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Changes in buccal cytome biomarkers in relation to ageing and Alzheimer’s disease.

A thesis submitted to the University of Adelaide for the degree of Doctor of Philosophy

Philip Thomas

B.Sc. (Hons)

University of Adelaide, School of Molecular Biomedi cal Science, Discipline of Physiology

And CSIRO Human Nutrition, Adelaide

September 2007

TABLE OF CONTENTS

DECLARATION........................................ .................................................................. i

ACKNOWLEDGEMENTS................................... ....................................................... ii

ABSTRACT ........................................... ................................................................... iii

PUBLICATIONS ARISING FROM THESIS................... ........................................... vi

ABBREVIATIONS ...................................... ............................................................. vii

CHAPTER 1. Genome mutation and Alzheimer’s disease. ................................... 1

1.1 Abstract........................................................................................................ 2

1.2 Introduction .................................................................................................. 2

1.3 Clinical diagnosis ......................................................................................... 5

1.4 Tau and Neurofibrillary Tangles................................................................... 8

1.5 β amyloid and neuritic plaques .................................................................. 10

1.6 Amyloid Cascade Hypothesis: Plaques or tangles?................................... 14

1.7 Genetics of Alzheimer’s Disease ............................................................... 19

1.8 Genomic Instability Events......................................................................... 24

1.8.1 Aneuploidy ............................................................................................... 24

1.8.2 Telomere shortening, oxidative stress, breakage fusion bridge cycles and

gene amplification. ............................................................................................ 27

1.9 Dietary and Nutrigenetic factors that affect Alzheimer disease risk ........... 35

1.9.1 B Vitamins................................................................................................ 35

1.9.2 Mutations in Folate, Methionine metabolism genes ................................. 37

1.10 Methylation ................................................................................................ 39

1.11 Antioxidants ............................................................................................... 41

1.12 Copper, Iron, Zinc, Selenium and Aluminium............................................. 44

1.13 Conclusion ................................................................................................. 46

Chapter 2: The buccal cytome and micronucleus frequ ency is substantially

altered in Down’s syndrome and normal ageing compar ed to young healthy

controls........................................... ........................................................................ 47

2.1 Abstract...................................................................................................... 48

2.2 Introduction ................................................................................................ 49

2.3 Methods ..................................................................................................... 51

2.3.1 Cell sampling and preparation ................................................................. 52

2.3.2 Feulgen staining and slide scoring........................................................... 54

2.3.3 Scoring criteria for buccal cytome assay.................................................. 55

2.3.4 Scoring method........................................................................................ 61

2.4 Statistical Analyses.................................................................................... 61

2.5 Results....................................................................................................... 62

2.6 Discussion ................................................................................................. 69

Chapter 3: Buccal cytome biomarkers may be associat ed with Alzheimer’s

disease............................................ ........................................................................ 74

3.1 Abstract...................................................................................................... 75

3.2 Introduction ................................................................................................ 75

3.3 Methods ..................................................................................................... 77

3.3.1 Recruitment and characteristics of participants........................................ 77

3.3.2 Cell sampling and preparation ................................................................. 79

3.3.3 Feulgen staining....................................................................................... 81

3.3.4 Scoring criteria for buccal cytome assay.................................................. 82

3.4 Statistical analysis...................................................................................... 87

3.5 Results....................................................................................................... 88

3.5.1 Sensitivity and Specificity......................................................................... 92

3.6 Discussion ................................................................................................. 94

Chapter 4: Telomere length in white blood cells, bu ccal cells and brain tissue

and it’s variation with ageing and Alzheimer’s dise ase.................................... 104

4.1 Abstract.................................................................................................... 105

4.2 Introduction .............................................................................................. 106

4.3 Methods ................................................................................................... 108

4.3.1 Recruitment and characteristics of participants...................................... 108

4.3.2 Cell sampling and preparation ............................................................... 111

4.3.3 DNA isolation ......................................................................................... 112

4.3.4 Quantitative real time PCR..................................................................... 114

4.4 Statistical analysis.................................................................................... 117

4.5 Results..................................................................................................... 118

4.5.1 WBCs .................................................................................................... 118

4.5.2 Buccal cells ........................................................................................... 119

4.5.3 Brain hippocampus ................................................................................ 122

4.5.4 Correlations............................................................................................ 124

4.5.5 Sensitivity and specificity ....................................................................... 124

4.6 Discussion .............................................................................................. 124

Chapter 5: Chromosome 17 and 21 aneuploidy in bucca l cells is increased with

ageing and in Alzheimer’s disease.................. ................................................... 129

5.1 Abstract.................................................................................................... 130

5.2 Introduction .............................................................................................. 130

5.3 Methods ................................................................................................... 133


5.3.2 Buccal cell collection and slide preparation............................................ 136

5.3.3 Brain tissue collection and slide preparation .......................................... 137

5.3.4 Preparation of chromosome 17 DNA probe ........................................... 139

5.3.5 Human metaphase preparation.............................................................. 139

5.3.6 Hybridisation and detection for chromosome 17 .................................... 141

5.3.7 Hybridisation and detection for chromosome 21 .................................... 142

5.3.8 Scoring Method...................................................................................... 144

5.4 Statistical Analyses.................................................................................. 144

5.5 Results..................................................................................................... 147

5.5.1 Normal ageing-Aneuploidy in buccal cells.............................................. 147

5.5.2 Down’s syndrome-Aneuploidy in buccal cells ........................................ 147

5.5.3 Alzheimer’s disease-Aneuploidy in buccal cells ..................................... 148

5.5.4 Alzheimer’s disease- Aneuploidy in Brain hippocampus........................ 148

5.6 Discussion ............................................................................................... 154

Chapter 6: Folate metabolism and Alzheimer’s diseas e .................................. 159

6.1 Abstract.................................................................................................... 160

6.2 Introduction .............................................................................................. 160

6.3 Methods ................................................................................................... 163


6.3.2 Cell sampling and preparation ............................................................... 166

6.3.3 Quantification of plasma folate............................................................... 167

6.3.4 Quantification of Vitamin B12 in plasma................................................. 169

6.3.5 Quantification of plasma total L-homocysteine....................................... 170

6.3.6 DNA isolation for genotyping.................................................................. 171

6.3.7 Genotyping............................................................................................. 173

6.3.8 Allelic discrimination primers for genotype detection.............................. 175

6.3.9 PCR conditions and reagents ................................................................ 175

6.4 Statistics .................................................................................................. 176

6.5 Results..................................................................................................... 176

6.5.1 Folate, B12 and homocysteine............................................................... 176

6.5.2 Polymorphisms ...................................................................................... 181

6.5.3 Correlations............................................................................................ 183

6.6 Discussion ............................................................................................... 187

Chapter 7: Ageing and polyphenols in a transgenic m ouse model for

Alzheimer’s disease 192

7.1 Abstract.................................................................................................... 193

7.2 Introduction .............................................................................................. 194

7.3 Materials and methods............................................................................. 196

7.3.1 Mouse model ......................................................................................... 196

7.3.2 Genotyping............................................................................................. 198

7.3.2.1 Tg(PSEN1) protocol ........................................................................ 198

7.3.2.2 Tg(APPswe) protocol....................................................................... 199

7.4 Study design ............................................................................................ 200

7.5 Diets......................................................................................................... 202

7.6 Animal welfare ......................................................................................... 203

7.7 Buccal cell collection................................................................................ 203

7.7.1 Scoring criteria for murine buccal micronucleus assay .......................... 204

7.7.2 Scoring method...................................................................................... 206

7.8 Blood collection for micronucleated erythrocyte assay ............................ 208

7.8.1 Acridine orange staining......................................................................... 208

7.9 DNA isolation for telomere length determination...................................... 209

7.9.1 DNA isolation of buccal cells.................................................................. 210

7.9.2 DNA isolation of Brain tissue.................................................................. 210

7.10 Real time PCR for absolute quantitation for telomere length ................... 211

7.11 Statistical analysis.................................................................................... 212

7.12 Results..................................................................................................... 213

7.12.1 Food consumption................................................................................ 213

7.12.2 Bodyweight .......................................................................................... 213

7.12.3 Buccal micronucleus cytome assay ..................................................... 216

7.12.3.1 Basal cells ..................................................................................... 216

7.12.3.2 Differentiated cells ......................................................................... 217

7.12.3.3 Micronucleated cells (combined basal and differentiated

micronucleated cells)................................................................................... 219

7.12.3.4 Early Karyolytic cells...................................................................... 221

7.12.3.5 Mid Karyolysis ............................................................................... 223

7.12.3.6 Late Karyolysis .............................................................................. 225

7.12.4 Whole blood micronucleus erythrocyte assay ...................................... 227

7.12.4.1 Micronucleated PCE...................................................................... 227

7.12.4.2 Micronucleated Non polychromatic erythrocytes ........................... 227

7.12.4.3 Polychromatic erythrocyte percentage .......................................... 228

7.12.5 Correlation between micronuclei in buccal cells and polychromatic

erythrocytes .................................................................................................... 230

7.12.6 Telomere length at 9 months ............................................................... 231

7.12.6.1 Olfactory lobe brain tissue ............................................................. 231

7.12.6.2 Buccal cell absolute telomere length ............................................. 232

7.12.7 Correlation between buccal cell and olfactory lobe telomere length .... 233

7.13 Discussion ............................................................................................... 233

7.14 Appendix 1: Clinical morbidity assessment for AD Mice performed weekly

241

Chapter 8: Conclusions and future directions ....... ........................................... 244

References......................................... ................................................................... 251

Appendix: Paper Reprints ........................... ........................................................ 302

i

DECLARATION

This thesis contains no material which has been accepted for the award of any other

degree or diploma in any university or tertiary institution, and to the best of my

knowledge and belief, contains no material previously published or written by another

person, except where due reference has been made in the text.

I give my consent to this thesis, when deposited in the University library, being

available for photocopy or loan.

Philip Thomas

ii

ACKNOWLEDGEMENTS Firstly, I would like to thank my supervisors Dr Michael Fenech and Associate

Professor Michael Roberts for all their wisdom, guidance and support throughout my

post graduate journey. Thank you for the belief and confidence that made this PhD

project a reality. Dr Jane Hecker and Dr Jeff Faunt deserve special mention for

clinically diagnosing the Alzheimer’s patients and agreeing to collaborate with us on

the project, and for arranging with Sue Moore at College Grove to help me in the

collection of both blood and buccal cells from Alzheimer’s patients. Furthermore, I

should like to thank all the staff at the CSIRO clinic for helping me organise potential

participants for the control cohorts. A special thank you is extended to all of the

participants who consented to take part in this study making the whole project

possible. Special thanks to Dr John Power and Robyn Flook for all their efforts in

providing me with hippocampal brain tissue from both Alzheimer’s and control brains.

I would also like to thank my good friend Shusuke Toden for his motivation and

inspiration, and the countless memorable conversations about boxing and music of

yesteryear, whilst drinking coffee overlooking the banks of the river Torrens. I thank

Dr Nathan O’Callaghan for all his support, advice and technical expertise during the

telomere assessment study.

Finally, I should like to thank my family and friends especially Eileen, Steve and

Elaine for all their continued support and encouragement. Thanks to Dylan Thomas

who during difficult times made the vision of Wales all the more clear-Diolch yn fawr,

Dylan.

iii

ABSTRACT The aim of this thesis was to investigate the possibility of using buccal cells derived

from a multi layered epithelial tissue from the oral mucosa as a model to identify

potential biomarkers of genomic instability in relation to normal ageing and premature

ageing syndromes such as AD and DS. A buccal micronucleus cytome assay was

developed and used to investigate biomarkers for DNA damage, cell proliferation and

cell death in healthy young, healthy old and young Down’s syndrome cohorts. Cells

with micronuclei, karyorrhectic cells, condensed chromatin cells and basal cells

increased significantly with normal ageing (P<0.0001). Cells with micronuclei and

binucleated cells increased (P<0.0001) and condensed chromatin, karyorrhectic,

karyolytic and pyknotic cells decreased (P<0.002) significantly in Down’s syndrome

relative to young controls.

The buccal micronucleus cytome assay was used to measure ratios of buccal cell

populations and micronuclei in clinically diagnosed Alzheimer’s patients compared to

age and gender matched controls. Frequencies of basal cells (P<0.0001), condensed

chromatin cells (P<0.0001) and karyorrhectic cells (P<0.0001) were found to be

significantly lower in Alzheimer’s patients, possibly reflecting changes in the cellular

kinetics or structural profile of the buccal mucosa.

Changes in telomere length were investigated using a quantitative RTm-PCR method

to measure absolute telomere length (in Kb per diploid genome) and show age-

related changes in white blood cells and buccal cell telomere length (in kb per diploid

genome) in normal healthy individuals and Alzheimer’s patients. We observed a

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significantly lower telomere length in white blood cells (P<0.0001) and buccal cells

(P<0.01) in Alzheimer’s patients relative to healthy age-matched controls (31.4% and

32.3% respectively). However, there was a significantly greater telomere length in

hippocampus cells of Alzheimer’s brains (P=0.01) compared to control samples (49.0

Buccal cells were also used to investigate chromosome 17 and 21 aneuploidy. A 1.5

fold increase in trisomy 21 (P<0.001) and a 1.2 fold increase in trisomy 17 (P<0.001)

was observed in buccal cells of Alzheimer’s patients compared to age and gender

matched controls. Chromosome 17 and chromosome 21 monosomy and trisomy

increase significantly with age (P<0.001). Down’s syndrome, which exhibits similar

neuropathological features to those observed in Alzheimer’s disease also showed a

strong increase in chromosome 17 monosomy and trisomy compared to matched

controls (P<0.001). However, aneuploidy rate for chromosome 17 and 21 in the

nuclei of hippocampus cells of brains from Alzheimer’s patients and controls were not

significantly different.

Observations that AD individuals have altered plasma folate, B12 and Hcy levels

compared to age-matched controls who have not been clinically diagnosed with AD

were investigated. Genotyping studies were undertaken to determine whether

polymorphisms within particular genes of the folate methionine pathway contributed

to AD pathogenesis. Correlations between folate, B12 and Hcy status with previously

determined buccal micronucleus assay cytome biomarkers for DNA damage, cell

proliferation and cell death markers was investigated.

Lastly, the potential protective effects of phytonutrient polyphenols on genomic

instability events in a transgenic mouse model for AD were investigated. We

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determined the effects of curcumin and GSE polyphenols on DNA damage by testing

the mice over a 9 month period utilizing a buccal micronucleus cytome assay, an

erythrocyte micronucleus assay and measuring telomere length in both buccal cells

and olfactory lobe brain tissue.

vi

PUBLICATIONS ARISING FROM THESIS 1. Chapter 1 : Philip Thomas and Michael Fenech A review of genome mutation and Alzheimer’s disease. Mutagenesis vol. 22 no. 1 pp. 15–33, 2007. 2. Chapter 2 : Philip Thomas, Sarah Harvey, Tini Gruner and Michael Fenech

The buccal cytome and micronucleus frequency is substantially altered in Down’s syndrome and normal ageing compared to young healthy controls Mutation Research Fundamental and Molecular Mechanisms of Mutagenesis 2007; doi:10.1016/j.mrfmmm.2007.08.012MUT10526 (In press)

3. Chapter 3 : Philip Thomas, Jane Hecker, Jeffrey Faunt and Michael Fenech

Buccal cytome biomarkers may be associated with Alzheimer’s disease Mutagenesis 2007; doi: 10.1093/mutage/gem029Mutagenesis (In press)

4. Chapter 4 : Philip Thomas, Nathan O’Callaghan and Michael Fenech

Telomere length in white blood cells, buccal cells and brain tissue and it’s variation with ageing and Alzheimer’s disease Mechanisms of ageing and development (In press)

5. Chapter 5 : Philip Thomas and Michael Fenech

Chromosome 17 and 21 aneuploidy in buccal cells is increased with ageing and in Alzheimer’s disease. Mutagenesis (In press)

vii

ABBREVIATIONS ACT Alpha-1-antichymotrypsin

ALT Alternative lengthening of telomere

AD Alzheimer’s disease

ANOVA Analysis of variance

APOE Apolipoprotein E

APOE4 Apolipoprotein E allele 4

APP Amyloid precursor protein

β amyloid 42 42 amino acid β amyloid peptide

BACE Beta site APP cleaving enzyme

BFB Breakage fusion bridge

BC Buccal cell

BSA Bovine serum albumin

CAT Catalase

CBS Cystathionine β synthase

CSIRO Commonwealth Scientific and Industrial Research organisation

CT Cycle threshold

Cu2+ Copper

DABCO 1, 4-diazabicyclo-(222) octane

DAPI 4, 6 diamidino-2-phenylindole

dATP 2’-deoxyadenosine 5’-triphosphate

dCTP 2’-deoxycytidine 5’-triphosphate

dGTP 2’-deoxyguanosine 5’-triphosphate

dNTP Deoxyribonucleotide triphosphate

DNA Deoxyribo nucleic acid

viii

DS Down’s syndrome

dTMP Deoxythymidine monophosphate

DTT Dithiothreitol

dTTP 2’-deoxythymidine 5’-triphosphate

dUMP Deoxyuracil monophosphate

EDTA Ethylenediamine tetraacetic acid

EGCG Epigallocatechin-3-gallate

FAD Familial Alzheimer’s disease

Fe2+ Iron

FBP Folate binding protein

FISH Fluorescence in situ hydridisation

FITC Fluorescein isothiocyanate

GPx Glutathione peroxidase

GSE Grape Seed extract

HCL Hydrochloric acid

Hcy Homocysteine

HO-1 Heme oxygenase-1

8-OHdG 8 hydroxy-2-deoxyguanosine

Kb kilobase

KOH Potassium hydroxide

MCI Mild cognitive impairment

MDS Mothers of Down’s syndrome

MgCL2 Magnesium chloride

MGSE Microencapsulated Grape Seed Extract

MPO Myeloperoxidase

ix

MMSE Mini Mental State Exam

MN Micronuclei

MN-NCE Micronucleated non polychromatic erythrocyte

MN-PCE Micronucleated polychromatic erythrocyte

Mo/HuAPP695 transgenic mouse secreting 695 amino acid APP peptide

MRI Magnetic Resonance Imaging

MTHFR Methylenetetrahydrofolate reductase

MTR Methionine synthase

MTRR Methionine synthase reductase

NAD Nicotinamide adenine dinucleotide

NINCDS-AD&DA National Institute of Neurological and Communicative Disorders

and Stroke-Alzheimer’s disease and related disorders association

PBS Phosphate buffered saline

PCE Polychromatic erythrocyte

PSEN1 Presenilin 1

PSEN1-dE9 Deletion in exon 9 of presenilin gene

PSEN2 Presenilin 2

ROS Reactive oxygen species

RLU Relative light units

RTm-PCR Real time polymerase chain reaction

SAH S-Adenosylhomocysteine

SAM S-Adenosyl Methionine

SNP Single nucleotide polymorphism

SOD Superoxide Dismutase

SSC Standard saline citrate

x

TERT Telomerase

WBC White blood cells

Zn2+ Zinc

Chapter 1: General Introduction

1

1 CHAPTER 1. Genome mutation and Alzheimer’s disease


2

1.1 Abstract

Alzheimer’s disease (AD) is a complex progressive neurodegenerative disorder of the

brain and is the commonest form of dementia. The prevalence of this disease is

predicted to increase threefold over the next thirty years and to date no reliable and

conclusive diagnostic test exists that will identify individuals presymptomatically of

susceptibility risk. This review examines the molecular, genetic, dietary and

environmental evidence underlying the known pathology of AD and proposes a

biologically plausible chromosome instability model to explain some of the features of

the disease. Genome damage biomarkers such as aneuploidy of chromosome 17 and

21, oxidative damage to DNA and telomere shortening together with abnormal

expression of APP, β amyloid and tau proteins are discussed in terms of their potential

value as risk biomarkers. These biomarkers could then be used in diagnosis and the

evaluation of potentially effective preventative measures.

1.2 Introduction Alois Alzheimer (Figure 1) was born in Marktbriet, Germany on June 14th 1864. He

studied medicine at the Universities of Berlin, Tϋbingen, and Wϋrzberg where he

completed his doctoral thesis under the supervision of Albert Kölliker on ceruminal

glands in 1887. From 1888-1903 Alzheimer worked as a medical resident and then

later as a senior physician at the municipal mental asylum in Frankfurt. It was here

that he forged his friendship with Franz Nissl, who developed histopathological stains

that allowed the histology of nervous tissue from various neurodegenerative disorders

to be studied.


3

On November 25th 1901 a patient called Auguste D was admitted to Frankfurt hospital

where she was seen and treated by Alzheimer. She exhibited various behavioural and

psychiatric symptoms including paranoia, delusions, hallucinations and impaired

memory [1]. After having suffered five years of illness she died in 1906. Her clinical

notes and brain were forwarded onto Alzheimer in Munich, where over the next few

months he examined Auguste‘s brain in great

detail. At the 37th Conference of German

psychiatrists meeting in Tϋbingen on November

4th 1906, Alzheimer reported for the first time the

histopathological changes that he had witnessed

in Auguste’s brain. In his journal he wrote “in the

centre of an almost normal cell there stands out

one or several fibres due to their characteristic

thickness and peculiar impregnability. Numerous

Figure 1: Alois Alzheimer (1864-1915) small miliary foci are found in the superior layers.

They are determined by the storage of a peculiar substance in the cerebral cortex. All

in all we have to face a peculiar disease process” [2]. The impregnable fibres so

described by Alzheimer were the neurofibrillary tangles, whereas the miliary foci were

to be later referred to as the amyloid based neuritic plaques. Both these structures

initially described by Alzheimer are now recognised as the characteristic hallmarks of

a disease that now bears his name. In 1910 Emil Kraepelin published the 8th edition of

his book The handbook of psychiatry where he describes a particularly serious form of

senile dementia with early age of onset as Alzheimer’s disease.


4

Having worked with Kraepelin in Munich from 1903-1912, Alzheimer was appointed to

the position of professor of Psychiatry in Breslau, Poland. However with the arrival of

the First World War conditions became increasingly more difficult. He found himself

under increasing stress until finally his health started to fail. Alois Alzheimer died in a

uraemic coma as a result of rheumatic endocarditis on December 19th 1915 at the age

of 51. Alzheimer’s many years of dedicated research provided the foundation for

today’s extensive research programmes, into trying to understand a disease that is

predicted to make a huge social and financial impact on the 21st Century. AD has been

classified as a progressive degenerative disorder of the brain and is the most common

form of dementia, with between 50 and 70% of all clinically presented cases being

histopathologically confirmed as AD at post mortem [3]. Worldwide a new case of

dementia is diagnosed every seven seconds. The global incidence of dementia is

estimated to be 24.3 million, with approximately 4.6 million new cases being

diagnosed annually [4,5]. Currently between 165,000 and 180,000 Australians suffer

from this disease, with an annual cost in 2004 to the Australian government of $3.6

billion dollars in lost productivity and medical care [6,7]. These numbers are set to

increase threefold over the next thirty years as a greater proportion of an already

ageing population reaches retirement age. Advancing age is the major contributing

factor for increased risk of developing Alzheimer’s. After the age of 65 a doubling of

risk occurs every five years affecting roughly 30% of individuals aged 80 years and

over [3],[8,9]. It is estimated that by 2025 at least 34 million people worldwide will

suffer from AD [10].


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1.3 Clinical diagnosis

At present, based upon criteria of cognitive impairment and behavioural changes

patients can be clinically diagnosed with between 60-70% accuracy of having AD [11].

