident. CSF analysis may prove especially
valuable in patients with EAD, which relatively often do not show MTA on MRI. 12,13,20
One of the limitations of the present study is the cross-sectional design, in which the value of two
different diagnostic methods was compared in subjects with the clinical diagnosis as gold
standard. Furthermore, we cannot exclude an overestimation of the value of CSF biomarkers over
the MTA score; the majority of the AD patients had an abnormal biomarker profile, while only
half of the patients had considerable MTA. This might be due to the relatively higher proportion
of subjects aged below 65 years old in this study, in which a LP is almost standard routine in our
memory clinic. Alternatively, it is conceivable that MTA is not the most powerful measure in this
group of patients. Other MRI-measures, such as whole brain volume or ventricle size should be
evaluated in further studies.
Among the strenghts of the study is the fact that only subjects with a follow-up period of at least
one year were included, while a standardized diagnostic work up was used for every subject. In
addition, MTA scores were assessed blinded for diagnosis. Although on visual inspection, our
data suggest a difference in MTA score but not in CSF markers between AD patients with early
and late onset disease -the latter is not congruent with a recent study 17- further study with larger
sample sizes is needed to properly assess these differences.
127
In conclusion, both CSF biomarkers and MTA seem to be of incremental value for the diagnosis
AD. By applying both disease markers together, diagnostic accuracy could be increased. CSF
biomarkers seem to be most promising in patients without appreciable MTA, which is common in
early onset AD patients.
128
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133
CHAPTER 8
GENERAL DISCUSSION
134
135
The area of research on biochemical markers in AD is very broad and refers to the fundamental
principles of the pathophysiology of AD as well as to the clinical utility. With this thesis we tried
to provide some tools for how to use the three CSF markers Aβ42, tau and Ptau within the
clinical context of a memory clinic of a secondary referral center. Before I come to the
conclusion and future perspectives of this thesis, I will comment on the studies described in
chapters 3-7.
8.1 Comments on chapters 3-7
Chapter 3.2 Effects of processing and storage conditions on CSF amyloid β (1-42) and tau
concentrations in cerebrospinal fluid: implications for use in clinical practice
According to the study described in chapter 3.2 CSF Aβ42 and tau are stable in samples stored
for several years at -80°C. The stability has been determined, however, by a protocol based on
the Arrhenius equation. The validity of this method for the peptides CSF Aβ42 and tau should be
confirmed in a real-time stability experiment. Furthermore, Ptau needs to be added to this panel
of biomarkers. A very recent study confirmed our data29, and showed that CSF Ptau was the most
stable marker of all three CSF markers. Since the end of 2000 we have collected CSF samples,
but for follow up studies longer time intervals are needed with large collections of CSF pools.
Another important issue is that the variability of CSF Aβ42 among centers might well be
attributable to the procedure of sample treatment in the first hours after collection. This issue has
not been investigated in our study and needs to be considered and studied in multi-center studies.
An international validity study has been started recently.30
The last point we would like to discuss here is the influence of internal factors -recovery rate and
linearity- on the quantitative test results of the INNOTESTTM β-amyloid (1-42) ELISA (see also
the Appendix for results from our laboratory). These findings, which might not be solely
attributed to this particular ELISA, give concern about the robustness of the Aβ42 assay.
Possibly, the same mechanisms might be involved as during repeated freeze/thaw cycles or when
samples are stored at temperatures > -80°C, i.e. conformational changes in the fibrillary β-
sheeted Aβ peptide or masking of the epitope by binding to another protein.23 Therefore, we also
wonder what is exactly measured in the INNOTESTTM β-amyloid (1-42) ELISA; full length
136
peptide Aβ42 only or the full length peptide in combination with an Aβ peptide, bound to a
combination of other proteins, like -Apo J, Apo E, α1-antichymotrypsin and/or albumin?31,32 In
the studies by Wiltfang et al.23,32 freezing prior to analysis influences the concentration of CSF
Aβ42 as measured by SDS-PAGE/immunoblot, while a higher CSF Aß42 concentration is
measured by this technique compared to ELISA. This might be attributed to carrier mediated
epitope masking, as SDS-heat denaturation may strip the Aβ42 peptide from the binding epitope
as detected in the Aß42 ELISA. Knowledge about whether we detect free or bound Aβ peptide is
very important applying CSF Aβ42 as marker of progression in longitudinal studies, especially
when measuring the effect of anti-amyloid drugs. Furthermore, it needs to be taken into account
in the differentiation of AD from other types of dementia, i.e. FTD and CJD, in which also
decreased CSF Aβ42 concentrations are found.36
Nonetheless, the Aβ42 peptide concentration has been shown to be decreased in CSF from the
majority of AD patients when measured by different laboratory techniques21, which makes the
use of CSF Aβ42 as diagnostic marker for AD very promising.
Chapters 4.1 and 4.2 Differences and similarities between two frequently used assays for
Amyloid β 42 in cerebrospinal fluid and Amyloid β 38, 40, and 42 species in cerebrospinal fluid:
more of the same?
The main findings of the two studies are that absolute concentrations of CSF Aβ42 as measured
by two distinct ELISAs are comparable and that CSF Aβ42 is selectively decreased in CSF as
compared to the other two most prominent CSF Aβ peptides, Aβ38 and 40. These results are
encouraging for the implementation of CSF Aβ42 as diagnostic marker for AD in clinical
practice, and seem to be irrespective of the ELISA used. Taking a closer look at the data, several
issues need attention. The first issue is the binding characteristic of the antigen which may vary
with temperature, buffer solutions and even among lots. Second issue is the variability of the
affinity of the antibodies for the various CSF Aβ peptides involved in the pathogenesis of AD.
With this study we did not exchange calibrators and antibodies used in the two assays, i.e. 6E10
and 3D6 (see also chapters 3.1 and 4.1) as well as the different C-terminally directed antibodies.
Innogenetics did study this issue to some extent33, and roughly the same results were found by a
multiparameter xMapTM technology-based assay: CSF Aβ42 is decreased in AD as measured by
137
different N-terminally directed antibodies (6E10, 3D6 and 4G8), although diagnostic accuracy
varied to some extent. The SELDI-TOF data reported by Innogenetics33 and SDSPAGE/Immunoblot data by Wiltfang23 give a more refined impression of the different types of
Aβ42 present in CSF, which may not only be promising for use in the early (MCI) stage of
disease, but also for differentiation between different types of dementia, especially between AD
and FTD. The tendency towards a difference in concentration between CSF Aβ 1-42 and Aβ N42 in FTD (chapter 4.1) is remarkable, and needs further investigation. By several research
groups a putative role for beta amyloid metabolism disturbances in the pathogenesis of some
types of FTD is found34,35.
