peripheral and central markers of inflammation in …
TRANSCRIPT
PERIPHERAL AND CENTRAL MARKERS
OF INFLAMMATION IN MILD COGNITIVE
IMPAIRMENT
A thesis submitted to the University of Manchester for the degree of MD
in the Faculty of Medical and Human Sciences
2011
Dr Salman Karim
School of Medicine
1
Contents
Page No’s
List of tables 3
List of figures 4
Abstract 5
Declaration and Copyright Statement 6
Acknowledgements 9
Dedication 10
List of abbreviations 11
Chapter 1: Introduction 12
Chapter 2: Methods 39
Chapter 3: Results 50
Chapter 4: Discussion 63
References: A to Z 74
Appendix 1: Information sheet for patient 91
Appendix 2: GP Information Letter 94
Appendix 3: Patient Consent Form 95
Appendix 4: Personal-Consultee assessment Form 97
Appendix 5: Nominated Consultee Assessment Form 99
2
Page No’s
Appendix 6:- Infection Screen 101
Appendix 7:- Protocol for collection of blood 102
3
List of Tables
Table 3.1 Demographics of MCI patients
Table 3.2 Demographics of MCI patients
Table 3.3 Anti-inflammatory drug use
Table 3.4 Blood test results
Table 3.5 Inflammatory marker levels of MCI patients over 2 years
Table 3.6 Cognitive test results of MCI patients over 2 years
Table 3.7 PET cohort Demographics
Table 3.8 Changes in inflammatory marker concentrations (PET cohort)
Table 3.9 Cognitive tests results over 3 years (PET cohort)
Table 3.10 Cognitive test results over 3 years (PET cohort)
Table 3.11 Mean PK11195 BPND in brain regions in MCI patients and controls
4
List of Figures
Figure 1.1: Progression of people from normal funtioning to Alzheimer’s Disease.
Figure 1.2: Conversion of people having a mild cognitive impairment to dementia
over 6 years.
Figure 1.3: Progression of the sub-types of mild cognitive impairments to dementia.
Figure 1.4: Beta-amyloid plaques induce neuroinflammation as characterized by glial
activation and elevation in local pro-inflammatory cytokine production.
Figure 1.5: Accumulation of amyloid plaques and associated inflammation response
resulting in release of pro-inflammatory cytokines such as IL-1beta, IL-6,
and TNF-alpha.
Figure 1.6: NSAIDs and neuroinflammation in Alzheimer’s Disease.
Figure 2.1: Recruitment
Figure 3.1: Transaxial, coronary and sagittal projections of BPND parametric images of
one MCI patient (upper row) and one healthy volunteer (lower row).
Figure 3.2: Areas of significantly increased 11C-(R)PK11195 binding in MCI group
compared with control group.
Figure 3.3:
Upper row: Areas of significantly increased 11C-(R)PK11195 binding in APoE +ve
compared with APoE-ve MCI subjects.
Lower row: Areas of significantly increased 11C-(R)PK11195 binding in APoE +ve MCI
compared with controls.
5
Abstract
The University of Manchester
Name: Dr Salman Karim
Degree: MD in the Faculty of Medical and Human Sciences
Title: Peripheral and central markers of inflammation in mild cognitive impairment.
There has been accumulating scientific evidence, over the last three decades, of the role of inflammatory processes in the development of Alzheimer’s disease (AD). Population based studies suggest that plasma levels of inflammatory markers are raised in peripheral blood of people with AD. People on long term use of non-steroidal anti-inflammatory drugs have a lower prevalence of AD. Moreover, both animal and human histopathology studies have reported localization of inflammation in brain areas primarily affected by AD pathology. Areas of increased inflammation can be visualized in vivo by Positron Emission Tomography (PET) scans using the PK11195 ligand that binds with the benzodiazepine receptor sites of activated microglial cells. Cognitive decline in AD has been shown to correlate with levels of microglial activation using PK11195 PET scans. People with amnestic mild cognitive impairment (MCI) are known to be at high risk of developing AD. We aimed to investigate the association between peripheral and central markers of inflammation and cognitive decline in a group of people with amnestic MCI. MCI subjects (n=70) underwent cognitive testing, IL-6 and CRP in peripheral blood were measured and repeated after 1 year. A sub group (n=15) was followed up for another year and central brain microglial activation was measured by PET using PK11195 along with cognitive and peripheral inflammatory marker measurement. The mean CRP and IL-6 levels of the cohort increased over one year but the rise was only significant for CRP. No association was detected between inflammatory markers levels and cognition as measured by a battery of cognitive instruments. Group comparisons of the PET cohort with healthy controls (n=5) showed increased PK11195 binding (mean binding potential) in frontal lobe, temporal lobe, parietal lobe, putamen, occipital lobes and significantly increased binding in posterior cingulate gyrus. This study, to our knowledge, is unique in studying makers of inflammation in amnestic MCI participants both in peripheral blood and brain. The results of this study, in the light of current literature, add to the importance of recognition of inflammatory processes in people at risk of developing AD. The results suggest that CRP levels rise significantly over time and are detectable in peripheral blood by using practically simple laboratory techniques. The results also suggest that activated microglia in amnestic MCI patients can be visualized in vivo by using PK11195 PET scans and show higher levels of activation as compared to healthy controls. These finding could be useful in identifying people with malactivated (pro-inflammatory) microglia as potential targets for prevention/early treatment strategies. Further studies with larger samples sizes and long term follow-up are needed to investigate whether these peripheral and central inflammatory markers could shed light on the aetiology of AD and be useful in monitoring disease progression.
6
Declaration
The data presented in this thesis form part of a collaborative clinical study of peripheral
and central inflammation in people with mild cognitive impairment funded by the Medical
Research Council (MRC). Prof. Alistair Burns (AB) was the principal investigator and
Pippa Tyrrell (PT), Steve Hopkins (SH), Nitin Purandari (NP) and Salman Karim (SK)
were co applicants. The study was conducted in conjunction with a research nurse, Jackie
Crowther (JC). The author of this thesis (SK) contributed to the study design and protocol.
He wrote the demographic information proforma, patient/GP information letters and
corresponded with the local ethics committee to get ethical approval for the study. SK
corresponded with the MRC to submit annual reports and gaining extensions for the study.
SK identified and recruited the patients for the study at two sites (Wythenshawe Hospital
and Stepping Hill Hospital) where he was working as a clinical lecturer and specialist
registrar. SK performed the initial assessments, blood tests and follow-up assessments with
JC. SK collaborated with Prof. Alan Jackson (Neuro-radiologist) for writing up the MR
protocol. SK collaborated with colleagues at the Wolfson Molecular Imaging Centre
(WMIC), Rainer Heinz (RH) and Karl Hereholz (KH) for writing the PET scan protocol.
The inflammatory marker essays were conducted by SH and his colleagues at Hope
hospital. SK analysed the demographic, blood and neuropsychological with the help of
Andy Vail (AV), Julie Morris (JM) and SH. SK and JC organized the PET and MR scans.
The PET data was analysed by Zhangjie Su and Alex Gerhard at the WMIC and SK
coordinated the results of the clinical, lab and imaging assessments.
No portion of the work referred to in the thesis has been submitted in support of
application for another degree or qualification of this or any other university or other
institute of learning.
7
Copyright Statement:-
i The author of this thesis (including any appendices and/or schedules to this thesis)
owns certain copyright or related rights in it (the “Copyright”) and s/he has given
The University of Manchester certain rights to use such Copyright, including for
administrative purposes.
ii Copies of this thesis, either in full or in extracts and whether in hard or electronic
copy, may be made only in accordance with the Copyright, Designs and Patents
Act 1988 (as amended) and regulations issued under it or, where appropriate, in
accordance with licensing agreements which the University has from time to time.
This page must form part of any such copies made.
iii. The ownership of certain Copyright, patents, designs, trade marks and other
intellectual property (the “Intellectual Property”) and any reproductions of
copyright works in the thesis, for example graphs and tables (“Reproductions”),
which may be described in this thesis, may not be owned by the author and may be
owned by third parties. Such Intellectual Property and Reproductions cannot and
must not be made available for use without the prior written permission of the
owner(s) of the relevant Intellectual Property and/or Reproductions.
iv. Further information on the conditions under which disclosure, publication and
commercialisation of this thesis, the Copyright and any Intellectual Property and/or
Reproductions described in it may take place is available in the University Ip
Policy (see http://www.campus.manchester.ac.uk/medialibrary/policies/intellectual-
property.pdf), in any relevant Thesis restriction declarations deposited in the
University Library, The University Library’s regulations (see
http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s
policy on presentation of Thesis.
8
Acknowledgements
This study was funded by the Medical Research Council and supported by the University
of Manchester.
I would like to thank Professor Alistair Burns, Dr Pippa Tyrrell and Dr Stephen Hopkins
for their support and guidance through all stages of this project. I would also like to thank
and acknowledge the valuable contribution of Mrs Jackie Crowther as a research nurse in
the recruitment, assessments and organization of this project. I am grateful to Dr Zhangjie
Su and Dr Alex Gerhard for their PET data analysis. I am also grateful to Mr Andy Vail
and Miss Julie Morris for their advice with the statistical analysis. I would like to
acknowledge the help offered by the ‘Memory Clinic’ team at the Wythenshawe Hospital
(Manchester Mental Health and Social Care Trust) and Dr Steven Bradshaw and his team
at the Old Age Psychiatry department in Stepping Hill Hospital (Pennine Care NHS
Foundation Trust) for recruitment for this study.
Finally I would like to thank all the participants and their families who agreed to take part
in this study.
9
Dedication
I would like to dedicate this thesis to my wife for her love and support, to my parents who
instilled in me the love of learning and to my children who make my life worthwhile.
10
Abbreviations
Aβ Beta amyloid
AD Alzheimer’s disease
APP Amyloid precursor protein
BMI Body Mass Index
CAMCOG-R Cambridge Cognitive Examination –Revised
COX Cyclo-oxygenase
CRP C-reactive protein
CSF cerebro-spinal fluid
DLB Dementia Lewy Body
ELISA Enzyme linked immuno-sorbent assay
FDG Fluro-deoxyglucose
IL-6 interleukin – 6
IL-I interleukin - 1
LPS Lipopolysaccharides
LREC Local Research Ethics Committee
MCI Mild Cognitive Impairment
MMSE Mini Mental State Examination
MRC Medical Research Committee
NART National Adult Reading Test
NSAIDs Non-steroidal anti-inflammatory drugs
PBM’C Peripheral blood mononuclear cells
PCR Polymerase chain reaction
PET Positron Emmission Tomography
RAGE Recepter for Advanced Glycation End
ROI Region of interest
SPECT Single photon emission tomography
11
SPM Statistical Parametric Mapping
TIA Transient ischemic attack
TNF-α Tumour necrosis factor - alpha
VaD Vascular dementia
WMIC Wolfson Molecular Imaging Centre
12
Chapter 1: Introduction
13
Introduction
The importance of inflammatory processes in the aetiology of Alzheimer’s disease (AD)
and other neurodegenerative disorders is increasingly recognised. The concept that neuro-
inflammation is associated with psychiatric illness is not new and was first suggested by
Wagner-Jauregg in1887 (Edward Shorter, 1997). He hypothesised that infection inducing
agents could be used for treating psychiatric illnesses and studied the possible role of
infection with malarial parasite as a therapy for dementia paralytica. He was subsequently
awarded the first Nobel Prize for psychiatry in 1927 for introducing the unique concept of
the role of inflammation in the causation and treatment of psychiatric illness. Lack of
availability of sophisticated histo-pathological and neuro-chemical technology probably
thwarted further developments at that time.
The last decade has, however, seen a resurgence of interest in the role of neuro-
inflammatory processes in the aetiology of neurodegenerative disorders in general and AD
in particular. Evidence from experimental studies, both animal and human, suggests that
inflammation plays a fundamental role in the pathogenesis of AD. (Eikelenboom et al
2002; McGeer et al, 2007; Tan and Seshadri, 2010).
Search strategy for the literature review
I searched PubMed, Google scholar, Medline and the Cochrane Library for all relevant
articles using the terms ‘Alzheimer’s disease’, ‘mild cognitive impairment’,
‘inflammation’, ‘Non steroidal anti-inflammatory agents’ and ‘PK11195 PET scans’. The
search outcome was then divided into review and original research articles and recorded on
two spread sheets. The review articles were then classified on the basis of subject,
authors/research groups, year and journal of publication. The original research articles
were classified on similar criteria along with sample size and outcome (both positive and
negative outcome studies were included).
14
Mild Cognitive Impairment
Mild Cognitive Impairment (MCI) is a term used to describe a syndrome where an
individual presents with cognitive decline greater than expected from age and educational
level but which does not interfere with every day activities (Gauthier et al, 2006).
Clinically, the person presents with cognitive problems, corroborated by an informant, with
an objective evidence of cognitive impairment but no evidence of dementia, in the absence
of any other illness likely to be the cause of the symptoms. Epidemiological studies of
MCI, based on this broad definition, have reported prevalence figures, in the elderly
population, ranging from 3 to 19% and a risk of developing dementia of 11to33% over 2
years (Ritchie et al, 2004). A study done at the Mayo clinic on a cohort of older people
(mean age 79 years) showed a 12% conversion rate to dementia per year in those with MCI
as compared to 1-2% per year for the rest of the cohort (Petersen et al, 2004). Nearly 80%
of the MCI cohort converted to dementia when followed up for 6 years. These studies
suggest that MCI is a pathological condition and not part of normal ageing. However, other
population based studies have reported that up to 44% of people with MCI become normal
after a year (Ritchie et al, 2004; Ganguli et al, 2004) yet others remain stable, highlighting
the fact that reversible factors such as depression and use of anticholinergic drugs could be
affecting the cognitive performance of older people presenting with MCI (figure1.1; figure
1.2).
15
Figure 1.1: Progression of people from normal funtioning to Alzheimer’s Disease
(Modified from W.B. Saunders).
16
Figure 1.2: Conversion of people having a mild cognitive impairment to dementia over 6 years. Approximately 80% convert to dementia during this time. (Modified from Petersen et al, 2004).
.
Clinically MCI can be classified into amnestic, multiple domain and single non-memory
domain types depending on the area of cognitive deficits with which the patient presents
(Petersen, 2004). Amnestic MCI is characterized by memory complaints corroborated by
an informant, memory impairment relative to age and education, general cognitive decline,
largely intact activities of daily living and no evidence of dementia. Non-amnestic type
MCI presents with cognitive problems in other cognitive domains such as visuo-spatial
deficits (figure 1.3).Studies on amnestic MCI have reported the highest rates of progression
to AD as compared to the general elderly population. In a 3 year multicenter randomized
trial, Petersen et al, (2005) reported a conversion rate of 16 % per year and this was similar
to other studies conducted previously (Grundman et al, 2004). One study (Geslani et al,
2005) reported a conversion rate of 41% after 1 year and 64% after 2 years.
17
Figure 1.3: Progression of the sub-types of mild cognitive impairments to dementia
(Modified from Petersen et al, 2001).
Amnestic MCI, can be considered to represent the transitional period between normal
ageing and very early AD, in other words, a pre AD stage (Burns and Zaudig, 2002).
Studies on this high risk group provide the opportunity to develop early diagnosis and
prevention strategies for AD.
Inflammation
Inflammation is defined as a reaction of living tissue to injury (Robins et al 1981). The
injurious agent can be foreign, like a virus, or part of self, for example a necrotic cell.
Inflammation encompasses the spectrum of patho-physiological responses generated by the
immune system as a response to tissue injury. The inflammatory response is a series of co-
ordinated and regulated chemical and cellular events culminating in repair and resolution.
Sometimes, however, inflammation becomes excessive and persistent resulting in acute
18
and chronic tissue injury and this process is known to play an important role in the patho-
physiology of a number of diseases (Nathan, 2002).
Inflammation has been traditionally divided into acute and chronic types and involves
innate and adaptive immune responses. Innate immune response is characterized by
activation of macrophages, natural killer cells, the complement system and numerous
cytokines and chemokines (Suffredini et al, 1999, Akiyama et al, 2000). The adaptive
immune response uses T and B lymphocytes and specific antibodies.
The process of inflammation can be described as a complex series of interactions between
cells responding to the insult/injury. These interactions are coordinated by numerous
inflammatory mediators including acute phase proteins, cytokines, antibodies, complement
proteins, kinins, histamine, nitric oxide, clotting proteins and lipid mediators including
leukotrienes, protaglandins and platelet activating factor.