The most commonly used criteria are those outlined by the National Institute of

Neurological and Communicative Disorders and Stroke-Alzheimer’s disease and

related disorders association (NINCDS-AD&DA), published in 1984 [12]. According to

this document, criteria for probable diagnosis for Alzheimer’s includes dementia as

determined by the mini mental state examination (MMSE) [13], which allows a brief

quantitative measure of cognition status to be determined. It can be used as a

measure of cognitive decline, to document cognitive changes with the passage of time

in relation to treatment, and as an effective tool in screening for elements of cognitive

impairment. Dementia is diagnosed when two of the following parameters are

impaired: amnesia (progressive worsening of memory), aphasia (impairment of

speech), apraxia (the inability to perform motor tasks) and agnosia (the inability to

identify and recognise individuals or objects, despite having knowledge of the

characteristics of those individuals and objects). Individual assessment includes

various psychiatric and behavioural changes such as depression, misidentifications,

delusions, and hallucinations that invariably lead to an individual’s inability to perform

everyday tasks, resulting in some form of full time care being required [8].

The age of onset for AD is usually after the age of 65yrs but can be earlier if

influenced by genetic mutations in familial Alzheimer’s genes. Other forms of systemic

disorders, which could also account for the progressive decline in both memory and

cognition function invariably need to be ruled out. Laboratory testing can aid in the

identification of conditions that need to be diagnostically eliminated in order to achieve


6

a more accurate diagnosis when a dementia profile is being evaluated. A complete

blood cell count and urinalysis profile is necessary to exclude signs of anaemia and

infection; metabolic disorders can be evaluated through analysis of serum metabolites

(such as glucose, calcium, urea, and creatinine) as well as performing various liver

function tests to eliminate other certain metabolic disorders such as Wilson’s

syndrome or Laennec’s cirrhosis. Additionally, neurosyphilis as well as micronutrient

deficiencies in folate and B12 need to be excluded as they can simulate symptoms of

dementia, thereby making an accurate diagnosis more difficult to achieve [14].

Until recently there was no diagnostic test available that could reliably and

conclusively identify those individuals for increased presymptomatic risk of AD.

Consequently it was impossible to develop and implement effective preventative

measures to curb the progress of the disease. However, recently a simple non-

invasive skin test that measures dilation of blood vessels has been developed, that

reflects a decline in function in specific blood vessel cell types affected by the disease.

It is claimed that different dementias can be differentiated and that detection can be

made up to two years before conventional clinical diagnosis [15,16]. A further

technique has been developed that involves the use of an intravenous amyloidophilic

compound labelled with 19F. This compound when administered to Amyloid precursor

protein (APP) transgenic mice, specifically labelled amyloid plaques that could be

visualised in living subjects by magnetic resonance imaging (MRI). This technique

would allow the identification of the disease at an earlier stage in presymptomatic

individuals, and to determine disease progression in response to various preventative

measures and selected treatments [17].


7

Although the pathogenesis of the disease is still not completely understood, it has

been shown that at post mortem there are two histopathological changes that occur

within the brain. These changes involve the abnormal clustering of proteins which

characterise individuals with AD. This abnormal clustering occurs in two forms: a)

those that occur within the neurons, i.e. the neurofibrillary tangles and b) those that

cluster extracellularly outside of the neuronal body, i.e. the amyloid based neuritic

plaques (Figure 2). Early changes occur within the entorhinal cortex projecting into the

hippocampus which leads to disruption of learning and short term memory processes.

Further protein deposits have been found within the temporal, frontal and inferior

parietal lobes mapping the spread of the disease throughout the brain. Later

developments in the pathology of AD include neuronal cell death resulting in loss of

tissue leading to overall shrinkage of brain size [10].

a) Tau based neurofibrillary tangle b) Amyloid based Neuritic plaque

Figure 2: Histopathological hallmarks of Alzheimer’s disease. a) Microscopic image of typical

neurofibrillary tangle. b) Microscopic image of a plaque showing a central β amyloid core

surrounded by black tau filaments.


8

1.4 Tau and Neurofibrillary Tangles

Neurofibrillary tangles are composed of the microtubule associated protein tau, the

gene of which is located at chromosome 17q21.1 [18]. The TAU gene comprises of 15

exons, with 11 of the exons coding for all of the major tau isoforms. Splicing of exons

2, 3 and 10 result in the six different forms of the tau protein. These forms differ from

each other by the presence or absence of two N-terminal exons and a single C-

terminal exon which results in variation of their amino acid length which ranges from

352-441 [19].

Tau proteins are important as they associate with tubulin in the formation of

microtubules. Microtubules impart shape and structure to cells and generate cellular

transport networks that allow movement of micronutrients, neurotransmitters and

organelles that are essential for normal cellular function [20]. The tau protein of

neurofibrillary tangles consists of paired helical threads that are hyperphosphorylated.

This hyperphosphorylation leads to a dissociation between tau and tubulin resulting in

a breakdown in the brain transport network eventually leading to resistance to protein

degradation [20] , loss of biological activity and cell death [18,20].

The level of tau phosphorylation is probably determined by the regulation of protein

kinases that modify tau through phosphorylation, and phosphatases that

dephosphorylate the modified tau. Tau kinases such as GSK3, cdk5 and p38 are

known as proline kinases and regulate proline modified serine and threonine motifs.

Both Cyclic-AMP and Ca2+/cadmodulin dependent kinases together with protein

kinase C are known as non-proline kinases that modify non-proline serine and

threonine motifs. Sequences involved in binding tau to tubulin are coded for within the


9

C-terminal exon and are positioned adjacent to the sequences for the tubulin binding

repeats [21] (Figure 3).

Tau phosphorylation is linked to microtubule stabilisation by regulating the binding of

tau to the microtubules. In AD under conditions following phosphorylation, decreased

binding occurs leading to a breakdown in microtubule stability resulting in tau

aggregation within the neurons [22]. Hyperphosphorylation may also lead to

microtubule spindle defects, resulting in aneuploidy for a number of chromosomes

including chromosome 17 that may lead to abnormal expression of Alzheimer’s related

genes such as TAU.

In the neurodegenerative disorder fronto-temporal dementia, the density of the

neurofibrillary tangles is directly correlated with the severity of exhibited dementia

[10,23]. This disorder is the result of point mutations within exon 10 of the TAU gene

such as Leu266Val and Glu342Val. The disorder is not associated with any amyloid

peptide formation or plaque deposition [24,25]. This is important as it suggests that

dementia can arise directly from abnormal processing and accumulation of tau [26,27]

that arises independently of any influence of abnormal amyloid metabolism.


10

Arrows showing phosphorylation sites for Cyclic-AMP, Ca2+/calmodulin, protein kinase c(Non-proline dependent protein kinases)

GSK3,cdk5, p38

352 amino acid isoform with 3 Binding repeats

1 352

Arrows showing Phosphorylation sites for

(Proline directed protein kinases)

Amino acid

Figure 3: Tau molecule showing kinase phosphorylation sites. Modified from Gomez-Ramos[21]

1.5 β amyloid and neuritic plaques The amyloid based neuritic plaque occurs extracellularly to the neuron body having

originated within the neuron and been secreted as a soluble peptide. It is thought to be

the first histopathological change to occur in AD [10]. The plaque consists primarily of

the 42 amino acid β amyloid peptide (β amyloid 42) originating from the abnormal

processing of amyloid precursor protein (APP), the gene of which is located on

chromosome 21q21. APP is a cell surface protein of between 695 to 770 amino acids

long, and plays a functional role in neurite outgrowth, cell adhesion, synaptic functions

and the induction of apoptosis [28].

The protein runs through the membrane leaving a short intracellular terminal and a

longer terminal extracellularly (Figure 4) .The β amyloid peptide is normally snipped


11

out of the APP protein that is adjacent to the cell membrane. APP proteolysis is

mediated by a series of secretase enzymes α, β, and γ [29,30]. Under normal

conditions, a harmless P3 fragment is formed by cleavage by α and γ secretases

resulting in a 40 amino acid β peptide [28,31].

Plasma Membrane

β Amyloid production

Extracellular

Intracellular

α secretaseβ secretase

γ secretase

APP protein

sAPPβsAPPα

83 amino acid APP fragment

Aβ40/Aβ42

99 amino acid carboxy APP fragment

695-770 amino acids

Harmless P3 fragment following α and γsecretase cleavage

Amyloid plaques

Figure 4: β amyloid production. APP is a membrane protein producing a number of isoforms

which range in size from 695-770 amino acids. Proteolysis of the APP protein involves α, β

and γ secretases. APP cleavage by α secretase releases sAPPα from the membrane leaving

an 83 amino acid APP fragment. Cleavage of the APP protein by β secretase releases sAPPβ

from the membrane and leaves behind a 99 amino acid fragment which can be further cleaved

by γ secretase to produce Aβ40/42 fragments extracellularly.

The α secretase is thought to be made up of metalloproteases of the tumour necrosis

factor α-converting enzyme and a disintegrin matrix [32]. Beta sectretase has been

identified as the enzyme BACE (beta site APP cleaving enzyme) the gene of which is

located on chromosome 11. The γ secretase is a complex multi protein comprising of

four components, Presenilin, nicastrin, Aph-1 and Pen2 all of which are required for

effective proteolytic activity [33].


12

In the Alzheimer’s brain, aberrant proteolysis occurs involving β secretase which

produces a series of products, that after having been cleaved by gamma secretase,

gives rise to the β amyloid 42 [29]. Aberrant proteolysis results in an abnormal

accumulation of soluble β amyloid 42 which aggregates into oligomers. When

fibrillised and subjected to an astrocyte induced inflammatory response, it matures into

an insoluble neuritic plaque measuring between 10 -120µm. [28,31,34].

Intraneuronal β amyloid 42 is generated initially within the endoplasmic reticulum,

golgi body and endosomes of the neuron where it accumulates, eventually transferring

to the extracellular space of the neuron as a soluble peptide [35-38]. It has also been

shown to accumulate in those vulnerable areas of the brain that are sensitive to

Alzheimer’s related pathological changes such as the perikaryon of the pyramidal

neurons of the hippocampus and entorhinal cortex [39] (Figure 6). Intraneuronal β

amyloid 42 could be considered to be an early pathological biomarker of the disease

and has been shown to be a contributory factor to neuronal dysfunction.

Billings et al have shown in a transgenic mouse model that animals manifested

symptoms of cognitive impairment that correlated with intraneuronal β amyloid 42

accumulation within the hippocampus and amygdala [40]. The mice were free from

both tangle and plaque pathology suggesting these structures contribute to further

cognitive decline during the later stages of the disease. It may also be that they are

incidental endpoint structures that are not directly responsible for the causative factors

leading to the pathology of the disease. By clearing the Intraneuronal β amyloid 42

using immunotherapy, the observed cognitive deficits were attenuated when memory


13

was assessed after measuring tasks that involve the hippocampus. This implies that

the intraneuronal β amyloid 42 has a role in the initiation of early stage cognitive

impairment and neuronal dysfunction in AD [40].

It has been shown that application of β amyloid 42 to cultured neurons is neurotoxic

and can directly initiate apoptosis [41,42]. The presence of β amyloid elevates

apoptotic vulnerability when cells are under conditions of increased oxidative stress,

which occurs naturally in the ageing brain. β amyloid induced oxidative stress results

in the generation of reactive oxygen species that can damage various cellular

components such as cell membrane proteins, mitochondrial DNA, lipids and

cytoplasmic proteins. In the brains of Alzheimer’s patients these components have

been shown to exhibit elevated levels of oxidative damage [43,44]. β amyloid causes

neurons to undergo apoptosis by sensitising their membranes following lipid

peroxidation. The normal ATPases associated with the membrane are impaired

leading to membrane depolarisation, and a disruption in glucose and glutamate

transportation and ATP energy depletion. β amyloid also modifies calcium flow across

the membrane [45]. Calcium is involved in mechanisms associated with memory and

learning as well as neuronal survival. The β amyloid peptide disrupts calcium

regulatory pumps within the membrane and elevates calcium influx through voltage

dependent channels, possibly as a result of induced oxidative stress leading in turn to

neuronal cell death [46].

Further signs of apoptosis in Alzheimer’s brains include elevated DNA fragmentation

and β amyloid induced caspase activation. Caspases are a family of cysteine

proteases and are the principal effectors of apoptosis. In Alzheimer’s brains caspase 3


14

has been shown to use APP as a substrate, producing a potent apoptotic promoting

peptide called C31 [47]. Other caspases such as caspase 8, 9 and 12 have been

shown to contribute to neurodegeneration [48,49]. Nakagara et al has shown that

caspase 12 located in the endoplasmic reticulum (which regulates cellular responses

to stresses such as high calcium and free radicals) induces apoptosis as a result of β

amyloid toxicity [49]. It has been suggested that caspase activation occurs initially at

the nerve synapses [50], leading to an overall loss of cerebral nerve terminals and

interneuronal communication within the neuronal network. This gradual degeneration

of terminals may correlate with the individual’s level of cognitive impairment. As nerve

cells slowly undergo further terminal loss with the passage of time, the dysfunctional

neurons eventually die in those areas of the brain that are initially susceptible to β

amyloid toxicity.

1.6 Amyloid Cascade Hypothesis: Plaques or tangles? One of the topics that has generated a great deal of interest within Alzheimer’s

research is the question of which of the histopathological landmarks, the neurofibrillary

tangle or the neuritic plaque, appears first? Does one influence the development of the

other or do they in fact develop independently via two separate pathways? The

amyloid cascade theory was proposed to explain the etiology and progression of the

disease [51-53] and indeed still forms the backbone of explanation for Alzheimer’s

development. However in recent years, it has been found that certain observations

cannot be explained by the hypothesis in its current form [54,55]. The cascade theory

currently states that elevated deposits of the β amyloid 42 occur as a result of

missense mutations or a failure of clearance mechanisms that invariably lead to the

production of neuritic plaques. These plaques precede intracellular accumulation of


15

tau and eventually result in neuronal cell death [52,53]. The hypothesis also suggests

that the plaques produce hyperphosphorylated tangles through the abnormal

regulation of kinases and phosphatases as the disease progresses [56].

Various lines of evidence have come to light in support of the hypothesis. Firstly,

mutations both within the APP and presenilin genes (genes implicated in early onset

AD) result in elevated production and accumulation of the β amyloid 42 [51,57,58].

The β amyloid 42 is more sensitive to fibrillization and therefore also more sensitive to

neuritic plaque formation [51]. Over-expression of the APP gene leads to elevated β

amyloid production resulting in the development of amyloid plaques. Down’s

syndrome patients possess three copies of chromosome 21 which codes for the APP

gene and are therefore susceptible to excessive expression of APP and possibly

generation of an excess of Aβ42. An identical brain histopathology to Alzheimer’s

patients is apparent in Down’s syndrome patients between the ages of 30-40 yrs [59-

61] with large numbers of tangles appearing between the third and fifth decades of life.

Secondly, mutations within exon 10 of the TAU gene give rise to frontotemporal

dementia characterised by cognitive impairment but occurring in the absence of

plaque formation [10,24,25]. This implies that severe tau production and accumulation

is sufficient to produce symptoms of dementia independently of amyloid plaques and

has little influence on the initiation of amyloid plaque formation. Thus Alzheimer

tangles would appear to be produced after changes in the amyloid production rather

than before [51]. Transgenic mouse models have been useful in yielding etiological

clues to both the progression and underlying mechanisms associated with disease.

JNPL3 transgenic mice expressing altered tau when crossed with Tg2576 transgenic

mice expressing altered APP showed no change in the number, age of development


16

and morphology of the neuritic plaques produced. However an increase in tau positive

tangles was more substantial within the limbic system indicating a role for APP or β

amyloid 42 in the formation of neurofibrillary tangles [62]. This suggests that changes

in the processing of the APP gene occur prior to tau alteration. Additional experiments

involving crossing APP transgenic mice with apolipoprotein allele 4 (APOE4) deficient

mice resulted in offspring with a decrease in the deposition of beta amyloid, indicating

an interaction with the APOE4 gene and amyloid processing [63]. Figure 5 outlines a

modified version of the Amyloid cascade hypothesis proposed by Hardy [52] and

Hardy and Selkoe [56].

Amyloid cascade hypothesisAmyloid cascade hypothesisAutosomal dominant forms of AD

Sporadic forms of AD

Missense mutations In APP, Presenilin 1 and 2, ACT

Chromosome 21 mosaicism, Ageing, APOE 4, failure to degrade or clear β amyloid

Increased levels of intraneuronal Aβ 42 production and accumulation

Oligomerisation in limbic and associated cortices of Aβ 42

Deposition of Aβ 42 as diffuse plaques

Microglial and astrocytic activation (release of cytokines and ACT)

Synaptic and neuronal damage and altered neuronal ionic homeostasis: oxidative damage

Altered regulation of kinases and phosphatases, leading to hyperphosphorylated tangles resulting in loss of microtubule instability.

Widespread neuronal/synaptic dysfunction. Cell death and neurotransmitter deficits.

Symptoms of Dementia

Mosaicism of chromosome 17, polymorphisms in tau gene

Alternate Tau Pathway

Abnormal production and accumulation of tau

Figure 5: . Amyloid cascade hypothesis showing pathways for β amyloid and tau production

and accumulation leading to Alzheimer’s pathology.

Although no other model trying to explain the natural history of AD has been put

forward, the model in its current form has come under a certain amount of criticism. It


17

has not been able to account for a number of observations that are important in the

pathology of AD. One of the main criticisms is that there is only a weak correlation

between plaque density and the degree of severity of dementia [64]. Additionally,

transgenic mice over-expressing the APP gene have been shown to exhibit little or no

neurodegeneration [65]. Further a small number of cases have been reported

involving exon 9 mutations within the Presenilin 1 gene involving Alzheimer’s patients

with spastic parapesis [66,67]. This condition is unusual in that few amyloid plaques

appear within the brains of affected individuals. Further evidence has indicated that

the neurofibrillary tangles appear at least a decade prior to the formation of neuritic

plaques [68,69]. Various studies have shown that tangles were present in areas of the

hippocampus and entorhinal cortex in all non-demented patients over sixty years of

age, whereas cases up to 90yrs old were found without plaques [70,71]. In their

monumental study investigating 2661 cases Braak and Braak [69] found neurofibrillary

tangles were evident in the entorhinal cortex in up to 98% of brains examined,

whereas only 70% had any evidence of neuritic plaque deposition [69]. Further

analysis showed that the initial phase of tangle development preceded plaques

deposition by up to two decades [72].


18

Frontal lobe : Responsible for voluntary movements, intellect, speech and memory.

Temporal lobe : Involved in understanding sounds, emotion and memory.

Parietal lobe : Determines sensations of touch, temperature and shape awareness.

Occipital lobe : Responsible for understanding visual images and written word.

Hippocampus : Internal to the temporal lobe. Comprises of entorhinal cortex, subiculum, dendate gyrus and CA1. Involved in memory and spatial orientation

Figure 6 : Showing areas of brain affected by Alzheimer’s disease. The problem is therefore how to explain the substantial evidence supporting the

amyloid peptide as a causative agent of Alzheimer’s on the one hand, with the equally

strong evidence implying that tangle formation precedes plaque deposition and

therefore does not fit into the current cascade hypothesis model. It has been proposed

that neurofibrillary tangles are an independent feature accumulating slowly with age

within the medial temporal lobes. However under the influence of altered amyloid

metabolism, which leads to plaque formation during the initial stages of Alzheimer’s,

there is an acceleration of tangle formation that spreads further to include the

neocortex [70]. It appears that tangles form normally with age independently of plaque

formation. The density of tangles increases with age in an exponential fashion and

without any amyloid influence appears to remain confined to the medial lobe [73]. As

tangle physiology involves synaptic and neuronal loss there would be a stronger


19

correlation between tangle density and degree of severity of dementia. This would be

facilitated as soon as tangle acceleration occurs as a result of plaque influence [70]. It

would appear that since its initial conception the cascade hypothesis has been

supported through a whole body of work that has emerged from laboratories from

around the world. Alternative models have not been proposed to explain deficiencies

within the cascade hypothesis with the same degree of experimental support that is

available for the current model. With the passage of time and with the emergence of

new experimental data, the current hypothesis will be either reshaped to explain the

pathogenesis of the disease or be replaced with an alternative model, which will have

to explain all facets of aetiology and progression of the disease.

1.7 Genetics of Alzheimer’s Disease Inheritance of known genes that predispose to AD accounts for only 5-10% of all

clinically presented cases [10,74]. Familial Alzheimer’s disease (FAD) can be

classified as either early onset or late onset. The genes implicated in early onset forms

of the disease which occur below 65yrs of age are the APP gene located on

chromosome 21q21; Presenilin 1 (PSEN1) located on chromosome 14q24.3 and

Presenilin 2 (PSEN2) on chromosome 1q31-q42 [23,74,75]. Mutations within the APP

occur around the processing sites of the APP molecule resulting in increased

production of the beta amyloid peptide [76]. Most cases containing APP mutations

have an age of onset between mid 40’s-50’s but can be modified by the presence of

the Apolipoprotein E (APOE) genotype [57]. Mutations within the APP gene appear to

be family specific and do not occur within the majority of sporadic Alzheimer’s cases.

Missense mutations within the PSEN 1 gene account for 18-50% of the early onset

autosomal dominant forms of AD [77]. Mutations within the PSEN1 lead to a


20

particularly aggressive form of the disease having an age of onset between 30 and

50yrs, which is not influenced by the APOE genotype. However a polymorphism found

within intron 8 of the PSEN1 gene was found to be associated with the development of

the late onset form of the disease [77,78]. To date over 75 mutations have been found

within the PSEN1 gene in families worldwide that are associated with the early onset

form of the disease [31]. All mutations within PSEN1 increase production of the β

amyloid 42 [57,58]. Mutations within PSEN2 have a variable age of onset (40-80yr),

appear not to be influenced by APOE and result in increased β amyloid peptide

production [57].

The gene for APOE is located on chromosome 19q13.2 and certain polymorphisms

are associated with the late onset form of AD (>65yrs) [23,79]. The E3 allele is

considered normal and occurs in ~74% of the population; the E2 and E4 allele are

less common, occurring in 10% and 16% of the population respectively [10,79]. The

APOE gene does not cause Alzheimer’s but acts as a marker altering individual risk

based on possession of allelic combinations of the APOE4 allele [80]. The highest risk

is associated with the E4/E4 genotype. It has been proposed by Corder et al [80], that

each copy of the APOE4 allele reduces the age of onset by 7-9yrs. An average age of

onset of 85yrs is given for individuals with no E4 alleles, 75yr for one allele and 68yrs

for individuals with two copies of the E4 allele [23,80].


21

PSEN 2 PSEN 1

APOEAPP

TAU

Figure 7: Chromosomes showing positions of the main Alzheimer’s related genes

Whereas genetic alterations in the previously mentioned four genes (Figure 7) are

generally accepted as being implicated in causing FAD, other studies highlighting the

potential role of other genes have come to light.

Alpha 2 macroglobulin functions as a protease inhibitor and has been found in neuritic

plaques. The gene is on chromosome 12p13.3 and variants of the gene are

associated with the late onset form of the disease [81,82].

Genetic linkage analysis has identified a potential AD gene at or near the Insulin

degrading enzyme gene found on chromosome 10q23-25 which is involved in the

cellular processing of insulin. At the current time further genetic analysis is being

undertaken to determine a thorough assessment of this potential locus [83,84].


22

The monoamine oxidase A gene serves to regulate the metabolism of neuroactive and

vasoactive amines within the central nervous system. polymorphisms within this gene

have also been implicated in the pathology of AD [85].

Myeloperoxidase (MPO) is an enzyme present in circulating monocytes and

neutrophils and is part of the host’s polymorphonuclear leukocyte defence system.