The decrease of Aβ42 in CSF compared to the other C-terminally truncated Aβ peptides, Aβ38
and 40, might be due to deposition of insoluble Aβ42 in the plaques has been stated in chapter
4.2. However, this is by far not clear yet. Another explanation might be that CSF Aβ42 is to a
higher extent bound to another protein than CSF Aβ38 and 40 as has been shown before32.
Evidence for this hypothesis is the decrease of CSF Aβ42 in Creutzfeldt-Jakob patients36 in
which no classic β-amyloid (neuritic) plaques are found in the brain 37 Here, a comparable (the
same?) pathological chaperone might be involved as well.
Chapter 5.1 Amyloid β 42 (1-42) and phosphorylated tau in CSF as markers for early onset
Alzheimer’s disease
The combination of low CSF Aβ42 and high Ptau-181 yields the highest diagnostic accuracy in a
cohort of EAD patients compared to FTD patients. This especially accounts for the specificity
and for the negative likelihood ratio with two markers negative compared to one positive. These
findings are most essential for clinical practice; a diagnostic marker is useful when it has a low
false positive rate and when it can with great certainty rule out the presence of a disease. The
sensitivity of the combination of CSF Aβ42 and tau did not achieve ≥ 85% in AD, which is
needed for an ideal biomarker in accordance to the Reagan Consensus Report (see also
Appendix).38 In some EAD patients either CSF Aβ42 was low or Ptau-181 was high. This is
probably due to the low cut off value applied for CSF Aβ42 comparing EAD with FTD.
Moreover CSF Aβ42 is also decreased in a substantial proportion of the FTD patients (see also
138
chapter 5.2). Therefore, according to our results, the best single marker to differentiate EAD
from FTD is CSF Ptau. On the contrary, CSF Ptau alone is found to be less specific than CSF tau
and Aβ42 in controls with subjective memory complaints. Comparing AD with controls, CSF
Aβ42 is the marker with the highest sensitivity for AD (Chapter 5.1). 21,39
Until now three assays are available measuring CSF tau phosphorylated at different epitopes;
phosphorylation at threonine 231 (Ptau-231), threonine 181 (Ptau-181), and serine 199 (Ptau199). These markers demonstrate comparable diagnostic accuracy comparing AD with controls.40
For the differentiation of AD from other types of dementia CSF Ptau-231 and Ptau-181
performed equally well (see also Appendix for our unpublished results comparing AD with
FTD). Combinations of the three markers did not add to the discriminative power when compared
to a single marker.40? Neuropathological data have shown that phosphorylation of tau at the three
epitopes occurs at different stages of disease. Unfortunately, no difference in the prediction of the
rate of cognitive decline between the different phosphorylated Ptau epitopes could be shown in
MCI patients with 1 year clinical follow up.41 A possible explanation for this finding might be the
relatively short time of follow up, but also test characteristics might be involved: not the absolute
quantification of the phosphorylation of tau at the specific epitope is measured in CSF, but the
presence of Ptau phosphorylated at this particular epitope in CSF. In addition, little is known
about CSF flow, kinetics and clearance dynamics and their influence on the concentration of
(P)tau proteins.42
Chapter 6 Biomarker profiles and their relation to clinical variables in mild cognitive
impairment
The findings of this study point to a relation of CSF Aβ42 and tau to clinical markers of AD in
the MCI stage of disease. These results are very important, not only because they add to the
biological validity of the markers, but they also support the added value of the biomarkers in
selecting MCI patients for clinical studies. We divided the MCI patients into three groups
according to their biomarker profile. The biomarker profile was assumed positive for AD when
the CSF Aβ42 concentration was decreased and CSF tau was increased. Preliminary results show
that 56% of our MCI cohort developed AD in a follow up period of 19 months.43 Both CSF Aβ42
and tau were significantly associated with AD at follow-up comparing progressive with stable
139
MCI patients. These associations were also found when the markers were analyzed separately.
These results justify our choice to divide the patients into three groups; high-, intermediate- and
low-risk group. Overall, patients within the high- and intermediate- risk group were comparable
for all clinical variables. Including CSF Ptau to the panel of biomarkers did not influence the
results and conclusions (unpublished results). All patients with a high CSF tau also had a high
CSF Ptau, except for one patient, who would therefore have an intermediate risk for AD instead
of a low risk.
The different relations of CSF Aβ42 and tau with MTA, PAS and memory impairment is
remarkable. However, our results are in line with those of another independent cohort study.44
The cross-sectional associations between CSF tau and neuropsychological markers may very well
be restricted to the MCI stage of disease. The VAT is an instrument that is changed very early in
the disease process45, even before the clinical diagnosis of AD is obtained. Until now, it was not
possible to find consistent relations between CSF biomarkers and neuropsychological markers in
AD46, except for a relation between CSF Ptau-231 at baseline and annual rate of change in
MMSE score in MCI.47
Chapter 7 Cerebrospinal fluid and magnetic resonance imaging markers independently
contribute to the diagnosis Alzheimer’s disease
Major finding of this study was that both CSF and MRI markers contribute to the clinical
diagnosis AD. Both diagnostic markers are supposed to reflect neuropathology of AD.48-50 All
studies investigating hippocampal volumes with postmortem neuropathology have found
reasonable associations with neuron loss as well as plaques and tangles densities.42,48,49
Associational studies between biochemical markers and postmortem neuropathological data are
very sparse and not conclusive.50,51 Unfortunately, postmortem CSF tau-, Ptau- and Aβ42concentrations seem not to be valuable to use for associational studies with neuropathological
findings, as the CSF concentrations are totally different from antemortem CSF concentrations,
with no distinction between AD and controls (unpublished results).52 Several explanations for the
absence of a relation between CSF biomarkers and MTA are described in the paper. Here, I
would like to comment on the presumed differences in early onset AD versus late onset AD
140
(EAD vs LAD), as well as the inability to detect longitudinal changes in CSF Aβ42, tau and Ptau
concentrations.
Although clinical presentation differs between EAD and LAD53, neuropathological findings are
comparable. However, the distribution of neuronal loss is in proportion to the clinical picture
from patients, especially in the early stage of disease; patients who present with focal signs like
aphasia, apraxia, executive dysfunction or visual disturbances have predominantly focal
degeneration of the brain, and in lesser extent hippocampal atrophy.54 In our study we did not
divide the AD patients into a memory versus a non-memory type according to their
neuropsychological profile. This would have revealed whether differences between the EAD and
LAD group with respect to discordance between CSF markers and MTA was due to fewer
patients in the EAD group presenting with memory disturbances and thus with less MTA.