Acute phase proteins are released in the acute phase of the inflammation and although a
number of them have been described, C-reactive protein (CRP) is the most commonly
studied. CRP is regarded as a sensitive marker of the acute phase of inflammation and its
plasma concentration can be easily measured.
Cytokines are a large group of regulatory peptides of inflammation. They are up regulated
by mono-nuclear cells or lymphocytes in response to inflammatory stimuli. They exert
their effect on target cells by interacting with specific receptors and inducing gene
expression (Arend, 2002). There are three main groups/families of cytokines including the
interleukin- 6 family (IL-6), interleukin-1 family (IL-1) and tumour necrosis factor (TNF-
α). These play a key role as early mediators of inflammation and are also involved in
regulating multiple steps in regulating the inflammatory response. IL-1 and TNF-α act
locally but IL-6 is released in the peripheral circulation to act at distant sites. Plasma levels
of IL-6 can be measured quite accurately by using immunoassays such as enzyme-linked
19
immunosorbent assay (ELISA) but IL-1 and TNF-α cannot be detected consistently
(Hopkins, 1995).
Cytokines are of particular relevance in clinical research as they have been implicated in a
number of neuro-degenerative disorders including AD (Hirsch et al, 2003; Bermajo et al,
2008).
Neuro-inflammation
Inflammatory reactions in the brain are different from those in the periphery. This is
because of to the brain’s unique innate defence system comprising of glial cells (microglia,
astrocytes) and its isolation from the rest of the body’s immune system due to the blood
brain barrier. Inflammation in the brain is characterised by activation of microglia and
astrocytes, and as in the periphery, is rapidly followed by release of a host of inflammatory
mediators (Lucas et al, 2006).
The term neuro-inflammation is generally used to denote the inflammatory reaction
characterized by the innate immune response involving activated microglia and astrocytes
in the brain. Neuro-inflammation results in chronic and sustained cycles of injury and
response by microglia and inflammatory mediators, for example, complement proteins,
cytokines and chemokines. Emerging evidence in the field of neurobiology suggests that
the cumulative effect of chronic activation of glial cells, particularly microglia, results in
the maintenance and worsening of the disease process (Streit et al 2004).
Neuro-inflammatory mechanisms are implicated in the aetiology and pathogeneses of AD
and other neurodegenerative diseases, for example multiple sclerosis, Parkinson’s and
Huntington’s disease (Akiyama et al 2000, Lue et al, 2001, Streit et al 2004).
20
The amyloidal cascade/neuro-inflammation hypothesis for Alzheimer’s disease
Amyloid deposition has been suggested as the catalyst for a cascade of damage starting
from the deposition of extracellular deposits of beta amyloid (Aβ) leading to neuro
fibrillary tangle (TNF-α) formation and ultimately resulting in neuronal death (Hardy and
Allsop 1991; Selkoe 1996 ) This concept has become more refined with the growing
evidence of the role of neuroinflammation and it is suggested that the Aβ deposits lead to
activation of microglial cells which produce neurotoxic substances such as reactive oxygen
and nitrogen species, proinflammatory cytokines, complement proteins and other
inflammatory mediators that bring about neurodegenerative changes (Akiyama et al 2000,
Eikelenbomm et al 2002, Streit et al 2004, Magaki et al, 2007).
The clinical importance of amyloid hypothesis is twofold. First, it opens a wide range of
avenues to be explored for developing pharmacological treatments (in contrast to the
current limited approach of targeting neurotransmitters) ranging from developing vaccines
for Aβ to the use of anti-inflammatory drugs (Akiyama et al 2000). Second, there is
potential for early diagnosis in people at risk (MCI) or in the very early stage of the disease
with laboratory or imaging techniques to detect and localise early signs of
neuroinflammation. Moreover as Aβ deposition is also seen in normal ageing and other
dementias such as Dementia with Lewy bodies (DLB), an understanding of the role of
neuro-inflammation could lead to the development of new pharmacological interventions
in these conditions (Figure 1.4).
The evidence for the role of neuroinflammation in AD comes from a wide range of
research areas including post-mortem histo-pathological studies, animal model studies,
genetic and gene expression studies, epidemiological studies on use of anti-inflammatory
agents, studies on the biological markers of inflammation and their association with AD,
and more recently neuro-imaging studies aiming at studying evidence of inflammation in
brains of living subjects.
21
Figure 1.4: Beta-amyloid plaques induce neuroinflammation as characterized by glial
activation and elevation in local pro-inflammatory cytokine production (Google images,
2011).
Neuro-inflammation in Alzheimer’s disease
The extra-cellular deposition of Aβ in the form of amyloid plaques in AD triggers a
chronic inflammatory reaction (Akiyama et al, 2000, Wyss-Coray and Mucke, 2002; Lucas
et al, 2006). The bulk of evidence comes from a number of in vitro studies showing that
Aβ aggregates can activate a variety of inflammatory pathways. For example, Aβ
deposition is well known to trigger microglial activation (Sheng et al, 1998) by binding to
the Receptor for Advanced Glycation End products (RAGE), scavenger receptors and
signalling receptors such as CD40 (Yan et al, 1999; Paresce et al, 1996; El Khouray et al,
22
1996; Tan et al, 1999). Aβ fibrils can also bind to RAGE on neurons resulting in the
release of inflammatory factors (Yan et al, 1999). Aβ deposits have been shown to activate
the complement system in vitro through the classical pathway by binding C1q and through
the alternative pathway by binding C3b (Rogers et al, 1992; Webster et al, 1997; Bradt et
al, 1998). Shen et al (2001) showed that neuro fibrillary tangle preparations from human
AD brains can also activate the complement pathway. The role of different inflammatory
pathways and their importance as biological markers will be discussed in the next section.
Cytokine Pathways
Cytokines are proteins which act as chemical messengers between the immune cells
stimulating or inhibiting their growth and activity both in brain and periphery. Their
persistently increased levels in plasma can be an indication of a chronic inflammatory
process including AD. Most commonly studied cytokines includes interleukin -1 (IL-1),
interleukin- 6 (IL-6) and tissue necrosis factor alpha (TNF-α).
IL-1 has been shown to be over expressed in plaque formation areas of AD brains (Griffin
et al 1995). The over expression of IL-1 occurs even in the early stages of plaque
formation (Griffin et al 1998) and also promotes the production of amyloid precursor
protein (APP) thus suggesting its possible role in initiating the cycle of excessive amyloid
deposition leading to plaque formation that in turn activates microglia to further IL-1
formation (Goldgaber et al 1989; Barger et al 1997).
IL-6 is another important mediator of immune responses in the central nervous system. It is
barely detectable in normal brains but is strongly over expressed by microglia, astrocytes
and neurons in pathological conditions (Valieres et al 1997; Van Wagoner et al 1999). A
number of pathological studies on AD brains have shown increased IL-6 immunoactivity
in areas with localised diffused (early) plaque formation in AD brains) and less
immunoactivity in classical (established) suggesting its possible role in early plaque
23
formation (Bauer et al 1991; Hull et al 1996). It is also known to increase Aβ production
influencing the amyloid precursor protein expression (figure 1.5).
TNF-α .is a messenger protein that plays a key role in promoting inflammation both in
brain and the periphery. It controls the production of other proinflammatory molecules and
also helps in cellular healing and repair. A number of studies have shown elevated levels of
TNF-α in peripheral blood and cerebral cortex of AD patients (Fillit et al 1991; Darkowski
et al 1999). It has shown to increase the expression of the amyloid precursor protein and
Aβ (Lucas et al, 2006), kill cells, and modulate neuro-transmission (Stellwagen and
Malenka, 2006) (figure 1.5).
Figure 1.5: Accumulation of amyloid plaques and associated inflammation response
resulting in release of pro-inflammatory cytokines such as IL-1beta, IL-6, and TNF-alpha
(Google images, 2011).
24
In summary, the combination of increased cytokine production and Aβ aggregation appears
to play a causal role in neuronal degeneration ( Licastro et al 2003 and Reale et al 2004).
The levels of IL-6 and TNF-α can be measured accurately in peripheral blood and cerebro-
spinal fluid and can potentially be used as markers of disease progression.
Complement Pathway
The complement pathway is divided into classical and alternate types. The classical
pathway is made of about twenty proteases that can be activated one after the other as an
amplifying cascade. The final result of its activation is the opening of transmembrane
channels at the surface of the neurons resulting in free movement of ions and small
molecules in and out of the cell causing disruption of cellular homeostasis and ultimately
cell death.
Beta amyloid and neurofibrillary tangles can activate both, the classical and alternative
complement pathways (Rogers et al 1992 and 1998). The complement proteins from both
these pathways have been shown to interact with beta amyloid to form dissociation
resistant complexes in senile plaques (Bradt et al,1998). Complement proteins attract
inflammatory cells (microglia and astrocytes) which lead to an aggregation of these cells in
areas of plaque formation (McGeer et al 1989; Shen et al 1997). Microglia and astrocytes
can also produce all the complement proteins when activated and their production has
shown to be up regulated in AD brains (Lue et al, 1997).
In summary, the evidence in AD brains of a cycle of increased beta amyloid production,
activation and increased production of complement proteins and aggregation of microglia
and astrocytes is suggestive of a chronic state of inflammation (Akiyama 2000; Wilson et
al 2002; Robert and Griffin, 2005).
25
Chemokine System
Chemokines induce movement of inflammatory cells towards the site of inflammation and
constitute a large family of polypeptides (more than 50 have been identified so far).
Increased expression of chemokines and their receptors have been reported in a wide range
of CNS illnesses for example multiple sclerosis, infection, trauma and stroke (Glabinski et
al, 1999) but more recent studies on AD brains have shown evidence of increased levels of
some chemokines (monocyte chemo-attractant protein-1 and IP-10) and their receptors
close to areas of senile plaque formation (Strohmeyer and Rogers 2001).
Cyclo-oxygenase
Cyclo-oxygenase (COX) is an enzyme that plays a crucial role in the synthesis of
prostaglandins, which play a key role in the regulation of inflammatory processes. NSAIDs
are known to exert their inhibitory effect on inflammation through inhibition of COX.
Some studies have suggested that pro-inflammatory mediators such as IL-1 and TNF-α
regulate COX expression to amplify the inflammatory reaction. Indirect evidence of the
importance of COX’s pivotal role in regulating the inflammatory processes come from the
epidemiological studies on NSAIDs showing their protective effect and the histochemical
studies reporting their increased expression by neurons and microglia in AD brains
(Kitamura et al 1999; Yermakova et al 1999).
Other Factors
A number of other mediators of inflammation (blood coagulation factors, fibrinolysins,
acute inflammatory phase proteins and free radicals) have also been reported to be
overactive in AD brains (Akiyama et al, 2000; Tuppo et al, 2005)
26
Importance of Biological Markers
The importance of biological markers of inflammation in AD from a clinical point of view
rests on the fact that they could potentially act as markers of disease presence or severity.
As a result, the concept of the “ideal bio-marker” for AD has been postulated (Nancy and
Ronald Reagan Research Institute of the Alzheimer’s Association (1998). An ideal
biomarker would be:
(a) Directed at the fundamental CNS patho-physiology of AD.
(b) Validated in neuropathologically confirmed cases
(c) Would mark more than increased risk of disease
(d) Would mark the presence of the disease itself
(e) Would track disease severity at early or pre clinical stages
(f) Should have a diagnostic sensitivity of more than 80% for detecting AD
(g) Should have a specificity of more than 80% for distinguishing other dementias
(h) Should be reliable, reproducible, non-invasive, simple to perform and inexpensive.
No such “ideal biomarker” is known to exist. Plasma and cerebrospinal fluid (CSF) levels
of inflammatory markers, such as IL-6, may provide some information about peripheral
and central inflammation but do not fulfil these criteria.
Current evidence for biomarkers of inflammation in Alzheimer’s disease
Based on the above mentioned evidence of increased inflammatory activity in AD it is
logical to look for evidence of increase in the levels of inflammatory markers such as
cytokines both in the centre and periphery. Most studies have looked for evidence of raised
cytokine levels in the cerebro-spinal fluid (CSF) and peripheral blood. Others have
investigated the cytokines released by the peripheral blood mono-nuclear cells (PMBCs).
27
CSF markers of inflammation in Alzheimer’s disease and Mild Cognitive Impairment
Although the CSF cytokine levels are more likely to be closely correlated with brain levels
but they are less practical and difficult to conduct prospectively. The initial studies such as
Lanzerin et al (1998) and Engleborghs et al (1999) were small in sample size and did not
report any differences in inflammatory marker levels between AD patients and controls.
Tarkowski et al (1999) compared AD, vascular dementia (VaD) and controls. They
reported a 25 fold increase of TNF-α in AD group. In a more recent study (Tarkowski et al,
2003) compared 56 mild cognitive impairment (MCI) patients with 25 controls and
reported increased TNF-α in the MCI group. Martinez et al (2000) reported an increase in
the IL-6 levels in CSF of AD patients and Tarkowski et al (1999) reported a correlation
between the IL-6 levels and Tau protein levels in CSF of AD patients.
Blood markers of inflammation in Alzheimer’s disease and Mild Cognitive
Impairment
Peripheral Blood
A number of population based studies have reported an association of IL-6 and CRP levels
in peripheral blood with cognitive decline. Schmidt et al (2002) in the ‘Honolulu-Asia
Aging’ study reported a three fold increase in relative risk of developing dementia with
increasing serum CRP levels. Yaffe et al (2003) in a longitudinal prospective study of a
population based sample reported that base baseline IL-6 and CRP levels were associated
with poor cognitive performance both at baseline and follow-up. A similar study by
Engelhart et al (2004) reported increased risk of dementia with increase in baseline levels
of CRP and IL-6.
Studies investigating peripheral blood levels are easier and less invasive than CSF studies.
There is however a debate in the scientific community about the link between the serum
cytokines levels and central inflammation although some research evidence exists that
28
shows links between central inflammation and serum cytokine levels. Song et al (2001)
reported that after intra-cerebral administration of Aβ 1-42, IL-6 gene expression increases
not only in brain but also in many peripheral organs.
Studies investigating blood levels, like CSF studies, have reported mixed results with some
showing no difference between AD patients and controls (Lombardi et al, 1999) and others
(Kalman et al, 1997; Licastro et al, 2000; Reale et al, 2004) showing raised IL-1, IL-6 and
TNF-α in AD patients. However, there may be issues such as sampling time (e.g. diurnal
variation), concurrent infection or medication that may affect cytokine concentrations in
serum and CSF, and the relationship between plasma and CSF levels remains unclear.
Peripheral Blood Mononuclear Cells (PMBCs) studies:
PMBCs consist of lymphocytes (85%) and monocytes (15%) and can be stimulated to
release cytokines in response to mitogens such as lipopolysaccharides (LPS) and
phytohemagglutinin (PHA). They have been used for modelling CNS microglial responses
in other illnesses such as multiple sclerosis. Research in this area has again shown mixed
results but more recent studies have shown an increased release of cytokines both in AD
and MCI patients (Guerreiro et al, 2007; Magaki et al, 2007). Two studies (Reale et al,
2004 and Gambi et al, 2004) have reported a decrease in cytokine levels after treatment
with Donepezil in AD patients and an increase in IL-4 which is believed to be ‘anti-
inflammatory’ or an antagonist to the pro-inflammatory cytokines.
In summary, there is some evidence from the current literature that cytokine levels in
serum or CSF may have a role as biomarkers of MCI or AD but there have been few large
systematic studies.
29
The role of anti-inflammatory drugs in the development and progression of Mild
Cognitive Impairment and Alzheimer’s disease
The discovery of activated microglia in the close vicinity of the senile plaques and tangles
in a number of histo-pathological studies lead to the hypothesis that people on long term
use of anti-inflammatory agents may be protected form the chronic brain inflammation in
AD. This lead to a number of epidemiological studies looking at case records of patients
suffering from various types of arthritis (arthritis, osteoarthritis and rheumatoid arthritis)
who were on long term treatment with anti-inflammatory medication.
A number of case control and clinical series indicated that regular use of anti-inflammatory
agents was associated with an estimated six fold sparing of AD as compared to age
matched people in general population (1996, 2006). As non-steroidal anti-inflammatory
agents (NSAIDs) were the most commonly used anti-inflammatory agents further studies
were focused on their use.