MPO catalyses the production of the oxidant hypochlorous acid and is thought to

contribute to Alzheimer’s pathology through oxidation of either β amyloid or APOE

[86]. These events could result in direct neuronal damage or promote insoluble

amyloid complexes. It is interesting to note that the E4 isoform of APOE is the most

readily oxidised and neurotoxic, conferring upon it a contributory role to increased risk

for the disease [87]. Microglia in normal brain tissue do not express MPO but it has

been found to be expressed in the microglia of the senile plaques and neurons of the

hippocampus and superior frontal gyrus within Alzheimer’s brains [88]. The gene for

MPO resides on chromosome 17q23.1 and recently a polymorphism (G463A) has

been associated with a 1.57 fold increased risk for AD in individuals carrying the MPO

GG genotype [87]. Novel polymorphisms found within the TAU gene have been

associated with an increased risk for AD. A case control study looking at the TAU

IVSII+90G→A polymorphism showed a significant association between early age of

onset in males and the possession of the A allele. This suggests that the risk factor for

developing the disease may be modified as a result of both age and gender [89]. A

further case control study examining the IVSII+34 G→A polymorphism showed a five

fold increased risk in individuals who carried both the APOE4 allele and were either

heterozygous /homozygous for the G allele (GA, GG). This would suggest that the

combined effect of both these alleles may have a significant outcome on Alzheimer’s


23

pathology [90]. Hyperdiploidy of chromosome 17 would also result in over expression

of both the MPO and TAU gene and may be expected to contribute to the etiology of

the disease.

Mutations within genes such as APOE, CYP46A1 and ABCA1 which play a role in

cholesterol and phospholipid metabolism have been investigated and shown to have

associations with AD. Recently a strong association between early onset Alzheimer’s

and polymorphisms within the ABCA2 gene have been shown adding support for the

role of these genes in Alzheimer’s pathology [91].

Alpha-1-antichymotrypsin (ACT) is a protease inhibitor and is associated with

astrocyte activity and the deposition of amyloid plaques. The G646T polymorphism

within the promoter region of ACT has been shown to be associated with a higher risk

for early onset AD. This higher risk factor occurs independently of the APOE 4

genotype; however the rate of cognitive decline is elevated in those individuals

homozygous for the ACT polymorphism and who also possess the APOE 4 genotype

[92].

It has recently been suggested through the results of linkage analysis that the

Ubiquilin 1 gene located at 9q22 could be a possible susceptibility gene for increased

risk for AD [93]. It plays an intriguing role in the degradation of proteins and has been

shown to interact with both PSEN1 and PSEN2, promoting the accumulation of

presenilin in vitro in cells over expressing both Ubiquilin 1 and presenilin 2 [94].

Further investigations will need to be undertaken to further assess the role of Ubiquilin

as a potential candidate risk gene for AD.


24

It is apparent that numerous families exist that possess the Alzheimer’s phenotype but

do not conform to the current pattern of known Alzheimer’s genetics. This would

indicate that there are as yet other loci waiting to be discovered that can act as genetic

determinants for FAD.

Although much emphasis has been placed on the role of APOE as a risk factor, this is

because of the current body of evidence that firmly establishes it in its role as a

susceptibility gene relative to other known or unknown genetic risk factors. Other

genes that have been reviewed are currently potential susceptibility genes but their

status as definite risk factors can only be confirmed or refuted as additional evidence

comes to light resulting from further investigation e.g. mutations within the progranulin

gene on chromosome 17 have recently been found to play a role in dementia and may

eventually be classified as a definite risk factor once these initial observations have

been replicated [95].

1.8 Genomic Instability Events

1.8.1 Aneuploidy Damage to the genome could lead to altered gene dosage and gene expression as

well as contribute to the risk of accelerated cell death in neuronal tissues. DNA

damage events such as micronuclei formation, which are biomarkers of chromosome

malsegregation and fragility were found to be elevated in lymphocytes from individuals

suffering from AD [96]. Micronuclei from Alzheimer’s patients tended to be centromere

positive relative to normal controls when examined with a centromeric probe,

indicating whole chromosome loss rather than breakage, suggesting individual


25

susceptibility to aneuploidy events possibly due to microtubule dysfunction [96,97].

Fluorescent probes for chromosome 13 and 21 were hybridised to lymphocyte

preparations from Alzheimer’s patients and showed an elevation in aneuploidy for both

chromosomes, but in particular for chromosome 21 [97],[98]. Further studies

investigating fibroblasts from both spontaneous and familial Alzheimer’s subjects

carrying mutations in the genes PSEN1, PSEN2, and APP were found to have a two

fold increase in the incidence of aneuploidy involving both chromosome 18 and 21

when compared to controls [99]. It is possible that chromosome aneuploidy,

particularly for chromosome 21, could be one of the mechanisms underlying both AD

and the dementia that occurs in Down’s syndrome patients [100].

Down’s syndrome (DS) is diagnosed cytogenetically as being aneuploid for

chromosome 21; individuals develop dementia that is histopathologically

indistinguishable from AD during the third or fourth decade of life [101]. Cells

containing trisomy 21 are found in both DS and Alzheimer’s patients. Over-expression

of the APP gene could lead to overproduction of the β amyloid 42 following cleavage

by the secretase enzymes, which is causally related to plaque formation in both DS

and Alzheimer’s brains [102]. APP processing is also altered in terms of the ratio of β

amyloid 42 over the normal 40 amino acid β amyloid peptide (Aβ40), resulting in the

increased production of the more amyloidogenic and neurotoxic form β amyloid 42

[102]. It has been proposed that individuals who are susceptible to AD may harbour

significant numbers of trisomy 21 neural stem cells that with the passage of time, can

result in brain segments having a DS phenotype which may contribute to the aetiology

of the disease [100]. It is possible that like DS this low level mosaicism may have

originated in utero as a result of age related parental non-disjunction, or under dietary


26

conditions such as low folate status that has been shown to increase the rate of

chromosome 17 and 21 aneuploidy [103]. Alternatively, mosaicism may arise in those

individuals who have a predisposition to aneuploidy events, which involve unequal

mitotic segregation in aneuploid susceptible tissues within areas of the brain

undergoing post-maturation neurogenesis. Such areas that may be affected include

the dendate gyrus of the hippocampus that is involved in short term memory and

learning and is readily affected in the initial stages of Alzheimer’s. These individuals

are predisposed to develop the disease but over a longer period of time, due to the

smaller population of mosaic cells that over express genes that contribute to the

symptoms of the disease such as APP and TAU. These hypotheses are biologically

plausible however further evidence needs to be acquired to determine conclusively the

potential roles of these mechanisms in Alzheimer pathology. Mutated presenilin genes

that contribute to early onset FAD [104-106], produce proteins that have been found to

be localised within the nuclear membrane, centrosomes and interphase kinetochores

indicating a role in chromosome segregation and organisation [99,106]. Mutations

within these genes that predispose to early onset FAD [104-106], may alter the ability

of the resultant proteins to lock on and release chromosomes to the nuclear

membrane at the appropriate time during mitosis, hence leading to errors in

chromosome segregation [106].

Aneuploid cells may be susceptible to programmed cell death directly leading to neuro

degeneration by over expressing presenilins and APP that increase the cells

sensitivity to apoptotic stimuli [107]. These cells having succumbed to apoptosis may

then give rise to areas of inflammation, induced by the cerebral phagocytes microglia,

that surround the neuritic plaques. Microglia induce astrocytes by expressing


27

Interleukin-1. The astrocytes in turn express α-chymotrypsin which promotes further

neurotoxic amyloid plaque formation [108,109].

Hyperphosphorylation of tau leads to a breakdown of the microtubule system which

may give rise to aneuploidy by causing defects in the mitotic spindle. Potentially an

elevation in chromosome 17 aneuploidy could lead to an over expression of the TAU

gene resulting in abnormal production and accumulation of the protein initiating further

neurofibrillary tangle formation. Additional chromosome 17 aneuploidy may occur as a

result of elevated levels of oxidative stress that are also associated with AD [110].

1.8.2 Telomere shortening, oxidative stress, breaka ge fusion bridge cycles and gene amplification.

Telomeres are hexanucleotide repeats that are located at the end of eukaryotic

chromosomes and their dysfunction has been implicated in AD. They play an

important role in maintaining genomic stability and preventing chromosomes from

becoming tangled and protect the chromosomal ends from being recognised as a site

of DNA damage [111,112]. During DNA replication somatic cells lose telomeric

repeats after every cell division undertaken, and therefore telomere length may serve

as a marker of a cells replicative history. Telomerase and associated proteins prevent

telomeres shortening in extreme proliferative cell types such as cancer cell lines and

stem cells. Telomerase is also present in other cells such as lymphocytes but at levels

that cannot prevent shortening of the telomeres leading to replicative senescence

[111,113].


28

It has been shown that telomere shortening is associated with an elevated incidence

of certain cancers (head, neck, lungs, epithelial cancers such as prostate) and is

exacerbated by other risk factors such as ageing and smoking [114]. Other studies

have shown that individuals exhibiting accelerated telomere shortening die 4-5yrs

earlier and have higher incidences of heart disease compared to age and gender

matched controls [115]. Telomere shortening results in a decrease in lymphocyte

proliferation activity and has been shown to impair the immune system in AD.

Telomere shortening is also associated with T cell clonal expansion involving immune

responses to auto antigens in Alzheimer’s patients. Panossian et al [112] found

significant telomere shortening in peripheral blood mononuclear cells from Alzheimer’s

patients compared to controls. T cell telomere length correlated with deficits in

cognitive function, as assessed by the mini mental state examination which

determines cognitive decline [112]. Telomeres have also been found to be significantly

shorter in leukocytes of individuals suffering from vascular dementia compared to age

and gender matched controls [116]. Genomic instability resulting from telomere loss

may lead to gene over expression as a result of gene amplification, through the

repeated breakage and fusion of chromosomes that occur through the

breakage/fusion/bridge (BFB) cycle [117-119].

The cycle can be initiated by telomere end fusions with short telomeres, which fuse to

form a dicentric chromosome. If the fusion occurs between homologous chromosomes

the dicentric chromosome will contain two copies of a gene positioned between two

centromeres. These centromeres are drawn to opposite poles during anaphase and

break unevenly as cytokinesis occurs. This results in a chromosome containing two

copies of a gene and a fragment that has lost its initial gene copy. These multiple


29

gene containing chromatids may further fuse during interphase to form another

dicentric chromosome increasing its gene complement which is then replicated during

nuclear division resulting in further amplification following the next BFB cycle [120,121]

(Figure 8).

It has been shown that smaller chromosomes such as chromosome 17 and 21 have

shorter telomeres than their larger genomic counterparts [122]. It may be possible that

these smaller chromosomes may be more susceptible to undergo BFB cycles [123],

resulting in over expression of Alzheimer’s related genes such as TAU and APP. This

hypothesis has biological plausibility but further evidence is required in order to

determine conclusively its role in Alzheimer’s pathology.


30

Breakage fusion bridge cycle

(A)

(B) (C)

(D)

(E)

(F)

(G)

Short telomeres

Figure 8: Breakage fusion bridge cycle resulting from telomere end fusions.

A) Chromosomes with shortened telomeres form a dicentric chromosome resulting from

telomere end fusion forming a dicentric chromosome. B) The dicentric chromosome is

replicated during S phase (C) and centromeres are pulled at opposite ends of the poles at

anaphase (D). Uneven breakage of the dicentric chromosome results in altered gene dosage

producing daughter cells containing extra gene copies (amplification) (F) whilst the remaining

daughter cell (E) has a deleted gene copy number. The multiple copy number chromosomes

may fuse again to form a dicentric chromosome housing increased gene copy number (G).

The dicentric is further replicated at (C) and the cycle is repeated.

Differences in the telomere length of human chromosomes may be a contributory

factor relating to a higher incidence of specific chromosome aneuploidy [124].

Telomeres are implicated in the positioning of chromosomes by forming a point of

attachment to the nuclear membrane within the interphase nucleus and in chromatid

segregation during mitosis. Smaller chromosomes with shorter telomeres such as


31

chromosomes 17 and 21 may be more susceptible to aneuploidy events as a result of

mitotic non-disjunction events or faulty interphase chromosomal positioning. It is also

possible that BFB cycle events involving dicentric chromosomes containing

homologous chromosomes may result in aneuploidy through the formation of

chromosomal end to end fusions resulting in subsequent gene amplification [122,125].

It has also been shown that telomere shortening is accelerated under conditions of

oxidative stress [116,126]. Some of the measurable genome instability events are seen

in Figure 9.

Figure 9: Genomic instability events. a) Lymphocyte showing micronuclei which are

biomarkers of chromosome loss or breakage. b) Lymphocyte showing fluorescent probes for

chromosome 17 and 21 to determine aneuploidy. c) Lymphocyte nucleus showing telomere

signals from a PNA fluorescent probe.

Oxidative stress is now accepted as playing a key role in the pathology of AD [127-

129], and is the result of an imbalance between elevated free radical production and a

decrease in either free radical scavenging or the mechanisms used to repair oxidised

macromolecules. This leads invariably to cellular dysfunction and eventual cell death.

a) Lymphocyte showing

micronuclei

b) Lymphocyte showing centromere specific fluorescent probes for Chromosome 17 (red) and 21(green).

c) PNA probes labelled With Cy5 hybridising to telomere sequence


32

Free radicals such as the hydroxyl ion, hydrogen peroxide and peroxynitrite have been

shown to induce cytotoxicity by interacting with and damaging major components of

the cell through oxidation of lipids and nucleic acids including the nucleus, membrane

and cytoplasmic proteins, mitochondrial DNA as well as being involved with neurotoxic

metal complexes, thereby compromising their cellular function. Neurons appear to be

particularly vulnerable to the damaging effects of free radicals, they are known to have

low levels of natural antioxidants such as glutathione which would aid in protecting the

neuron [43], as well as requiring an increased oxygen demand to maintain brain

metabolism [130]. The elevated oxygen environment is ideal as it can be used as a

substrate in reactions with compounds that are primary producers of free radicals e.g.

β amyloid.

APOE may be beneficial by reducing neuronal death caused by β amyloid and

hydrogen peroxide by acting as an antioxidant [131]. Of the three allelic states the E2

isoform is the most effective antioxidant with the E4 allele (associated with late onset

AD) being the least effective in its protective capacity [132]. However it has also been

shown that the APOE4 isoform is the most sensitive to free radical attack compared to

the more resilient E2 isoform and that peroxidation levels in the brains of AD patients

that possessed the E4 allele are elevated compared to those individuals possessing

either the E2 or E3 allele [133].

It has recently been shown using a modified version of the comet assay that there is a

twofold increase in levels of DNA damage and oxidised DNA bases (pyrimidines and

purines) in leukocytes of individuals with mild cognitive impairment (MCI) and AD

when compared to matched controls [134]. MCI individuals display the initial signs of


33

cognitive decline (memory loss) but not to the extent that they cannot pursue or

participate in everyday activities. This suggests that oxidative damage occurs at the

early stages of AD, as MCI patient’s progress to Alzheimer’s with an estimated

probability of 50% within four years or approximately 12% per year [134,135],

suggesting that MCI represents the early stages of the disease and that oxidative

stress directly contributes to disease pathology.

A further marker of oxidative stress 8-Hydroxy-2-deoxyguanosine (8-OHdG) is

elevated in both peripheral tissues of MCI and AD [129,134,136]. It has also been

shown that oxidative stress is clear within the post mortem Alzheimer’s brain where an

increase in mitochondrial and nuclear oxidative damage is evident [44,135].

Interestingly it appears that an increase in both 8-OHdG and 3- Nitrotyrosine within the

Alzheimer’s brain occur prior to the development of both tangles and plaques

indicating that oxidative stress may be one of the initiating factors leading to further

genomic instability [44,136,137].

The genome instability model of AD outlined in Figure 10 allows for the possibility that

certain disease states may have already been pre-determined in utero. Aneuploidy

prone individuals (either as a result of individual genome or micronutrient deficiency

e.g. folate) can give rise to low levels of mosaicism for individual chromosomes such

as chromosome 17 and 21. Gene amplification may occur as a result of telomere end

fusions (Figure 8). Aneuploidy may result in additional copies of both APP and TAU

leading to the altered homeostasis of both these proteins. The Alzheimer’s phenotype

becomes apparent in stem cells which differentiate into neural stem cells with

abnormal APP and tau levels, which with the passage of time influence the initial


34

stages of neurodegeneration. These stem cells could also differentiate into non-neural

somatic cells (e.g. buccal or fibroblast which having an elevated tau and APP level)

and could be used to study genomic instability events such as elevated micronuclei

and aneuploidy.

Genome instability model of Alzheimer’s disease

Telomere shortening

a) Oxidative stress b) Micronutrient deficiency

Breakage fusion bridge cycle

Increased gene amplificationIncreased aneuploidy 17 and 21in stem cells

Defects in APP and Tau expression and processing.

Inherited genetic defects

Increased neuronal cell death

Neurodegenerative disease

In Utero

Alzheimer phenotype in stem cell subsets.

Abnormal APP and Tau in non neural somatic cells

Elevated MN, aneuploidy excess APP, βamyloid and Tau in somatic tissues

Figure 10 . Genome instability model of Alzheimer’s disease.


35

1.9 Dietary and Nutrigenetic factors that affect Al zheimer disease risk

1.9.1 B Vitamins

Many case control studies have shown that Alzheimer’s patients have been found to

be deficient in certain micronutrients such as folate, vitamin B12 but have elevated

levels of the sulphur based amino acid homocysteine [138,139]. These factors are

associated with increased micronucleus formation and the alteration of methylation

patterns that could modify gene expression [120,140,141]. Folate and vitamin B12

play an important role in DNA metabolism. Folate is the methyl donor for the

conversion of dTMP from dUMP which is required for DNA synthesis and repair.

Under conditions of low folate, dUMP accumulates producing DNA strand breaks and

micronucleus formation as a result of uracil misincorporation into DNA in place of

thymine [120,142]. Both folate and Vitamin B12 are required in the synthesis of

methionine through the remethylation of homocysteine, and in the synthesis of S-

adenosyl methionine (SAM) which is involved in maintaining genomic methylation

patterns that determine gene expression [143]. Folate deficiency reduces SAM

resulting in the depletion of cytosine methylation in DNA, and thereby elevating

homocysteine levels. Additionally folate deficiency has been shown to increase

trisomy of chromosome 17 and 21 which code for the TAU and APP genes

respectively [103].

Hyperhomocysteinemia has been shown to be a strong independent risk factor for AD

in a number of epidemiological studies [144-148]. It appears that nervous tissue may

be extremely sensitive to excessive homocysteine as it promotes excitotoxicity and

damages neuronal DNA giving rise to apoptosis [149]. Studies have also shown a


36

strong correlation between a reduction in hippocampal width, which is associated with

short term memory loss and concentrations of plasma homocysteine [150]. Recently

MRI measurements have shown that an inverse relationship exists between plasma

homocysteine and cortical and hippocampal volume [151]. The above findings have

been interpreted as involving neuronal damage within the hippocampal regions

leading to memory loss, which is characteristic of AD. Elevated homocysteine has also

been implicated as playing a role in an iron dysregulation/oxidative stress cycle that is

thought to be central to the pathogenesis of the disease [152]. Homocysteine levels

are usually maintained within physiologically correct limits by remethylation to

methionine in a reaction involving folate and vitamin B12 (Figure 11). Homocysteine

can also be converted to cystathionine by the involvement of the enzyme

cystathionine β-synthase, resulting in increased levels of glutathione which is a natural

anti oxidant [153].

Studies have shown that supplementation with B group vitamins such as folate, B12

and B6 reduce the levels of homocysteine in patients suffering from AD [138,154]. It

has also been shown that low levels of B12 are associated with reduced memory

recall in those individuals who are APOE4 carriers who are at greater risk of

developing dementia. These individuals may derive benefits in memory recall by

enhancing supplementation of both folate and B12 [155]. Niacin (Vitamin B3) has a

role in DNA synthesis and repair as well as in neural cell signalling. Recently it has

been implicated in reducing cognitive decline and protecting against the onset of AD.

Individuals consuming niacin in excess of 22.4mg/day were estimated to be 80% less

likely to suffer cognitive decline when compared to groups consuming lesser amounts

[156]. Niacin is also essential as a precursor for Nicotinamide adenine dinucleotide


37

(NAD) an essential cofactor for poly ADP ribose polymerase which has been shown to

play an essential role in memory function of the mollusc Aplysia [157]. NAD dependent

sirtuins such as SIRT1 have been implicated as one of the key regulatory factors

influencing extended lifespan under conditions of calorific restriction. It has also

recently been shown that SIRT1 promotion may influence Alzheimer neuropathology

by activating kinases that regulate the processing of APP [158]. Although these initial

results are promising, further studies need to be performed to verify conclusively the

role of niacin as an effective therapy in the protection against AD.

1.9.2 Mutations in Folate, Methionine metabolism ge nes As AD is related to low folate, B12 and elevated homocysteine levels, investigators

have looked towards genetic polymorphisms within the folate methionine pathway

(Figure 11) to explain these micronutrient differences. Polymorphisms within these

genes may alter folate metabolism as a result of reduced enzyme activity. A

polymorphism resulting in altered folate metabolism and increased homocysteine

occurs within the methylenetetrahydofolatereductase gene (MTHFR). MTHFR

converts 5, 10 methylenetetrahydrofolate to 5- methyltetrahydrofolate which donates a

methyl group for remethylation of homocysteine to methionine. A common

polymorphism involves the C to T transition at position 677 resulting in an alanine to

valine substitution and reduced enzyme activity. Enzyme activity of the heterozygote

C/T and the homozygote TT is reduced by 35% and 70% respectively when compared

to the normal C/C genotype [159]. Homozygosity for the T allele occurs in ~9% of

Caucasian populations and is associated with reduced enzyme activity resulting in

mild to moderately elevated homocysteine levels [160]. Other polymorphisms within


38

the MTHFR gene include A1298C and G1793A which may have regulatory roles in the

activity of the enzyme [161]. In determining the risk factor of C677T in relation to AD

no association between C677T and increased susceptibility to Alzheimer’s risk was

found [162]. However if combinations of polymorphisms within a gene are considered

together then sometimes effects become apparent that are not always evident if those

same polymorphisms are considered in isolation. Wakutani et al [163] found that the

MTHFR 677C-1298C-1793G haplotype to be protective in Japanese populations

against late onset AD [163]. Methionine synthase (MTR) catalyses the remethylation

of homocysteine to methionine. The A2756G polymorphism within the MTR gene has

been shown to be associated with hyperhomocysteinemia, and to be an APOE4

independent risk factor for AD [164]. This implies that alterations within the genes for

enzymes of the homocysteine metabolic pathway are involved in Alzheimer’s

pathogenesis [165].


39

MTHFR

dUMP

DIET

CH3

dTMP

Polyglutamates

DNA synthesisand repair

DNAmethylation

Gene expression andgenome stability

Tran sulphuration pathway (cysteine

synthesis)

DHF

THF

5,10-MethyleneTHF

Homocysteine

Methionine

SAM

SAH5-Methyl THF

B12

Monoglutamates SerineGlycine

SHMT/B6

CBS/B6Serine

ThymidylateSynthase

METHIONINESYNTHASE

Folate and Methionine Pathway

NeurotransmitterSynthesis

Figure 11 . Metabolism of Folic Acid. Adapted from Wagner C., Biochemical Role of Folate in

Cellular Metabolism. Folate in Health and Disease. Bailey L.B.(Ed), p 26, 1995. SAM: S-

Adenosyl Methionine, SAH: S-Adenosyl Homocysteine, CBS: Cystathione b Synthase, THF:

Tetrahyrdofolate, DHF: Dihydrofolate, MTHFR: Methylene Terahydrofolate Reductase, SHMT:

Serine hydroxy-methyltransferase,

1.10 Methylation

Changes in methylation patterns of ageing cells involve global hypomethylation and

CpG island hyper-methylation. Folate deficiency decreases S-adenosyl methionine

(SAM) levels which act as a methyl donor for gene regulation, thereby potentially

impairing methylation pathways. Individuals with AD were found to have reduced

levels of SAM both in the brain and cerebrospinal fluid [166]. SAM also activates the

enzyme Cystathionine β-synthase (CBS) which is highly expressed in the


40

hippocampus and cerebellum [167]. CBS reduces homocysteine to cystathionine and

L-cysteine producing hydrogen sulphide which acts as a neural modulator by

facilitating hippocampal long term potentiation and therefore may have a role in

learning [167,168]. Hydrogen sulphide has also been shown to protect neurons

indirectly from oxidative stress by promoting the production of the potent antioxidant

glutathione [169]. CBS activity is reduced in AD patients, resulting in a decrease in

hydrogen sulphide and an elevation in homocysteine, which may play a role in the

cognitive decline associated with the disease [168,170].