Interesting in this light is the finding of a relationship between the clinical phenotype of EAD –
either the amnestic phenotype or the non-memory phenotype- and the presence of ≥ 1 Apo E ε4
allele.55 Furthermore, hippocampal atrophy is also considered to increase with age.56 Patients with
AD still tended to have higher MTA scores compared to age-matched controls (unpublished
results, see also Appendix).57 However, we cannot exclude the possibility that younger AD
patients have less MTA than older AD patients due to the age factor.
Until now no longitudinal changes of CSF Aβ42, tau and Ptau could be demonstrated, except for
CSF Aβ42 in one study with prolonged follow up.58 If the CSF markers are supposed to reflect
neuropathological changes in AD, one would expect a decrease of CSF Aβ42 and an increase of
CSF tau and/or Ptau with time, as a result of increased plaque deposition and neuron loss,
comparable to the increase of MTA with progression of disease. Probably more complex
mechanisms are involved; one hypothesis might be that there is an increased total production of
Aβ42 during progression of disease, not per se leading to a decreased but even to a steady or a
paradoxically increased CSF Aβ42 concentration, which can only be detected after prolonged
follow up. In addition, with disease progression less neurons are left to release (P)tau in CSF,
which might result in steady or decreased CSF (P)concentrations. But, also CSF flow and
clearance dynamics might be involved42,59, as well as ELISA characteristics like epitope masking
of Aβ42, or the presence of various Aβ peptides in CSF, which might have a different role in
progression of disease. Taking all these considerations into account, it is not surprising that the
141
CSF biomarkers Aβ42, tau and Ptau, which are already changed before the clinical picture of AD
becomes overt, do not have a relation with MTA, which increases as disease progresses.
142
8.2 CONCLUSIONS
The studies described in this thesis intended to assess whether the CSF biomarkers Aβ42, tau and
Ptau can be used for early and differential diagnosis of AD. Findings from former studies were
confirmed in a clinical setting, with the addition of some new insights: the combination of CSF
Aβ42 and Ptau achieved the highest diagnostic accuracy for the differentiation of EAD from
FTD; CSF biomarkers are not independent from other clinical parameters in the MCI stage of
disease; and both CSF Aβ42, tau and Ptau and MTA are of incremental value for the diagnosis
AD. Furthermore, the variability of CSF Aβ42 concentrations is explained by pre-analytical and
internal (ELISA) factors. However, the commercial ELISAs are quite reliable as diagnostic
method compared to the other methods available.
None of the biochemical markers is sufficiently accurate to be used as the sole diagnostic tool.
Will there ever be one, as the gold standard for AD is still the clinical diagnosis? Without a
doubt, more clinicopathological studies are needed, although it is not very likely that all clinically
diagnosed AD patients will have a pure form of AD neuropathologically, which might be again
confusing to interpret the CSF data. Be that as it may , the results of the present thesis led us to
the conclusion that the three CSF biomarkers Aβ42, tau and Ptau can be used as diagnostic tool
for AD in a secondary referral setting within the clinical context and only in addition to other
diagnostic methods. Most promising are the CSF markers in the diagnostic evaluation of EAD.
Furthermore, CSF Aβ42, tau and Ptau are potential markers for prediction of AD in MCI
patients. Until now, CSF Aβ42, tau and Ptau do not appear to be good markers to track
progression of disease. The absence of neuropathological confirmation of the diagnosis in most
cases requires prolonged follow up time of the patients especially in the early stage of disease.
Answers to the questions in chapter 2 are summarized below. Recommendations or guidelines
for the use of the CSF biomarkers in clinical practice are listed at the end of this paragraph (see
also chapter 1.2):
Are CSF samples stable as far as Aβ42 and tau are concerned?
-
CSF Aβ42 and tau are stable when stored for years at -80°C. CSF Aβ42 concentrations
are influenced by storage temperatures > -80°C and after repeated freeze/thaw cycles.
143
CSF tau is stable under these conditions, except when stored for more than 10 days at
37°C.
Are CSF concentrations of Aβ42 comparable when measured by two different ELISAs?
-
In AD and controls CSF Aβ42 concentrations are comparable when measured by two
different ELISAs for Aβ42. In FTD, CSF Aβ42 concentrations as measured by the two
ELISAs slightly differ, which suggest a role of β amyloid metabolism disturbances in
FTD. Both ELISAs have a comparable diagnostic accuracy in AD versus controls.
Is there a relation between various C-terminally truncated Aβ peptides in CSF?
-
All three C-terminally truncated Aβ peptides in CSF are interrelated in both AD and
controls. CSF Aβ42 is selectively decreased in AD.
What is the diagnostic value of CSF Aβ42, tau and Ptau in early onset AD versus frontotemporal
dementia?
-
Diagnostic accuracy of the combination of CSF Aβ42 and Ptau-181 in a cohort of EAD
and FTD patients is good, especially the specificity and negative likelihood ratio. CSF
Ptau is a better marker for the differentiation of EAD from FTD than CSF tau.
Are CSF Aβ42 and tau independent predictors of AD?
-
At baseline in MCI, CSF Aβ42 and tau have relations with other indicator markers of AD,
i.e. MTA and memory loss. Furthermore, patients with a higher risk of AD according to
their biomarker profile also perform less well on neuropsychological tests as well as the
preclinical AD scale. These findings suggest that the CSF markers are not independent in
the MCI stage of disease.
What is the relation between CSF markers and medial temporal lobe atrophy?
-
No relation could be found between CSF markers and MTA in AD or controls. Both
disease markers seem to reflect another neuropathological substrate at one point in time.
Both disease markers contribute independently to the diagnose AD.
144
Guidelines for the use of CSF Aβ42, tau and Ptau in clinical practice
1. Determine Aβ42, tau and Ptau in CSF when there is doubt about the diagnosis AD,
and when MRI markers and neuropsychological findings are not conclusive
2. Determine Aβ42, tau and Ptau in CSF in presenile dementias, as the differential
diagnosis here is wider and more complicated, and the existing diagnostic tools less
sensitive
3. Determine Aβ42, tau and Ptau in CSF in the early stage of disease, in patients for
whom treatment is being considered.