NSAIDs and Alzheimer’s disease pathology
NSAIDs are known to exert their anti-inflammatory effects by decreasing the production of
the key inducers of inflammation - prostaglandins and thromboxanes. Their direct target is
cyclooxygenase which has two common forms COX-1 and COX-2 and they vary in their
ability to inhibit these two forms (Kaufman et al, 1997). Traditional NSAIDs like aspirin
inhibit COX-1 and have a variable action on COX-2. They may also inhibit
neuroinflammation by target -secretase, an enzyme required for the generation of A
peptides, and decrease the production of the more toxic and fibrillogenic A 42. Aside from
these effects, neuroinflammation and disease progression may also be influenced by
NSAIDs acting on peripheral cells or immune cells, thereby altering the production of
growth factors and cytokines, which can act across the blood-brain barrier (Tony Wyss-
Coray, 2005) (figure 1.6).
30
Newer drugs like celecoxib have a selective action on COX-2 and have fewer gastric side
effects. There has been a debate in literature about whether conventional COX-1 inhibiting
NSAIDs are more relevant to inhibition of inflammation in AD as compared to the newer
COX-2 inhibitors. COX-1 has been shown to be up regulated in reactive microglia
(Hoozemans et al, 2002) but COX-2 has not yet been detected in AD microglia
(Hoozemans et al, 2003). This may suggest that NSAIDs with COX-1 inhibitory properties
are more likely to reduce brain inflammation selectively (McGeer, 2006).
Figure 1.6: NSAIDs and neuroinflammation in Alzheimer’s Disease. Modified from Tony Wyss-Coray (2005).
31
A post-mortem study (Mackenzie, 1998 & 2001) reported that arthritis patients using
conventional NSAIDs showed a three times reduction in the number of activated microglia
as compared to normal controls without arthritis and long-term NSAIDs use. It was also
noted that NSAID use did not alter the number of amyloid plaques and tangles in both
groups.
NSAIDs and animal models of Alzheimer’s disease
Transgenic mice are the most commonly used animal model for AD. Although all such
studies have the inherent disadvantage of applying an animal model to human disease, they
also have a number of advantages like controlling the type, dose and duration of NSAID
used.
Lim et al (2001) showed that, in APP transgenic mice, 6 months treatment with ibuprofen
lead to reduction in amyloid plaque numbers and microglial activation around plaques and
the expression of inflammatory markers interleukin-1β (IL-1β). Other studies using
ibuprofen and indomethacin showed similar results (Jantzen et al, 2002; Yan et al, 2003;
Quinn et al, 2003). Out of two studies with the newer COX-2 inhibiting NSAID
(celecoxib), one did not show any benefit (Jantzen et al, 2002) and the other showed a
substantial increase in amyloid deposition (Kukar et al, 2005). This disparity between the
outcomes of the use of COX-1 and COX-2 inhibiting NSAIDs probably suggest that COX-
2 inhibition is the wrong target for reducing inflammation in AD brains or NSAIDs like
ibuprofen act through other pathways to reduce amyloid production (Weggen et al, 2001;
Yyss-Coray et al, 2006; Sastre et al, 2006).
Disease modifying role of NSAIDs
McGeer et al (1996) reviewed 17 epidemiological studies and reported an overall odd ratio
of 0.475 for NSAID use and AD. Two other studies conducted in the early 90’s, one,
32
comparing NSAID users and non-users AD patients showed significantly slower disease
progression in users (Rich et al 1995) and the other a double blind placebo controlled trial
of indomethacin in AD patients over six months showed significantly less cognitive
decline in users as compared to the placebo group (Rogers et al 1993). A prospective study
conducted in Baltimore comparing users and non-users of NSAIDs reported a relative risk
of 0.50 among users (Stewart et al 1997).
In contrast to the above, 2 subsequent major studies showed no evidence of benefit from
use of NSAIDS in AD. Beard and colleagues (1998) in a case control study of around 300
new onset AD patients with 300 controls found no association between the disease and
NSAIDs use in the 2 years prior to onset. The Rotterdam study group (in 't Veld et al,
1998) in a three year prospective study of 74 AD patients and 232 matched controls found
no association between NSAID use and risk of incident AD. An explanation for these
apparently conflicting results from different studies can be inferred from a large long term
prospective study (N=6989) (Velt et al, 2001). The risk of AD was estimated in relation to
the use of NSAIDS for short term (less than a month) intermediate term (1-24 months) and
long term (24 months or more). Results showed that the relative risk of AD was 0.20 in
those with long term use but no major difference between short and intermediate term use
was found. This suggests that short term NSAID use may not be protective against AD.
This also suggests that the apparent protective affect of NSAIDs against AD is limited to
their use 2 or more years before the onset of dementia (Brightener and Zandi 2001).
The dose of NSAIDS or aspirin does not appear to be crucial and these medications taken
in low doses could be equally effective (Broe et al 2000; Anthony et al 2000). Englehart, et
al (2003) in a systematic review of 9 studies reported a relative risk of 0.27 amongst people
who are users of NSAIDS for more than 2 years. A more recent study comparing a
traditional non selective NSAID (naproxen) with a selective COX 2 inhibitor (Rofecoxib)
in patients with mild to moderate AD over a period of one year showed no evidence for
33
the slowing of cognitive decline in AD patients compared with placebo suggesting that
NSAIDS may be more beneficial in prevention rather than in established disease.
Other Anti-inflammatory Agents
Steroids or synthetic glucocorticoids are known to be important anti-inflammatory agents
but their action on the central nervous system has been shown to have different short term
and long term consequences. In short term, treatment with glucocorticoids has been shown
to attenuate post traumatic and post ischemic neuronal damage (Cacabelos et al 1994) but
long term exposures can prevent recovery from brain injury (Morse et al 1992 and Woods
et al 1999). A randomised placebo control trial of use of low doses of prednisone or
placebo in a group of 138 subjects with AD did not show any difference in the rate of
decline (Aisen et al 2000).
Use of other anti-inflammatory drugs such as hydroxychloroquine, vitamin E and
selegilene did not show benefit on the progression of AD (Van Gool et al 2001; Sano et al
1997).
Use of neuro-imaging in the diagnosis and assessment of Mild Cognitive Impairment
and Alzheimer’s disease:
Structural neuro-imaging
The use of neuro-imaging as a diagnostic and assessment tool in AD has evolved with the
advancements in neuro-imaging techniques over the last few decades. A number of studies
using Cat-axial Tomography (CT) scans and Magnetic Resonance (MR) imaging have
shown promising results in helping with the diagnosis and progression of established AD.
Moreover MR techniques using hippocampal volume measures have been shown to have a
high correlation with cognitive decline in people with AD as compared to general
population (Mueller and Dickerson, 2008). However the structural decline in hippocampal
34
volume does not appear to be linear during the progression from MCI to AD. In MCI the
volumetric measures by MRI have a less predictive accuracy for progression to AD and
functional neuro-imaging holds promise in detecting and diagnosing very early functional
changes that precede the full blown clinical picture in AD.
Functional neuro-imaging
Positron Emission Tomography (PET) is a technique in which the uptake of radio-labelled
tracer molecules into the brain can be quantitatively measured to obtain regional
measurements. PET provides the opportunity to study brain function in vivo and the most
commonly used tracer is Fluoro-deoxyglucose (FDG) (Herholz, 2003; Foster et al, 2007).
Its uptake by the brain reflects glucose consumption which is closely related to neuronal
function as glucose is the energy source for neurons to maintain ionic gradient and
synthesize neurotransmitters. PET FDG studies suggest that it can provide a better
prediction of conversion from MCI to AD as compared to structural imaging (Herholz,
2003) which could be useful for clinical use in future. It however lacks the specificity with
regards to the molecular mechanisms of functional decline in AD. The development of
newer radiolabelled tracers that bind specifically to receptor subtypes allows the
quantitation of receptor numbers and occupancy (Banati, 2002).
Imaging inflammation in the Brain:
Measuring inflammatory processes in life with imaging has become possible recently due
to the development of PET tracer molecules that bind specifically to activated microglia.
As microglial activation is closely linked and anatomically confined to the sites of
inflammation they can be used as a target for clinical imaging (Banati, 2002). The process
of activation of microglia from their normal resting state is associated with an increased
expression of certain receptors cites which can act as binding cites for radio-active ligands.
35
Two different types of receptors sites have been described in activated microglia including
the benzodiazepine (Gavish et al, 1999) and cannabinoid receptors (Cabral and Cabral,
2005).
The benzodiazepine binding cite has a strong affinity for the radio labelled ligand
PK11195. PET scanning with PK11195 provides the opportunity to detect areas of
increased microglial activity in patients with a variety of disorders.
Acute and long term activation of microglia using PK11195 has been shown in herpes
encephalitis (Cagnin 2001), peripheral nerve injuries (Banati et al 1997), ischemic stroke
(Pappata et al 2000), vasculitis (Goerres et al 2001), and multiple sclerosis (Banati et al
2000). The data on AD and MCI is limited and summarised in table 1.1.
36
Table 1.1: PK11195 studies in Alzheimer’s disease and Mild Cognitive Impairment
Author Patients (N) Controls (N) Design Outcome Comments
Groom et al, 1995
Cagnin et al, 2001
Versijpt et al, 2003
Edison et al, 2008
Okello et al, 2009
Clayton et al, 2009
8 AD* Patients
8 AD patients
1 MCI** patient
10 AD patients
13 AD patients
13 MCI patients
6 AD patients
6 MCI patients
1
15
9
10
No controls
5
Cross sectional
Cross sectional
Cross sectional
Cross sectional
Cross sectional
Cross sectional
No difference in PK11195 binding with control.
Increased cortical PK binding in AD patients.
Intermediate PK binding in MCI subject.
Increased cortical PK binding in AD patients.
Increased cortical PK binding in AD patients.
Increased PK binding in 5 out of 13 MCI patients.
No difference in PK binding between MCI and control subjects.
First study with PK11195 in AD patients.
Only 1 MCI subject.
Potential for further studies in MCI.
Usefulness of PK in measuring microglial activation.
PK binding correlated with MMSE scores.
Used broader criteria for MCI.
Used broader criteria for MCI
*Alzheimer’s Disease **Mild Cognitive Impairment
37
In an initial small study of AD Groom et al (1995) did not find an increase in binding of
PK11195 in mild to moderate AD cases but subsequent studies using more refined
techniques showed more promising results.
Cagnin et al (2001) studied 8 AD patients, 1 MCI patient and 15 healthy controls from
ages 30-80 years. They reported increased uptake in widespread brain regions including
temporal lobe, left parahippocampal gyrus left amygdala, left posterior cingulate gyrus,
fusiform gyrus and inferior parietal lobe. The regional distribution of PK11195 uptake was
correlated with the regional volume loss over 12 to 24 months seen on MR imaging and
also with decreased blood flow on PET FDG. In the single MCI patient the uptake was
intermediate between controls and AD.
In a comparable study Versipjt et al (2003) used PK 11195 as a ligand for single photon
emission tomography (SPECT) and reported increased uptake in AD but in a different
regional distribution with frontal lobes more involved. They also reported a significant
relationship between regional increased uptake of PK11195 and cognitive deficits on
neuropsychological testing.
Two studies have been reported in the literature on MCI subjects with PK11195 and have
drawn somewhat conflicting conclusions. Okello et al (2009), in 13 subjects with MCI,
reported that microglial activation could be detected in MCI subjects and 5 subjects
showed a higher uptake of PK11195 as compared to healthy controls. A similar but smaller
study by Clayton et al (2009), in 6 subjects with MCI, did not find any difference in
PK11195 uptake compared with healthy controls and AD subjects.
The limited evidence available suggests that microglial activation might play a role in all
the stages of AD including MCI and PET using PK11195 is able to provide in vivo
imaging evidence of microglial activation. However larger studies including all stages of
AD (from mild cognitive impairment to established dementia) are required to determine
38
whether PET with PK11195 can be used as a diagnostic tool in the early detection and
diagnosis of the disease, and to identify those at high risk.
Conclusion:
There is good evidence to suggest that inflammatory processes play an important role in
the pathogenesis of AD. Raised inflammatory markers in peripheral blood and activated
neuroglia in vivo using PET have been studied in established AD and provide an
opportunity to study people with MCI who are at a high risk of developing the disease.
Further studies are needed to study the peripheral makers of inflammation and microglia
activation in MCI and their possible use in early diagnosis and progression of AD.
Aims
This study aimed to investigate the peripheral and central inflammatory markers in a group
of participants with amnestic MCI.
Hypothesis
1. Cognitive decline in people with amnestic mild cognitive impairment is associated with
a chronic inflammatory process.
2. IL-6 and CRP levels in peripheral blood and PK11195 binding measured by PET can be
used as markers of the inflammatory process.
39
Chapter 2: Methods
40
Ethics
Ethics approval was obtained from the South Manchester and Stockport Local research
ethics committees (LREC) for recruitment of patients. Permission to administer PK11195
at the WMIC was obtained from the Administration of Radioactive Substances Advisory
Committee (ARSAC) of the United Kingdom.
Methods
Study population (figure 2.1)
The participants were recruited from the Memory Clinic at Wythenshawe Hospital in
South Manchester (Manchester Mental Health and Social Care Trust) and the Old Age
Psychiatry services at Stepping Hill Hospital (Pennine Care NHS Foundation Trust) in
Stockport (figure 2.1). They were invited to participate in the study via an information
letter sent by post (appendix 1). They were also provided an opportunity to see SK or JC
along with their family members to clarify any details of the project. Written informed
consent (appendix 3) for participation and genetic testing was obtained by SK and JC at the
time of recruitment. General Practitioners (GPs) were sent information letters about their
patient’s participation in the study (appendix 2). Personal and nominated consultees assent
forms were also designed in line with the Mental Capacity Act (appendix 4 &5).
All participants underwent a comprehensive assessment process by a multidisciplinary
team including a senior old age psychiatrist and psychologist. The initial assessment
involved detailed history taking, neurological examination, cognitive assessment, routine
blood tests and CT brain scans. A diagnosis of amnestic mild cognitive impairment was
established using Petersen’s criteria for MCI (Petersen et al 2005).
41
Inclusion Criteria
• Memory complaint corroborated by an Informant
• Memory impairment relative to age-matched and education-matched healthy
people
• Typical general cognitive function
• Largely intact activities of daily living
• Not clinically demented
Exclusion Criteria • Established AD or other neurodegenerative disorders
• Vascular dementia
• History of chronic/recurrent inflammatory disease
• History of auto-immune disease
• Depression
• Severe mental illness
Cerebro-vascular pathology
All potential participants were assessed for the possibility of cerebro-vascular disease’s
contribution to the cognitive decline in the multi-disciplinary assessment. People with
vascular dementia were excluded along with those where cerebro-vascular disease was
considered to be the main cause of cognitive decline. People with vascular factors were
however not excluded as they are recognized risk factors for AD.
42
Figure 2.1: Recruitment
12 0 Patients approached
81 Agreed to participate
70 Patients Consented/recruited
8 Dropped out (2 died, 3 moved out of area, 3 withdrew consent)
62 Patients reviewed after 12 months
30 Patients agreed for scans (PET and MR)
16 dropped out (10 withdrew consent, 2 dropped out, 1 DNAed, 3 scans failed due to low PK yield)
14 Patients scanned
43
Study entry assessment
The baseline assessment included collection of demographic and clinical information,
brief physical examination, administration of infection screening questionnaire,
venepuncture for blood samples and neuropsychological assessments.
Demographic/Clinical information
The demographic information included age, sex, ethnicity and address. The clinical
information was obtained both from the participants and their case notes and included the
following:
• Vascular risk factors: smoking, hypertension, diabetes mellitus, dyslipidemia,
coronary artery disease, atrial fibrillation, previous transient ischemic attack
(TIA)/stroke.
• History of any infection or serious health problem in the past 6 weeks.
• Current list of medication
Physical examination
The physical examination included a record of height, weight, temperature, pulse rate and
rhythm, blood pressure and body mass index (BMI).
Venous blood sampling
Venous blood samples (15 mls) were taken for the plasma measurement of IL-6 (measured
using a sandwich ELISA) and CRP (using a high sensitivity competitive ELISA) and
Apolipoprotein E status (measured by PCR). A small amount of the blood sample was
stored, with appropriate consents, for possible use in future research.
A standard protocol (appendix 7) was observed for all the venous blood sample/processing
(Collection time 9 a.m. to 12:30 p.m).