It has been shown that low satellite DNA methylation leads to aneuploidy and

breakage of chromosome 1 which codes for PSEN2 [141,171], whereas low genome

promoter methylation leads to increased expression of PSEN1 and BACE (β

secretase) resulting in elevated Aβ production [140,172]. It has also been shown that

a reduced DNA methylation status in the APP gene results in increased production of

the β amyloid 42, which leads to further elevated plaque deposition [173]. Moreover,

when methylation status is increased by the addition of SAM a normalisation of the

PSEN1 and BACE expression occurs in vitro thus restoring normal gene expression

leading to a reduction in Aβ levels [140]. Alzheimer’s related genes may also be

amplified via breakage-fusion-bridge cycles caused by folate deficiency [120] although

direct evidence for this possibility has yet to be published. Therefore promoter

hypomethylation, aneuploidy and gene amplification resulting from deficiencies in

folate and B12 and elevated homocysteine, may contribute to abnormally increased

expression of genes relating to AD.


41

1.11 Antioxidants

Oxidative stress and inflammation have been implicated as some of the main

contributing factors in the pathogenesis of AD. Recently a number of studies have

come to light that show the positive effects of dietary antioxidants as an aid in

reducing potential neuronal damage by free radicals [43,174,175].

The Cache County study has shown that combined supplementation with antioxidant

Vitamins C and E may reduce the prevalence of AD [176]. It has recently been shown

that hippocampal gene expression in mice can be influenced by a deficiency in

Vitamin E. Important genes regulated by vitamin E were associated with the clearance

of beta amyloid, programmed cell death and neurotransmission, suggesting a

protective role on Alzheimer’s progression [177].

Curcumin is the yellow phenolic pigment in the Indian curry spice turmeric. It has been

shown to possess both antioxidant and anti-inflammatory properties as well as the

ability to reduce beta amyloid 42 toxicity by preventing the formation of beta 42

oligomers leading to amyloid plaques [178,179]. In animal models curcumin was

shown to inhibit amyloid plaque formation by blocking the aggregation of the beta

fibrils that make up the structure of the amyloid plaque [179,180]. Curcumin may also

prevent the formation of plaques by behaving as a chelator, binding metals such as

copper and iron that have been shown to form complexes with beta amyloid 42

resulting in oxidative stress and free radical formation [181].

Out of 60 fruit and vegetables analysed for their antioxidant capability, blueberries

rated highest in their ability to mop up free radicals [182]. Blueberries contain high


42

levels of the antioxidant anthocyanins; these prevent damage to the collagen matrix of

cells by forming complexes with collagen fibres, to form a more stable structure that is

more resistant to the damaging effects of free radicals [183]. In animal models it

appears that blueberries not only protect against oxidative damage, but also play a

vital role in preventing cognitive decline in mice genetically engineered to develop the

amyloid plaques typical of AD [183,184].

Proanthocyanins, a group of polyphenol compounds that occur within grape seed

extract (GSE), have been found to be up to 20 times more effective in scavenging free

radicals than vitamin E, and up to 50 times more effective than vitamin C [185]. In

experiments involving brain cells from rats, it was shown that cells treated with GSE

and then exposed to beta amyloid were protected against free radical accumulation

and neuronal damage, compared to GSE untreated brain cells that subsequently died

as a result of free radical accumulation [186]. It has also been shown that GSE used

as a dietary supplement affects certain proteins within the healthy brain that may

serve to protect against brain ageing and future age related dementia [187].

Green tea has been shown to contain antioxidant flavonoids that can protect against

neuronal damage caused by free radicals. One of the mechanisms by which green tea

offers protection, is by its action as a chelating agent, binding excess iron levels which

serve to reduce the amount of oxidative stress caused from free radical production

[188].

Animal studies involving Alzheimer’s transgenic mice show that a green tea flavonoid

epigallocatechin-3-gallate (EGCG) has the ability to reduce levels of beta amyloid and


43

neuronal plaques within the brain [189]. This suggests that dietary supplementation

with EGCG may be effective in preventing plaque formation that is characteristic of the

disease.

Acetylcholine is a neurotransmitter that is reduced in AD. Green tea has been shown

to inhibit the activity of certain brain enzymes associated with reduced cognitive

function and the development of AD [190]. Green tea drinkers were found to have

lower activity in both acetylcholinesterase which breaks down acetylcholine and

butylcholinesterase which has been found in brain deposits of Alzheimer’s patients. β

secretase an enzyme that plays an integral role in the aberrant proteolysis of APP

resulting in plaque formation was also found to have lower enzyme activity in

individuals exposed to green tea flavonoids [190]. A study investigating cognitive

function and green tea consumption revealed that individuals who drank more than 2

cups of green tea a day had a 50% lower chance of developing memory disorders

compared to individuals who drank less than 3 cups a week. Cognitive function was

determined by the use of the mini mental state examination, a method that is widely

used to assess changes in the cognitive status of individuals [191].

Continued studies into the chemo-preventative components of foodstuffs are

important, in order to quantify their role as protective therapies for AD.


44

1.12 Copper, Iron, Zinc, Selenium and Aluminium

Recently, associations between metals such as copper (Cu2+), iron (Fe2+) and zinc

(Zn2+) and amyloid plaques have been proposed as a potential mechanism to explain

the aetiology of AD. Metals play a major catalytic role in the generation of free radicals

which are known to be toxic and induce cellular damage at both DNA and protein

levels. High concentrations of Cu2+, Zn2+ and Fe2+ are found in the cerebral neocortex

[192]. These ions are released during neurotransmission resulting in increased ion

concentration within the synaptic region [193]. It has been shown that the

concentration of these ions is elevated within the extracellular beta amyloid plaques

[194-196]. Both copper and iron initiate the aggregation of beta amyloid peptides

under slightly acidic conditions [197]. The precipitation and redox potential of β

amyloid can be modified through reduction reactions utilising oxygen as a substrate to

produce hydrogen peroxide [194,197,198]. Hydrogen peroxide is highly permeable

and diffusible, whereupon it can induce apoptosis and necrosis and produce highly

reactive hydroxyl ions bringing about further cellular damage [199]. The resultant

hydrogen peroxide offered a possible mechanism to explain neurotoxicity and cell

death mediated by the beta amyloid–metal complexes [198].

Zinc2+, unlike copper and iron, is redox inert, but is still found in elevated levels within

the amyloid plaques [194-196,200]. It appears that zinc, like copper and iron, can

initiate amyloid precipitation, however it has an inhibitory effect on hydrogen peroxide

production by competing with other metals for active sites on the β amyloid [197,201].

It is thought that zinc leads to beta amyloid aggregation at the physiological pH of

about 7.4 and this results in an inability of the plaques to be cleared or broken down.

Zinc has been shown to have some antioxidant activity in relation to minimising the


45

neurotoxic effect of the β amyloid 42; however it is not completely effective in

alleviating peroxide production and apoptosis. It would appear as if zinc could

potentially play a dual role depending on the concentration of the ion present. At lower

levels it appears to render β amyloid less toxic whereas at elevated levels it

contributes to plaque formation.

Further support for the involvement of zinc in the histopathology of AD was

demonstrated by Lee et. al. who showed a reduction in beta amyloid production in the

brains of mice that were deficient for zinc transporters which are required for transport

of zinc into synaptic vesicles [202]. It has been proposed that release of excessive

synaptic zinc during neurotransmission, could contribute to plaque formation which is

dominant to the histopathology of AD [202]. The selenium present in Brazil nuts, tuna

and some meats has been shown to be inversely associated with levels of

homocysteine. It was found that serum selenium had a greater regulatory capacity to

minimise homocysteine levels in elderly persons, even when compared to folate

regulatory levels [203]. Selenium is also indirectly responsible for maintaining levels of

antioxidants such as vitamin C and E intact via the enzyme glutathione peroxidase.

The metalobiology of aluminium and its role as a risk factor in AD has been a

controversial issue. The purported relationship between aluminium and AD was based

on studies reporting the detection of aluminium in the neurofibrillary tangles [204,205]

and neuritic plaques [35,206]. However later studies found no evidence of aluminium

in the plaques of Alzheimer patients [207]. Similar patterns emerge from

epidemiological studies investigating environmental levels of aluminium in drinking

water. Some studies showed a positive association whereas others reported no such


46

relationship [208,209]. To date the evidence is considered circumstantial

demonstrating no definite causal relationship between aluminium, and AD.

Government regulatory agencies together with the medical research community

review the current evidence at regular intervals, but to date no public health

recommendations have been put forward regarding aluminium and AD risk.

1.13 Conclusion

AD was once described as like being slowly immersed into a dissipating fog, that

surrounds everything that is familiar and everything that characterises the make up of

an individual [210]. As the fog descends and thickens so everything loses its form and

function. As we stare into the 21st. century we are faced with a disease that is

predicted to make a pronounced impact on our lives both socially and economically.

The prospect of an early and conclusive diagnostic test based on abnormal

expression of APP, tau and genome instability markers is essential in order to identify

individuals presymptomatically who are at an increased risk for developing AD. Once

this has been achieved this may allow us to develop and implement effective

preventative measures against AD, as well as other degenerative diseases caused by

an excessive genome damage rate.

Chapter 2: Buccal cytome in ageing and Down’s syndr ome

47

2 Chapter 2: The buccal cytome and micronucleus

frequency is substantially altered in Down’s syndro me

and normal ageing compared to young healthy control s


48

2.1 Abstract The buccal micronucleus cytome assay was used to investigate biomarkers for DNA

damage, cell death and basal cell frequency in buccal cells of healthy young, healthy

old and young Down’s syndrome cohorts. With normal ageing a significant increase in

cells with micronuclei (P<0.05, average increase +366%), karyorrhectic cells

(P<0.001, average increase +439%), condensed chromatin cells (P<0.01, average

increase +45.8%) and basal cells (P<0.001, average increase +233%) is reported

relative to young controls. In Down’s syndrome we report a significant increase in cells

with micronuclei (P<0.001, average increase +733%) and binucleated cells (P<0.001,

average increase +84.5%) and a significant decrease in condensed chromatin cells

(P<0.01, average decrease -52%), karyolytic cells (P<0.001, average decrease -

51.8%) and pyknotic cells (P<0.001, average decrease -75.0%) relative to young

controls. These changes show distinct differences between the cytome profile of

normal ageing relative to that for a premature ageing syndrome, and highlights the

diagnostic value of the cytome approach for measuring the profile of cells with DNA

damage, cell death and proportion of cells with proliferative potential (i.e. basal cells).

Significant correlations amongst cell death biomarkers observed in this study were

used to propose a new model of the inter-relationship of cell types scored within the

buccal micronucleus cytome assay. This study validates the use of a cytome approach

to investigate DNA damage, cell death and cell proliferation in buccal cells with

ageing.


49

2.2 Introduction Ageing is an inevitable consequence of the life cycle of any organism. It is

characterised by a general reduction in physiological efficiency and function resulting

in homeostatic imbalance, leading to both morbidity and eventual mortality [211,212].

Ageing appears to be the result of genetically predetermined events resulting in

phenotypic changes to both cellular and nuclear structure. Such events may be

caused by genetic defects, micronutrient deficiency [142,213] or external influences

such as environmental toxins [214]. Ageing inevitably results in an elevation in

genomic instability events that are associated with a decreased capacity for repair of

cellular or DNA damage [215,216]. It has been shown that genomic instability

biomarkers such as micronuclei are elevated with advancing age in accessible

somatic tissues such as peripheral lymphocytes and fibroblasts [217-219]. However,

cell types that repair DNA damage efficiently are likely to show lower levels of residual

damage than cells less proficient in DNA repair [220,221]. Buccal cells have been

shown to have limited DNA repair capacity relative to peripheral blood lymphocytes,

and therefore may more accurately reflect age related genomic instability events in

epithelial tissues [222].

A thorough understanding of the effects of ageing on micronucleus formation and

other nuclear anomalies is essential, before the buccal cell system can be properly

used to assess the impact of dietary and environmental factors on DNA damage and

cytotoxicity in this important epithelial tissue. Therefore, a buccal micronucleus cytome

assay was used to investigate biomarkers for genomic instability and cell death, as

well as frequency of basal cells in healthy young, healthy old and a Down’s syndrome

(DS) cohort as a model of premature ageing, in an attempt to identify unique changes


50

in the profile of the buccal mucosa between these three groups [223]. Figure 1a

illustrates diagrammatically the various cell types and nuclear anomalies observed

and scored in the buccal micronucleus cytome assay. Figure 1b illustrates a possible

model of the spatial relationships of these various cell types.

Normal Basal Cell

CELL DEATH CELLS DNA DAMAGE CELLS

Condensed chromatin cell

Karyorrhectic cell

Pyknotic cell

Karyolytic cell

Normal differentiated cell

Micronucleated differentiated cell

Nuclear bud cell

Binucleated cell

Micronucleated basal cell

NORMAL CELLS

Figure 1a : Diagrammatic representation of the various cell types observed in the

buccal cytome assay based on the scheme proposed by Tolbert et al [224]


51

Cross section of normal healthy buccal mucosa

RETE PEGSBasal Cells

ORAL CAVITY

Stratum Corneum

Stratum Granulosum

Stratum Spinosum

Key: Condensed chromatin

Karyorrhectic

Keratinised

KaryolyticBasal

Micronucleateddifferentiated Pyknotic

Figure 1b : Shows a cross section of normal buccal mucosa of healthy individuals

illustrating the different cell layers and possible spatial relationships of the various cell

types.

2.3 Methods

Approval for this study was obtained from CSIRO Human Nutrition, Adelaide

University and Southern Cross University human experimentation ethics Committee’s.

30 younger controls (age 18-26yrs), 31 older controls (age 64-75yrs) and 21 DS

individuals (age 5-20yrs) not receiving anti-folate therapy or cancer treatment, were

recruited for the study. Volunteers did not receive any remuneration for their

participation. There were no gender ratio differences between the control and DS

cohorts (P>0.05). Demographic characteristics of the cohorts are shown in Table 1.


52

Table 1 Age and gender ratio of cohorts studied Young controls Down’s

Syndrome Older controls

Age (years) Group size 30 21 31 Mean±S.D 22.47±2.177 10.43±5.582 67.1±2.57 Range 18-26 5-20 64-75 Gender Group size 30 21 31 Male 15 11 12 Female 15 10 19

2.3.1 Cell sampling and preparation

Buccal cells originate from a multilayered epithelium that lines the oral cavity. Buccal

cells were collected from consented volunteers using an established procedure based

on a modified version of the method used by Beliën et al [225]. Prior to buccal cell

collection the mouth was rinsed thoroughly with water to remove any unwanted debris.

Small headed toothbrushes (Supply SA, code 85300012) were used to collect buccal

cells by rotating the brush 20 times in a circular motion against the inside of the cheek,

starting from a central point and gradually increasing in circumference to produce an

outward spiral effect. Both cheeks were sampled using separate brushes. The heads

of the brushes were individually placed into separate 30ml yellow top containers

(Sarstedt code 60.9922.918) containing buccal cell (BC) buffer (0.01M Tris-HCL

(Sigma T-3253), 0.1M EDTA tetra Sodium salt (Sigma E5391), 0.02M Sodium chloride

(Sigma S5886)) at pH 7.0 and agitated to dislodge the cells. Cells from both right and

left cheeks were transfered into separate TV-10 centrifuge tubes (Sarstedt, code

60.9921.829) and spun for 10 mins at 1500rpm (MSE Mistral 2000). Supernatant was


53

removed and replaced with 10mls of fresh BC buffer. The BC buffer helps to inactivate

endogenous DNAases and aids in removing bacteria that may complicate scoring.

Cells were spun and washed twice more, with a final volume of 5mls of BC buffer

being added to the cells. Buccal cells occur as an epithelial cell layer. Therefore, in

order to improve slide preparation and analysis each sample was treated to produce a

single cell suspension. The cell suspension was vortexed for 10 seconds and then

thoroughly dispersed for 2 mins in a hand homogeniser (Wheaton scientific 0.1-0.15

mm gauge) to increase the number of single cells in suspension. Left and right cheek

cell populations were pooled into a 30ml yellow top container and drawn into a syringe

with a 21G gauge needle and expelled to induce further cellular separation. Cells were

then passed into a TV-10 tube through a 100µm nylon filter (Millipore,code

MILNYH02500) held in a swinex filter (millipore, code MILSX0002500) to remove large

aggregates of unseparated cells that hinder scoring of various cell types. Cells were

further spun at 1500rpm for 10mins and the supernatant removed. Cells were

resuspended in 1ml of BC buffer and the cell concentration determined by a Coulter

counter (Beckman Coulter Model ZB1, Settings Attenuation:1, Threshold:8,

Aperture:1/4, Manometer:0.5). Cell suspensions were prepared containing 80,000

cells/ml after initial readings from a 1:50 dilution (300µl/15mls isoton). 50 µl/ml of

Dimethyl Sulphoxide (Sigma 2650) was added to further improve cell separation. 120

µl of cell suspension was added to cytospin cups and spun at 600 rpm for 5 mins in a

cytocentrifuge (Shandon cytospin 3). Slides containing two spots of cells were air

dried for 10 mins and then fixed in ethanol:acetic acid (3:1) for 10 mins. Slides were

air dried for 10 mins proir to staining.


54

2.3.2 Feulgen staining and slide scoring

Fixed slides were treated sequentially for 1 min each in 50% and 20% ethanol and

then washed for 2 mins in deionised water generated from a Milli-Q water purification

system (Adelab Scientific, South Australia). Slides were treated in 5M hydrochloric

acid for 30 mins and then washed in running tap water for 3 mins. Slides were drained

but not allowed to dry out before being treated in room temperature Schiff’s reagent

(Sigma 3259016) in the dark for 60 mins. Slides were washed in running tap water for

5 mins and rinsed well in deionised water for 1 min. Slides were stained for 30 secs in

0.2% light green (Sigma L-1886) and rinsed well in deionised water for 2 mins. Slides

were allowed to air dry, covered with No 1 coverslips (Crown Scientific, South

Australia) and mounted in DePeX (BDH 361254D). Using transmitted light

microscopy, nuclei and micronuclei appear magenta in colour, whilst the cytoplasm

appears green. Slides were scored using a Nikon E600 microscope equipped with a

triple band filter (Dapi, FITC and Rhodamine) at 1000X magnification. Cells containing

micronuclei on bright field can be confirmed as being positive by examining the cell

under fluorescence. This minimises the incidence of false positives, as DNA material

such as nuclei and micronuclei fluoresce when viewed under fluorescence with a far

red filter (Figure 2).


55

NormalDifferentiated cell

MN

Differentiated cellWith Micronucleus

Differentiated cell with nuclear bud

Karyorrhectic cell

Figure 2. Image of same cells under both Feulgen and fluorescence. The use of

fluorescence microscopy helps to clarify the presence and morphology of nuclear

material thereby reducing the possibility of recording false positives and/or false

negative results.

2.3.3 Scoring criteria for buccal cytome assay

The various distinct cell types and nuclear anomalies scored in the buccal

micronucleus cytome assay were determined based on criteria described by Tolbert et

al [226]. These criteria are intended to classify buccal cells into categories that

distinguish between “normal” cells and cells that are considered “abnormal”, based on

their aberrant nuclear morphology. These abnormal nuclear morphologies are thought


56

to be indicative of DNA damage and/or various stages of morphogenetic or toxicity-

induced cell death. Photographic images showing distinct cell populations as scored in

the buccal cytome assay are outlined in Figure 3. Detailed descriptions of the various

cell types are given below.

Basal Cells (Figure 3a):

These are the cells from the basal layer. The nuclear to cytoplasm ratio is larger than

that in differentiated buccal cells which are derived from basal cells. Basal cells have a

uniformly stained nucleus and they are smaller in size when compared to

differentiated buccal cells. Basal cells can contain micronuclei and were scored in the

assay

Normal “differentiated” Cells (Figure 3b):

These cells have a uniformly stained nucleus which is usually oval or round in shape.

They are distinguished from basal cells by their larger size and by a smaller nuclear to

cytoplasmic ratio. No other DNA containing structures apart from the nucleus are

observed in these cells. These cells are considered to be terminally differentiated

relative to basal cells because no mitotic cells are observed in this population.


57

Cells with micronuclei (Figure 3a and 3c):

These cells are characterised by the presence of both a main nucleus and one or

more smaller nuclei called micronuclei. The micronuclei are usually round or oval in

shape and their diameter may range between 1/3 to 1/16 the diameter of the main

nucleus. Cells with micronuclei usually contain only one micronucleus. It is possible

but rare to find cells with more than 6 micronuclei. The nuclei in micronucleated cells

may have the morphology of normal cells or that of dying cells (i.e. condensed

chromatin cells). The micronuclei must be located within the cytoplasm of the cells.

The presence of micronuclei is indicative of chromosome loss or fragmentation

occurring during previous nuclear division [217]. Micronuclei were scored only in basal

and differentiated cells with uniformly stained nuclei. Cells with condensed chromatin

or karyorrhectic cells were not scored for micronuclei.

Cells with Nuclear Buds (Figure 3d):

These cells have nuclei with an apparent sharp constriction at one end of the nucleus

suggestive of a budding process, ie elimination of nuclear material by budding. The

nuclear bud and the nucleus are usually in very close proximity and are apparently

attached to each other. The nuclear bud has the same morphology and staining

properties as the nucleus, however its diameter may range from a half to quarter of

that of the main nucleus. The mechanism leading to this morphology is not known but

it may be due to elimination of amplified DNA or DNA repair complexes [120,227,228].


58

Binucleated cells (Figure 3e):

These cells have two nuclei instead of one. The nuclei are usually very close to each

other and may be touching. The nuclei usually have the same morphology as that

observed in normal cells. The significance of these cells is unknown but they may be

indicative of failed cytokinesis following the last nuclear division.

Condensed chromatin cells (Figure 3f):

These cells have nuclei with regions of condensed or aggregated chromatin exhibiting

a speckled or striated nuclear pattern. In these cells it is apparent that chromatin is

aggregating in some regions of the nucleus while being lost in other areas. When

chromatin aggregation is extensive the nucleus may appear to be fragmenting. These

cells maybe undergoing early stages of apoptosis although this has not been

conclusively proven. These cells may appear to contain micronuclei but should not be

scored for micronuclei in the assay.

Karyorrhectic cells (Figure 3g)

These cells are characterised by the more extensive appearance of nuclear chromatin

aggregation (relative to condensed chromatin cells) leading to fragmentation and

eventual disintegration of the nucleus. These cells may be undergoing a late stage of

apoptosis but this has not been conclusively proven. These cells should not be scored

for micronuclei in the assay.


59

Pyknotic cells (Figure 3h):

These cells are characterised by a small shrunken nucleus, with a high density of

nuclear material that is uniformly but intensely stained. The nuclear diameter is usually

one to two-thirds of a nucleus in normal differentiated cells. The precise biological

significance of pyknotic cells is unknown but it is thought that these cells may be

undergoing a form of cell death; however the precise mechanism remains unknown.