4. All three biomarkers CSF Aβ42, tau and Ptau should be measured in order to
differentiate AD from subjects ith subjective memory complaints as well as patients
with other types of dementia
5. The biomarker profile is positive for AD when in addition to CSF Aβ42, also tau or
Ptau are abnormal; i.e. at least two markers should be positive
6. Try to achieve postmortem verification of the diagnosis or otherwise prolonged follow
up time
7. In case of a negative biomarker profile at baseline, repeat the CSF measurements
when the patient clinically progresses to AD or MCI, preferably at least one year after
the first LP
145
Laboratory guidelines for the use of CSF Aβ42, tau and Ptau
1. Preferably, samples should be stored at -80°C immediately after collection
2. Baseline- and follow up- CSF samples should be analyzed after comparable storage
conditions and within the same ELISA to avoid confounders by repeated freeze/thaw
cycles or test characteristics
3. For longitudinal studies we recommend storing large collections of CSF pools, which
can be used as control samples to measure degradation of biomarkers over time
4. As the median concentrations of CSF Aβ42, tau and Ptau differ between laboratories,
we recommend to define internal cut off values until international validity studies are
completed (see Appendix for reference values of the VUMC)
146
8.3 FUTURE PERSPECTIVES
In chapter 2 ‘topics for future research’ are listed. In the present chapter I will mainly focus on
how and which biomarkers could be used for tracking the progression of the disease, especially in
the early stage of disease and in relation to promising therapies. Next, a brief commentary on the
few studies about plasma markers for the (early) diagnosis of AD will be given.
Obviously, more longitudinal prospective studies are needed. CSF Aβ42 is a good marker to
predict AD, even in asymptomatic elderly patients.60 Very interesting in this light are the results
of Fagan et al.61, in which a relation was found between in vivo brain amyloid, as detected by
PET imaging of the amyloid-binding agent PIB, and decreased CSF Aβ42 levels in 7 patients,
including 3 non-demented subjects. These findings however are not yet replicated by others.
Results depend also on which type of Aβ42 peptide is measured: the N-terminally truncated
forms of Aβ42, which might be indicator markers of the early stage of disease18,33 or full length
Aβ 1-42, which is decreased throughout the whole spectrum of disease. Then, oligomers of Aβ
peptides seem to be very promising for early detection of disease and possibly therapeutic
monitoring, also because they are directly associated with memory loss due to their toxic effects
on synapses. 82
No change of CSF Aβ42 is found with progression of disease, but also not in relation to therapy,
as has been shown in studies with acetylcholinesterase inhibitors62,63, and even after Aβ
immunization CSF Aβ42 remained the same.64 Although concentrations of CSF Aβ40 are found
to be comparable between AD and controls, there might be a role for this peptide in follow-up
studies, as the peptide has been shown to be increased in CSF of MCI patients at follow up.28
CSF Aβ38 might be interesting to study in relation to therapy, as this peptide has been shown to
increase after treatment with non-specific anti-inflammation drugs (NSAIDs) in cells and mice
studies, while amyloidogenic CSF Aβ42 is decreased, probably due to an allosteric effect on γsecretase.65,66 No studies are published yet investigating the effect of NSAIDs on CSF Aβ42 or
38 in humans, and only a trend was found to decreased plasma Aβ42 levels in NSAID users.67
Recently a promising study is published, in which the effect of γ-secretase inhibitors on
147
reductions of CSF Aβ40 levels in mice is described.68 While CSF Aβ42 is thus not a good marker
to measure effect of therapeutics, Aβ (auto) antibodies might be69; subgroup analysis suggests
that patients who developed antibodies reactive to amyloid plaques after Aβ immunization
perform better on neuropsychological tests compared to patients who did not develop these
antibodies.70 However, all these studies are very preliminary and must be interpreted cautiously.
The same implies for the decrease of CSF tau in 11 patients, who received Aβ immunization,
which might be due to reduced rate of cellular degeneration in patients who developed high titers
of anti-AN1792 antibodies64, but also a dilutional effect of CSF tau might be involved, as
ventricular enlargement and reduced brain volume is found in the antibody responders.71 CSF
Ptau-231 has been shown to decrease in AD with disease progression in one study.72 Further
studies are needed to investigate the value of CSF tau and Ptau to track progression of AD/MCI.
The plasma Aβ42 and Aβ40 markers are not useful for diagnosis, as has been shown by 8
studies.69 Aβ42 is increased in plasma of affected and even unaffected family members with
mutations in PSEN 1 and 2 and APP, as well as in patients with Down syndrome with and
without dementia.73 Probably this increase of plasma Aβ42 is a result of an overall increase in
Aβ42 production, in the brain but also in peripheral sources such as blood.74 There are findings
pointing to an increase of Aβ42 in plasma of some patients long before and during the early
stages of AD, with a decline thereafter.74 The plasma Aβ42 marker might therefore be used to
track patients at risk for AD (which might be patients with ≥ 1 Apo E ε4 allele and a strong
positive family history), but only when followed for longer periods as the differences in
frequency of AD by plasma Aβ42 emerge only after 2-3 years and the specificity of AD
diagnosis is higher in more advanced stages.74 Moreover, ethical issues are involved; until there
is no absolute cure for AD the knowledge for the patient of having a biomarker profile indicative
for AD is not warranted, making the use of Aβ42 as predictive (plasma or CSF) marker in most
cases only a topic for research.
Isoprostanes are markers of oxidative stress and involved in a number of neurodegenerative
disorders, including AD. It can be measured in CSF, plasma and urine, and is increased in AD
and MCI in CSF.75,76 Conflicting results are found in plasma concentrations of isoprostanes in
148
AD versus controls.75,77 One study showed an increase of isoprostanes in CSF at follow up in
MCI.42 As diagnostic marker isoprostanes seem not be very useful as they lack specificity, but
there might be possible role as marker of progression to dementia.
Conflicting results are also found in inflammatory markers measured in serum: some authors
found an increase of interleukine 6 (Il-6) in serum of AD patients, while others could not
replicate this finding. 69 The same accounts for α1-antichymotrypsine (α1-ACT) in serum.78
These differences might be contributed to differences in assay methodology and sensitivity, and
small sample sizes with heterogeneous patient and control populations. We could not find
differences in Il-6 and α1-ACT in serum between AD and controls in our laboratory (unpublished
results). In a collaboration study with investigators in Milan we could not demonstrate
differences between the chemokines Interferon-γ-inducible Protein-10 (IP-10), Interleukin-8 (IL8), and Monocyte Chemotactic Protein-1 (MCP-1) in serum from AD, MCI and controls.79,80 CSF
appears to be a better fluid to investigate interleukins and chemokines, however, as differences
were found in a cross-sectional study for CSF IP-10, IL-8 and MCP-1 in mild-moderate AD and
MCI versus controls80, although the last two markers seem not to be specific for AD.81 Follow-up
studies in MCI might reveal whether these markers might be used for prediction or even
progression of disease. Furthermore, additional studies are needed to confirm our unpublished
data of increased CSF α1-ACT concentrations in AD versus controls as compared to the serum
concentration. As α1-ACT is found at a very early stage of AD in the neuritic plaques, studies are
underway to investigate the relation of α1-ACT and Aβ42 in CSF and whether it is possible to
detect complexes of these two peptides in CSF.