44
Measures taken to reduce the possibility of false positive results:
• To avoid measurement of inflammatory markers that might be attributable to acute
events the participants were encouraged to report any acute physical health
problem/infection at the time of organizing the appointment for both baseline and
follow-up assessment. The assessment was delayed for 2 weeks if an acute event
such as infection was reported.
• The patients were administered an infection screen questionnaire (appendix 6) to all
the participants, on the day of assessment, both at baseline and follow-up. This
questionnaire is a check list of possible infections over the last 6 weeks along with
a record of the details of infection including type, duration and treatment. The
blood sample taking was delayed for 2 weeks if the participants scored positive on
the infection screen.
• On baseline and follow-up assessments, if the CRP or IL-6 concentrations were
raised above 3mg/l, a second sample was taken after an interval of at least 6 weeks.
The lower of the two readings was considered for the data analysis. For both CRP
and IL-6 reading a total of 16 samples were repeated both at baseline and follow-
up.
Neuropsychological assessments
A battery of neuropsychological tests including the following instruments was
administered:
1. Mini Mental State Examination (MMSE), Folstien et al (1975): It is a brief 30-point
questionnaire assessing various cognitive domains including orientation in time and place,
concentration, arithmetic, recall, language use and comprehension, visuo-spatial tasks and
45
basic motor skills. It is internationally validated for use both as a screening instrument for
dementia and to estimate the severity of cognitive impairment at a given point in time.
2. Cambridge Cognitive Examination-Revised (CAMCOG-R), Roth et al (1999). It is a
comprehensive neuro-psychological test which forms part of the Cambridge Examination
for Mental Disorders of the Elderly (CAMDEX), Roth et al, 1986. It has 105-points and
allows the assessment and comparison of eight ‘domains’ of cognitive function including
orientation, comprehension, expression, memory, attention, calculation, praxis, abstract
thinking and perception. A score of 80/105 is suggestive of cognitive impairment. One of
its major advantages is the ability to detect mild forms of cognitive impairment.
3. National Adult Reading. Test (NART), Blair & Spreen (1989). It is a widely
used instrument for estimating pre-morbid level of intellectual ability in people with
brain damage and dementia. The test requires subjects to read out loud a set of 50 words
which are irregular in terms of their grapheme- phoneme correspondences (Coltheart et al,
1987). The responses are individually scored as correct or incorrect, according to their
pronunciation. This score can then be used to derive a pre-morbid IQ estimate.
4. Free and Cued Recall Selective Reminding Test (FCRSRT), Buschke, (1984). It has
been widely used to identify prevalent dementia, predict future dementia, identify those
patients with MCI destined to develop AD and distinguish AD from nonAD dementias
(Grober et al, 2011). Unlike most other memory tests, the FCSR begins with a study phase
designed to control attention and cognitive processing to identify memory impairment that
is not secondary to other cognitive deficits. Patients identify pictured items (e.g., grapes,
vest) in response to category cues (fruit, clothing). In the test phase, subjects are asked to
recall the items they learned (free recall). The category cues are used to prompt recall of
46
items not retrieved by free recall to generate a score termed cued recall. The sum of free
and cued recall is termed total recall. These procedures are based on the theoretical concept
that controlled learning remediates the mild retrieval deficits that occur in many healthy
elderly individuals but has only modest benefits in patients with dementia, thus enhancing
the FCSRT's discriminative validity for the diagnosis of dementia in comparison to tests
that do not control the conditions of learning.
5. Verbal fluency test (FAS), Spreen and Strauss (1998). It is a widely used test of frontal
lobe/executive function where the participants are asked to tell as many word as possible
starting with letters F, A and S. A total score of 30 is considered normal.
6. Cognitive Estimation Test (CET), Axelrod and Millis (1994). This instrument measures
cognitive estimation/executive skills. The participants are asked questions that require
individuals to make approximate judgments using deductive reasoning and problem-
solving skills. The scoring is based on the degree to which an individual’s response
deviates from the mean standardized responses. Possible scores for the CET range from 0
to 20 points, with higher scores representing greater deviation from the responses given by
the normative sample.
Follow-up assessments
Eight participants dropped out and 62 were re-assessed after an interval of about twelve
months. The assessment included clinical information, a brief physical examination, and
administration of infection screening questionnaire, venous blood sample and
neuropsychological assessments.
47
Brain scans
At the time of recruitment for the study we planned and identified 30 participants for
scanning. Unfortunately there was a delay of more than 24 months in starting the PET
scans at the WMIC. This resulted in a number of methodological and practical difficulties
in carrying out the scans. A number of patients became unavailable for brain scans. Ten
participants withdrew consent, 2 dropped out, 1 did not attend, 3 scans failed due to low
PK11195 yield on the day of scanning. We were able to do 14 successful scans.
On the day of scanning the participants had a physical examination, an infection screen and
blood test for inflammatory markers on the day of scanning and blood was collected on a
subsequent occasion (>6 wk later) for CRP and IL-6 measurement if the initial values were
higher than 3mg/l. All the participants gave written informed consent prior to the scanning.
The MR scans were done with in 2 weeks of PET scans for structure- function co-
registration and excluding structural lesions.
Power calculation and statistical analysis
We used linear regression to establish that 70 participants would provide an 80% chance of
identifying a correlation of at least 0.33 between inflammatory markers and cognitive
decline. Thirty participants would be sufficient for the microglial activation studies to
provide an 80% chance of identifying a correlation of at least 0.50 between either
PK11195 binding and inflammatory markers or between PK11195 binding and cognitive
decline.
In order to analyse the data for an association between inflammatory marker levels and
cognitive decline we encountered the problem of having two inflammatory marker scores
(CRP and IL-6) which are strongly correlated. We calculated a ‘combined inflammatory
score’ that would provide a combined measure of the inflammatory burden by the
following statistical methods:
48
Step 1. ̀'Normalise' values for each inflammatory marker by taking natural logarithms of
the value.
Step 2. 'Standardise' each inflammatory marker by subtracting the mean and dividing by
the SD. The standardised value, or "Z-score", measures how many standard deviations
above or below the mean each individual's value is.
Step 3. Average these z-scores to give a combined measure of inflammatory burden.
The data was analysed using SPSS to look at demographics, changes in inflammatory
marker levels and neuropsychological tests scores over the follow-up period. We used
regression analyses to look at the relationship between inflammatory markers levels and
cognition and controlled for the confounding role of demographic/baseline features.
PET data analysis:
From each subject’s raw imaging PET data, comprising of 18 frames in 60 minutes, a
summative image was obtained using Linux windows PET data processing programme.
The summed PET images and MR scans of each subject were co-registered by using
software package Vinci (Max-Planck Institute for Neurological Research, Cologne,
Germany).
Statistical parametric mapping (SPM5, Functional Imaging Laboratory, Wellcome
Department of Imaging Neuroscience, University College London, UK) was used for
segmentation of the co-registered images into grey matter and white matter images. Object
maps of these images were created by using the Hammersmith Brain Atlas maximum
probability map (Hammers, et al. 2003) and ‘Analyze’ software (Analyze AVW, Mayo
Clinic, Rochester, US). This process created an individualized anatomic brain atlas with 83
regions for each subject which is later used to sample BPND values from the parametric
images of binding potential (BP). BPND represents the ratio of specifically bound
radioligand over non-displaceable ones in tissues at equilibrium. In reference tissue models
49
it compares the concentration of radio-ligand in receptor-rich and receptor-free regions.
Parametric images of BPND were generated using a simplified reference tissue model
(SRTM), using the software ‘RPM the basis function implementation of SRTM’ written in
Matlab (The Mathworks Inc., Natick, MA). BPND values were estimated using the SRTM
with a supervised clustering algorithm to extract a reference tissue input function. We
chose the appropriate reference region by fitting the time-activity curve of each pixel with
a database of tissue kinetics (normal gray and white matter, blood pool, muscle, skull, and
pathologic tissue with high benzodiazepine receptor density) and defined a reference grey
matter tissue devoid of specific benzodiazepine receptor binding (Turkheimer et al. 2007).
We applied the whole brain and grey matter object map to extract region of interest (ROI)
data from the BPND parametric images. The groups mean BPND values were sampled using
the ‘Analyze’ software in the following regions of interest: temporal lobe, parietal lobe and
association cortices, frontal lobe, occipital lobe, posterior cingulate gyrus and putamen.
Statistical comparison of BPND values in ROIs between MCI subjects and healthy controls
was performed using Wilcoxon rank sum test in Matlab.
To compare binding of PK11195 in all the MCI patients with controls the individual
parametric images of BPND were normalized and spatially smoothed. Statistical
comparisons of BPND parametric images between the MCI patients and controls were made
using a two sample t-test in SPM with a voxel threshold of p<0.01 and an extent threshold
of 50 vowels. All clusters with p<0.01 were considered to be significant.
50
Chapter 3: Results
51
Patient characteristics
The majority (62) of patients were recruited from the ‘memory clinic’ at Wythenshawe
hospital in South Manchester. Eight patients were recruited from the old age psychiatric
services at the ‘Stepping Hill Hospital’ in Stockport. The baseline characteristics at entry
and follow up are presented in tables 3.1, 3.2 & 3.3.
Sixty percent were males and 40% were females. The mean age of the cohort was 70 years
and majority of the participants were white (84%). The percentage of patients with one or
more vascular risk factor was high with more than half having a history of dyslipidemia
and 21% having a history of cerebrovascular event in the past. The smoking rate was also
high with 50% ex and 17% current smokers. More than half of the group were APoE 4
positive.
The mean height was 1.67 meters and mean weight 75.2 kg. The mean body mass index
was 26.8 with a range of 26 to 28 and the mean systolic blood pressure was 141 mm Hg.
Thirty eight participants were on anti-inflammatory drugs and 47% were on more than one
drug (table 3.3).
52
Table 3.1: Demographics of MCI patients
Characteristic N (%)
Male
Female
Ethnicity (white)
Ethnicity (other)
Smokers (current)
Smokers (ex)
Hypertension
Diabetes Mellitus
Stroke
Dyslipidemia
Atrial fibrillation
Coronary artery disease
Peripheral vascular disease
APoE4* positive
42 (60)
28 (40)
59 (84)
11 (16)
12 (17)
35 (50)
27 (39)
7 (10)
15 (21)
39 (56)
13 (19)
17 (24)
8 (11)
37 (53)
*Apolipoprotien E 4
53
Table 3.2: Demographics MCI patients
Characteristic Mean (95% CI*)
Age (years)
Height (meters)
Weight (kilograms)
Waist (inches)
Body mass index
Systolic BP** (mm of mercury)
69.8 (68 – 72)
1.67 (1.64 – 1.69)
75.2 (71 – 79)
37.2 (36 – 38.5)
26.8 (26 – 28)
141 (136 – 148)
* Confidence interval; ** blood pressure
Table 3.3: Anti-inflammatory drug use in MCI patients
Group N (%)
Aspirin
NSAIDs*
Statins
Combination
38 (54)
26 (37)
38 (54)
34 (48)
* Non steroidal anti-inflammatory drugs
54
Blood Counts
The results of the full blood count showed that the mean values of haemoglobin levels,
white call and platelet count were with normal range (table 3.4).
Table 3.4: Blood test results MCI patients
Characteristic Mean (range)
Haemoglobin
White cell count
Platelet count
14.1 (11.7 – 16.8)
6.12 (4.0 – 10.0)
4.69 (4.0 – 6.0)
Inflammatory marker levels
The inflammatory marker levels were done at base line and repeated after one year. The
mean baseline levels were within the normal range. The CRP levels increased significantly
but the change in IL-6 levels was insignificant over the follow up period (table 3.5).
Table 3.5: Inflammatory marker levels of MCI patients over 2 years
Geometric mean values
(range)
Ratio 1
year/baseline
(95% CI)
Significance
Baseline 1 year
IL-6 (n=61) 2.25
(1, 21)
2.36
(0, 25)
1.05 (0.85,1.28) P=0.67
CRP (n=61) 1.35
(0, 10)
1.69
(0, 20)
1.25
(1.06, 1.48)
P=0.008
55
Cognitive tests:
The cognitive test results are shown in table 3.6. There was no significant change in the
scores apart from the NART over the follow-up period.
Table 3.6: Cognitive test results of MCI patients over 2 years
Mean (sd) values Difference
(95% CI)
Significance Baseline 1 year
MMSE 26.9
(2.3)
26.3
(3.3)
-0.5 (-1.2, 0.1) P=0.10
FAS 37.3
(11.0)
38.8
(12.4)
1.4 (-0.8, 3.7) P=0.21
CAM Cog 90.4
(7.4)
89.0
(11.1)
-1.3 (-3.0, 0.3) P=0.10
Cognitive Estimates 6.3
(4.1)
7.0
(4.4)
0.8 (-0.2, 1.7) P=0.13
NART 115.8
(8.7)
117.3
(8.3)
1.4 (0.6, 2.3) P=0.001
BUSCHKE 79.7
(22.4)
80.2
(24.1)
0.5 (-3.9, 4.9) P=0.82
56
Inflammatory maker levels and cognitive change
We looked at the association between IL-6 and CRP and cognitive change over the follow
up period. There was no significant association between changes in IL-6 and CRP levels
and changes in any of the neuropsychological instruments.
A multiple regression analysis showed that the findings were not confounded by
demographic/baseline features including age, sex, smoking status, BMI, systolic blood
pressure, history of stroke and diabetes.
Average of the z-scores were calculated for log IL-6 and log CRP at baseline (z-inflam-
baseline) and for the change between baseline and follow-up (z-inflam-change) and found
no significant correlation with z-inflam-change with change in any of the cognitive
measures.
Comparison of APOE +ve and –ve subjects:
The cohort was divided into APoE positive and negative groups and the possible
differences in inflammatory marker levels at baseline and change over 12 months were
looked into. No significant differences were detected between the two groups for both the
inflammatory markers.
The possible differences between the two groups on the scores of cognitive instruments
were also looked into. No significant differences were detected in changes of cognitive
scores over 12 months.
Comparison between users and non NSAIDs users:
The cohort was divided into the above mentioned groups to investigate possible differences
in scores of cognitive measures. The analysis did not reveal statistically significant
differences between the two groups both in cognition and inflammatory marker levels.
57
PET scan cohort
The PET cohort (14 subjects) had 79% males with a mean age of 65.4 years (table 3.7).
Half were APoE positive and around 60% were using non steroidal anti-inflammatory
drugs (NSAIDs) or statins. The inflammatory marker concentrations (table 3.8) did not
show a significant change over two year’s period. The average scores of cognitive
instruments, as a group, did not change significantly, apart from the NART, measuring pre-
morbid IQ (table 3.9 and 3.10). However 2 patients had declined significantly over 24
months to fulfil the criteria for AD.
Healthy controls:
PET data from 4 age matched healthy controls was compared with the PET cohort data.
The healthy controls included 3 males and 1 female with a mean age of 64 years. The
mean CRP levels at baseline screening were 0.76 (range: 0.55–1.00) and IL-6 levels were
2.46 (range: 1.10–3.61). At the time of PET scans, the mean CRP were 1.56 (range: 1.18–
2.05) and the mean IL-6 levels were 4.79 (range: 1.00–8.08).
The visual inspection of BPND parametric images of scans of MCI subjects revealed
increased 11C-(R) PK11195 binding as compared to controls. Figure 3.1 shows BPND
parametric images of one subject and one control. Figure 3.2 shows transaxial, coronary
and sagittal projections of statistical parametric maps of areas with significantly increased
(p<0.01, uncorrected) 11C-(R) PK11195 binding of 11C-(R) PK11195 in the MCI group
compared with controls. Figure 3.3 (upper row) shows transaxial, coronary and sagittal
projections of statistical parametric maps of areas of significantly increased binding
(p<0.01, uncorrected) of 11C-(R) PK11195 in APoE +ve MCI patients compared with
APoE –ve patients and with controls. These differences however did not remain significant
after correction for multiple comparisons.
We then performed group comparison of 11C-(R) PK11195 binding in different regions of
brain of the MCI group and controls. The results revealed significantly increased binding
58
the occipital lobe, temporal lobe, frontal lobe, parietal lobe, putamen, and the posterior part
of cingulate gyrus in the MCI group. After corrections for multiple comparisons, PK11195
uptake in the posterior cingulate gyrus of MCI group remained significantly raised as
compared to healthy controls (Table 3.11). No significant correlation was detected between
the MMSE scores of MCI subjects and 11C-(R) PK11195 binding in any of the regions.