Karyolytic cells (Figure 3i):

In these cells the nucleus is completely depleted of DNA and apparent as a ghost-like

image that has no Feulgen staining. These cells thus appear to have no nucleus. It is

probable that they represent a very late stage in the cell death process but this has not

been conclusively proven. These cells should not be scored for micronuclei in the

assay.


60

i) Karyolytic cell

f) Condensed Chromatin cell

g) Karyorrhectic cell (early stage)

h) Pyknotic cell

d) Differentiated cell with Nuclear bud

e) Binucleated cell

MN

MN

a) basal cell with Micronuclei (MN)

b) Normal differentiated cell

c) Differentiated cellWith MN

Figure 3 Images showing distinct buccal cell types as scored in the buccal cytome

assay.


61

2.3.4 Scoring method

1000 cells were scored per subject to determine the frequency of the various cell

types outlined in the buccal cytome assay. These consisted of basal cells, cells

containing micronuclei, nuclear buds, binucleated cells and cells with condensed

chromatin, karyorrhexis, pyknotic nuclei and karyolytic cells. A total of 1000

differentiated and basal cells were scored in order to determine the frequency of

micronuclei in a total of 1000 cells. Only basal and normal differentiated cells were

scored for micronuclei and their scores were combined to give the overall incidence.

Cells were scored using both bright field and fluorescence. Cells containing

micronuclei on bright field were confirmed as being positive by examining the cell

under fluorescence. The incidence of false positives can be minimised as DNA

material such as nuclei and micronuclei fluoresce when viewed under fluorescence

with a far red filter.

2.4 Statistical Analyses

One way ANOVA analysis was used to determine the significance of the cellular

parameters measured, whereas pair wise comparison of significance was determined

using Tukey’s test. Gender ratios were tested using the Chi square test. ANOVA

analysis values were calculated using Graphpad PRISM (graphpad inc., San Diego,

CA). Cross correlation analysis of biomarkers was performed using SPSS 14.0,

(SPSS Inc, Chicago). Significance was accepted at P<0.05.


62

2.5 Results

The results for the buccal micronucleus cytome assay are summarised and illustrated

in Figures 4-6 and Table 2.

A significant increase in micronuclei was found in the older cohort (366%) relative to

the young cohort (P<0.05). The DS cohort was found to have significantly elevated

frequency of micronuclei when compared to both the older (78.5%) and younger

groups (733%) (P<0.0001). Nuclear buds were slightly elevated in the Down’s cohort

when compared to the healthy young and older groups although this difference did not

achieve significance (P=0.0686).

Basal cells were significantly reduced in both the young (70.1%) and Down’s cohorts

(82.9%) when compared to older controls (P<0.0001). Binucleated cells were

significantly increased in the Down’s cohort when compared to both young (87.9%)

and old control groups (37.9%) (P<0.0001).

A significant reduction in cells containing karyorrhectic (P<0.0001) and condensed

chromatin cells (P<0.0001) was apparent in both the young and Down’s syndrome

cohorts when compared to the older control group. Pyknotic cell frequency was

significantly reduced in the DS cohort (-75.0%) (P=0.0002) when compared to

younger controls but there was no difference when compared to the older controls.

Karyolytic cells were significantly reduced in the Down’s (51.8%) and the older cohort

(37.7%) when compared to the young controls (P<0.0001).


63

Cells with micronuclei

Young

Con

trol s

Down 's

synd

rom

e

Older c

ontro

ls0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

P<0.0001

a

b

c

A

Freq

uenc

y in

100

0 ce

lls

Cells with nuclear buds

Youn g C

ontro

ls

Down'

s syn

dro

me

Older

contro

ls

0.0

0.5

1.0

1.5

2.0

2.5

P=0.0686

a

a

a

B

Freq

uenc

y in

100

0 ce

lls

Figure 4. DNA damage markers in buccal cells of young controls (N=30), Down’s

syndrome (N=21) and older controls (N=31). (A) Frequency of cells containing

micronuclei in 1000 buccal cells with normal nuclear morphology. (B) Frequency of

nuclear buds in 1000 buccal cells. Groups not showing the same letter are significantly

different from each other.


64

Basal cells

Young

Con

trols

Down's

synd

rom

e

Older c

ontr o

ls0

25

50

75

100

P<0.0001

a

a

c

A

Fre

quen

cy in

100

0 ce

lls

Binucleated cells

Young

Cont

rols

Down's sy

ndro

me

Older c

ontro

ls

0

5

10

15

20

25

P<0.0001

a

b

a

B

Freq

uenc

y in

100

0 ce

lls

Figure 5. Frequency of (A) basal cells and (B) binucleated cells scored in a total of

1000 buccal cells in young controls (N=30), Down’s syndrome (N=21) and older

controls (N=31). Groups not showing the same letter are significantly different from

each other


65

Condensed chromatin cells

Young C

ontro

ls

Down's

s ynd ro

me

Older c

ontro

ls

0

25

50

75

P<0.0001

a

b

c

A

Fre

quen

cy in

100

0 ce

lls

Karyorrhectic cells

Young

Con

t rols

Down's

synd

rome

Older c

ont ro

ls0

10

20

30

40

50

60

P<0.0001

a

a

b

B

Fre

quen

cy in

100

0 ce

lls

Pyknotic cells

Young

Con

trols

Down's sy

ndro

me

Older c

ontro

ls

0

1

2

3

4

P=0.0002

a

bc

ac

C

Freq

uenc

y in

100

0 ce

lls

Karyolytic cells

Young

Co nt

rols

Down's

synd

rome

Older c

ontro

ls

0255075

100125

150175200

225

P<0.0001

a

b

D

b

Freq

uenc

y in

100

0 ce

lls

Figure 6 Cell death rates in buccal cells of young controls (N=30), Down’s syndrome

(N=21) and older controls (N=31). Frequency of (A) cells containing nuclei with

condensed chromatin morphology, (B) cells containing karyorrhectic nuclei, (C) cells

with pyknotic nuclei, (D) karyolytic cells per 1000 total cells scored. Groups not

showing the same letter are significantly different from each other.


66

In summary the changes relative to the young controls in DS and normal ageing were

an increase in cells with micronuclei and binucleated cells and a decrease in pyknotic

and karyolytic cells, but changes were in opposite directions for basal cells,

condensed chromatin and karyorrhectic cells (Table 2).

Table 2 : Changes in the buccal cytome biomarkers of both older control and Down’s syndrome cohorts relative to the young controls Older controls Down’s syndrome Cells with micronuclei

(+366%) (+733%)


NC (+100%)

Basal cells

(+233.0%) (-41.0%)

Binucleated cells

(+36.0%)

(+84.5%)

Condensed chromatin

(+45.8%) (-52.0%)

Karyorrhectic cells

(+439%) (-89.2%)

Pyknotic cells

(-37.5%) (-75.0%)

Karyolytic cells

(-37.7%) (-51.8%)

NC= No change

Denotes increase relative to young controls Denotes decrease relative to young controls

Numbers in parentheses refer to the percentage change relative to the value for young controls.


67

Cross correlation analysis between the biomarkers of the buccal cytome assay for the

combined cohorts (Table 3) showed a positive correlation between karyorrectic cells

and condensed chromatin (r=0.406, P<0.0001) and basal cells (r=0.659, P<0.0001).

Pyknotic cells showed a negative correlation with binucleated cells (r=-0.240,

P=0.030) and a positive correlation with karyolytic (r=0.412, P<0.0001) and

condensed chromatin cells (r=0.305, P=0.005). Condensed chromatin cells showed a

positive correlation with basal cells (r=0.470, P<0.0001).


68

Table 3: Cross correlation results between biomarkers of the buccal micronucleus cytome assay for combined cohorts (N=82).

Cells with

micronuclei karyorrhexis pyknosis binucleates karyolysis Nuclear buds Condensed chromatin

karyorrhexis Pearson

Correlation NS

Sig. (2-tailed) pyknosis Pearson

Correlation NS .243(*)

Sig. (2-tailed) .030 binucleates Pearson

Correlation NS NS NS

Sig. (2-tailed) karyolysis Pearson

Correlation NS NS NS NS

Sig. (2-tailed) Nuclear buds Pearson

Correlation NS NS NS NS NS

Sig. (2-tailed) condensed Pearson

Correlation NS .500(**) .297(**) NS .375(**) NS

chromatin Sig. (2-tailed) .000 .007 .001 basal Pearson

Correlation NS .620(**) NS NS NS NS .478(**)

Sig. (2-tailed) .000 .000

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). NS-Not significant


69

2.6 Discussion

The aim of the study was to validate the use of the buccal micronucleus cytome assay

to investigate age-related changes within the buccal mucosa by examining samples

from young, old and DS cohorts. Changes in the ratios of distinct buccal cell

populations were evident in the older control group when compared to a younger

cohort, and significant changes were also evident specific to the premature ageing DS

group. These changes suggest normal age-related and premature ageing-related

biomarkers that may reflect differences in the cellular kinetics and/or structural profile

of the buccal mucosa.

The buccal mucosa is a stratified squamous epithelium consisting of four distinct

layers (Figure 1b) [229,230]. The stratum corneum or keratinised layer lines the oral

cavity comprising cells that are constantly being lost as a result of everyday activities

such as mastication. Below this layer lies the stratum granulosum or granular cell layer

and the stratum spinosum or prickle cell layer containing populations of both

differentiated, apoptotic and necrotic cells. Beneath these layers are the rete pegs or

stratum germinativum, containing actively dividing basal cells which produce cells that

differentiate and maintain the profile, structure and integrity of the buccal mucosa. By

comparing the results of the buccal cytome assay between the older and younger

cohorts, significant differences in markers for genome damage, cellular proliferation

and cell death are apparent that reflect ‘normal’ age related changes in the structural

profile of the buccal mucosa.


70

A clear association is shown between ageing and a significant increase in the

biomarkers scored for DNA damage. Micronuclei, which are biomarkers for whole

chromosome loss and chromosome breakage, have been shown to be increased with

advancing age in both peripheral lymphocytes and fibroblasts [211,213,231,232]. In

this study we observed a significant age-related increase in micronuclei within buccal

cells in individuals whose age ranged from 22-67yrs (P<0.0001). These observations

confirm earlier results from biomonitoring studies that also found an age-related

increase in micronucleus frequency [233-235]. The frequencies of micronuclei as

scored in the assay were found not to be significantly different between basal cells

(0.33%) and differentiated cells (0.22%). Nuclear buds, which are thought to reflect

gene amplification events, were non-significantly elevated by 20.96% in the older

cohort and to the best of our knowledge this is the first time that such an effect has

been reported.

It has been shown that ageing results in a decrease in the thickness of the epidermis

and the underlying cell layers [236]. The rete pegs become less prominent and less

convoluted, possibly because of a reduction in basal cells, resulting in a more

flattened appearance [237,238]. The paradoxical significant increase in the frequency

of basal cells sampled in the older cohort may reflect the reduced thickness of the

buccal mucosa. The observed increase in cell death (condensed chromatin and

karyorrhexis) and the reduction in karyolytic cells may determine the thickness of the

outer layer. This effectively would bring the basal cell layer closer to the surface,

making it more likely that basal cells would be sampled compared to healthy mucosa

in which only the peaks of rete pegs are likely to be accessible points for basal cell

collection. With a lower age-related cellular proliferation rate and a thinning of the


71

buccal mucosa, older individuals may exhibit modifications in order to maintain the

integrity of the buccal mucosa. The significant increase in the condensed chromatin

and karyorrhectic cells and the corresponding decrease in pyknotic cells and karyolytic

cells maybe the result of insufficient time for the former cell types to undergo pyknosis

and karyolysis prior to reaching the mucosal surface, resulting in a higher proportion of

the found cell types becoming apparent.

DS is characterised by the cellular presence of an extra copy of chromosome 21 and

is an example of a premature ageing disorder [223,239,240]. The buccal cytome

assay identified age-related biomarkers that were specific to this cohort when

compared to both the young and older control groups (Table 2). Micronuclei were

significantly elevated in the Down’s cohort and were found to be roughly 10 fold higher

than in the young control group and almost double those found in the older controls,

confirming the observation of elevated genome damage in this syndrome [241,242].

Nuclear buds were also found to be elevated in the Down’s group also reflecting a

more pronounced genomic instability. Basal cell frequency was found to be non-

significantly lower by 41.97% in the Down’s cohort compared to the younger controls,

possibly reflecting either an excessive reduction of basal cells and/or a thickening of

the buccal mucosal layers. The number of binucleates was found to be significantly

elevated when compared to both the young and older control groups which may reflect

a possible impairment during cytokinesis. It has been shown that non-disjunction

occurs with a higher frequency in binucleated cells that fail to complete cytokinesis

rather than in cells that have completed cytokinesis [243]. This recently identified

mechanism, thought to be a cytokinesis checkpoint for aneuploid binucleated cells,

can result in ultimate formation of tetraploid cells and subsequent aneuploid cells once


72

the tetraploid cell eventually divides [243]. DS is known to have higher rates of

aneuploidy 21 and the binucleate cell ratio may therefore prove to be an important

biomarker for identifying individuals with cytokinesis defects, which could lead to

higher than normal rates of aneuploidy. The four cell death parameters (condensed

chromatin, karyorrhexis, pyknosis and karyolysis) were found to be reduced in the

Down’s cohort compared to the younger controls and may reflect important changes

within the profile of the buccal mucosa within this group. With a reduction in the

number of basal cells, fewer cells would be available to maintain the thickness and

integrity of the buccal mucosa. In order to compensate for a reduced regenerative

layer, a potential adaptation may be to reduce the amount of cells undergoing

programmed cell death and a permissive cell cycle check point to reduce cell cycle

time. This would lead to the production of enough cells to maintain the thickness of the

buccal mucosa from a reduced and flattened rete peg layer. No evidence currently

exists that clarify or refute these proposed models, only further investigation using

histological sections and biopsies will allow models to be formulated that best reflect

the structural profile and cellular kinetics within the buccal mucosa for both ageing and

premature ageing syndromes.

The results of the cross-correlation study suggest a significant positive relationship

between basal cells, condensed chromatin cells, pyknotic cells and karyolytic cells.

The strong positive correlation between basal cells and karyorrhectic cells and the

positive correlation between condensed chromatin and karyorrhectic cells, suggests

that the latter are either derived directly from basal cells, or may originate secondarily

from condensed chromatin cells. The positive correlation between condensed

chromatin cells and pyknotic and karyolytic cells and the positive correlation between


73

pyknotic and karyolytic cells suggests that karyolytic cells are derived directly from

condensed chromatin cells or indirectly via pyknotic cells. Figure 7 illustrates a

possible model of the inter-relationships between buccal cytome cell types that are

significantly correlated with each other, assuming that the correlations are indicative of

the biological association between the cell types and their likely sequential

development. However, we realise that because association does not necessarily

imply causation, further evidence (e.g. real time recordings of different cell type

changes) would be required to verify the accuracy of the model.

In conclusion, the buccal micronucleus cytome assay has been successfully used to

identify important changes in DNA damage and different cell types that reflect

advancing age within the normal population and within a premature ageing syndrome.

Normal genome

Normal differentiated cell

Micronucleated cell

Nuclear bud cell

Binucleated cellKaryolytic cellPyknotic cell

CondensedChromatin

cell

Karyorrhecticcell

Chromosome breakage or loss

Gene amplification

Cytokinesisdefect

Cell Death

Basal Cell

2007 REVISED BUCCAL CYTOME MODEL SHOWING CELLULAR RELATIONSHIPS

R=0.65

R=0.47

R=0.31R=0.41

R=0.41

R=0.38

Figure 7 : Diagram illustrating revised model for inter-relationships between the

various cell types observed and scored in the buccal micronucleus cytome assay.

Chapter 3: Buccal cytome and Alzheimer’s disease

74

3 Chapter 3: Buccal cytome biomarkers may be associat ed

with Alzheimer’s disease


75

3.1 Abstract

Alzheimer’s disease is a progressive degenerative disorder of the brain and is the

commonest form of dementia. To date there is no reliable and conclusive non-invasive

diagnostic test that can identify individuals for susceptibility risk to Alzheimer’s

disease. A buccal cytome assay was used to measure ratios of buccal cell populations

and micronuclei in clinically diagnosed Alzheimer’s patients compared to age and

gender matched controls. Frequencies of basal cells (P<0.0001), condensed

chromatin cells (P<0.0001) and karyorrhectic cells (P<0.0001) were found to be

significantly lower in Alzheimer’s patients. These changes may reflect alterations in

the cellular kinetics or structural profile of the buccal mucosa, and may be useful as

potential biomarkers in identifying individuals with a high risk of developing

Alzheimer’s disease. The odd’s ratio of being diagnosed with Alzheimer’s disease for

those individuals with a basal cell plus karyorrhectic cell frequency <41 per 1000 cells

is 140, with a specificity of 97% and sensitivity of 82%.

3.2 Introduction

Alzheimer’s disease (AD) is a neurodegenerative disorder that is characterised

clinically by cognitive decline, memory loss, visuo-spatial and language impairment

and is the commonest form of dementia [3,8,10,46]. Regions of the brain that are

involved in short term memory and learning such as the temporal and frontal lobes are

impaired as a result of neuronal loss and the breakdown of the neuronal synaptic

connections [50]. The disease is histopathologically confirmed at post mortem within

the brain by the presence of neurofibrillary tangles and amyloid plaques [244,245].


76

The greatest risk factor for contracting the disease is advancing age and that risk is

significantly increased beyond the age of 70 yrs [3,4,9]. To date the global prevalence

is estimated to be 24.3 million with that number expected to triple within the next thirty

years. At least 4.9 million new cases are reported annually with a predicted

prevalence worldwide of 80 million people suffering from the disease by 2040 [4,5].

Currently clinical diagnosis of AD is based upon criteria of cognitive impairment and

behavioural changes [11]. One such diagnostic tool is the mini mental state

examination (MMSE) which allows a quantitative measurement of cognition to be

determined [12,13]. However the diagnosis for having AD is only between 60-70%

accurate when using these criteria and can only be conclusively confirmed after

histopathological investigation [11].

Biomarkers that may identify individuals who are at an early stage of AD would be

useful as this would allow timely preventative intervention. There is an increasing

interest in the evaluation of chromosome damage markers within the somatic cells of

neurodegeneration patients [96-98]. Genome damage could lead to altered gene

dosage and gene expression as well as contribute to the risk of accelerated cell death

in neuronal tissue [246]. Genomic instability markers such as micronuclei (MN), have

been shown to be elevated within the peripheral blood lymphocytes and fibroblasts of

Alzheimer’s patients [96,97,247].

The aim of this study was to assess whether MN and other parameters of genome

damage and cell death in the buccal mucosa could be used as a non-invasive method

of identifying those at risk of developing AD. In effect we adopted a cytome approach

in which all the various cell types and their ratios were quantified to identify which


77

parameters if any, were most strongly associated with AD. A flow diagram illustrating

plausible cellular relationships of the buccal cytome assay is shown in Figure 1.

Normal genome

Normal

Micronucleated

Nuclear bud

BinucleatedKaryolysisPyknosis

Condensedchromatin

Karyorrehxis

Chromosome breakage or loss

Gene amplification

CytokinesisDefect orproliferativeindex

Apoptotic Cell Death(morphogeneticor induced by

genome damage)

NecroticCell death ?

Basal Cell

BUCCAL CYTOME MODEL SHOWING CELLULAR RELATIONSHIPS

Figure 1 : Diagram illustrating the most plausible relationships between the various cell

types observed and scored in the buccal micronucleus cytome assay.

3.3 Methods

3.3.1 Recruitment and characteristics of participan ts


University and Ramsay Healthcare Ethics Committee’s. 26 older controls (age 66-

75yrs), and 54 clinically diagnosed Alzheimer’s patients (Age 58-93yrs) not receiving

anti-folate therapy or cancer treatment or having any family history of AD, were


78

recruited for the study. Alzheimer’s patients were recruited at the College Grove

Private Hospital, Walkerville, Adelaide, South Australia following their initial diagnosis

and prior to commencement of therapy. Diagnosis of AD was made by clinicians

according to the criteria outlined by the National Institute of Neurological and

Communicative Disorders and Stroke-Alzheimer’s Disease and related Disorders

Association (NINCDS-AD&DA) [12], which are the well recognised standards used in

all clinical trials.

Volunteers did not receive any remuneration for their participation. Alzheimer’s

patients were separated into two distinct groups. One group was age matched to the

control, whilst the second group was classified as an older Alzheimer’s cohort. Age,

gender and MMSE scores of the cohorts are shown in Table 1. Gender ratio

differences between the groups were not significant (Chi square P>0.05). MMSE

scores between the two AD groups were not significantly different P>0.05. The age of

the control group compared to the younger AD group was not significantly different but

the latter group had a significantly lower age relative to the older AD group P<0.0001.

MMSE scores were not available for the controls. The controls were “normal”

functioning healthy individuals, who self volunteered and consented to the study and

did not report a history of cognitive impairment.


79

Table 1: Age, gender ratio and MMSE scores in study groups

Controls* Younger AD Older AD Age (years) Group size 26 23 31 Mean±S.D 68.7±2.6 70.7±4.1 83.13±4.5 Range 66-75 58-75 78-93 Gender Group size 26 23 31 Male 11 8 8 Female 15 15 23 MMSE (0-30) NA Group size 23 31 Mean±S.D 22.52±3.013 22.13±3.6.76 Range 15-27 12-29

* Age and gender matched to younger AD group NA-Not available


Buccal cells were collected from consented volunteers. Cells were collected using a

modified version of the method used by Beliën et al [225]. Prior to buccal cell

collection the mouth was rinsed thoroughly with water to remove any unwanted debris.

Small headed toothbrushes (Supply SA, code 85300012) were rotated 20 times in a

circular motion against the inside of the cheek, starting from a central point and

gradually increasing in circumference to produce an outward spiral effect. Both cheeks

were sampled using separate brushes. The heads of the brushes were individually

placed into separate 30ml yellow top containers (Sarstedt code 60.9922.918)

containing buccal cell (BC) buffer (0.01M Tris-HCL (Sigma T-3253), 0.1M EDTA tetra

sodium salt (Sigma E5391), 0.02M sodium chloride (Sigma S5886)) at pH 7.0 and

agitated to dislodge the cells. Cells from both right and left cheeks were transfered into


80

separate TV-10 centrifuge tubes (Sarstedt, code 60.9921.829) and spun for 10 mins at

1500rpm (MSE Mistral 2000). Supernatant was removed and replaced with 10mls of

fresh BC buffer. The BC buffer helps to inactivate endogenous DNAases and aids in

removing bacteria that may complicate scoring. Cells were spun and washed twice

more, with a final volume of 5mls of BC buffer being added to the cells. The cell

suspension was vortexed and then homogenised for 2 mins in a hand homogeniser

(Wheaton scientific 0.1-0.15 mm gauge) to increase the number of single cells in

suspension. Left and right cell populations were pooled into a 30ml yellow top

container and drawn into a syringe with a 21G gauge needle and expelled to

encourage cellular separation. Cells were passed into a TV-10 tube through a 100µm

nylon filter (Millipore,code MILNYH02500) held in a swinex filter (millipore, code

MILSX0002500) to remove large aggregates of unseparated cells that hinder slide

preparation and cell analysis. Cells were further spun at 1500rpm for 10mins and the

supernatant removed. Cells were resuspended in 1ml of BC buffer and the cell

concentration determined by a Coulter counter (Beckman Coulter Model ZB1, Settings

Attenuation:1, Threshold:8, Aperture:1/4, Manometer:0.5). Cell suspensions were

prepared containing 80,000 cells/ml after initial readings from a 1:50 dilution

(300µl/15mls isoton). 50 µl/ml of dimethyl sulphoxide (Sigma 2650) was added to help

clarify cellular boundaries by further separating the cells. 120 µl of cell suspension

was added to cytospin cups and spun at 600 rpm for 5 mins in a cytocentrifuge

(Shandon cytospin 3). Slides containing two spots of cells were air dried for 10 mins

and then fixed in ethanol:acetic acid (3:1) for 10 mins. Slides were air dried for 10

mins prior to staining.