149
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159
APPENDIX
160
161
Chapter 1.1
NINCDS-ADRDA criteria1:
Probable AD
-
Dementia
-
Clear conscience
-
Dysfunction in two or more cognitive domains
-
Progressive deterioration of cognitive dysfunction
-
Age between 40 and 90 years old
-
No signs of systemic disorder or other brain disease
Possible AD
-
Dementia of the Alzheimer type
-
Presence of a systemic disorder or brain disease
Amnestic MCI (Petersen et al. 16) :
-
Memory complaint
-
Memory disturbances at neuropsychological screening tests
-
No other cognitive dysfunction
-
Intact function in daily activities
-
No dementia
162
Chapter 1.1
Proteolysis of amyloid precursor protein (APP)87
163
Chapter 3.3
Figure 1
164
Chapter 3.3
Figure 2
165
Chapter 8.1
Spike recovery of CSF Aβ42 concentration
Table 1
Sample1
(pg/mL)
Sample 2
(pg/mL)
Sample 3
(pg/mL)
Sample 4
(pg/mL)
Undiluted
(pg/mL)
438
520
266
319
Measured Aβ42
concentration
(calculated
concentration)
981(1119)
917(1260)
896(1133)
875(1160)
Recovery (%)
76.2
72.7
79.0
75.4
The spike recovery of CSF Aβ42 was evaluated in two different runs by spiking four CSF
samples 1:1 with the highest standard of the INNOTESTTM β-amyloid (1-42) ELISA, i.e. 2000
pg/mL. Recoveries ranged from 75.4 to 79% with an overall mean recovery of 76%.
166
Recovery of expected value of CSF Aβ42 concentration
Table 2
Sample +
sample
diluent
Sample 1
(pg/mL)
Recovery
of exp
value (%)
Sample 2
(pg/mL)
Recovery of Sample 3
(pg/mL)
exp value
(%)
Recovery
of exp
value (%)
100 + 0
1055
100
806
100
1124
100
80 + 20
966
114
605
94
930
103
60 + 40
802
125
593
122
-----
----
50 + 50
778
147
446
111
851
151
40 + 60
696
165
375
116
-----
------
20 + 80
403
191
255
158
451
201
In three different runs three CSF samples were assayed at five serial dilutions with sample
diluent. In Table 2 the percent recovery of expected value (or linearity) is listed. Recoveries
ranged from 158 to 201% in the experiment with the highest dilution (1:5). See also Figure 1.
167
Figure 1 Recovery of the expected value of CSF Aβ42 concentration
recovery of the expected value
250
200
sample 1
%
150
sample 2
100
sample 3
50
0
1
1,25
1,67
2
2,5
5
dilution factor
168
Chapter 8.1
Criteria for an ideal biomarker for AD38:
- Reflection of neuropathological changes in AD
- Gold standard: at autopsy neuropathological changes typical for AD
- Sensitivity ≥ 85%
- Specificity ≥ 75%
- Able to detect AD early on the course of disease
- Useful in monitoring disease progression and treatment effect
- Reliable and precise
- Non-invasive and simple procedure
- Not expensive
169
Chapter 8.1
ROC curve CSF Ptau-231 and Ptau-181 in AD (N = 30) versus FTD (N =21)
ROC Curve
1,0
,8
Source of the Curve
Sensitivity
,5
Reference Line
,3
PTAU231
PTAU181
0,0
0,0
,3
,5
,8
1,0
1 - Specificity
Diagonal segments are produced by ties.
Ptau-181, cut off 55 pg/ml, sensitivity = 87%, specificity = 62%
Ptau-231, cut off 40 pg/ml, sensitivity = 87%, specificity = 62%
Areas under the curve (95% CI):
Ptau-181 =
0.79 (0.66-0.92)
Ptau-231 =
0.78 (0.64-0.92)
170
Chapter 8.1
MTA in EAD and LAD versus age-matched controls
Table 3
≥ 65 years old
< 65 years old
Average MTA (min-max)
AD
Controls
P
AD
1 (0-2.5)
0 (0-0.5) <0.001 1.5 (0-3.5)
Controls
P
0 (0-3)
0.001
MTA = medial temporal lobe atrophy; Average MTA: MTA R+L/2; P = P-value comparing AD
with controls (Mann Whitney U test).
171
Chapter 8.2
Reference values of the VUMC
AD:
Controls:
Aβ42 < 500 pg/mL
Aβ42 ≥ 500 pg/mL
Tau > 350 pg/mL
Tau ≤ 350 pg/mL
Ptau-181 ≤ 60 pg/mL
Ptau-181 > 60 pg/mL
Aβ42
Tau
Ptau
Alzheimer’s disease
Decreased
Increased
Increased
Lewy Body Dementia
Decreased
Normal
Normal
Vascular Dementia
Normal - decreased
Normal - increased
Normal
Frontotemporal Dementia
Normal - decreased
Normal – increased
Normal
Creutzfeldt Jakob Disease
Normal - decreased
Strongly increased
Relatively normal
Non-demented elderly
Normal
Normal
Normal
172
173
SUMMARY
The diagnose Alzheimer’s disease (AD) is based on clinical criteria, supported by
neuropsychological tests, neuroimaging and extended follow up. A definite diagnose can only
be obtained at autopsy. With the advent of disease modifying therapeutics, it is important to
diagnose AD as early as possible, before extensive brain damage has occurred. In this early
stage biochemical markers are needed for diagnosis as clinical symptoms are subtle and other
diagnostic methods fairly normal. Up to now amyloid β 42 (Aβ42), total tau (tau) and
phosphorylated tau (Ptau), as measured in cerebrospinal fluid (CSF), are considered to be the
most promising biochemical markers for AD. The present thesis tells us how and when to use
these markers for the early and differential diagnosis AD in clinical practice.
We conclude that the triplet of Aβ42, tau and Ptau must be measured in CSF in order to
differentiate AD from normal aging and other types of dementias. Particularly useful are
these biomarkers in presenile dementias –starting before 65 years old- as the differential
diagnosis here is wider and more complicated. At least two of the markers must be abnormal
for the diagnosis AD, while all three markers negative can practically rule out the disease.