Table 3.7: PET cohort Demographics
Characteristic N (%)
Sex
Ethnicity
APoE +ve
Smokers
NSAID* use
Statin use
11(79%) Male
11(79%) White
7(50%)
3(21%)
9(64%)
8(57%)
* Non steroidal anti-inflammatory drugs
59
Table 3.8: Changes in inflammatory marker concentrations (PET cohort)
Measure Baseline 1st year 2nd year P value
CRP* 1.29
(0.24 to 6.70)
1.48
(0.43 to 6.59)
1.37
(0.64 to 5.64)
P=0.70***
IL6** 1.7
(0.7 to 21.3)
1.7
(0.7 to 18.3)
1.2
(0.5 to 8.2)
P=0.13****
* CRP Geometric mean (range)
** IL6 Median (range)
*** Repeated measures ANOVA
**** Friedman test
Table 3.9 Cognitive tests results over 3 years (PET cohort)
Geometric mean (range) Repeated
measures
ANOVA
Initial F-UP (1) F-UP (2)
MMSE 27.6
(25 to 30)
27.6
(23 to 30)
27.1
(20 to 30)
P=0.64
FAS 34.1
(12 to 54)
37.7
(17 to 54)
32.5
(5 to 55)
P=0.17
60
Table 3.10 Cognitive test results over 3 years (PET cohort)
Median (range) Friedman test
Initial F-UP (1) F-UP (2)
CAM Cog 90.5
(85 to 102)
94.0
(75 to 102)
94.0
(62 to 104)
P=0.10
Cognitive
Estimates
5.0
(1 to 23)
6.0
(1 to 20)
5.5
(0 to 25)
P=0.98
NART 116
(95 to 127)
121
(98 to 129)
122
(101 to 129)
P=0.001
Figure 3.1: Transaxial, coronary and sagittal projections of BPND parametric images of one MCI patient (upper row) and one healthy volunteer (lower row).*
*The colour bar indicates BPND values.
61
Figure 3.2: Areas of significantly increased 11C-(R)PK11195 binding in MCI group compared with control group.*
*The colour bar indicates t values.
Figure 3.3: Upper row: Areas of significantly increased 11C-(R)PK11195 binding in APoE +ve compared with APoE-ve MCI subjects. Lower row: Areas of significantly increased 11C-(R)PK11195 binding in APoE +ve MCI compared with controls.*
* The colour bar indicates t values.
62
Table 3.11: Mean 11C-(R)PK11195 BPND values in different brain regions in MCI
patients compared with health controls
MCI patients
(mean ± SD, n=12)
Healthy volunteers
(mean ± SD, n=4)
P values
Whole brain 0.030 ± 0.036 -0.038 ± 0.057 0.025
Occipital lobe 0.101 ± 0.060 0.008 ± 0.068 0.018
Temporal lobe -0.014 ± 0.064 -0.100 ± 0.070 0.025
Frontal lobe 0.086 ± 0.031 0.008 ± 0.073 0.021
Parietal lobe 0.081 ± 0.048 -0.002 ± 0.053 0.004
Posterior cingulate
(R)
Posterior cingulate
(L)
0.138 ± 0.063
0.111 ±0.060
-0.012 ± 0.070
-0.012 ± 0.062
0.001*
0.001*
Putamen (R)
Putamen (L)
Pallidum (L)
Insula (R)
0.106 ± 0.074
0.078 ± 0.070
0.123 ± 0.085
0.024 ± 0.056
-0.012 ± 0.070
-0.038 ± 0.080
-0.036 ± 0.080
-0.056 ± 0.077
0.009
0.018
0.007
0.028
*remains significant after correction for multiple comparisons
63
Chapter 4: Discussion
64
The aim of this study was to investigate the association between peripheral and central
markers of inflammation and cognitive decline in people with amnestic MCI. A group of
MCI subjects were recruited; their cognitive functions and inflammatory marker levels (IL-
6 and CRP) in peripheral blood were measured at base line and over 1 year follow up
period. A sub group of participants was followed up for another year and central brain
microglial activation was measured by PET using PK11195 along with cognitive and
peripheral inflammatory marker measurement. The main findings were:
(1) There were a relatively high proportion of APoE4 positive participants in the
cohort.
(2) The mean CRP and IL-6 levels of the cohort increased over one year but the rise
was only significant for CRP.
(3) No association was detected between change in IL-6 and CRP levels and changes
in cognitive test.
(4) There was no significant correlation between the combined inflammatory score (Z
score) of IL-6 and CRP and change in any of the cognitive tests over 1 year.
(5) Group comparisons of the PET cohort (14 participants) with healthy controls (4
participants) showed ncreased PK11195 binding (mean binding potential) in frontal
lobe, temporal lobe, parietal lobe, putamen, occipital lobes and significantly
increased binding in posterior cingulate gyri.
This section discusses the general methodology of the study, results and their
interpretation, future direction of research and draws conclusions at the end.
65
Demographics of the cohort
The memory clinic at Wythenshawe hospital in south Manchester is an established
assessment, teaching and research center. It provides memory assessments and treatment to
local residents along with assessment and diagnostic service to the whole of North West
region. A multi-disciplinary team, of which SK was a part, is involved in the assessment,
diagnosis and treatment process. Stepping Hill hospital is the district general hospital for
Stockport and has an established old age psychiatric service providing memory assessment
and treatment to the local population. The patients recruited for the study from these two
services underwent a rigorous assessment process as described in the methods section. No
major difficulties were encountered in the recruitment of participants due to the large
number of patients referred to these services. The study incorporated well established
measures of cognitive function and decline.
The demographic profile of the participants (table 1, 2& 3) was generally representative of
the memory services in South Manchester and Stockport. An audit of the memory clinic in
South Manchester (2005) looking at the profiles of 405 referrals reported that mean age
was 69.7 years and 59.5% of them were females. 37% (151) of the referrals were
diagnosed with mild cognitive impairment and 43% (175) with dementia. The study cohort
had a similar mean age of 69.8 but had more males (60%). The percentage of current
smokers (12%) is similar to the national figure of 13% for people above the age of 60
(Office of National Statistics, 2010). The percentage of ex-smokers (35%) was higher
than the national average of 30% which could be explained on the basis that the North
West has been reported to have highest smoking rates amongst all the regions of UK and a
larger percentage of men are smokers (Office of National Statistics, 2010). The percentage
of participants with vascular risk factors including hypertension, coronary heart disease,
diabetes and dyslipidemia was higher than the national average (Majeed and Moser, 2005;
Office of National statistics, 2010) but similar to population studies investigating vascular
66
risk factors in MCI (Lopez et al, 2003). Around half of the study patients were on statins
and aspirin and the mean systolic blood pressure was 141 mm of Hg indicating that the risk
factors were being treated in primary care. The higher prevalence of vascular risk factors in
this cohort could also be explained on the basis of unhealthy life style linked with of high
levels of deprivation (Shohaimi et al 2003) in the North West in general and Wythenshawe
area in particular (Indices of Deprivation, 2000).
Fifty three percent of participants were found to be ApoE4 positive which has been
reported as a risk factor both for AD (Aggarwal et al, 2005) and MCI (Boyle et al, 2010).
The higher percentage of ApoE4 positive participants is significant for the outcome of this
study as it has been associated with lower levels of inflammatory markers (Eiriksdottir et
al, 2006; Roberts et al, 2009). A population based study by Lopez et al (2003) looking at
risk factors for MCI reported that 26% of a sample of 577 MCI patients were ApoE4
positive. Another hospital based study (Wang et al, 2010) reported that out of a sample of
304 MCI patients, 26.6% were ApoE4 positive. Schuitemaker et al (2009) enrolled 67 MCI
participants in a tertiary referral center for memory disorders to investigate the relationship
of inflammatory markers with cognitive decline in MCI and AD patients. They reported
that 52% of their cohort was ApoE4 positive. The relatively high proportion of ApoE4
positive people in our cohort is probably indicative of them being recruited from a selected
population of people referred to the memory assessment services.
Cognitive testing
The scores of cognitive tests did not change significantly over 1 year apart from the
increase in NART scores. Four patients (6%) were clinically diagnosed to have converted
to AD over the one year period. Although people with amnestic MCI are known to have a
high risk of conversion to AD and some studies have reported annual conversion rates of
up to 15% (Petersen et al, 2004), it is recognized to be a heterogeneous condition and up to
67
44% of people are likely to remain stable or even improve over time (Palmer et al,
2008).Moreover the diagnosis of conversion to AD from MCI is based on clinical criteria
and not exclusively on the change in cognitive scores. The individual scores of converters
are expected to change but the mean scores of the cohort might not change significantly.
Dik et al (2005), investigating cognitive decline and inflammatory markers, followed up a
population based sample of more than one thousand older people over 3 years. They
reported that in the cohort, median MMSE score of 28 did not show a significant change
over the follow-up period.
The significant increase in NART scores is unexpected as it is a test of vocabulary and
provides a measure of pre-morbid intelligence Blair & Spreen (1989). NART is known to
have a relatively high degree of inter-rater reliability when used by experienced
psychologist (O’Carroll, 1987). Both assessors for the study, the author and the research
nurse, were not experienced psychologists and the unexpected result has probably resulted
due to poor inter-rater reliability.
Inflammatory markers in peripheral blood
The mean baseline levels of both inflammatory markers (IL-6 and CRP) were within
normal range. One of the strengths of this study was that measures were adopted to avoid
higher measurements of inflammatory markers that might be attributable to acute events.
The participants were encouraged to report any acute physical health problem/infection at
the time of organizing the appointment for the baseline assessment. A second sample was
taken with an interval of 2 weeks if the CRP or IL-6 concentrations were raised above
3mg/l on the first blood test result and the lower of the two readings was considered for the
data analysis. There was a rise in the mean levels, at one year follow-up, of both CRP and
IL-6 but the change was only significant for CRP. This indicates a rise in peripheral
inflammation over time despite using rigorous protocols to avoid false positive readings.
68
We compared the users and non-users of NSAIDs but no significant differences were
observed.
We then looked at the association between IL-6 and CRP change and cognitive change
over the follow up period. There was no significant association in both IL-6 and CRP
levels with any of the neuropsychological measures. We looked at possible confounding
factors including NSAIDs use. Multiple regression analysis showed that this finding was
not confounded by factors including NSAIDs use and other demographic factors including
age, sex and vascular risk factors including smoking status, systolic blood pressure, history
of stroke and diabetes. As IL-6 and CRP are strongly correlated with each other, we
calculated a combined inflammatory score (Z score) that would provide a combined
measure of the inflammatory burden (see chapter 2 for details). Change in the Z scores
over the follow up period did not show a significant correlation with change in any of the
cognitive measures. We also looked at the possible differences in people with or without
NSAIDs use and other demographic variables by multiple regressions analysis and they did
not reveal any significant differences.
In summary the results of our study suggest that although there was a rise in both
inflammatory maker levels over 1 year, it was only significant for the CRP and the change
in the total inflammatory burden was not significantly correlated with change in cognitive
measures. These findings suggest that although the mean inflammatory maker levels, of the
cohort, rose over 1 year but the mean scores of the cognitive measures did not change
significantly in this time period and no significant correlation between the rise in
inflammatory marker levels and cognitive decline was observed.
Other studies, on general population, AD and MCI samples, exploring the link between
inflammatory markers and cognitive decline have reported conflicting results.
Yaffe et al (2003) looked at a population based sample of about three thousand people,
followed them up for 2 years and found that those with high levels of CRP and IL-6 in
69
peripheral blood had poor cognitive performance at baseline and were at a higher risk of
decline at follow-up. They however did not do extensive neuropsychological tests and
used modified MMSE scores only. Similar results were reported by Weaver et al (2002) in
a 7 year follow-up study of a cohort of 776 elderly participants showing that people with
highest levels of IL-6 were more likely to decline over time. Other population based
studies have also reported significant association between IL-6 and cognitive decline
(Ozturk et al, 2007; Alley et al, 2008).
Yet other population based studies have reported negative results. Dik et al (2005) enrolled
a population based sample of more than a thousand people from general population and
followed them up for 3years and found no relationship between IL-6 and CRP levels with
cognitive decline. Similarly Weuve et al (2006) investigated a population sample of about
four thousand women who were participating in a women’s health study. They looked at
the CRP levels taken over a gap of 4-6 years and performance on extensive cognitive tests
and found no evidence of a link between raised CRP and cognitive decline.
Komulainen et al (2007) investigated the relationship between peripheral blood CRP
concentration at baseline and cognitive function at 12 year follow-up in a population based
sample. MMSE scores were done at baseline but extensive tests including MMSE, Word
Recall Test and Cognitive speed tests were performed at follow-up. They found that higher
baseline CRP was associated (longitudinal association) with poor performance on Word
Recall Test on 12 year follow-up but there was no association between CRP levels at
baseline and MMSE scores or cognitive speed at follow-up. Similarly there was a weak
association (cross-sectional association) between CRP levels and Word Recall Test but
there was no association between CRP levels at follow up and MMSE scores or cognitive
speed tests.
70
In summary, the majority of population based studies have shown an association between
cognitive decline and inflammatory markers but not one specific marker or cognitive test.
Yet others have reported negative results.
Studies comparing MCI, AD and controls to investigate the link between cognitive decline
and inflammation have also reported conflicting results but there have been differences in
methodology. The main difference between these studies is the methods of measurement of
inflammatory markers in peripheral blood and secretion of inflammatory markers by
peripheral blood mononuclear cells (PBMCs).
Studies investigating secretion of a variety of inflammatory makers including IL-6 by
PBMCs monocytes have reported increased cytokine production including IL-6 in MCI
and AD patients as compared with healthy controls (Guerreiro et al, 2007, Magaki et al,
2007). By contrast, more recent studies of inflammatory marker levels in peripheral blood
have not reported raised IL-6 levels in MCI patients. Bermejo et al (2008) compared MCI,
AD and healthy controls and reported raised IL-6 levels in AD but not in MCI suggesting
the possibility of a difference in the pattern of inflammatory markers in AD and MCI
subjects. Similar findings were reported by Schuitemaker et al (2009) from two groups of
people with MCI (n=67) and AD (n=145) and measured inflammatory markers in
peripheral blood and cerebro-spinal fluid (CSF). They reported significantly high levels of
CRP both in peripheral blood and CSF in MCI subjects as compared to AD but no
difference was detected for IL-6 between the two groups. Roberts et al (2009), in a large
population based sample of about five thousand people, identified those with normal
cognition, MCI and dementia. MCI subjects were further divided into amnestic and non-
amnestic MCI. They looked at the association between CRP, IL-6 and TNF –alpha levels
in peripheral blood and cognitive performance using an extensive battery of tests. They
reported a significant overall association between CRP levels and the total MCI cohort but
not with IL-6 and TNF – alpha. The significance of association of CRP varied with the
71
MCI subtype. The amnestic MCI subtype did not show a significant association with CRP
and it was only significant with non-amnestic MCI. They suggested that the lack of
association of CRP levels in the amnestic MCI cohort could be due to a higher proportion
of APoE4 positive subjects (31.5 %) as compared to non-amnestic MCI cohort as it is has
been associated with lower inflammatory marker levels.
The findings, in this study, of a significant rise of CRP but not of IL-6 in peripheral blood
over the 1 year period are consistent with the more recent studies on MCI subjects
discussed above. They suggest that in the MCI cohort, secretion of IL-6 by the PMBC
might be a better alternative to measurements in the peripheral blood. It is however likely
to make it practically less useful if inflammatory marker levels were to be used in clinical
setting. The lack of overall association between CRP and change in cognitive measures is
also consistent with the Robert et al (2009) study as our cohort had amnestic MCI and
more than half were APoE4 positive. It is possible that a longer follow-up period, as in
most studies discussed above, could have revealed significant changes in cognitive scores
and provided an opportunity to explore their association with changes in inflammatory
marker levels. Other possible explanation of our results could be firstly that circulating
cytokines in peripheral blood in MCI might not reflect the tissue levels, especially so in the
brain because of the blood brain barrier. Secondly, the rise in the CRP levels over the
follow-up period could be unrelated to neurodegenerative processes and linked to systemic
factors such as vascular disease and ageing (Tan et al, 2007).