81

3.3.3 Feulgen staining

Fixed slides were treated for 1 min each in 50% and 20% ethanol and then washed for

2 mins in deionised water generated from a Milli-q water purification system (Millipore

Australia Pty Ltd, New South Wales, Australia). Slides were treated in 5M hydrochloric

acid for 30 mins and then washed in running tap water for 3 mins. Slides were drained

but not allowed to dry out before being treated in room temperature Schiff’s reagent

(Sigma 3259016) in the dark for 60 mins. Slides were washed in running tap water for

5 mins and rinsed well in deionised water for 1 min. Slides were stained for 30 secs in

0.2% light green (Sigma L-1886) and rinsed well in deionised water for 2 mins. Slides

were allowed to air dry, covered with No 1 coverslips (Crown Scientific, South

Australia) and mounted in DePeX (BDH 361254D). Nuclei and micronuclei are

stained magenta, whilst the cytoplasm appears green. Slides were scored using a

Nikon E600 microscope equipped with a triple band filter (Dapi, FITC and Rhodamine)

at 1000X magnification. Cells containing micronuclei on bright field can be confirmed

as being positive by examining the cell under fluorescence. The incidence of false

positives can be minimised as DNA material such as nuclei and micronuclei fluoresce

when viewed under fluorescence with a far red filter (Figure 2).


82

NormalDifferentiated cell

MN

Differentiated cellWith Micronucleus

Differentiated cell with nuclear bud

Karyorrhectic cell

Figure 2 . Image of same cells under both Feulgen and fluorescence. The use of

fluorescence microscopy helps to clarify presence and morphology of nuclear material

thereby reducing the possibility of recording false positives and /or false negative

results.

3.3.4 Scoring criteria for buccal cytome assay

The various distinct populations used in the buccal cytome assay were determined

based on criteria outlined by Tolbert et al [226]. These criteria are intended to classify

buccal cells into categories that distinguish between “normal” cells and cells that are

considered “abnormal”, based on nuclear morphology. These abnormal nuclear

morphologies are thought to be indicative of DNA damage or cell death. Photographic

Images showing distinct cell populations as scored in the buccal cytome assay are

shown in Figure 3. Detailed descriptions of the various cell types are given below.


83

i) Karyolytic cell

f) Condensed Chromatin cell

g) Karyorrhectic cell (early stage)

h) Pyknotic cell

d) Differentiated cell with Nuclear bud

e) Binucleated cell

MN

MN

a) basal cell with Micronuclei (MN)

b) Normal differentiated cell

c) Differentiated cellWith MN

Figure 3: Images showing distinct buccal cell types as scored in the buccal cytome

assay


84

Basal Cells (Figure 3a):

These are the cells from the basal layer. The nuclear to cytoplasm ratio is larger than

that in differentiated buccal cells which are derived from basal cells. Basal cells have a

uniformly stained nucleus and they are smaller in size when compared to

differentiated buccal cells. Basal cells can contain micronuclei and were scored in the

assay.

Normal differentiated Cells (Figure 3b):

These cells have a uniformly stained nucleus which is usually oval or round in shape.

They are distinguished from basal cells by their larger size and by a smaller nuclear to

cytoplasmic ratio. No other DNA containing structures apart from the nucleus are

observed in these cells. These cells are considered to be terminally differentiated

relative to basal cells because no mitotic cells are observed in this population.

Cells with micronuclei (Figure 3a and 3c):

These cells are characterised by the presence of both a main nucleus and one or





may have the morphology of normal cells or that of dying cells (i.e. condensed

chromatin cells). The micronuclei must be located within the cytoplasm of the cells.

The presence of micronuclei is indicative of chromosome loss or fragmentation

occurring during previous nuclear division [217]. Micronuclei were scored only in basal


85

and differentiated cells with uniformly stained nuclei. Cells with condensed chromatin

or karyorrhectic cells were not scored for micronuclei.

Cells with Nuclear Buds (Figure 3d):

These cells have nuclei with an apparent sharp constriction at one end of the nucleus

suggestive of a budding process, ie elimination of nuclear material by budding. The

nuclear bud and the nucleus are usually in very close proximity and are apparently

attached to each other. The nuclear bud has the same morphology and staining

properties as the nucleus, however its diameter may range from a half to quarter of

that of the main nucleus. The mechanism leading to this morphology is not known but

it may be due to elimination of amplified DNA or DNA repair complexes.

[120,227,228].

Binucleated differentiated cells (Figure 3e):

These cells have two nuclei instead of one. The nuclei are usually very close to each

other and may be touching. The nuclei usually have the same morphology as that

observed in normal cells. The significance of these cells is unknown but they may be

indicative of failed cytokinesis following the last nuclear division.

Condensed chromatin cells (Figure 3f):

These cells have nuclei with regions of condensed or aggregated chromatin exhibiting

a speckled or striated nuclear pattern. In these cells it is apparent that chromatin is

aggregating in some regions of the nucleus while being lost in other areas. When

chromatin aggregation is extensive the nucleus may appear to be fragmenting. These


86

cells maybe undergoing early stages of apoptosis although this has not been

conclusively proven. These cells may appear to contain micronuclei but should not be

scored for micronuclei in the assay.

Karyorrhectic cells (Figure 3g)

These cells are characterised by the more extensive appearance of nuclear chromatin

aggregation (relative to condensed chromatin cells) leading to fragmentation and

eventual disintegration of the nucleus. These cells may be undergoing a late stage of

apoptosis but this has not been conclusively proven. These cells should not be scored

for micronuclei in the assay.

Pyknotic cells (Figure 3h):

These cells are characterised by a small shrunken nucleus, with a high density of

nuclear material that is uniformly but intensely stained. The nuclear diameter is usually

one to two-thirds of a nucleus in normal differentiated cells. The precise biological

significance of pyknotic cells is unknown but it is thought that these cells may be

undergoing a form of cell death however the precise mechanism is unknown. These

cells should not be scored for micronuclei in the assay.

Karyolytic cells (Figure 3i):

In these cells the nucleus is completely depleted of DNA and apparent as a ghost-like

image that has no Feulgen staining. These cells thus appear to have no nucleus. It is

probable that they represent a very late stage in the cell death process but this has not


87

been conclusively proven. These cells should not be scored for micronuclei in the

assay.

Scoring method

1000 cells were scored (500 per cytospin spot) per subject for all the various cell types

outlined in the buccal cytome assay. These consisted of cells containing micronuclei,

nuclear buds, basal cells, binucleates and the cell death parameters condensed

chromatin, karyorrhectic, pyknotic and karyolytic cells. A total of 1000 differentiated

and basal cells were scored in order to determine the frequency of micronuclei in a

total of 1000 cells. Only basal and normal differentiated cells were scored for

micronuclei and their scores were combined to give the overall incidence. Cells were

scored using both bright field and fluorescence. Cells containing micronuclei on bright

field were confirmed as being positive by examining the cell under fluorescence. The

incidence of false positives can be minimised as DNA material such as nuclei and

micronuclei fluoresce when viewed under fluorescence with a far red filter.

3.4 Statistical analysis

One way ANOVA analysis was used to determine the significance of the cellular

parameters measured between the old control, younger AD and older AD cohorts. Pair

wise comparison of significance between these groups was determined using Tukey’s

test. ANOVA analysis values, positive predictive values, negative predictive values,

sensitivity, specificity, likelihood ratios and odds ratio were calculated using Graphpad

PRISM (Graphpad inc., San Diego, CA). Cross correlation analyses were performed

using SPSS 14.0, SPSS inc, Chicago. Significance was accepted at P<0.05.


88

3.5 Results

The results for DNA damage markers (cells with micronuclei or nuclear buds), cell

proliferation markers (basal cells, binucleated cells) and cell death parameters

(karyorrhectic cells, condensed chromatin cells, karyolytic cells and pyknotic cells) are

summarised and illustrated in Figures 4-6. Cells with micronuclei or nuclear buds were

slightly elevated in the younger AD group when compared to age-matched controls

although this difference did not achieve significance (P=0.12, P=0.62 respectively).

88% of all micronucleated cells were in differentiated cells whilst the remaining 12%

were found in the basal cells. Basal cells were found to be lower by 81% in the

younger AD and by 79% in the older AD cohorts when compared to the control group

(P<0.0001). Binucleate cell frequency showed no significant differences between the

AD and control groups (P=0.99). The frequency of cells with condensed chromatin

was found to be reduced by 37.2% in the younger AD and by 56.6% in the older AD

cohorts when compared to the control group (P<0.0001). The frequency of

karyorrhectic cells was found to be reduced by 82.9% in the younger AD and by

77.7% in the older AD cohorts when compared to the control group (P<0.0001).

Pyknotic and karyolytic cells were slightly lower in both the dementia groups but did

not achieve significance when compared to the control (P=0.47, P=0.84 respectively).

There were no gender ratio differences between the control and the AD groups. There

were no gender differences in biomarkers occurring within each cohort except for a

significant increase in nuclear buds in males compared to females within the younger

AD group (P<0.01). Cross correlation analysis between MMSE scores and the

biomarkers of the buccal cytome assay showed no positive correlation.


89

Cells With micronuclei

Contro ls

Young

er A

D

Older A

D

0

1

2

P=0.1148

a

a

a

A

Fre

quen

cy in

100

0 ce

lls


Controls

Younge

r AD

Older A

D

0

1

2

P=0.6150

a

a

a

B

Fre

quen

cy in

100

0 ce

lls

Figure 4: DNA damage markers in buccal cells of controls (N=26), younger AD

(N=23) and older AD (N=31). (A). Frequency of cells containing micronuclei in 1000

buccal cells with normal nuclear morphology. (B). Frequency of cells with nuclear

buds. Groups not showing the same letter are significantly different from each other


90

Basal cells

Contro

ls

Young

er A

D

Older A

D

0

25

50

75

100

125

P<0.0001

a

b b

A

Fre

quen

cy in

100

0 ce

lls

Binucleated cells

Contro

ls

Youn ger

AD

Older

AD

0

10

20

P=0.9934

a a a

B

Fre

quen

cy in

100

0 ce

lls

Figure 5: Frequency of (A) basal cells and (B) binucleated cells amongst 1000 total

cells scored in controls (N=26), younger AD (n=23) and older AD (N=31). Groups not

showing the same letter are significantly different from each other.


91

Condensed chromatin cells

Contro ls

Young

er A

D

Older A

D

0

25

50

75

P<0.0001

a

b

b

A

Freq

uenc

y in

100

0 ce

lls

Karyorrhectic cells

Contro

ls

Younge

r AD

Older A

D

0

10

20

30

40

50

60

P<0.0001

a

b b

B

Fre

quen

cy in

100

0 ce

lls

Pyknotic cells

Contro

ls

Young

er A

D

Older

AD

0.0

0.5

1.0

1.5

2.0

2.5

P=0.4681

aa

a

C

Fre

quen

cy in

100

0 ce

lls

Karyolytic cells

Contro

ls

Younger A

D

Older

AD

0

25

50

75

100

125

P=0.8441

a a a

D

Freq

uenc

y in

100

0 ce

lls

Figure 6: Cell death rates in buccal cells of controls (N=26), younger AD (n=23) and

older AD (N=31). Frequency of (A) cells containing nuclei with condensed chromatin

morphology, (B) cells containing karyorrhectic nuclei, (C) cells with pyknotic nuclei, (D)

karyolytic cells per 1000 total cells scored. Groups not showing the same letter are

significantly different from each other.


92

3.5.1 Sensitivity and Specificity

Values for both basal and karyorrhectic cells were analysed singularly and in

combination to determine the sensitivity and specificity of these potential biomarkers,

which were most different between the control and AD groups. Table 2 lists the

sensitivity and specificity data for diagnosis of AD based on basal and karyorrhectic

cell frequency at different cut off values. The odds ratio for being diagnosed with AD

for a combined karyorrhectic and basal cell frequency value of < 41 per 1000 cells is

140 with a specificity of 97% and a sensitivity of 82%. This would indicate that a false

positive rate for these potential diagnostic biomarkers within the general population

would be 2.3% (positive predictive value of 97.7%) and that 23.1% (negative

predictive value 76.9%) of those individuals tested that are likely to have AD would be

falsely detected as normal. The relationship of basal cell and karyorrhectic cell

frequencies shows a clear separation in distribution of these values for the control and

AD cohorts (Figure 7).


93

Table 2: Positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, likelihood ratio (LR), odds ratio (OR) and P values for karyorrhectic and basal cell frequency PPV NPV Sensitivity Specificity LR OR (95% CI) P

Value Karyorrhectic cell

frequency <30* 85.5% 85.2% 92.1% 74.2% 3.6 33.8(9.2-124) 0.0001 Basal cell frequency <27* 93.5% 77.8% 84.3% 90.3% 8.7 50.1(12.3-205) 0.0001 Basal cell plus karyorrhectic cell frequency <41* 97.7% 76.9% 82.4% 96.8% 25.5 140 (16.8-1165) 0.0001

*denotes number of cells in 1000 buccal cells scored

0 50 100 150 2000

50

100

150ADCONTROLS

Basal cell frequency per 1000 cells

Kar

yorr

hect

ic c

ell f

requ

ency

per

1000

cel

ls

Figure 7: Shows a scatter plot for basal and karyorrhectic cell frequency biomarkers

as expressed in Controls and AD cohorts


94

3.6 Discussion

This study is the first to use the buccal micronucleus cytome assay, which is based on

cellular and nuclear morphology, to identify potential biomarkers that are associated

with individuals that have just been clinically diagnosed with AD. Results showed a

significant decrease in the number of basal cells (P<0.0001), karyorrhectic cells

(P<0.0001) and condensed chromatin cells (P<0.0001) in the AD patients, suggesting

potential changes in the cellular kinetics or structural profile of the buccal mucosa. The

combination of basal and karyorrhectic cells as potential biomarkers within the buccal

mucosa may be useful as a potential future diagnostic to identify individuals with a

high risk of developing or having AD.

The buccal mucosa is a stratified squamous epithelium consisting of four distinct

layers (Figure 8a). The stratum corneum or keratinised layer lines the oral cavity

comprising cells that are constantly being lost as a result of everyday abrasive

activities such as mastication. Below this layer lie the Stratum granulosum or granular

cell layer and the stratum spinosum or prickle cell layer containing populations of both

differentiated and apoptotic cells. Integrated within these layers are convoluted

structures known as rete pegs, containing the actively dividing basal cells known as

the stratum germinativum which produce cells that differentiate and maintain the

profile and integrity of the buccal mucosa.


95

a) Cross section of Normal buccal mucosa

RETE PEGSBasal Cells

ORAL CAVITY

Stratum Corneum

Stratum Granulosum

Stratum Spinosum


Karyorrhectic

Keratinised

Karyolytic

Basal

Micronucleateddifferentiated Pyknotic

Figure 8a: Shows a cross section of normal buccal mucosa illustrating the different

cell layers.

With increasing age the cell renewal process becomes less efficient and cellular

regeneration decreases [248,249]. Ageing results in a decrease in the thickness of the

epidermis and the underlying cell layers [236]. Studies have shown that there is a

decline in epidermal thickness with advancing age in both sexes with values occurring

in the range from 11.4 to 22.6 microns [250]. The number of cells within the stratum

corneum does not diminish and therefore does not compromise its function as an

essential protective layer [251]. The rete pegs become less prominent and less

convoluted resulting in a more flattened appearance [237,238]. This flattening of the

dermal–epidermal junction makes the skin more susceptible to mild mechanical

trauma.


96

The results from the buccal cytome assay suggest significant changes within the

buccal cell profile of AD patients when compared to the control cohort. Two models

were considered to explain the observed changes of buccal cell populations within this

group of individuals (Figures 8b and 8c). Both proposed models make the assumption

that there is an excessive structural flattening of the rete pegs beyond normal ageing,

resulting in a reduced basal cell population. Within both the AD cohorts the number of

mitotically active basal cells was significantly reduced. A reduction in the number of

basal cells would result in reduced cellular proliferation per unit volume and

consequently fewer cells would be made available to maintain the thickness and

integrity of the buccal mucosa. In model 1 ( Figure 8b) in order to compensate for a

reduced proliferation rate, a potential adaptation may be to reduce the amount of cells

undergoing morphogenetic programmed cell death, possibly as a result of an

increased cell cycle time. This would lead to the production of just enough cells to

maintain the required thickness of an adequately functional buccal mucosa (Figure

8b). The study showed a significant reduction in the populations of cells with

condensed chromatin and in the number of karyorrhectic cells collected which is

indicative of a reduced apoptotic rate.


97

b) Alzheimer Buccal cell Model 1

ORAL CAVITY

Flattened rete pegs and lower basal frequency

Stratum Corneum

Stratum Granulosum

Stratum Spinosum


Karyorhexic

Keratinised

Karyolytic

Basal

Micronucleated

differentiated Pyknotic

Figure 8b) Model 1 shows a proposed cross section of buccal mucosa that may occur

in AD individuals, with flattening of rete pegs, lower basal cell frequency and reduced

frequency of cells undergoing apoptosis with an increased average distance between

basal layer and surface of the mucosa.

An alternative model illustrated in model 2 (Figure 8c) proposes that cell death rate

does not change and is comparable to the same rate of cell death as seen in normal

controls. With fewer mitotically dividing cells being produced within the basal cell layer

and a normal apoptotic rate, less differentiated cells would be made available to

maintain the thickness and integrity of the buccal mucosa. Consequently, the

thickness of the dermal-epidermal layer would be severely compromised resulting in a

general thinning of the buccal mucosa. No evidence currently exists that clarify or

refute these proposed models, only further investigation with sectional biopsies will

verify whether these models truly reflect the cellular kinetics within the buccal mucosa


98

of AD patients. Model 1 appears to be the better model given that both basal and

apoptotic cells (karyorrhectic and condensed chromatin cells) are reduced in this

study, and that the flattening of the basal cell layer would in itself increase the distance

from the surface, making it less likely that these cells would be collected during

sampling.

C) Alzheimer Buccal cell Model 2

ORAL CAVITY

Stratum Corneum

Stratum Spinosum

Flattened rete pegs and lower basalfrequency


Karyorhexic

Keratinised

Karyolytic

Basal

Micronucleated

differentiated Pyknotic

Figure 8c ) Model 2 shows flattening of rete pegs with a lower basal cell proliferation

and frequency whilst maintaining a normal apoptotic rate resulting in thinning of the

buccal mucosa, and a shorter average distance between the basal cell layer and

mucosal surface.

It is plausible that the changes within the ratios of the cell populations of the buccal

mucosa of AD patients may reflect some of the physiological changes that contribute

to the etiology of the disease. AD is histopathologically confirmed by the presence

within the brain of neurofibrillary tangles consisting of the microtubule associated

protein tau and amyloid plaques which contain the 42 amino acid β amyloid (Aβ42)


99

resulting from the aberrant proteolysis of the amyloid precursor protein (APP). The

gene for APP is found on chromosome 21 at 21q21 [252]. Both of these AD

associated proteins are present within vertebrate buccal mucosa [253,254]. It has

been shown that the level of tau in Alzheimer’s oral epithelium had a significant

positive correlation with tau levels in the cerebrospinal fluid [253]. This indicates that

buccal cells potentially may reflect some of the patho-physiological changes that occur

within the AD brain. Individuals suffering from AD had significantly higher levels of oral

epithelial tau when compared to controls who were clinically diagnosed as not

suffering from AD [253]. It has also been shown that Aβ42 has been detected within

the buccal mucosa of a genetically accelerated senescence mouse model [254] and

that APP has been detected in the basal cell layer of human skin epidermis [255]. APP

at low levels (1nM-10nM) has been shown to have a positive effect on the rate of

proliferation of basal cells. However at higher concentrations >10nM the rate of

proliferation is significantly impaired. Whether increased tau, Aβ42 or APP expression

alters proliferation rate of the basal cells and cell ratios of the buccal mucosa remains

unclear. Only future studies combining these multiple parameters may answer this

question.

Micronutrient deficiency such as zinc has also been shown to have a number of

effects on the structural profile of the buccal mucosa [256,257]. Rats fed on a zinc

deficient diet exhibited hyperplastic changes within the buccal mucosa. After 9 days

the keratin layer showed parakeratosis and significant thickening [257]. After 18 days

all cells within the keratin layer showed further thickening and a complete

parakeratotic transformation with a doubling of the mitotic rate within the basal cell

layer. These changes were readily reversible once the rats returned to a normal


100

control diet containing the normal amount of zinc [258]. It is plausible that AD patients,

if suffering from a micronutrient deficiency such as zinc, or if zinc is not bioavailable

because it is aggregated by β amyloid [259] may exhibit similar changes within the

buccal mucosa. If such thickening were apparent, then the number of basal cells

sampled would be significantly reduced as the keratinised layer thickened. Future

studies need to be performed to investigate the effects of micronutrient zinc deficiency

or availability of free zinc on changes in both cellular kinetics and structure of the AD

buccal mucosa.

An alternative explanation for the reduced proportion of basal and apoptotic cells

could be differences in cell sampling between AD and control groups. However, we

think that this is unlikely because collections were done by one person following a

standard protocol. Nevertheless, studies were performed involving repeated sampling

on the same day which showed that basal cells are increased as deeper layers are

sampled (Table 3). The proportion of karyorrhectic and condensed chromatin cells

were found not to be significantly changed with repeated sampling (Table 3). Although

a trend for an increase of karyorrhectic cells with repeated sampling was evident (P

trend=0.049), the increase in both basal cells and karyorrhectic cells at the fifth

sample was 195% and 69% greater than the first sample. This is much less than the

427% increase in basal cells and 486% increase in karyorrhectic cells of the normal

older controls relative to AD subjects. This argues against the possibility that observed

differences between controls and AD, may be explained by less vigorous sampling in

AD compared to the controls. In addition condensed chromatin cells were reduced in

AD but remained unchanged with repeated sampling. More attention maybe needed to


101

standardise the sampling protocol in order to obtain reproducible results especially

when multiple samplers are involved.

Previous studies by Migliore and colleagues showed that micronucleus frequency is

increased in lymphocytes and skin fibroblasts of AD patients [96,97,247]. However,

our results in buccal mucosa do not show a marked difference between AD and

controls for MN frequency or nuclear buds. As expression of MN requires nuclear

division, MN frequency in buccal mucosa is also dependent on the proportion of once

divided cells. It is possible that the reduced number of basal cells and perhaps a

reduced proportion of dividing basal cells in AD may inhibit MN and nuclear bud

expression (the latter being S-phase dependent) [227].

Future developments of the buccal cytome assay may involve automation either

through image analysis or flow cytometry in order to evaluate a larger number of cells

and provide a more accurate measure of buccal cell division kinetics, differentiation

and cell death.

Changes in the ratios of buccal cell populations may form the basis of a non invasive

test that could identify potential biomarkers that are specific to individuals suffering

from AD. Through further investigation it may be possible to further refine the buccal

cytome assay to include other DNA damage markers such as telomere shortening

[112], aneuploidy [97,99] and oxidative stress [134,137] which have been shown to

contribute to the etiology of the disease. If combined with quantitative measures of tau

and β amyloid, a more comprehensive assay with even greater diagnostic value could


102

potentially be developed and used to non-invasively identify individuals

presymptomatically of increased risk of AD.