CSF Aβ42, tau and Ptau are potential markers to predict AD in the preclinical stage of
disease. However, in this early stage the markers are not independent from other clinical
parameters. Moreover, the combination of the three CSF markers and atrophy of the medial
temporal lobe are of incremental value for the diagnosis AD. Hence, the three CSF
biomarkers Aβ42, tau and Ptau can only be used as diagnostic tool in addition to other
diagnostic methods. Variability of CSF Aβ42 concentrations is explained by pre-analytical
and internal (ELISA) factors. Current (commercial) ELISAs are quite reliable as diagnostic
method compared to the other methods available.
174
175
SAMENVATTING
De diagnose ziekte van Alzheimer (AD) wordt gesteld op basis van klinische criteria, met
ondersteuning van neuropsychologische tests, beeldvorming en langdurige follow-up. De
definitieve diagnose kan alleen worden vastgesteld bij obductie. Van belang is om de
diagnose in een zo vroeg mogelijk stadium te stellen zodat, voordat er in de hersenen schade
is aangericht, kan worden gestart met therapie. Juist in dit preklinische stadium van de ziekte
is er behoefte aan biochemische markers, aangezien de klinische symptomen subtiel zijn, en
andere diagnostische methoden vaak normaal. Liquor cerebrospinalis (cerebrospinal fluid,
CSF) wordt verondersteld een goede afspiegeling te geven van wat zich in de hersenen
afspeelt. Tot nu toe is gebleken dat bepaling van Aβ42, totaal tau (tau) en Ptau in CSF erg
sensitief is voor de diagnose AD. In dit proefschrift wordt uiteengezet hoe en wanneer deze
drie biochemische markers het beste kunnen worden gebruikt voor de diagnose AD in een
klinische setting.
Alledrie de markers zijn nodig om AD te kunnen onderscheiden van normale veroudering en
verschillende soorten dementie. Voor de diagnose AD moeten twee van de drie markers
positief zijn, terwijl als alledrie de markers negatief zijn de ziekte vrijwel is uitgesloten. De
markers zijn met name van belang bij het onderscheid tussen verschillende vormen van
preseniele dementie (ontstaan van klachten voor het 65ste jaar), waarbij de differentiële
diagnose uitgebreid is, en overige diagnostische methoden niet eenduidig. CSF Aβ42, tau en
Ptau zijn veelbelovend om te gebruiken bij het voorspellen van AD in een preklinisch
stadium. Echter, ze zijn niet onafhankelijk van andere klinische variabelen, en dragen
supplementair bij aan de diagnose AD in combinatie met een MRI scan. Geadviseerd wordt
om de markers alleen te bepalen naast andere diagnostische methoden. De variabiliteit van de
Aβ42 concentratie in CSF wordt veroorzaakt door preanalytische en interne (ELISA)
factoren. De gangbare (commerciele) ELISA’s zijn net zo goed als diagnostische methode
vergeleken met andere analysemethoden.
176
177
DANKWOORD
Geen proefschrift zonder dankwoord. Wetenschap bedrijven binnen de geneeskunde is niet
eenzaam, aan één artikel werken tenminste 6 mensen mee. In feite nog meer, als je rekent
vanaf de patiënt naar de lumbaalpunctie via het lab, de analyse van data, de vergaderingen,
koffiepauzes, praatjes, congressen, etc. Pas in de laatste fase sta je er min of meer alleen voor,
met als moment suprême: de verdediging van het ‘boekje’. Daarom wilde ik graag iedereen
bedanken die op een of andere manier betrokken is geweest bij het stand komen van dit
proefschrift en niet in de laatste plaats de patiënten zelf en hun familie. In het bijzonder gaat
mijn aandacht naar:
Prof.dr. Ph Scheltens, Philip, wat heb ik er veel aan gehad om bij jou te mogen werken. De
combinatie van vrijheid en vertrouwen was goed voor mij: ik mocht veel zelf doen, maar je
begeleidde toch heel strak en stipt, waardoor we niet verzandden in de vele zijwegen die
mogelijk zijn in biomarkerland. Als initiator, inspirator, en zeer goed manager van het
Alzheimercentrum zorg je ervoor dat de onderzoeksgroep nog steeds uitbreidt, en iedereen
wel bij jou zou willen werken. Gelukkig is er een stevig thuisfront, waar je kan bijkomen van
alle drukte, maar dan nog houd je intensief (e-mail)contact met je ‘kinderen’ van de VU.
Prof.dr. MA Blankenstein, Rien, ook al stapte je halverwege het onderzoek pas in, meteen
was je erg betrokken en enthousiast. Dankzij jouw heldere visie op de toepassing van
biomarkers in de klinische praktijk ging het ineens heel hard met de ‘basale’ stukken van dit
proefschrift, en zullen er nog velen volgen.
Dr. GJ Van Kamp, Gerard, bedankt voor je begeleiding vanuit de klinische chemie. Als artsonderzoeker werd ik voor 40% bij jullie aangesteld en als eenvoudig doktertje had ik
natuurlijk weinig verstand van ELISA’s. Jij was er voor de puntjes op de i, ook toen je al met
pensioen was, en ik bezig met de laatste fasen van dit proefschrift.
Prof.dr. K Blennow, prof.dr. F Barkhof, prof.dr. E Hack, dr. MM Verbeek: thank you for
attending the ‘reading committee’ as well as to get the opportunity to collaborate with you.
Prof.dr. RB Schutgens, u heeft aan de wieg gestaan van dit onderzoek en u heeft mij destijds
aangenomen, waarvoor dank. Ik hoop dat het resultaat enigszins aan uw verwachtingen
voldoet.
Prof.dr. JJ Heimans, beste Jan, ik ben benieuwd naar jouw visie op mijn proefschrift als leek
op het gebied van biochemische markers bij de ziekte van Alzheimer. Tevens wil ik je
bedanken voor de mogelijkheid die je mij biedt om de opleiding tot neuroloog te volgen in de
VU.
Cees Mulder, met jou heb ik daadwerkelijk het meeste geschreven. Ook al dachten we vaak
ergens anders over, we kwamen er altijd wel uit als we de tijd namen en e.e.a lieten bezinken.
Bewondering heb ik voor je doorzettingsvermogen en consciëntieuze manier van werken,
waarbij je het ene artikel na het andere schrijft (wanneer promoveer jij nu eens? Je kan het!).
178
Yolande, je bent een fantastische collega. Ook wij discussieerden, schreven en lachten veel,
nog steeds overigens. Jouw enthousiasme voor je werk is aanstekelijk, en gelukkig delen we
de interesse voor de cognitieve neurologie, zodat de samenwerking hopelijk op een of andere
manier in de toekomst kan worden voortgezet. Succes met het afronden van jouw promotie!
Astrid Kok, Eef van Elk, en alle andere analisten van het ‘immunolab’: heel erg bedankt voor
jullie inzet om hersenvocht, bloed en urine op de juiste manier op te slaan en te verwerken.