PET cohort
The PET cohort had the inflammatory marker levels measured at baseline, 1st and 2nd
years. Both IL-6 and CRP levels did not change significantly over this period. The PET
scans showed increased PK11185 binding (table 11) in all the 4 lobes of cerebral cortex
along with significantly increased binding in posterior cingulate gyrus as compared to the
72
controls. No correlation was detected between the cognitive scores and the regions of
interest showing increased binding of PK11195.
There have been a number of PET studies with PK11195 in established AD. A small initial
study by Groom et al (1995) did not report increased binding of PK11195. More recent
studies however reported increased binding in a number of brain regions including frontal,
temporal, parietal, occipital and cingulate cortices (Versipjt et al, 2003; Edison et al, 2008)
indicating widespread microglial activation in cerebral cortex. Edison et al (2008) also
reported that microglial activation correlated with MMSE scores in AD subjects. Only two
studies, to our knowledge, have been conducted on MCI subjects with PK11195 and have
drawn somewhat conflicting conclusions. Okello et al (2009), in 13 subjects with amnestic
MCI, reported that in 5 subjects there was an increased binding of PK11195 as compared
to healthy controls. A similar but smaller study by Clayton et al (2009), in 6 subjects with
MCI, did not find any difference in PK11195 binding compared with healthy controls and
AD subjects. They however used a broader criterion for MCI and did not recruit amnestic
MCI subjects specifically.
Our results are consistent with Edison et al (2008) on AD patients as they have shown
similar pattern of microglial activation in the cerebral cortex. Our cohort of amnestic MCI
is also considered to be closet to AD in terms of having the highest risk of developing the
disease (Petersen et al, 2008). We however did not detect a correlation between cognitive
scores and microglial activation which could be explained on the basis lower levels of
inflammation in MCI as compared to established AD. A bigger cohort with a longer
follow-up period and repeat of PK11195 PET scans might be able to detect the increase in
levels of inflammation over time along with its correlation with cognitive decline. We also
did not detect any significant rise/change in the inflammatory makers in peripheral blood
in this cohort despite the microglial activation over large areas of cerebral cortex. This
finding raises the possibility, as discussed in the previous section, of the inflammation in
73
MCI being more central and detectable by PK11195 PET scans and not in peripheral
blood. It also suggests that both in AD and MCI the inflammation appears to be a more
diffuse phenomenon and not confined to a particular part of cortex such as hippocampus.
Conclusion
This study, to our knowledge, is unique in studying makers of inflammation in a high risk
group of AD participants (amnestic MCI) both in peripheral blood and brain. The results of
this study, in the light of current literature, add to the importance of recognition of
inflammatory processes in people at risk of developing AD. The results suggest that CRP
levels rise significantly over time and are detectable in peripheral blood by using
practically simple laboratory techniques. The results also suggest that activated microglia
in amnestic MCI patients can be visualized in vivo by using PK11195 PET scans and show
higher levels of activation as compare to healthy controls. These finding could be useful in
identifying people with malactivated (pro-inflammatory) microglia as potential targets for
prevention/early treatment strategies. Further studies with larger samples sizes and long
term follow-up are needed to investigate whether these peripheral and central
inflammatory markers could shed light on the aetiology of AD and be useful in monitoring
disease progression.
74
References
Aggarwal NT, Wilson RS, Bienias JL, et al.2005. The apolipoprotein E e4 allele and
incident Alzheimers disease in persons with Mild Cognitive Impairment. Neurocase. 11, 3-
7.
Aisen PS, Grundman M, Ronald G. 2000. A randomised controlled trial of prednisone in
Alzheimer’s disease. Neurology ,54, 3:588-593.
Akiyama H, Barger S. et al. 2000. Inflammation and Alzheimer’s disease. Neurobiology of
Aging 21 383 –421.
Alley DE, Crimmins EM, Karlamangla A, Hu P, Seeman TE. 2008. The inflammation and
rate of cognitive change in high-functioning older adults. J Gerontol A Biol Sci Med
Sci.63, 1: 50–55.
Anthony JC, Breitner S, Zandi Meyer MR, Jurasova I, Norton MC, Stone SV. 2000.
Reduced prevalence of AD in users of NSAIDs and H2 receptor antagonists. The Cache
County study. Neurology, 54:2066-2071.
Arend WP. 2002. The mode of action of cytokine inhibitors. J Rheumatol Suppl.
Sep;65:16-21.
Axelrod B, Millis S. 1994.Preliminary Standardization of the Cognitive Estimation Test
Assessment September 1: 269-274.
Banati RB 2002. Visualising microglial activation in Vivo. GLIA 40:206-217.
Banati RB Newcombe J, Gunn RN, Cagnin A, Turkheimer F, Hepner F, Price G, Wegner
F, Giovannoni G, Miller DH, Perkin GD, Smith T, Hewson AK, Bydder G, Kreutzberg
GW, Jones T. Cuzner MI, Myers R. 2000. The peripheral benzodiazapine binding site in
the brain in multiple sclerosis. Quantitative in vivo imaging of microglia as a measure of
disease activitiry. Brain, 123:2321-2337 .
75
Banati RB, Cagnin A, Brooks DJ, Gunn RN, Myers R, Jones T, Birch R, Anand P 2001.
Long term trans-synaptic glial responses in the human thalamus after peripheral nerve
injury. NeuroReport 12:3439-3442.
Banati RB, Myers R Kreutzberg GW, 1997 PK (peripheral bensodiazapines) binding sites
in the CNS indicate early and discrete brain lesions: microautoradiographic detection of
(3H) PK11195 to activated microglia, J Neurocytal 26:77-82.
Banati RB. 2002. Inflammation, neiroimaging, neurodegeneration, mitochondrial
benzodiazapines receptor. GLIA 40;206-217 .
Barger SW, Harmon AD 1997. Microglial activation by Alzheimer amyloid precursor
protein and modulation by apolipoprotein E. Nautre; 388:878-81.
Bauer J, Strauss S, Schreiter-Gasser u, et al 1991. IL-6 and alpha-2 macroglobulin indicate
an acute-phase state in Alzheimer’s disease cortices. FEBS Lett,285:111-4
Bermejo P, Martín-Aragón S, Benedí J, Susín C, Felici E, Gil P, Ribera JM, Villar AM.
2008. Differences of peripheral inflammatory markers between mild cognitive impairment
and Alzheimer's disease. Immunol Lett. May 15;117(2):198-202.
Boyle PA, Buchman AS, Wilson RS, Kelly JF, Bennett DA. 2010. The APOE epsilon4
allele is associated with incident mild cognitive impairment among community-dwelling
older persons. Neuroepidemiology. 34(1):43-9.
Blair JR, Spreen O, 1989. Predicting premorbid IQ: A revision of the national adult
reading test. The Clinical Neuropsychologist 3. 129–136.
Bradt BM, Kolb WP, Cooper NR. 1998. Complement-dependent proinflammatory
properties of the Alzheimer's disease beta-peptide. J Exp Med. Aug 3;188(3):431-8.
Zandi PP, Breitner JC. 2001. Do NSAIDs prevent Alzheimer's disease? And, if so, why?
The epidemiological evidence. Neurobiol Aging. Nov-Dec;22(6):811-7.
Broe GA, Grayson DA,Creasey JM, Waite LM. 2000. Anti-inflammatory Drugs Protect
Against Alzheimer Disease at Low Doses. Arch Neurol. 2000;57:1586-1591.
76
Burns A, Zaudig M. Mild cognitive impairment in older people. 2002. Lancet 360: 1963–
65.
Buschke H. 1973. Conservative Radiation Therapy for Advanced Disease.
JAMA.;223(2):170-171.
Cabral G.A. & F Maciano Cabral. 2005. Cannabinoid receptors in microglia of the central
nervous system:- immune functional relevance. J. Leukoe. Biol. 78: 1192-1197.
Cacabelos R, Alvarez XA, Fernandez-Novoa L, et al 1994. IL-1 beta in Alzheimer’s
disease and vascular dementia. Exp clin Pharmacology; 16:141-51.
Cagnin A, Myers R, Gunn RN, Lawrence AD, Stevens T, Kreutzberg GW, Jones T, banati
RB, 2001. In vivo visualization of activated glia by (11C) (PK11195-PET following
herpes encephalitis reveals projected neuronal damage beyond the primary focal lesion.
Brain 124:2014-2027
Clayton A. Wiley,Brian J. Lopresti, BS; Sriram Venneti; Julie Price; William E. Klunk;
Steven T. DeKosky; Chester A. Mathis. 2009. Carbon 11–Labeled Pittsburgh Compound B
PK11195 Positron Emission Tomographic Imaging in Alzheimer’s disease. Arch
Neurol. 66(1):60-67.
Corrada M, Stewart W, Kawas C. 1996. Nonsteroidal anti-inflammatory drugs and the risk
of Alzheimer's disease. Neurology; 46:433.
Dik MG, Jonker C, Hack CE, Smit JH, Comijs HC, Eikelenboom P. 2005. Serum
inflammatory proteins and cognitive decline in older persons. Neurology. Apr
26;64(8):1371-1377.
Edison P, Archer HA, Gerhard A, Hinz R, Pavese N, Turkheimer FE, Hammers A, Tai YF,
Fox N, Kennedy A, Rossor M, Brooks DJ. 2008. Microglia, amyloid, and cognition in
Alzheimer's disease: An [11C](R)PK11195-PET and [11C]PIB-PET study. Neurobiol Dis.
Dec; 32(3): 412-9.
Eikelenboom, P. Hoogendijk, WJ. 2002. Immunological mechanisms and the spectrum of
psychiatric syndromes in Alzheimer's disease. J. Psychiatr. Res. 36, 269-280 .
77
Eiriksdottir G., Aspelund T., Bjarnadottir K., Olafsdottir E., Gudnason V., Launer L.J.
2006. A polipoprotein E genotype and statins affect CRP levels through independent and
different mechanisms: AGES-Reykjavik Study. Atherosclerosis;186:222–224.
El Khouray, J., Hickman, S.E., Thomas, C.A., Cao, L., Silverstein, S.C. and Loike, J.D.,
1996. Scavenger receptor-mediated adhesion of microglia to beta-amyloid fibrils. Nature
382, pp. 716–719.
Engelborghs S, De Brabander M, De Crée J, D'Hooge R, Geerts H, Verhaegen H, De Deyn
PP. 1999. Unchanged levels of interleukins, neopterin, interferon-gamma and tumor
necrosis factor-alpha in cerebrospinal fluid of patients with dementia of the Alzheimer
type. Neurochem Int. Jun; 34(6):523-30.
Engelhart MJ, Geerlings MI, Meijer J, et al. 2004. Inflammatory proteins in plasma and the
risk of dementia: the Rotterdam Study. Archives of Neurology; 61:668–672.
Englehart, M. J. Geerlings, M. L., Meijer, J. Kiliaan, R. Ruitenberg. A, van
Swieten,Etminan M et al, 2003, Effect of non-steroidal anti-inflammatory drugs on risk of
Alzheimer’s disease: systematic review and meta-analysis of observational studies. British
Medical Journal, 327:128.
Etminan M, Gill S, Samii Ali. 2003. Effect of non-steroidal anti- inflammatory drugs on
risk of Alzheimer's disease: systematic review and a meta -analysis ofobservational
studies. BMJ. 2003 Jul 19;327(7407):128.
Fillit H, Ding WH, Buee L, et al 1991. Elevated circulating TNF levels in Alzheimer’s
disease. Neurosci Lett 129:318-20.
Folstein M, Folstein SE, McHugh PR. 1975. A practical method for grading the cognitive
state of patients for the clinician. J Psychiatr Res; 12:189-198.
Foster NL, Heidebrink JL, Clark CM, et al. 2007. FDG-PET improves accuracy in
distinguishing frontaltemporal dementia and Alzheimer’s disease. Brain; 130:2616-2635.
78
Gambi, F, Reale, M, Iarlori, C, Salone, A, Toma, L, Paladini, C et al, 2004. Alzheimers
patients treated with an AchE Inhibitor show higher IL4 and lower IL beta levels and
expressions in peripheral blood mononuclear cells, Journal of Clinical
Psychopharmacology, 24; 314-321.
Ganguli M, Dodge HH, Shen C, DeKosky ST. 2004. Mild cognitive impairment, amnestic
type: An epidemiologic study. Neurology. Jul 13;63(1):115-21.
Gauthier S, Reisberg B, Zaudig M, Petersen RC, Ritchie K, Broich K, Belleville S,
Brodaty H, Bennett D, Chertkow H, Cummings JL, de Leon M, Feldman H, Ganguli M,
Hampel H, Scheltens P, Tierney MC, Whitehouse P, Winblad B; 2006. International
Psychogeriatric Association Expert Conference on mild cognitive impairment. Mild
cognitive impairment. Lancet. Apr 15;367(9518):1262-70.
Gavish M, Bachman I, Shoukrun R, Katz Y, Veeman L, Weisinger G, Weizman A. 1999.
Enigma of the peripheral benzodiazepine receptor. Pharmacology Review, 51:629-650.
General Lifestyle Survey 2008: Smoking and drinking among adults. Office for National
Statistics. 2010.
Geslani D, Tierney MC, Herrmann N, Szalai J. 2005. Mild cognitive impairment: an
operational definition and its conversion ratio in Alzheimer’s disease. Dement Geriatr
Cogn Disorder; 19.
Glabinski AR, Ransohoff RM, 1999. Chemokines and chemokine receptors in CNS
pathology. J Neurovirol, 5:3-12.
Goldgaber D, Harris HW, Hla T, et al 1989. Interleukin 1 regulates synthesis of amyloid
beta-protein precursor mRNA in human endothelial cells. Proc Natl Acad Sci USA;
86:7606-10.
Goerres GW, Revesz T, Duncan J, Banati RB. 2001. Imaging cerebral vasculitis in
refractory epilepsy using [(11)C](R)-PK11195 positron emission tomography. AJR Am J
Roentgenol. Apr;176 (4):1016-8.
79
Griffin WS, Sheng JG, Roberts GW, Mark RE, 1995. IL-1 expression in different plaque
types in Alzheimer’s disease: significance in plaque evolution. J Neuropatho Exp Neurol
54:276-81
Griffin WS, Sheng JG, Royston MC, et al 1998. Glial-neuronal interactions in Alzheimer’s
disease: the potential role of a ‘cytokine cycle’ in disease progression. Brain Pathology,
8:65-72.
Groom GN, Junck L, Foster NL, Frey KA, Kuhl DE.1995. PET of peripheral
benzodiazepine binding sites in the microgliosis of Alzheimer's disease. J Nucl Med.
Dec;36(12):2207-10.
Grundman M, Petersen RC, Ferris SH, et al. 2004. Mild cognitive impairment can be
distinguished from Alzheimer’s disease and normal aging for clinical trials. Arch Neurol;
61: 59–66.
Guerreiro, R.J., Santana, I., Bras, J.M., Santiago, B., Paiva, A., Oliveira, C., 2007.
Peripheral inflammatory cytokines as biomarkers in Alzheimer's disease and mild
cognitive impairment. Neurodegenerative. Disorders. 4, 406–412.
Hammers, A., Allom, R., Koepp, M.J., Free, S.L., Myers, R., Lemieux, L.,Mitchell, T.N.,
Brooks, D.J., Duncan, J.S., 2003. Three-dimensional maximum probability atlas of the
human brain, with particular reference to the temporal lobe. Hum. Brain Mapp. 19 (4),
224–247.
Hampel H, Scheltens P, Tierney MC, Whitehouse P, Winblad B. 2006. International
Psychogeriatric Association. Expert Conference on mild cognitive impairment. Mild
cognitive impairment. Lancet. Apr 15;367(9518):1262-70.
Hardy J, Allsop D, 1991. Amyloid deposition as the central event in the aetiology of
Alzheimer’s disease. Trends Pharmacol Sci 12:383-388.
80
Herholz K, 2003. PET studies in Dementia. Ann Nucl Med 2003;17:79–89.
Hirsch EC, Breidert T, Rousselet E, Hunot S, Hartmann A, Michel PP. The role of glial
reaction and inflammation in Parkinson’s disease. Ann New York Acad Sci. 2003; 991:
214-228.
Hoozemans JJ, Veerhuis R, Janssen I, van Elk EJ, Rozemuller AJ, Eikelenboom P. 2002.
The role of cyclo-oxygenase 1 and 2 activity in prostaglandin E(2) secretion by cultured
human adult microglia: implications for Alzheimer's disease. Brain Res. Oct 4;951(2):218-
26.