103

Table 3 : Shows the changes in the ratios of buccal cells (mean, standard deviation and P values) following sequential buccal cell sampling. Buccal cells were collected from volunteers (N=4, 2 male, 2 female, age range 40-50yrs) over five different time points 0 mins, 90 mins, 270 mins, 360 mins and 450 mins. Buccal cells were collected as outlined in the cell sampling and preparation part of this manuscript. (Page 6) Slides were stained as outlined in the Feulgen staining part of this manuscript (Page 8). Slides were classified and scored as outlined under the scoring criteria part of this manuscript (Page 9-14). Statistical analysis for mean, standard deviation and one way ANOVA and linear P trends were calculated using Graphpad PRISM (Graphpad inc., San Diego, CA). Significance was accepted at P<0.05. Groups not showing the same letter are significantly different from each other. Sequential samples

Micronuclei per 1000 cells

Nuclear buds Per 1000 cells

Basal cells per 1000 cells

Binucleated cells per 1000 cells

Condensed chromatin cells per 1000 cells

Karyorrhectic cells per 1000 cells

Pyknotic cells per 1000 cells

Karyolytic cells per 1000 cells

Sample1 (0 mins)

0.50±0.57a 0.50±0.57

a 28.75±12.79

a 9.25±4.78

a 25.75±15.59

a 20.3±13.1

a 0.50±0.57

a 156.5±118.4

a

Sample 2 (90 mins)

0.50±0.57a 0.25±0.50

a 51.5±7.9

bf 12.0±4.16

a 22.5±11.47

a 29.0±16.79

a 0.7±1.5

a 111.8±49.17

a

Sample 3 (270 mins)

0.0±0.0a 0.25±0.50

a 59.5±6.75

cf 9.75±3.78

a 30.0±5.1

a 31.0±18.31

a 0.0±0.0

a 135.5±49.17

a

Sample 4 (360 mins)

0.50±0.57a 0.25±0.50

a 65.5±5.19

df 11.5±5.82

a 21.25±2.06

a 29.3±19.21

a 0.0±0.0

a 102.0±32.30

a

Sample 5 (450mins)

0.25±0.5a 0.0±0.0

a 84.75±6.0

e 9.0±1.83

a 31.0±13.29

a 34.3±23.16

a 0.0±0.0

a 129.3±25.25

a

ANOVA P values

0.6272 0.6363 <0.001 0.7968 0.6749 0.2320 0.5032 0.6696

P Value for Linear trend

0.5744 0.1742 <0.001 0.8841 0.6146 0.0489 0.1672 0.4729

Chapter 4: Telomere length

104

4 Chapter 4: Telomere length in white blood cells, bu ccal

cells and brain tissue and it’s variation with agei ng and

Alzheimer’s disease


105

4.1 Abstract Changes in telomere length have been associated with ageing and with certain age

related degenerative diseases. This study involves using a quantitative RTm-PCR

method to measure absolute telomere length (in Kb per diploid genome) and show

the age-related changes in white blood cells and buccal cell telomere length (in kb

per diploid genome) in normal healthy individuals and Alzheimer’s patients. A

significantly lower telomere length was observed in white blood cells (P<0.0001) and

buccal cells (P<0.01) in Alzheimer’s patients relative to healthy age-matched controls

(31.4% and 32.3% respectively). However, there was a significantly greater telomere

length in hippocampus cells of Alzheimer’s brains (P=0.01) compared to control

samples (49.0%). It was also observed that telomere length in buccal cells was

52.2%-74.2% shorter than in white blood cells (P<0.0001). The odd’s ratio of being

diagnosed with Alzheimer’s disease was 10.8 (95% CI 1.19-97.85) if white blood cell

telomere length was less than 115kb per diploid genome with a specificity of 46%

and sensitivity of 92.9%. The odds ratio for AD diagnosis was 4.6 (95% CI 1.22-

17.16) if buccal cell telomere length was less than 40kb per diploid genome with a

sensitivity of 72.7% and a specificity of 63.1%. These results suggest important

differences in telomere maintenance in Alzheimer’s cases compared to healthy

controls depending on sampled tissue.


106

4.2 Introduction The ends of eukaryotic chromosomes, which consist of highly conserved

hexanucleotide repeats (TTAGGG) are known as telomeres. Telomeres play an

essential role in the maintenance of genomic stability because they act to protect the

ends of chromosomes from DNA damage and prevent chromosomal end to end

fusions [111,112,260,261]. Due to the nature of the DNA replication mechanism

copying of the 3’ DNA strand ends is incomplete. Consequently, somatic cells lose

between 50-150bp of the telomere repeats every time a cell replicates its DNA and

divides. Therefore, telomere content may serve as an effective biomarker of a cell’s

replicative history [262].

Telomere size is maintained by a unique ribonucleoprotein enzyme called telomerase

(TERT) that mediates the synthesis of telomere repeats in a wide range of tissues

[263]. TERT activity is increased in germ line, malignant cells and stem cells

[115,264]. Thereby, it has been postulated that this increased activity is essential in

establishing a status of “immortality” and uncontrolled cell proliferation which is

characteristic of cancer [265]. Although normal somatic cells may have a limited

capacity to restore telomere length, this does not appear to be sufficient to overcome

telomere shortening caused by the telomere end replication problem or by other

mechanisms induced by oxidative stress [113,266,267].

Thus ageing, involves progressive telomere shortening which is caused by the

inevitable increase in DNA replication with time, and possibly as a result of other

factors such as breaks and deletions in the telomere sequence, deficiencies in

telomere repair and reduced TERT activity. Telomere shortening leads to


107

chromosomal end to end fusions resulting in chromosomal instability due to the

initiation of breakage fusion bridge (BFB) cycles, cellular senescence, apoptosis and

potential neoplastic changes [261,268]. It has been shown that telomere shortening

is associated with an elevated risk of degenerative disease states such as cancers of

the head, neck, lungs, prostate and bladder and increased risk of cardiovascular

disease [114,115,269,270].

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is

characterised clinically by cognitive impairment, memory loss, visuo-spatial and

language impairment and is the most common form of dementia [3,8,10,46].

Currently the global prevalence of AD is 24.3 million with 4.6 million new cases being

diagnosed annually [4,5]. To date no reliable biomarker exists that will identify

individuals with an increased risk for AD.

AD is an example of a premature ageing syndrome and has been associated with

elevated frequencies of genomic instability biomarkers. Genomic instability

biomarkers found to be elevated within AD include micronuclei,

( biomarkers of whole chromosome loss and breakage ) [96,242], aneuploidy of

chromosome 21 in lymphocytes and fibroblasts [97-99] and telomere shortening in

both lymphocytes and fibroblasts [112,271,272]. These results indicate that genomic

instability may play a key role in the etiology of this disease.

The primary aim of the study was to investigate age-related changes in telomere

length in white blood cells (WBC) and buccal cells and to determine whether

excessive shortening of telomere length was a common feature of WBCs, buccal


108

cells and brain tissue from clinically diagnosed or histopathologically confirmed AD

patients, compared to age and gender matched healthy controls. A secondary aim of

the study was to compare telomere length in WBCs and buccal cells because the

extent to which telomere length differs in these tissues remains unknown. In this

study the quantitative RTm-PCR method of Cawthon [273] was adapted to obtain an

absolute measure of telomere length and report for the first time results with this new

method.

4.3 . Methods


Approval for this study was obtained from the Human Experimentation Ethics

Committee’s of CSIRO Human Nutrition, Adelaide University, and College Grove

Hospital. Participants in this study consisted of three distinct groups: 30 young

controls (age 18-26yrs), 26 old controls (age 64-75yrs), and 54 clinically diagnosed

Alzheimer’s patients (age 58-93yrs). None of the participants recruited to the study

were receiving anti-folate therapy or cancer treatment. Age, gender and MMSE

scores of the cohorts are shown in Table 1. Gender ratio differences between the

groups were not significant (Chi square P>0.05). Young and old controls were

recruited through the clinic of CSIRO Human Nutrition. Alzheimer’s patients were

recruited at the College Grove Private Hospital, Walkerville, Adelaide, South

Australia following their initial diagnosis and prior to commencement of therapy.

Diagnosis of AD was made by two experienced clinicians according to the criteria

outlined by the National Institute of Neurological and Communicative Disorders and

Stroke-Alzheimer’s Disease and related Disorders Association (NINCDS-AD&DA)


109

[12]. These are well recognised standards used in all clinical trials. Mini Mental State

Examination scores (MMSE) which are a recognised measure of cognitive

impairment were only available for the Alzheimer’s cohorts’. Participants did not

receive any remuneration for their participation. Alzheimer’s patients were separated

into two distinct groups. The younger AD group was age-matched to the old control

group, whilst the second older AD group was classified as an older Alzheimer’s

cohort. MMSE scores between the two AD groups were not significantly different

(P>0.05). The age of the old control group compared to the younger AD group was

not significantly different, but the younger AD group had a significantly lower age

relative to the older AD group (P<0.0001). The young and old controls were “normal”

functioning healthy individuals, who self volunteered, consented to the study and did

not report a history of cognitive impairment.


110

Table 1 Age, gender ratio and MMSE scores in study groups

Young

Controls

Old Controls* Younger AD Older AD Alzheimer Brain Tissue Group

Control Brain Tissue Group

N=30 N=26 N=23 N=31 N=13 N=9 Age (Mean±S.D)

22.47±2.177 68.7±2.6 70.7±4.1 83.13±4.5 75.75±7.8 74.10±10.95

Age (Range) 18-26 66-75 58-75 78-93 59-88 60-98 Gender Ratio (Male/Female)

15/15 11/15 8/15 8/23 5/8 6/3

MMSE (Mean±S.D)

NA NA 22.52±3.013 22.13±3.6.76 NA NA

MMSE (Range)

15-27 12-29

* Age and gender matched to younger AD group

NA= Not available


111


Blood was collected from consented young and old controls by trained nursing staff

at the CSIRO Human Nutrition clinic. Buccal cells were also collected from these

cohorts. Blood was collected from consented clinically diagnosed Alzheimer’s

patients prior to medical treatment by trained nursing staff at College Grove Private

Hospital, Walkerville, Adelaide. Buccal cells were also collected from these cohorts.

A single 8ml EDTA tube was collected by venapuncture from all consented

individuals, placed on ice and then transported to the laboratory at CSIRO Human

Nutrition. Prior to buccal cell collection the mouth was rinsed thoroughly with water to

remove any unwanted debris. Small headed toothbrushes (Supply SA, code

85300012) were rotated 20 times in a circular motion against the inside of the cheek,




(Sarstedt code 60.9922.918) containing buccal cell (BC) buffer (0.01M Tris-HCL

(Sigma T-3253), 0.1M EDTA tetra sodium salt (Sigma E5391), 0.02M sodium

chloride (Sigma S5886)) at pH 7.0 and agitated to dislodge the cells. Cells from both

right and left cheeks were transfered into separate TV-10 centrifuge tubes (Sarstedt,

code 60.9921.829) and spun for 10 mins at 1500rpm (MSE Mistral 2000).

Supernatant was removed and replaced with 10mls of fresh BC buffer. The BC buffer

helps to inactivate endogenous DNAases and aids in removing bacteria.


112

Frozen non-fixed hippocampal brain tissue from histopathologically confirmed

Alzheimer’s patients (positive for the presence of amyloid plaques and neurofibrillary

tangles) was provided by the Brain Bank of South Australia, Centre of Neuroscience,

Flinders University. Control hippocampal brain tissue from histopathologically normal

individuals was provided by both the New South Wales tissue resource centre,

Department of Pathology, University of Sydney and the Brain Bank of South

Australia. Tissue provided from the hippocampus was taken from slices. Cores were

taken using a special drill bit and battery powered drill with the slices being kept on a

bed of ice during retrieval. The removed cores were placed in a small test tube and

stored at -70oC until transported.

4.3.3 DNA isolation

The isolation of DNA from whole blood, buccal cells and brain tissue was performed

under conditions that minimise in vitro oxidation. It has been shown that under

conditions of commonly used DNA isolation protocols, oxidative adducts can

spontaneously form thereby affecting the integrity of the acquired DNA [274,275] . A

modified version of the protocol outlined by Lu was used [276]. DNA was isolated

using the silica-gel membrane based DNeasy blood and tissue kit (Qiagen Cat no

69506), following the manufacturers instructions. Prior to isolation all buffers were

purged for five minutes in nitrogen and supplemented with 50µM phenyl-tert-butyl

nitrone (Sigma B7263) which acts as a free radical trap and scavenger, the use of

phenol and high temperatures (>56 oC) were avoided.


113

DNA from WBCs was isolated as follows:

100µl of whole blood was added to a microtube containing 20µl of proteinase K and

adjusted to 220µl with phosphate buffered saline (PBS). 200µl of nitrogen purged

DNeasy (Qiagen) AL buffer was added and incubated at 37 oC for 2hrs. 200µl of

ethanol was added and vortexed for 10 seconds. The mixture was pipetted into

another microtube housed in a collection tube and spun for 1 min at 8000rpm

(Eppendorf, Centrifuge 5415R). The spin column was placed inside another

collection tube and 500µl nitrogen purged DNeasy (Qiagen) AW1 buffer was added

and spun for 1 minute at 8000 rpm. The spin column was placed inside another


and centrifuged for 3 minutes at 14,000 rpm to dry the DNeasy membrane. DNA

was eluted by placing the spin column in a 2ml collection tube and adding 200µl of

nitrogen purged DNeasy (Qiagen) AE buffer and spun at 8000rpm for 1 minute.

DNA from buccal cells was isolated using a modified version of the protocol used to

isolate DNA from WBCs. Buccal cell pellets were resuspended in 0.5ml of BC buffer

and 100µl was used for the DNA isolation according to the above protocol. Buccal

cells were incubated with proteinase K over night prior to the final steps of DNA

elution.

For isolation of DNA from brain tissue we used a modified version of the protocol

used to isolate DNA from WBCs. 25 mg of brain tissue was cut into small pieces and

placed into a microcentrifuge containing 180µl of nitrogen purged DNeasy (Qiagen)

ATL buffer. After the addition of proteinase K the samples were incubated at 37 oC for

4hr until completely lysed. DNA elution occurred as above.


114

All samples were quantified using a nanodrop ND-1000 spectrophotometer

(Nanodrop Technologies, Wilmington, U.S.A)

4.3.4 Quantitative real time PCR The quantitative Real-Time amplification of the telomere sequence was performed as

described by Cawthon (2002) with the following modifications. A standard curve was

established by dilution of known quantities of a synthesised 84mer oligonucleotide

containing 14 TTAGGG repeats. The number of repeats in each standard was

calculated using standard techniques, as follows: the oligomer is TTAGGG repeated

14 times, 84bp in length (MW= 26667.2). The highest concentration standard

(standard 1) contained 1.9 x1010 telomere hexamer repeats units in 60pg which is

equivalent to 1.18 x108 kb of telomere sequence. Assays on serial dilutions were

performed to determine a standard curve for measuring kb of telomeric sequence

(Figure 1). Plasmid DNA (pBR3222) was added to each standard to maintain a

constant 20ng of total DNA per reaction tube.


115

Telomere standard curve

2 3 4 5 6 714

16

18

20

22

24

26

LOG [Telomere length (kb)]

Ct

Figure 1. Standard curve used to calculate absolute telomere length. CT (cycle

threshold) is the number of PCR cycles which enough SYBR-I green fluorescence is

detected above background. X-axis represents amount of telomere sequence in kb.

Correlation coefficient is 0.979. The graph shown here represents the linear range of

the PCR – DNA amount was optimised so that experimental samples are detected

within the linear range. The value generated from the experimental samples utilising

this standard curve is equal to kb of telomere sequence per sample. Standard curve

was generated using an ABI 7300 Sequence Detection System with the SDS Ver. 1.9

software (Applied Biosystems, Foster City, CA).

All samples were run on an ABI 7300 Sequence Detection System with the SDS Ver.

1.9 software (Applied Biosystems, Foster City, CA). After the reaction is completed

the AB system produces a value that is equivalent to telomere sequence length (kb)


116

per 20ng of total genomic DNA which is equivalent to telomere sequence length (kb)

per 2983 diploid genomes. The telomere sequence length (kb) per diploid genome

can then be derived from this value by dividing by 2983. A standard curve was

generated in each assay run. Each sample was analysed in duplicate. 36B4

amplification for every sample was also performed to verify accurate quantification of

the amount of template in each well. If the results for duplicate samples differed by

more than one CT value, the results were discarded and the assay repeated. Each

20µl reaction was performed as follows: 20ng DNA, 1xSYBR Green master mix,

100nM telo1 forward (CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGG TTTGGGTT),

100nM telo2 reverse (GGCTTGCCTTACCCTTACCCTTACCC TTACCCTTACCCT)

[273,277]. Cycling conditions (for both telomere and 36B4 amplicons) were: 10min at

95oC, followed by 40 cycles of 95oC for 15sec, 60oC for 1min. DNA from the 1301

lymphoblastoid cell line was used as a control in each plate run. Using the 1301 data

we estimated that the inter-experimental variability was ≤ 7 % (n=34) and the intra-

experimental variability ±1.1 % (n=17). The quantitative RT-PCR technique was

correlated against the established relative RTm-PCR which has been validated

against the southern blot technique (r=0.73, P<0.0001) (Figure 2).


117

0 50 100 150 200 250 3000.0

0.5

1.0

1.5

2.0

2.5

Absolute vs relative

r=0.73,P<0.0001

Absolute telomere length

Rel

ativ

e te

lom

ere

leng

th

Figure 2 : Graph showing correlation between absolute RT-PCR technique and

established relative RTm-PCR method.


One way ANOVA analysis was used to determine the significance of differences

between groups for the measurement of telomere length, whereas pair wise

comparison of significance was determined using Tukey’s test. Comparisons

between two groups were performed using student’s t-test. ANOVA analysis and t-

test values, positive predictive values, negative predictive values, sensitivity,

specificity, likelihood ratios and odds ratio were calculated using Graphpad PRISM

(Graphpad inc., San Diego, CA). P values <0.05 were considered to be significant.


118

4.5 Results

The results for the differences in telomere length in WBCs, buccal cells and brain

hippocampus for the cohorts investigated are shown in Table 2 and Figures 3-6.

4.5.1 WBCs (Figure 3) There was a significant difference in WBC telomere length between the young and

old controls (P=0.01). The mean value was lower in the old group by 21.0%.

Telomere length in the young and old controls was greater than that in AD patients

(P<0.0001). Telomere length of the younger AD cohort were significantly shorter than

that of their age-matched old controls (P=0.007). The older AD cohort was also

significantly shorter than the old controls (P=0.001). There were no significant

differences in telomere length between the younger AD and older AD cohorts

(P=0.512) (Figure 3). A correlation analysis was performed of age against telomere

length for all the cohorts for WBC values. An inverse relationship was obtained

between these two parameters with an r value of -0.5098 and a 2 tailed P<0.0001.


119

WBC telomere length

Young

contr

o ls

Old co

ntrols

Younger

AD

Older

AD

0

25

50

75

100

125

150

175 a

b

P<0.0001

c c

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 3 . Absolute telomere length in WBC DNA of young controls (N=30), old

controls (N=26), younger AD (N=14) and older AD cohorts (N=18). Groups not

sharing a letter are significantly different from each other. Error bars represent SE of

the mean.

4.5.2 Buccal cells (Figure 4) There were no significant differences in telomere length in buccal cells between the

young and the old control cohort (P>0.05). The Younger AD group tended to have a

lower telomere length when compared to the older control group but this difference


120

did not achieve significance (P>0.05). The Older AD group had a significantly lower

telomere length compared to the older controls (P=0.01) (Figure 4). Results from

these studies showed that telomere length in buccal cells were consistently lower by

52.2% to 74.2% than the corresponding value for WBCs (Figure 5).

Buccal telomere length

Young

cont

rols

Old co

ntro

ls

Young

er A

D

Older A

D

0

10

20

30

40

50

P=0.01

aa

ab

b

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 4 . Absolute telomere length in DNA from buccal cells of young controls

(N=30), old controls (N=26), younger AD (N=23) and older AD cohorts (N=30).

Groups not sharing a letter are significantly different from each other. Error bars

represent SE of the mean.


121

you ng

contr

ols

youn

g cont

rols

old c

ontro

ls

old c on

trols

you ng

er A

D

youn

ger A

D

older

AD

olde r A

D

0

25

50

75

100

125

150

175

P<0.0001

WBCs v Buccal cells

P<0.001

P<0.001

P<0.05P<0.001

Buccal cells

WBCs

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 5. Comparison of absolute telomere length in whole blood and buccal cell

DNA from the same cohorts. Young controls (N=30), old controls (N=26), younger

AD (N=23) and older AD cohorts (N=30). Error bars represent SE of the mean.


122

4.5.3 Brain hippocampus There was a significant increase in telomere length in the hippocampus of

Alzheimer’s brain tissue compared to control hippocampus tissue (P=0.01) (Figure

6).

There were no significant gender effects for telomere length within any of the cohorts

for any of the tissues investigated.

AD Brain tissue Control Brain tissue

0

50

100

150

200

P=0.01

Brain hippocampus telomere length

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 6 . Absolute telomere length in DNA from hippocampal brain tissue of a

histopathologically confirmed Alzheimer’s cohort (N=13) and a normal control cohort

(N=9). Error bars represent SE of the mean.


123

Table 2: Mean and standard deviation values for cohort absolute telomere lengths Young

Controls (Mean±SD)

Old controls (Mean±SD)

Young AD (Mean±SD)

Old AD (Mean±SD)

AD Brain (Mean±SD)

Control Brain (Mean±SD)

WBC 144.7±58.44a 110.3±28.24 72.04±33.45b 79.36±29.59 NA NA Buccal 41.98±32.66 40.57±19.28 34.41±34.05 20.51±18 .04* NA NA Brain NA NA NA NA 176.9±44.44** 118.7±49.57 NA: Not available a P<0.05 comparing blood telomere length between young and old controls b P<0.05 comparing blood telomere length between Young AD and older controls * P<0.05 comparing buccal telomere length between older AD and old controls **P=0.01 comparing telomere length between AD brain hippocampus and control hippocampus brain tissue


124

4.5.4 Correlations Combined data for all cohorts showed no significant correlation between buccal cell

and WBC telomere length. Correlation for MMSE scores and WBC telomere length

(r=0.45, -0.02) or buccal telomere length (r=-0.03, 0.04) in the younger AD cohort or

older AD cohort (respectively) were not significant.

4.5.5 Sensitivity and specificity

Values for telomere length for both WBCs and buccal cells in the younger AD group

and the age and gender-matched older control group were analysed to determine the

sensitivity and specificity and thus the usefulness of changes in telomere length as a

potential biomarker for AD. For WBC telomere length <115 Kb per diploid genome

the odds ratio of being diagnosed with AD is 10.8 (95% CI 1.19-97.85) with a

specificity of 46% and sensitivity of 92.9%.

For buccal cell telomere length <40kb per diploid genome the odds ratio of being

identified with AD is 4.6 (95% CI 1.22-1716) with a specificity of 63% and sensitivity

of 72.7%.

4.6 . Discussion

The aim of the study was to investigate age-related changes in telomere length in

WBCs and buccal cells and compare results for these two cell types which are

commonly used in population and biomonitoring studies. It was also determined


125

whether there were alterations in telomere length in WBCs, buccal cells and brain

tissue within clinically diagnosed or histopathologically confirmed Alzheimer’s

patients compared to control cohorts.

A significantly lower telomere length was found in WBCs in the younger AD

(P=0.007) and the older AD (P=0.001) cohorts compared to the old control group

(Figure 3). There were no significant differences in telomere length between the

younger AD and older AD cohorts (P=0.512). Whole blood contains diverse

populations of WBCs some, or all of which, may demonstrate telomere shortening in

relation to ageing, as well as a result of certain genetic or environmental factors

[266,278]. It has been shown that telomeres from T and B lymphocytes, and

monocytes are shorter in AD patients compared to controls [112]. These results are

consistent with these previous observations. A significantly lower telomere length

was observed between the old controls and the young cohort (P=0.01). Taken

together these results suggest that any observed effects of telomere shortening with

ageing, may be influenced by effects in sub-groups susceptible to developing AD.