Veel heb ik ook van jullie geleerd, en nog steeds, want het werk gaat door! Bijna 1000
liquoren in DE Bank, en iedereen helpt mee met het ontwikkelen van eigen ELISA’s met
eigen antistoffen, geweldig!
Pieter Jelle Visser, en Wiesje van der Flier; het AD-centrum kan niet meer zonder jullie, en
jullie beider (verschillende) kwaliteiten als post-docs zijn heel leerzaam voor ons. Ook met
jullie hoop ik nog te blijven samenwerken de komende jaren.
Femke, een betere opvolgster had ik niet kunnen wensen. Volgens mij ben je al bijna klaar,
terwijl je ondertussen ook nog neuroloog én moeder bent geworden. Petje af.
Laura, Ingeborg en Maaike (en later weer Femke); met heel veel plezier denk ik aan onze
oude kamer terug. Ik mis af en toe zeker de gezelligheid, de gesprekken, en o ja, het werk ook
natuurlijk. In de kliniek is het toch anders en hectischer, maar gelukkig delen we die meer
ontspannen tijd.
Esther, Alie, Rutger, Jasper, Ilse, Wouter, Freek, Rolinka, en al die andere onderzoekers en
medewerkers van het AD-centrum: het was een gezellige tijd! En Esther: wat zal jij ook blij
zijn als je klaar bent: succes!
Prof.dr. MJ De Leon, dear Mony, thank you for the opportunity to work at your lab in New
York, the Center for Brain Health (still a brilliant name). Your experience and way of
thinking about mechanisms behind Alzheimer’s disease are really inspiring, and I hope there
will be in some way opportunities to stay in contact with you. The same applies for Susan De
Santi, your co-worker and friend.
Dr. PD Mehta, Pankaj, our collaboration was successful! I learned a lot about ELISA’s at
your lab, and you have been always very hospitable. What will be the next project?
Dr. H Vanderstichele, en andere medewerkers van Innogenetics: de samenwerking met jullie
heb ik als prettig ervaren, en is uiteindelijk ook vruchtbaar gebleken. We zijn goed ontvangen
op het lab in Gent!
Daniela Galimberti and Elio Scarpini, we did a good job together! Daniela, your dedicated
precise laboratory work and writing deserves all those publications. Hopefully we are able to
continue the collaboration in the future (still not been in Milan….).
Marijke en Ina, gouden handen hebben jullie als het gaat om assisteren bij LP’s! Volgens mij
zouden jullie het best zelf kunnen na al die jaren. Ook alle andere medewerkers van de poli:
179
bedankt voor jullie hulp met het zoeken van statussen, foto’s, kamers, en plannen van de vele
patiënten. Ik zal niet altijd de makkelijkste zijn geweest met mijn drukdoenerij.
Els van Deventer, niets was teveel, je vond altijd alle relevante literatuur en updates, dank!
Dear Isabel, Kim, and Chase, you became real friends during my stay in New York. Although
we live now in Berlin, Amsterdam, and Brooklyn, we still have contact, and I hope this
friendship will last.
Serge, je bent een echte wetenschapper, veel leerde ik van jou op dit gebied. Succes met je
nieuwe baan bij Columbia University!
Judith, Juut, jou ken ik al vanaf de intreeweek. Het eerste jaar waren we huisgenoten, en
stond ons huis altijd open voor iedereen, met veel logeerpartijen en feestjes. Wie had toen
gedacht dat we allebei gelijksoortig onderzoek zouden gaan doen? Met name in het begin,
met het opzetten van de liquorbank, hebben we veel aan elkaar gehad, en zaten we tot laat in
de avond te pipetteren. Voor mij was het niet meer dan logisch je te vragen als paranimf.
Voor Annick, Lonneke, Loes, en Henneke was ik regelmatig niet bereikbaar, -je neemt nooit
je telefoon op!- maar jullie accepteerden dat redelijk. Ik weet overigens niet of dat nu zal
veranderen.
Mijn familie is altijd een grote steun geweest, in alles wat ik doe: mijn vader door de juiste
vragen te stellen, en bij te houden of ik op schema ben; mijn moeder door te zorgen dat ik aan
mezelf blijf denken, en niet te hard werk; Merlijn, door te relativeren en kritisch te blijven.
Zonder jullie was ik nooit zover gekomen.
Job en Manu, er is meer dan werk; jullie zijn de ‘sjeu’ van mijn leven en Job is de stille
kracht. Dankzij jouw onvoorwaardelijke steun en vertrouwen kan ik mijn eigen weg gaan.
180
181
CURRICULUM VITAE
Niki Schoonenboom (03-03-1972) is in Wassenaar opgegroeid en voltooide daar het
gymnasium β aan het Rijnlands Lyceum in 1990. Ze is in hetzelfde jaar geneeskunde gaan
studeren aan de Universiteit van Amsterdam. Na de studie werd de interesse voor de oudere
mens gewekt als AGNIO ouderenpsychiatrie bij de Robert Fleury Stichting in Leidschendam,
en later verder als AGNIO neurologie in het Slotervaartziekenhuis in Amsterdam (1999). In
2000 begon ze met promotieonderzoek bij prof.dr. P. Scheltens, Alzheimer Centrum, VUmc
(2000-2004). In 2002 kreeg ze de gelegenheid om 5 maanden deelonderzoek te doen in New
York, bij het ‘Center for Brain Health’ van NYU, en het ‘Institute for Basic Research in
Developmental Disabilities’, Staten Island, onder leiding van respectievelijk prof.dr. MJ De
Leon en dr. PD Mehta. Eind 2004 kon ze beginnen als AGIO neurologie in het VUmc,
waarmee ze hopelijk in 2010 klaar zal zijn.
182
CURRICULUM VITAE
Niki Schoonenboom (03-03-1972) grew up in Wassenaar, and graduated in 1990 from the ‘
Rijnlands Lyceaum’ (Gymnasium β). The same year she moved to Amsterdam (University of
Amsterdam) to study Medicine. After obtaining her medical degree, she started her carreer as
physician at Geriatric Psychiatry (Robert Fleury Stichting, Leidschendam) and Neurology
(Slotervaartziekenhuis, 1999). From 2000-2004 she worked on her PhD thesis under the
supervision of prof.dr. P Scheltens at the Alzheimer Center of the VUmc. In 2003 she got the
opportunity to do a research project at the Center for Brain Health, NYU, New York, and the
Institute for Basic Research in Developmental Disabilities, Staten Island, US, under the
supervision of prof.dr. MJ De Leon and dr. PD Mehta respectively. Since 2004 she works as a
resident in Neurology at the VUmc, which she hopefully will conclude in 2010.