Hoozemans JJ; Veerhuis Robert; Rozemuller AJ; Eikelenboom P. 2003. Non-steroidal
Anti-inflammatory Drugs and Cyclooxygenase in Alzheimer’s Disease. : Current Drug
Targets, Volume 4, Number 6, August , pp. 461-468(8).
Hopkins SJ. 1995. Cytokine measurement. Eur J Lab Med.; 3:185-200.
Hull M, Berger M, Volk B, Bauer J, 1996. Occurrence of IL-6 in cortical plaques of
Alzheimer’s disease patients may precede transformation of diffuse into neuritic plaques.
Ann NY Acad Sci 777:205-12.
in 't Veld BA, Launer LJ, Hoes AW, Ott A, Hofman A, Breteler MM, Stricker BH. 1998.
NSAIDs and incident Alzheimer's disease. The Rotterdam Study. Neurobiol Aging. Nov-
Dec;19(6):607-11.
Jantzen PT, Connor KE, DiCarlo G, Wenk GL, Wallace, JL, Rojiani AM, et al. 2002.
Micro activation and beta-amloid deposit reduction caused by as nitric oxide-releasing
nonsteroidal anti-flammatory drug in amyloid precursor protein plus presenilin -1
transgenic mice. J. Neurosci:22:2246-52.
Kalman J, Juhasz A, Laird G, et al 1977. Serum interleukin 6 levels correlate with the
severtity of dementia in Down syndrome and in Alzheimer’s disease. Acta Neurol Scand,
96; 236-40.
81
Kitamura Y et al. 1999. Increased expression of cyclooxgenases and peroxisome
profliferator-activated receptor-gamma in Alzheimer’s disease brains. Biochem Biophys
Res Commun 254:582-6.
Komulainen P, Lakka TA, Kivipelto M, Hassinen M, Penttilä IM, Helkala EL, Gylling H,
Nissinen A, Rauramaa R. 2007 . Serum high sensitivity, C-reactive protein and cognitive
function in elderly women. Age Ageing. Jul;36(4):443-8.
Kukar T, Mirphy MP, Eriksen JL, Sagi SA, Weggen S, Smith TE, et al 2005.Diverse
compounds minic Alzheimer disease causing mutations Ab42 production. Nature Med,
11:545-50.
Lanzrein AS, Johnston CM, Pery VH, Jobst KA, King EM, Smith AD. 1998. Longitudinal
study of inflammatory factory in the serum, cerebrospinal fluid, and brain tissue in
Alzheimer disease: interlukin-1β interlukin-6, interlukin-1 receptor antagonist, tumor
necrosis factor-α and the soluble tumor necrosis factor receptors I and II and α1-
antichymotrypsin. Alzheimer Dis Assoc Disord 12: 215–227.
Licastro F, Pedrini, S, Caputo, L, Annoni, G, Davis, L, J, Ferri, C, et al (2000). Increased
plasma levels of interleukin-1, interleukin-6, and alpha-1 antichymotrypsin in patients with
Alzheimers disease; Peripheral inflammation or signals from the brain. Journal of
Neuroimmunology, 103,97-102.
Licastro, F., Pedrini, S., Ferri, C., Casadei, V., Govoni, M., Pession, A.,Sciacca, F.L.,
Veglia, F., Annoni, G., Bonafe, M., Olivieri, F.,Franceschi, C., Grimaldi, L.M., 2003.
Interleukin-6 gene alleles affect the risk of Alzheimer’s disease and levels of the cytokine
in blood and brain. Neurobiol. Aging 24, 921–926.
Lim GP, Yang F, Chu T, Gahtan E, Ubeds O, Beech W et al 2001. Ibruprofen effects on
Alzhiemer’s pathology and open field activity in APPsw transgenic mice. Neurobiol
Ageing, 22-983-91.
Lombardi VR, Garcia M, Rey L, Cacebelos, R.1999. Characterizaion of cytokine
production, screening of lymphocyte subset patterns and in vitro apoptosis in healthy and
Alzheimers’s Disease (AD) individuals. Journal of Neuro immnunology, 97,163-171.
82
Lopez OL, Jagust WJ, DeKosky ST, et al. 2003. Prevalence and classification of mild
cognitive impairment in the Cardiovascular Health Study Cognition Study: part 1. Arch
Neurol 60:1385-9.
Lucas SM, Rothwell NJ, Gibson RM. 2006. The role of inflammation in CNS injury and
disease. British Journal of Pharmacology147,1; 232–240.
Lue LF, Shen Y, Yang LB, Rydel RE, Hampel H, Rogers J. 1997. Constitutive and
amyloid β peptide-stimulated secretion of inflammatory mediators by Alzheimer’s disease
and control microglia. In: Rogers J, editor. Neuroinflammation and Alzheimer’s disease.
Basel: Birkhauser Press.
Lue, L. F., Rydel, R., Brigham, E. F., Yang, L. B., Hampel, H., Murphy, G. M., Jr.,
Brachova, L.,Yan, S. D., Walker, D. G., Shen, Y., and Rogers, J. 2001a. Inflammatory
repertoire of Alzheimer’s disease and nondemented elderly microglia in vitro. Glia 35, 72–
79.
Mackenzie IRA, Munoz D G. 1998. Nonsteroidal anti-inflammatory drug use and
Alzheimer’s -type pathology in ageing. Neurology, 50, 986-990.
Mackenzie, I R A, (2001) Postmortem studies of the effect of anti-inflammatory drugs on
Alzheimer’s type pathology and associated inflammation. Neurobiology of Ageing, 22,
819-822.
Magaki S, Mueller C, Dickson C, Kirsch W. 2007. Increased production of inflammatory
cytokines in mild cognitive impairment Experimental Gerontology
Volume 42, Issue 3, March ; 233-240.
Majeed A, Moser K. 2005. Prevalence of treated chronic diseases in general practice in
England and Wales – trends over time and variations by the ONS area classification.
Presents the prevalence of five treated chronic diseases, and examines trends between 1994
& 1996 by 1991 ONS area classification. Health Statistics Quarterly, no 2, 25-32.
Martinez, M, Fernandez, Vivancos, E, Frank, A,De la, F M, Hermanz. A. 2000. Increased
cerebrospinal fluid as (Apo-1) levels in Alzheimer’s disease. Relationship with IL6
concentrations. Brain Res. 869 (1/2), 216-219.
McGeer Pl, Akiyama H, Itagaki s, McGeer EG.1989. Activation of the classical
complement pathway in brain tissue of Alzheimer patients. Neurosci Lett; 107:341-6.
83
McGeer PL; McGeer EG. 2007. NSAIDs and Alzheimer disease: Epidemiological, animal
model and clinical studies. Neurobiology of Aging - May (Vol. 28, Issue 5, Pages 639-647.
McGeer PL, Schulzer M, McGeer EG .1996. Arthritis and anti-inflammatory agents as
possible protective factors for Alzheimer’s disease: a review of 17 epidemiolgoic studies.
Neurology; 47:425-432.
McGeer PL, McGeer, EG. 2007. NSAIDs and Alzheimer disease: Epidemiological, animal
model and clinical studies. DOI: 10.1016/j.neurobiolaging.2006.03.013)
Moore AH, O’Banion MK. 2002. Neuroinflammation and anti-inflammatory therapy for
Alzheimer’s disease. Adv Drug Deliv Rev: 54:1627-56.
Morse JK, DeKosky St, Scheff SW, Neurotrophic effects of steroids on lesion-induced
growth in the hippocampus. Hormone replacement. Exp Neurol 1992; 118:47-52.
Nathan C. 2002. Points of control in inflammation. Nature. Dec 19-26;420(6917):846-52.
Office of National statistics 2010.Results from a cross-sectional population study BMC
Public Health 2010, 10:595.
O'Carroll, R. E. (1987). The inter-rater reliability of the National Adult Reading Test
(NART): A pilot study. British Journal of Clinical Psychology, 26, 229-230.
Okello A, Edison P, Archer HA, et al. 2009. Microglial activation and amyloid deposition
in mild cognitive impairment: A PET study. Neurology, 72(1):56-62.
Ozturk C, Ozge A, Yalin OO, Yilmaz IA, Delialioglu N, Yildiz C, et al. 2007. The
diagnostic role of serum inflammatory and soluble proteins on dementia subtypes:
correlation with cognitive and functional decline. Behav Neurol.;18:207–215.
84
Palmer K, Bäckman, L, Winblad B, Fratiglioni L. 2008. Mild Cognitive Impairment in the
General Population: Occurrence and Progression to Alzheimer Disease. American Journal
of Geriatric Psychiatry: July - Vol.16; 7603-611.
Pappata S , Levasseur M, Gunn RN, 2000. Thalamic microglial activation in ischemic
stroke detected in vivo by PET and [ 11C]PK11195. Neurology 2000;55:1052 -1054.
Paresce, D.M., Ghosh, R.N. and Maxfield, F.R., 1996. Microglial cells internalize
aggregates of the Alzheimer's disease amyloid β-protein via a scavenger receptor. Neuron
17, 553–565.
Petersen RC. 2004. Mild cognitive impairment as a diagnostic entity. J Intern Med; 256:
183–94.
Petersen RC, Thomas RG, Grundman M, Bennett D, Doody R, Ferris S, Galasko D, Jin S,
Kaye J, Levey A, Pfeiffer E, Sano M, van Dyck CH, Thal LJ; Alzheimer's Disease
Cooperative Study Group. 2005. Vitamin E and donepezil for the treatment of mild
cognitive impairment. N Engl J Med. Jun 9;352(23):2379-88.
Petersen RC, Negash S. 2008. Mild cognitive impairment: an overview. CNS Spectr.
2008;13(1):45-53.
Quinn J, Montine T, Morrow J Woodward WR, Kulhanek D, Eckenstein F. 2003.
Inflammation and cerebral amyloidosis are disconnected in an animal model of Alzheimers
disease, J Neuroimmunology, 137:32-41
Reale, M, Iarlori, C, Gambi, F, Feliciani, C, Salone, A, Toma, L, et al. (2004) Treatment
with an acetylcholinesterase inhinitor in alzheimer’s patients modulates the expression and
production of the pro-inflammatory and anti-inflammatory cytokines. Journal of
Neuroimmunology, 148, 162-171.
Rich JB, Rasmusson DX, Folstein MF, Carson KA, Kawas C, Brandt J, 1995. Nonsteroidal
anti-inflammatory drugs in Alzheimer’s disease. Neuorology; 45:51-5.
Ritchie K. Mild cognitive impairment: An epidemiological perspective. 2004. Dialogues
Clin Neurosci; 6: 401–08.
85
Robbins SL, Agnell M, Kumar V. 1981. Basic Pathology 3rd edition. Philadelphia: W.B.
Saunders
Robert M, Griffin S. (2005). "Glia and their cytokines in progression of
neurodegeneration". Neurobiology of Aging 26: 349–354.
Roberts RO, Yonas E. Geda, David S. Knopman, Bradley F. Boeve, Teresa J.H.
Christianson, V. Shane Pankratz, Iftikhar J. Kullo, Eric G. Tangalos, Robert J. Ivnik,
Ronald C. Petersen. 2009. Association of C-reactive protein with mild cognitive
impairment. Alzheimer's & Dementia: The Journal of the Alzheimer's Association –
September, Vol. 5, Issue 5, Pages 398-405.
Rogers J, Cooper NR, Webster S, et al 1992. Complement activation by beta-amyloid in
Alzheimer’s disease. Proc Natl Acad Sci USA 89:10016-20.
Rogers J, Kirby LC, Hempelman SR, et al 1993. Clinical trial of indomethacin in
Alzheimer’s disease. Neurology; Aug: 43:1609-11.
Rogers J, Lue LF, Yahg LB, et al 1998. Complement activation by neurofibrillary tangles
in Alzheimer’s disease. Neuroscience 24:1268.
Roth M, Huppert FA, Mountjoy CQ, Tym E. 1999. The Cambridge Examination for
Mental Disorders of the Elderly—Revised. Cambridge: Cambridge University Press
Sano M, Ernesto C, Thomas RG, et al 1997. A controlled trial of selegiline, alpha-
tocopherol, or both as treatment for Alzheimer’s disease. The Alzheimer’s disease
Cooperative Study. N Engl J med 336:1216-22.
Sastre M, Dewachter I, Rossner S. Bogdanovic N. Rosen E, Borghgraef, P Evert BE,
Dumitrescu-Ozimek L. 2006. Nonsteroidal anti-inflammatory drugs repress {beta}-
secretase gene promoter activity by the activation of PPAR{gamma} PNAS, January 10,
103(2): 443 - 448.
86
Schmidt R, Schmidt H, Curb JD, Masaki K, White LR, Launer LJ. 2002. Early
inflammation and dementia: A 25-year follow-up of the Honolulu-Asia Aging Study. Ann
Neurol;52:168–174.
Schuitemaker A, Dik MG, Veerhuis R, Scheltens P, Schoonenboom NS, Hack CE,
Blankenstein MA, Jonker C. 2009. Inflammatory markers in AD and MCI patients with
different biomarker profiles. Neurobiol Aging. Nov;30(11):1885-9.
Selkoe DJ. 1996. Amyloid-β protein and the genetics of Alzheimer’s disease. J Biol Chem
271:18295-18298.
Shen , Y., Lue, L.-F., Yang, L.-B., Roher, A., Kuo, Y.-M., Strohhmeyer, R., Goux, W.J.,
Lee, V., Johnson, G.V.W., Webster, S.D. et al., 2001. Complement activation by
neurofibrillary tangles in Alzheimer's disease. Neurosci. Lett. 305, pp. 165–168.
Shen Y, Li R, McGeer EG, McGeer PL 1997, Neuronal expression of mRNAs for
complement proteins of the classical pathway in Alzheimer brain. Brain Res 769:391-5.
Sheng JG, Griffin WS, Royston MC, Mrak RE.1998. Distribution of interleukin-1-
immunoreactive microglia in cerebral cortical layers: implications for neuritic plaque
formation in Alzheimer's disease. Neuropathol Appl Neurobiol. Aug;24(4):278-83.
Shorter E. 1997. A history of psychiatry. John Wiley & Sons. Inc.
Shohaimi S, Luben R, Wareham N, Day N, Bingham S, Welch A, Oakes S, Khaw K-T.
2003. Residential area deprivation predicts smoking habit independently of individual’s
educational level and occupational social class. A cross sectional study in the Norfolk
cohort of the European Investigation into Cancer (EPIC-Norfolk). J Epidemiol Community
Health;57:270–276.
Song DK, Im YB, Jung JS, Cho J, Suh HW, Kim YH. 2001. Central beta-amyloid peptide-
induced peripheral interleukin-6 responses in mice. J Neurochem. Mar;76(5):1326-35.
87
Stellwagen D, Malenka RC. 2006. Synaptic scaling mediated by glial TNF-alpha. Nature.
Apr 20;440(7087):1054-9.
Spreen,O, Strauss E. 1998. A Compendium of Neuropsychological Tests. 2nd edition> New
York, Oxford University Press.
Stewart WF et al 1997. Risk of Alzheimer’s disease and duration of NSAID use.
Neurology 48; 626-632.
Striet WJ, Mrak RE, Griffin WS, 2004. Microglia and neuroinflammation: a taphological
perspective. Journal of Neuroinflammation1:14
Strohmeyer R, Rogers J. 2001. Molecular and cellular mediators of Alzheimer’s disease
inflammation. J. Alzheimer’s Dis 3:131-57.
Suffredini AF, Giamila Fantuzzi G, Raffaele Badolato R, Joost J. Oppenheim J and
Naomi P, O'Grady NP. 2000. New Insights into the Biology of the Acute Phase Response.
Journal of Clinical Immunology.Volume 19, Number 4, 203-214.
Tan ZS and Seshadri S. 2010. Inflammation in the Alzheimer's disease cascade: culprit or
innocent bystander? Alzheimer's Research & Therapy, 2:6;12 April 2010.
Tan, J., Town, T., Paris, D., Mori, T., Suo, Z., Crawford, F., Mattson, M.P., Flavell, R.A.
and Mullan, M., 1999. Microglial activation resulting from CD40–CD40L interaction after
β-amyloid stimulation. Science 286; 2352–2355.