183
PUBLICATIONS
184
Schoonenboom NS, Pijnenburg YA , Mulder C, Rosso SM , Van Elk EJ , Van Kamp GJ, JC
Van Swieten, Scheltens P. Amyloid β 1-42 and phosphorylated tau in CSF as markers for
early onset Alzheimer’s disease. Neurology 2004;62:1580-4.
Schoonenboom NS, Visser PJ, Mulder C, Lindeboom J, Van Elk EJ, Van Kamp GJ,
Scheltens P. Biomarker profiles and their relation to clinical variables in mild cognitive
impairment. Neurocase 2005;11:8-13.
Schoonenboom NS, Mulder C, Vanderstichele H, Van Elk EJ, Kok A, Van Kamp GJ,
Scheltens P, Blankenstein MA. Effects of processing and storage conditions on amyloid beta
(1-42) and tau concentrations in cerebrospinal fluid: implications for use in clinical practice.
Clin Chem 2005;51:189-95.
Schoonenboom NS, Mulder C, Vanderstichele H, Pijnenburg YA, Van Kamp GJ, Scheltens
P, Mehta PD, Blankenstein MA. Differences and Similarities between Two Frequently Used
Assays for Amyloid (beta) 42 in Cerebrospinal Fluid. Clin Chem 2005;51:1057-60.
Schoonenboom NS, Mulder C, Van Kamp GJ, Mehta SP, Scheltens Ph, Blankenstein MA,
Mehta PD. Aβ38, 40 and 42 in cerebrospinal fluid: more of the same? Ann Neurol
2005;58:139-42.
Schoonenboom SNM, Hampel HH, Scheltens Ph, De Leon M. Cerebrospinal fluid markers
for the diagnosis of dementia. Gauthier S, Scheltens P, Cummings JL, ed; Alzheimer’s
disease and related disorders Annual 2005; 2:17-33. London: Taylor & Francis, 2005.
Pijnenburg YA, Schoonenboom NS, Rosso SM, Mulder C, Van Kamp GJ, van Swieten JC,
and Scheltens P. CSF tau and A 42 are not useful in the diagnosis of frontotemporal lobar
degeneration. Neurology 2004;62:1649.
Pijnenburg YA, Schoonenboom NS, Scheltens P. Tau and Abeta42 protein in CSF of patients
with frontotemporal degeneration. Neurology. 2003;60:353-4; author reply 353-4.
Pijnenburg YA, Schoonenboom NS, Barkhof F, Knol DL, Mulder C, Van Kamp GJ, Van
Swieten JC, Scheltens P. CSF biomarkers in frontotemporal lobar degeneration: relations with
clinical characteristics, apolipoprotein E genotype, and neuroimaging. J Neurol Neurosurg
Psychiatry 2006;77:246-8.
Mulder C, Schoonenboom NS, Wahlund LO, Scheltens P, van Kamp GJ, Veerhuis R, Hack
CE, Blomberg M, Schutgens RB, Eikelenboom P. CSF markers related to pathogenetic
mechanisms in Alzheimer's disease. J Neural Transm. 2002;109:1491-8.
Mulder C, Schoonenboom NS, Jansen EE, Verhoeven NM, van Kamp GJ, Jakobs C, and
Scheltens P. The transmethylation cycle in the brain of Alzheimer patients. Neurosci Lett
2005 30;386:69-71.
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Galimberti D, Schoonenboom N, Scarpini E, Scheltens P; Dutch-Italian Alzheimer Research
Group. Chemokines in serum and cerebrospinal fluid of Alzheimer's disease patients. Ann
Neurol 2003;53:547-8.
Galimberti D, Schoonenboom N, Scheltens P, Fenoglio C, Venturelli E, Pijnenburg YA,
Bresolin N, Scarpini E. Intrathecal chemokine levels in Alzheimer disease and
frontotemporal lobar degeneration. Neurology 2006;66:146-7.
Galimberti D, Schoonenboom N, Scheltens P, Fenoglio C, Bouwman F, Venturelli E, Guidi I,
Blankenstein MA, Bresolin N, Scarpini E. Intrathecal chemokine synthesis in mild cognitive
impairment and Alzheimer disease. Arch Neurol 2006;63:538-43.
Bouwman FH, Schoonenboom SN, van der Flier WM, van Elk EJ, Kok A, Barkhof F,
Blankenstein MA, Scheltens P. CSF biomarkers and medial temporal lobe atrophy predict
dementia in mild cognitive impairment. Neurobiol Aging, 2006, [Epub ahead of print].
Van der Flier WM, Schoonenboom SN, Pijnenburg YA, Fox NC, Scheltens P. The effect of
APOE genotype on clinical phenotype in Alzheimer disease. Neurology 2006;67:526-7.
Verbeek MM, Schoonenboom SNM. Liquordiagnostiek bij dementia. Tijdschrift voor
neurologie en neurochirurgie 2005;106:54-62.
Verbeek MM, Pijnenburg YA, Schoonenboom NS, Kremer BP, Scheltens P. Cerebrospinal
fluid tau levels in frontotemporal dementia. Ann Neurol 2005;58:656-7; author reply 657.
Bouwman FH, van der Flier WM, Schoonenboom NS, van Elk EJ, Kok A, Scheltens P,
Blankenstein MA. Usefulness of longitudinal measurements of beta-amyloid1-42 in
cerebrospinal fluid of patients with various cognitive and neurologic disorders. Clin Chem
2006;52:1604-6.
Rosso SM, van Herpen E, Pijnenburg YA, Schoonenboom NS, Scheltens P, Heutink P, van
Swieten JC. Total tau and phosphorylated tau 181 levels in the cerebrospinal fluid of patients
with frontotemporal dementia due to P301L and G272V tau mutations. Arch Neurol
2003;60:1209-13.
Minnema MC, Wittekoek ME, Schoonenboom N, Kastelein JJ, Hack CE, ten Cate H.
Activation of the contact system of coagulation does not contribute to the hemostatic
imbalance in hypertriglyceridemia. Arterioscler Thromb Vasc Biol. 1999;19:2548-53.
Schoonenboom SNM, Scheltens P. De differentiële diagnose van de ziekte van Creutzfeldt
Jakob. Neurologen Vademecum, Uitgeverij Bohn Stafleu Van Loghum, 2001.
Schoonenboom SNM, P Scheltens. Hoe is het met de ziekte van Creutzfeldt Jakob buiten
Engeland? Is er een toename? Neurologen Vademecum, Uitgeverij Bohn Stafleu Van
Loghum, 2002.
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