Tan ZS, Beiser AS, Vasan RS, Roubenoff R, Dinarello CA, Harris TB, Benjamin EJ, Au
R, Kiel DP, Wolf PA, Seshadri S. 2007. Inflammatory markers and the risk of Alzheimer
disease: the Framingham Study. Neurology. May 29;68(22):1902-8.
88
Tarkowski E, Blennow K, Wallin a, Tarkowski A 1999. Intracerebral production of , TNF-
α local neuroprotective agent, in Alzheimer disease and vascular dementia. J clin Immunol
19:223-30.
The Ronald and Nancy Reagan Research Institute of the Alzheimer’s Association and the
National Institute on Aging Working Group. Consensus report of the Working Group on:
“Molecular and biochemical markers of Alzheimer’s disease”. Neurobiol Aging 1998;
19:109-16.
Tuppo E.E., Arias H.R. 2005. The role of inflammation in Alzheimer's disease. The
International Journal of Biochemistry & Cell Biology 37 289–305.
Turkheimer FE, Edison P, Pavese N, Roncaroli F, Anderson AN, Hammers A, Gerhard A,
Hinz R, Tai YF, Brooks DJ. 2007. Reference and target region modeling of [11C]-(R)-
PK11195 brain studies. J Nucl Med. Jan;48(1):158-67.
Vallieres L, Rivest S.1997. Regulation of the genes encoding IL-6, its receptor, and gp130
in the rat brain in response to the immune activator lipoploysaccharide and the
proinflammatory cytokine IL-1 beta. J Neurochem 69:1668-83.
Van Wagoner NJ, Oh JW, Repovic P, Benveniste EN 1999. IL-6 (IL-6) production by
astrocytes: autocrine regulation by IL-6 and the soluble IL-6 receptor. J Neurosci 19:5236-
44.
Van-Gool, WA, Weinstein, HC, Scheltens, PK Walstra, G I. 2001. Effect of
hydroxychloroquine on progression of dementia in early Alzheimer’s disease. An 18
month randomised, double-blind, placebo-controlled study. Lancet 358, 455-460.
Velt B.A, Ruitenberg A, Hofman A, Launer LJ, van Duijin CM, Stijen T, et al. 2001.
Nosteroidal antiflammatory drugs and the risk of Alzheimers disease. New Eng J
med:345:1515-21.
Versijpt JJ, Dumont F, Van Laere KJ, et al. 2003. Assessment of neuroinflammation and
microglial activation in Alzheimer’s disease with radiolabelled PK11195 and single photon
emission computed tomography. A Pilot study. Eur Neurol.; 50:39-47.
89
WangZ, Dong B, Zeng G, Li J, Wang W, Wang B, Yuan Q. Is there an association
between mild cognitive impairment and dietary pattern in Chinese elderly? BMC Public
Health. 2010 Oct 8;10:595.
Weaver JD, Huang MH, Albert M, Harris T, Rowe JW, Seeman TE. 2002. Interleukin-6
and risk of cognitive decline: MacArthur studies of successful aging. Neurology;59:371–
378.
Webster, S., Bradt, B., Rogers, J. and Cooper, N., 1997. Aggregation state–dependent
activation of the classical complement pathway by the amyloid β peptide. J. Neurochem.
69, 388–398.
Weggen S, Eriksen JL, Das P, Sagi SA, Wang R, Pietrzik CU, et al. 2001. A subset of
NSAID’s lower amyloidogenic Abeta42 independently of cyclooxygenase activity.
Nature; 414-212-6.
Weuve J, Ridker PM, Cook NR, Buring JE,Grodstein F. 2006. Highsensitivity C-reactive
protein and cognitive function in older women. Epidemiology ;17: 183–9.
Wilson CJ, Finch CE, Cohen HJ, 2002. Cytokines and cognition – the case for a head-to-
toe inflammation paradigm. J Am Geriatr Soc; 50:2041-56.
Woods AG, Poulsen FR, Gall CM 1999. Dexamethasone selectively suppresses microglial
tropic responses to hippocampal deafferentation. Neuroscience; 91:1277-89.
Wyss-Coray T, Mucke L. 2002. Inflammation in neurodegenerative disease--a double-
edged sword. Neuron. Aug 1;35(3):419-32.
Wyss-Coray T. 2005. Nature Medicine 11, 472 – 473. doi:10.1038/nm0505-472
Yaffe, K, Lindquist, K, Penninx, B, W, Simonsick, E, M, Pahor, M Kritchevsky, S. 2003.
Inflammatory markers and cognition in well-functioning African-American and white
elders. Neurology, 61, 76-80.
90
Yan S.D., Roher, A., Schmidt, A.M. and Stern, D.M., 1999. Cellular cofactors for amyloid
β-peptide-induced cell stress. Moving from cell culture to in vivo. Am. J. Pathol. 155;
1403–1411.
Yan, Q., Zhang, J., Liu, H., Babu-Khan, S., Vassar, R., Biere, A.L.,Citron, M., Landreth,
G., 2003. Anti-inflammatory drug therapy alters beta-amyloid processing and deposition in
an animal model of Alzheimer's disease. J. Neurosci. 23,7504–7509.
Yasojima K, Schwab C, McGeer EG, McGeer PL 1999. Up-regulated production and
activation of the complement system in Alzheimer’s disease brain. Am J Pathol 154; 927-
36.
Yermakova A, Rollins J, Callahan LM, Rogers J, O’Banion MK 1999. Cyclooxygenase -1
in human Alzheimer’s and control brain: quantitative analysis of expression by microglia
and CA3 hippocampal neurons. J neuropathol Exp neurol; 58:1135-46.
91
Appendix 1
INFORMATION SHEET FOR PATIENT
M EASURES OF INFLAMMATION IN PEOPLE WITH MILD COGNITI VE IMPAIRMENT
Dear
I am writing to ask if you would be prepared to take part in a research study. This
information sheet provides details of the project. Please take your time to read it carefully
and discuss it with your family, friends, and/or family doctor. Thank you for your time.
What is the study about?
We are investigating the reasons why people develop memory loss, why that memory loss
gets worse, and why people develop diseases like Alzheimer’s disease. One theory is that
there is an inflammation in the body, particularly in the brain, which sets up a reaction
which, after many years, can affect the way the brain works and eventually cause
symptoms of memory loss, emotional changes, and sometimes diseases like Alzheimer’s
disease. We are trying to discover whether we can detect any changes in the blood or in
the brain that may shed light on the reason for this inflammation. If we understand this
better, then this potentially may help in trying to discover new drugs which can lessen the
symptoms of memory loss and perhaps even lead on to something that might prevent
diseases such as Alzheimer’s disease. We would like to take a blood sample and do some
tests on memory and attention with about 70 patients. On about 30 of these people, chosen
at random from the 70, we will be asking whether they wish to take part further in the
study involving more tests of memory and brain scans.
92
Why have I been chosen?
You have been chosen because you have symptoms of memory loss and have asked for
help in discovering the reasons for this. By examining people who complain of memory
loss but who do not have diseases such Alzheimer’s disease, we feel we will learn more
about the role inflammation has in causing these symptoms.
What will the study involve?
We would like to take a blood sample at the start of the study and after one year to measure
proteins in the blood that might be associated with inflammation. We would also like to
perform tests aimed at discovering the genetic basis of memory problems and store the
blood sample for future research in these areas. We may ask for a second sample to check
that your levels of blood protein have not altered since the first sample was taken.
The memory tests will consist of paper and pencil tests which can be carried out at the
hospital or in your own home. These are similar to the tests you may have had before and
will test your memory and attention and will take about 1 hour to complete. The memory
tests will also be carried out when you enter the study and 12 months later.
Can I refuse to take part?
Most definitely:- Whether you take part in this research project or not will not affect in
any way whatsoever the care you receive in the hospital or from your GP (who will be told
if you do agree to take part in the study). Even if you agree to take part, you can withdraw
at any time without giving a reason.
93
What will happen to the information in the trial?
The results of your tests will be stored anonymously on a computer for analysis at the end
of the study.
Who is funding the study?
The Medical Research Council in the UK is funding the study.
What happens if I come to any harm?
You are protected by the NHS Complaints Procedure. Full details are available from:
Consumers for Ethics in Research (CERES) publish a leaflet entitled ‘Medical Research
and you’. This leaflet gives more information about medical research and looks at some
questions that you may want to ask. A copy may be obtained from CERES, PO Box 1365,
London N16 0BW.
If you have any questions about this study, please contact:
Dr Salman Karim/Professor Alistair Burns
94
Appendix 2
GP INFORMATION LETTER
Dear Dr
Re: Your Patient:
We have approached the above named patient of yours to consider taking part in a study
we are carrying out in Manchester. We are trying to find whether levels of inflammatory
markers in blood or increased inflammatory activity in the brain seen on PET scans can
shed light on inflammatory aetiology of neurodegenerative diseases like Alzheimer’s
disease.
We are aiming to recruit 70 people diagnosed as mild cognitive impairment. Initially, we
will do neuropsychological testing, and blood samples will be taken from the participants
to measure the levels of inflammatory markers and genetic studies. Thirty patients from
this group will undergo MRI and PET scanning to look for increased inflammatory activity
in the brain. After a gap of one year, the process of taking blood samples and brain
scanning will be repeated.
The above mentioned investigations will be conducted at The Hope Hospital, The
Wellcome Clinical Research Facility, and The Woolfson Molecular Imaging Centre.
The study is funded by the Medical Research Council and an approval from the local ethics
committee has been obtained. Please do not hesitate to contact us if you have got any
concerns about this patient’s participation in the above mentioned project.
Yours sincerely
95
Appendix 3
Consent form for Patient: Blood sample and memory tests
CONSENT FORM
M EASURES OF INFLAMMATION IN PEOPLE WITH MILD COGNITI VE IMPAIRMENT
I ……………………………………….have read and understood the Information Sheet
about this study.
I confirm that:
(delete as necessary)
I have read and understood the Information Sheet Yes No
I have had the opportunity to ask questions and discuss the study Yes No
I agree to having tests on my memory and attention Yes No
I agree to a blood sample being taken and a second sample Yes No
if necessary at the start and after 1 year of the study
I agree to my GP being informed about the study Yes No
I agree that my blood sample be included in genetic research Yes No
I agree to a blood sample being stored for future research Yes No
96
Name of participant ………………………………………………….
Signed ………………………………………………………………..
Date …………………………………………………………………..
Name of researcher ………………………………………
Signed ………………………………………………………………..
Date ……………………………………………………
97
APPENDIX:-4
PERSONAL-CONSULTEE ASSESSMENT FORM
M EASURES OF INFLAMMATION IN PEOPLE WITH MILD COGNITI VE IMPAIRMENT
The researcher has given me my own copy of the project information sheets which I have
read and understand. The sheet explains the nature of the research and what my relative
would be asked to do as a volunteer.
I confirm that:
(delete as necessary)
(1) I have read and understood the Information Sheets, Yes No
(version 6, march 2007 brain scans and blood
samples version 1 July 2007, tests on memory and attention)
(2) I have had the opportunity to ask questions and discuss this part of Yes No
the study with the researcher.
(3) I agree to support Mr./Mrs./Ms./Miss……………………………. Yes No
in their participation in the study including brain scans, blood samples
and tests on their memory and attention.
(4) I understand that participation of the person for whom I care is Yes No
voluntary, and that they may be withdrawn or I can withdraw them
from the study at any time without giving a reason and that their
medical care or legal rights will not be affected.
98
(5) I understand that data collected during the study and relevant sections Yes No
of the medical notes of the person for whom I care may be looked at
by responsible individuals in the research team. I give permission
for these individuals to have access to the appropriate records
6) I agree to the G.P. of the person for whom I care and other relevant Yes No
health care staff being informed of their participation.
(7) I agree to the person for whom I care continuing to take part in the Yes No
study and have no reason to believe that they would not have wished
to participate if they were able to make that decision.
Name of Participant ………………………………………………….
Name of Personal Consultee…………………………………………………………
Signed ………………………………………………………………..
Date …………………………………………………………………..
Name of Researcher ………………………………………………….
Signed ………………………………………………………………..
Date …………………………………………………………………..
99
Appendix 5
NOMINATED CONSULTEE ASSESSMENT FORM
M EASURES OF INFLAMMATION IN PEOPLE WITH MILD COGNITI VE IMPAIRMENT
The researcher has given me copies of the project information sheets which I have read and
understand. The sheets explain the nature of the research and what
Mr./Mrs./Ms./Miss…………. would be asked to do as a volunteer.
I confirm that:
(delete as necessary)
(1) I have read and understood the Information Sheets, Yes No
(version 7, Jan 2008 brain scans and blood
samples , version 1 July 2007, tests on memory and attention)
(2) I have had the opportunity to ask questions and discuss this part of Yes No
the study with the researcher.
(3) I agree to support Mr./Mrs./Ms./Miss……………………………. Yes No
in their participation in the study including brain scans, blood samples
and tests on their memory and attention.
(4) I understand that participation of Mr./Mrs./Ms./Miss……………… Yes No
is voluntary, and that they may be withdrawn or that I can withdraw
them from the study at any time without giving a reason and that
their medical care or legal rights will not be affected.
100
(5) I understand that data collected during the study and relevant sections Yes No
of the medical notes of Mr./Mrs./Ms./Miss…………………………….
may be looked at by responsible individuals in the research team. I give
permission for these individuals to have access to the appropriate records.
(6) I agree to provide information required during the study to monitor
any changes or progress of Mr./Mrs./Ms./Miss…………………………. Yes No
(7) I agree to Mr./Mrs./Ms./Miss G.P. being informed they are participating Yes No
in this study.
Name of Participant ………………………………………………….
Name of Nominated Consultee……………………………………………
Signed ………………………………………………………………..
Date …………………………………………………………………..
Name of Researcher ………………………………………………….
Signed ………………………………………………………………..
Date …………………………………………………………………..
101
APPENDIX 6
INFECTION SCREEN
A cold or cold-like symptoms?
Cough?
Cough productive of sputum?
Sore throat?
Episodes of high temperature?
Episodes of shivering?
Discharge from the ears?
Discharge from eyes?
Stomach upset such as vomiting and/or diarrhoea?
Discomfort or burning when passing urine?
Dental/oral infection?
Skin rashes/boils/blisters/abscesses/wounds?
Any other infection that you are aware of?
102
Appendix 7
Protocol for collection of blood (MCI Study)
Subjects: Patients with mild cognitive impairment
Collection time: 9 a.m. to 12:30 p.m.
1) Turn on centrifuge (in B326) to cool to 4°C.
2) Collect red-capped polypropylene tubes, each containing100u pyrogen-free heparin
(10u/ml final after blood collection), from the rack in the cold room and place in
polystyrene racks of a designated cool box. Add a large freezer block from the
freezer.
3) Collect 15ml blood into a 20ml syringe.
4) Remove needle and transfer to the 10 ml to a polypropylene tube (Red cap)
containing 100u pyrogen-free heparin (10u/ml). Add remaining blood to f.b.c. tube
to be sent to haematology.
5) Mix heparinised blood tube thoroughly by gentle inversion x 10 and label tube with
subject name.
6) Record Patient name, collection time, subject No. and hospital No. on label
7) Replace heparin tube(s) in the cool box rack and place this in the sample collection
box.
8) Transfer samples to the laboratory.
103
9) Remove 4 x 50µl aliquots of blood from heparin tube and place in 4 clear, screw
topped 0.5ml freezer vials. Label each tube with the following information -
Subject initials, Subject Code Number, Date sample was taken and the Lab. Code
Number. Write Lab. Code Number on vial lid.
10) Remaining blood in heparin tube to be balanced with like tubes, or with pre-
prepared similar balance tubes, in the centrifuge and centrifuged for 15 min at
2,000 x g.
11) Transfer approx. 4 - 5ml plasma from each heparin tube into to a labelled, red-
topped ‘decant’ tube, using a sterile transfer pipette and taking great care not to
disturb cell layer.
12) Dispense 6 x ~0.75ml aliquots of the heparin ‘decant’ tube plasma to 6 clear, 2ml
screw-topped freezer vials, using a sterile transfer pipette. Label each tube with the
following information - Subject initials, Subject Code number, Date sample was
taken and the Lab. code number. Write Lab. Code Number on vial lid.
13) Switch off centrifuge.
14) Wipe working surfaces with (whatever local safety rules require) and switch off fan
and light.
15) Place all racked sample tubes in the MCI storage tray in the designated -70°C study
freezer.