The buccal cell telomere length tended to be shorter in the AD groups compared to

the old controls (Figure 4). This is the first time that an association between buccal

cell telomere length and AD has been reported. Unlike WBCs, there was no

significant age-related telomere shortening trend occurring between the young and

old control cohorts. When buccal cell telomere length was compared to the

measurements in WBCs made from the same cohort it is evident that the buccal cell

telomere length is consistently significantly shorter across all groups. Buccal and

WBC telomere length were not found to be significantly correlated. This supports


126

observations in other studies that telomere length in one tissue does not predict

telomere maintenance in other parts of the body [279,280].

Shorter telomeres in buccal cells may be due to a higher rate of cell division in

epithelial tissues relative to WBC tissue, given a high turn over rate in buccal

exfoliate cells of 21 days relative to a half life of 6 months or greater in lymphocytes.

However, neutrophils which represent the majority of white blood cells, have a life

span of no more than 10 hrs in the blood [281-284]. Despite the differences in half-

life, telomere length in neutrophils is only 5% shorter than in lymphocytes, suggesting

that the effect of replicative history of the different cell types on telomere length may

not be a strong one [285]. An alternative explanation for the shorter telomeres in

buccal cells could be the heterogeneous population sampled which contains

karyorrhectic, karyolytic, pyknotic and cells with condensed chromatin that are in the

process of cellular senescence [225]. This may have affected telomere length

measurements in buccal cells if telomeres are degraded during cell senescence or

cell death. It is possible that buccal cell samples may over-represent dying/dead cells

and under-represent viable cells such as basal and normal differentiated cells. This

highlights the need for methods resulting in more selective sorting of cells that could

potentially lead to a more precise and sensitive assay. It is also not currently evident

whether telomerase activity occurs in any of these buccal cell populations.

Alternatively, the microenvironment of the buccal mucosa which is highly oxygenated

may have an effect on telomere content as a result of oxidative stress, which has

been shown to shorten telomeres [267].


127

Telomere length within the brain hippocampal tissue was found to be significantly

longer in the Alzheimer’s brain compared to normal control tissue (P=0.01), which is

opposite to the trends observed in WBCs and buccal cells (Figure 6). It has recently

been shown that cells within the dendate gyrus of the hippocampus continue to

divide throughout adult life and may succumb to factors that may influence the

mechanisms underlying cell proliferation [286,287]. Assuming telomere length

reflects proliferation history, then one can conclude that the longer hippocampal

telomeres in the AD group are due to a weaker proliferative capacity relative to

healthy controls. An alternative explanation for the longer telomeres in the AD brain

may be due to initial telomere shortening followed by telomere to telomere end

fusions and amplification of telomere sequences due to breakage /fusion /bridge

cycles [120,121]. It has also recently been shown that DNA methylation is an

important repressor of telomeric DNA recombination [288].

Reduced methylation in subtelomeric sequences possibly as a result of folate, B12

and choline deficiency may result in telomeric elongation either through increased

telomeric recombination events or as a result of increased telomerase activity [288].

Decreases in methylation of subtelomeric regions results in a more “open” chromatin

structure in telomeres, allowing greater accessibility for telomerase and proteins

involved in the alternative lengthening of telomeres mechanism (ALT) [289]. It is

possible that certain somatic tissues susceptible to folate deficiency and in particular

those of the brain, may be more sensitive to such mechanisms regulating telomere

length. There is no evidence to confirm or refute these hypotheses. Only further

experimentation will shed light on hippocampal telomere kinetics. Further studies are

needed in order to determine brain telomere status and functionality.


128

One of the limitations of the study is that it is not evident which populations of cells

contribute to the changes in telomere content, and whether there is uniform

chromosomal shortening, or shortening of only a specific subset of chromosomes.

Homogeneous cell populations could be made available through fluorescently

labelled cell surface markers and separated by flow cytometry, thereby reducing the

influence of non-viable cells and cell type mixtures on overall telomere content. From

these results it would appear that WBC DNA is potentially a more sensitive measure

of differences in telomere length between AD cases and controls compared to buccal

cells. However, individual cell types may need to be identified to further improve

sensitivity and specificity and more accurately evaluate telomere length as a viable

biomarker for accelerated ageing syndromes.

Chapter 5: Aneuploidy

129

5 Chapter 5: Chromosome 17 and 21 aneuploidy in bucca l

cells is increased with ageing and in Alzheimer’s

disease


130

5.1 Abstract

Alzheimer’s disease is a premature ageing syndrome characterised by cognitive

impairment arising from neuropathological changes occurring within specific areas of

the brain. This study found a 1.5 fold increase in trisomy 21 (P<0.001) and a 1.2 fold

increase in trisomy 17 (P<0.001) in buccal cells of Alzheimer’s patients compared to

age and gender matched controls. Chromosome 17 and chromosome 21 monosomy

and trisomy increase significantly with age (P<0.001). Down’s syndrome, which

exhibits similar neuropathological features to those observed in Alzheimer’s disease

also showed a strong increase in chromosome 17 monosomy and trisomy compared

to matched controls (P<0.001). These results suggest that an increased incidence of

aneusomy for both chromosomes 17 and 21, which may lead to altered gene dosage

and expression of both the Tau and APP genes, may contribute to the etiology of

Alzheimer’s disease. However, aneuploidy rate for chromosome 17 and 21 in the

nuclei of hippocampus cells of brains from Alzheimer’s patients and controls were not

significantly different.

5.2 Introduction Alzheimer’s disease (AD) is a complex progressive neurodegenerative disorder of

the brain, and is the commonest form of dementia [3]. Neurodegenerative changes

appear firstly within the entorhinal cortex and then progress to the hippocampus

eventually disrupting learning and short term memory [290,291]. The disease is

clinically defined by progressive memory loss, visuo-spatial and language impairment

and various psychiatric and behavioural changes [3,8,10,46]. The two

histopathological structures present within the brain that positively identify AD


131

conclusively at post mortem are the neurofibrillary tangles and the amyloid based

neuritic plaques [10,46].

Neurofibrillary tangles are composed of the microtubule associated protein tau, the

gene of which is located on chromosome 17q21.1 [18]. Tau is important as it

associates with tubulin in the formation of microtubules. Microtubules impart shape

and structure to cells, and also form the basis of a cellular transport network allowing

the movement of neurotransmitters, micronutrients and organelles that are essential

for normal cellular function [20]. Microtubules also provide points of attachment for

chromosomes during cell division, which if disrupted may result in an increased

incidence of chromosome malsegregation [292]. The neurofibrillary tangles contain

structures known as paired helical threads comprised of tau which are

hyperphosphorylated. This hyperphosphorylation leads to a dissociation between

tubulin and tau resulting in a breakdown of the brain transport system leading to loss

of biological activity, cell death and potential microtubule dysfunction leading to

chromosome malsegregation [18,20]. The second histopathological feature in the

brain of AD patients is the amyloid based neuritic plaques. These consist of the 42

amino acid β amyloid peptide 42 (Aβ42), which originates from the aberrant

proteolysis of the amyloid precursor protein (App), the gene (APP) of which is located

on chromosome 21q21 [28].

Down’s syndrome (DS) like AD is a premature ageing syndrome characterised by

various degrees of chromosome 21 trisomy and an elevated incidence of genome

instability [241,293]. DS individuals develop dementia and manifest brain changes

that are histopathologically indistinguishable from AD, usually during the third or


132

fourth decade of life [101,294]. For this reason it has been suggested that both AD

and DS share underlying mechanisms involving susceptibility to chromosome

malsegregation events, particularly those involving chromosome 21. Alteration in

gene dosage and expression for the TAU and APP gene resulting from aneuploidy

may be an important contributor to the etiology of AD. It has not yet been determined

whether aneuploidy of chromosome 17 has a higher incidence in AD and DS and

whether gene dosage and altered gene expression of the TAU gene may play a

potential contributory role in AD and DS pathology.

There is much evidence from previous studies to show that both AD and DS share an

increased susceptibility to genomic instability events. Micronuclei are elevated in AD

lymphocytes and were shown to be centromere positive indicating whole

chromosome loss [96]. Migliore et al also showed a significant increase in

micronuclei in the lymphocytes of young Down’s syndrome mothers (MDS) and

showed they were more prone to non-disjunction events for chromosome 13 and 21

[295]. A similar predisposition to increased aneuploidy events for chromosome 13

and 21 has been shown in lymphocytes of AD patients [97,98]. Fibroblast cultures

from sporadic and familial AD patient’s that carry mutations within the presenilin 1,

presenilin 2 and the amyloid precursor protein were found to have an approximately

2 fold increase in the number of trisomy 21 cells compared to cultures from normal

individuals [99]. These findings suggest that aneuploidy may have a contributing role

to early changes in disease development.

The aim of this study was to use fluorescent in situ hybridisation (FISH) and

fluorescently labelled DNA probes, to determine the incidence of aneuploidy of


133

chromosome 17 and 21 in the buccal mucosa and hippocampal brain tissue of

Alzheimer’s patients compared to age and gender matched controls. It was also our

intention to investigate any age-related effects on aneuploidy involving these two

chromosomes between a young and old cohort, and whether aneuploidy for

chromosome 17 in the buccal mucosa of DS was significantly different from controls.

Buccal cells were selected for this study because they can be collected non-

invasively and originate from the neuroectoderm from which brain tissue is derived

[296]. Buccal cells may therefore exhibit genetic defects common to brain tissue

acquired during the early stages of development.

5.3 Methods



University, Ramsay Health Care and Southern Cross University Human

Experimentation Ethics Committee’s. Participants in this study consisted of four

distinct groups: 30 younger controls (age 18-26yrs), 31 older controls (age 64-75yrs),

21 DS individuals (age 5-20yrs) and 54 clinically diagnosed Alzheimer’s patients (age

58-93yrs). None of the participants recruited to the study were receiving anti-folate

therapy or cancer treatment. Alzheimer’s patients were recruited at the College

Grove Private Hospital, Walkerville, Adelaide, South Australia following their initial

diagnosis and prior to commencement of therapy. Diagnosis of AD was made by

experienced clinicians according to the criteria outlined by the National Institute of

Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and


134

related Disorders Association (NINCDS-AD&DA) [12]. These are recognised

standards used in all clinical trials. Mini Mental State Examination scores (MMSE)

which are a recognised measure of cognitive impairment were only available for the

Alzheimer’s cohorts. Participants did not receive any remuneration for their

participation.

Alzheimer’s patients were separated into two distinct groups. One group (younger AD

group) was age matched to the older control, whilst the second group was classified

as the older AD group. Gender ratio differences between the groups were not

significant (P>0.05). MMSE scores between the two AD groups were not significantly

different (P>0.05). The age of the older control group compared to the younger AD

group was not significantly different but the younger AD group had a significantly

lower age relative to the older AD group (P<0.0001). The younger and older controls

were “normal” functioning healthy individuals, who self volunteered and consented to

the study and did not report a history of cognitive impairment. Demographic

characteristics of the cohorts are shown in Table 1. Consent from AD and DS

volunteers’ was provided by either partners or guardians.


135

Table 1 Age, gender ratio and MMSE scores in study groups Young

controls

Down’s

syndrome

Old Controls* Younger AD Older AD Alzheimer’s Brain Tissue Group


N=30 N=21 N=26 N=23 N=31 N=13 N=9

Age (Mean±S.D)

22.47±2.177 10.43±5.582 68.7±2.6 70.7±4.1 83.13±4.5 75.75±7.8 74. 10±10.95

Age (Range) 18-26 5-20 66-75 58-75 78-93 59-88 60-98

Gender Ratio (Male/Female)

15/15 11/10 11/15 8/15 8/23 5/8 6/3

MMSE (Mean±S.D)

NA NA NA 22.52±3.013 22.13±3.6.76 NA NA

MMSE (Range)

15-27 12-29

* Age and gender matched to younger AD group NA= Not available


136

5.3.2 Buccal cell collection and slide preparation

Buccal cells were collected using a modified version of the method used by Beliën et

al [225]. Prior to buccal cell collection the mouth was rinsed thoroughly with water to

remove any unwanted debris. Small headed toothbrushes (Supply SA, code

85300012) were rotated 20 times in a circular motion against the inside of the cheek,




(Sarstedt ,code 60.9922.918) containing buccal cell (BC) buffer (0.01M Tris-HCL


chloride (Sigma S5886)) at pH 7.0 and agitated to dislodge the cells. Cells from both

right and left cheeks were transfered into separate TV-10 centrifuge tubes (Sarstedt,

code 60.9921.829) and spun for 10 mins at 1500rpm (MSE Mistral 2000).

Supernatant was removed and replaced with 10mls of fresh BC buffer. The BC buffer

helps to inactivate endogenous DNAases and aids in removing bacteria that may

complicate scoring. Cells were spun and washed twice more, with a final volume of

5mls of BC buffer being added to the cells. The cell suspension was vortexed and

then homogenised for 2 mins in a hand homogeniser (Wheaton scientific 0.1-0.15

mm gauge) to increase the number of single cells in suspension. Left and right cell

populations were pooled into a 30ml yellow top container and drawn into a syringe

with a 21G gauge needle and expelled to encourage cellular separation. Cells were

passed into a TV-10 tube through a 100µm nylon filter (Millipore,code

MILNYH02500) held in a swinex filter (Millipore, code MILSX0002500) to remove

large aggregates of unseparated cells that hinder slide preparation and cell analysis.


137

Cells were further spun at 1500rpm for 10 mins and the supernatant removed. Cells

were resuspended in 1ml of BC buffer and the cell concentration determined by a

Coulter counter (Beckman Coulter Model ZB1, Settings Attenuation:1, Threshold:8,

Aperture:1/4, Manometer:0.5). Cell suspensions were prepared containing 80,000

cells/ml after initial readings from a 1:50 dilution (300µl/15mls isoton). 50 µl/ml of

dimethyl sulphoxide (Sigma 2650) was added to help clarify cellular boundaries by

further separating the cells. 120 µl of cell suspension was added to cytospin cups

and spun at 600 rpm for 5 mins in a cytospin (Shandon cytospin 3). Slides containing

two spots of cells were air dried for 10 mins and then fixed in ethanol:acetic acid (3:1)

for 10 mins. Slides for FISH were air dried for 10 mins prior to being stored at -70°C

in a sealed dessicated slide box.

5.3.3 Brain tissue collection and slide preparation




Flinders University. Control hippocampal tissue from histopathological normal








138

200mg of brain tissue was weighed (Sartorius Scales type 1475) inside a biological

safety cabinet (Gelman Sciences, BH series) and placed on a slide inside a petri dish

and moistened with a few drops of phosphate buffered saline (PBS),(120 mM sodium

chloride, 2.7 mM pottasium chloride, 10 mM potassium phosphate monobasic,10 mM

sodium phosphate dibasic, pH 7.4) . Tissue was minced and chopped thoroughly

using a scalpel blade (Blade No 11,Swann-Morton Ltd, Sheffield, England) and

transferred to TV-10 tube. 2ml PBS washings were taken of the slide within the

inclined petri dish and transfered to the TV-10 tube. Three washings per slide were

made. A glass pipette was used to draw up and release the cell suspension to

encourage the separation of single cells. Care was taken to avoid the production of

aerosols whilst pipetting. The tube was balanced and centrifuged at 2500 rpm for 10

mins. The supernatant was removed and replaced with 6mls of PBS. The cell pellet

was drawn up and released several times using a glass pipette to further encourage

the production of single cells. Cells were drawn up into a 10ml syringe and filtered

into a TV-10 tube through a 100µm nylon filter (Millipore, code MILNYH02500) held

in a swinex filter (Millipore, code MILSX0002500) to remove large aggregates of

unseparated cells that hinder slide preparation and cell analysis. 1ml of Carnoys fix,

ethanol: glacial acetic acid (3:1) was added and the suspension mixed. Tubes were

spun for 2500rpm for 10 mins. Supernatant was aspirated and fresh fix added to a

volume of 6mls and centrifuged at 2500rpm for 10 mins. Fixation was repeated and

cells resuspended in 4mls of fix to produce a cloudy suspension. Cells were dropped

onto clean slides, air dried for 10 mins and placed in a slide box at -20°C with

desiccant ready for FISH analysis.


139

5.3.4 Preparation of chromosome 17 DNA probe Centromeric chromosome 17 specific DNA probe was generated by PCR labelling

with centromere specific primers for the chromosome (α17A1: 5' AAT TCG TTG

GAA ACG GGA TAA TTT CAG CTG 3'; α17B2: 5' CTT CTG AGG ATG CTT CTG

TCT AGA TGG C 3' (Geneworks, Thebarton, Adelaide) [297,298] . The length of the

amplification product is 227bp (26). Briefly, PCR was carried out with 0.2 µM of each

primer, 60 µM Digoxingenin-11-dUTP (Roche No: 1093088), 140 µM dTTP, 200 µM

dATP, dCTP and dGTP (Roche No: 1969064). The PCR was started with pre-

denaturation at 94°C for 2 min, followed by 25 cycles of 92°C for 1 min, 61°C for 2

min, 72°C for 2min, and terminal extension at 72°C for 10min. Chromosome 17

centromeric probe was validated by hybridising to human metaphases to determine

exact position and ensure no cross hybridising had occurred.

5.3.5 Human metaphase preparation 5mls of whole blood was collected in a lithium heparin tube. 500µl of whole blood

was added to 10ml of RPMI-1640 media (Trace lot DO8183-100) containing 20%

fetal calf serum (Trace LotAO6168-100),100IU/ml penicillin/streptomycin (Trace Lot

DO5335-100), 0.7mmol L-glutamine (Sigma G7513) and 90µg/ml

Phytohaemagglutinin (Ref No:HA15, Remel Europe Ltd, U.K). Duplicate cultures

were incubated at 37oC for 48hrs.100µl of Thymidine (30mg/ml in distilled water

Sigma T-9250) was added to each 10ml culture and incubated for 18hrs at 37oC. 100

µl of 2-deoxycytidine (Sigma cat no: D-3897) was added to each culture at a final

concentration of 2.4µg/ml and further incubated at 37oC.for 5 hours. 100µl of

colchicine (Sigma, C-9754) was added at a final concentration of 0.1µg/ml and


140

incubated for 20 minutes after being transferred to conical based centrifuge tubes

(Sarstedt, cat No: 60.9921.829). All tubes were spun at 1500rpm for 10 minutes, after

which the supernatant was removed and replaced drop wise with 1ml of 0.022M

potassium chloride (Sigma P-8041) which acts as a hypotonic. A further 7mls of

hypotonic was added and incubated at 37oC for 20 mins. 1ml of ice cold 3:1 (ethanol:

acetic acid) fixative was added drop wise to the cultures and left for 5mins. Tubes

were inverted to allow even distribution of the fix and then spun down at 1500rpm for

10 mins. The supernatant was removed leaving ~ 1 ml of cell pellet and a further

7mls of fix was added. The tubes were inverted and subsequently spun down; fixing

was performed a total of three times producing a white cell pellet.

Slides were cleaned in ethanol prior to being placed in a freezer to chill down before

metaphase preparation. Cold cell suspension was dropped onto the slides from a

height of ~ 12 inches and Newtons rings allowed to expand and dry on the bench.

Slides were checked under phase contrast to determine chromosome length, mitotic

index and degree to which metaphases had spread out. Slides were then used to

validate the specificity of prepared chromosome 17 labelled DNA probes (Figure 1).

Chromosome 17 was identified by chromosomal length and centromeric position in

relation to other group E chromosomes. Group E chromosomes are the short,

submetacentric human chromosomes, comprising of chromosome pairs 16, 17, and

18.


141

Chromosome 17Chromosome 17

Figure 1 : Metaphase showing hybridised DNA labelled probe specific to

chromosome 17 centromere.

5.3.6 Hybridisation and detection for chromosome 17

Prior to hybridization and detection the buccal slides were pre-treated with pepsin

(Sigma P-7012) (300µg/ml in 0.01N HCL (BDH Lab supplies)) for 10 mins whilst

lymphoblastoid control slides were treated with (5µg/ml pepsin in 0.01N HCL) at 37

°C for 10 min and then washed twice in phosphate-buffered saline (PBS, pH 7.0) for

5 min at room temperature. Afterwards, the slides were dehydrated in a cold ethanol

series (70%, 70%, 80%, 90%, and 100%) for 2 mins each and air dried.

Hybridizations were performed according to a modified technique of Pinkel et al

[299,300]. Slides were denatured at 79°C for 5 min in pre-warmed 70% formamide

(Sigma Aldrich No:295876)/2XStandard Saline Citrate (SSC), (0.15M sodium

chloride, 0.015M sodium citrate) and then dehydrated through an ethanol series

(70%, 70%, 80%, 90%, 100%,for 2 min each) at 4°C. 2 µl of the digoxigenin -11-


142

dUTP labelled PCR product, 1 µl of 2mg/ml herring sperm DNA (Sigma D7290) were

mixed with 6 µl hybridization buffer (55% formamide, 10% dextran (Sigma D 6001) in

1x SSC), 1 µl of water and denatured at 79°C for 5 min. The probe mixture was then

added to the slides (5 µl/cytospin spot), a coverslip was applied and sealed with

rubber cement. Hybridization was carried out overnight (18-20hrs) in a humidified

chamber at 37°C. Cover slips wee removed with forceps and post-hybridization

washing at 45°C occurred in coplin jars as follows, twice in 2 X SSC for 5 min, twice

in 50% formamide (2x SSC, pH 7.0) for 5 min and twice in 0.1XSSC for 5min

followed by a 30 minute incubation in block buffer (3% Bovine serum albumin (BSA)

(Sigma No: B 4287)/ 4 X SSC) at 37°C. The signal was detected using anti-

digoxigenin rhodamine (1:300) (Roche Diagnostics No:1207750) at 37°C for 30 min

followed by 3 washes in 4xSSC/ 0.03% Tween 20 (Sigma P1379) at 45°C for 5 min

each. The nuclei were counterstained with 4, 6-diamidino-2-phenylindole (DAPI,

Sigma No: D9542) (0.1µg/ml in 4XSSC with 0.06% Tween 20) for 5 min at room

temperature and cover-slipped in anti-fade solution [0.2333g of 1, 4-diazabicyclo-

(2.2.2)-octane (DABCO, Sigma D 2522) in 800µl purified water, 200µl 1M Tris-HCL

(Sigma T 3252), 9ml glycerol (Sigma G 5516)]. The coverslips were sealed with nail

varnish and kept at –20°C in dark.

5.3.7 Hybridisation and detection for chromosome 21

Chromosome 21 aneuploidy was investigated using a directly labelled commercially

bought fluorescent probe (Vysis-LSI 21 probe labelled with spectrum orange, No: 32-

190002). LSI 21 is approximately 200 kb and contains unique DNA sequences

complementary to the loci D21S259, D21S341, and D21S342 (21q22.13-q22.2). It


143

was intended to probe the slides simultaneously, but due to delays in acquiring a

suitably labelled chromosome 21 probe and specific filter blocks, slides were probed

independently for both chromosomes.

Hybridisation and detection of the probe was performed according to the

manufacturer’s instructions following a pre-treatment. Prior to in situ hybridization the

buccal slides were pre-treated with pepsin (Sigma) (300µg/ml in 0.01N HCL) for 10

mins whilst lymphoblastoid control slides were treated with (5µg/ml pepsin in 0.01N

HCL) at 37 °C for 10 min and then washed twice in phosphate-buffered saline (PBS,

pH7.0) for 5 min at room temperature. Afterwards, the slides were dehydrated in a

cold ethanol series (70%, 70%, 80%, 90%, and 100%, for 2 min each) and air dried.

Slides were denatured at 79°C for 5 min in pre-warmed 70% formamide/2XSSC and

then dehydrated through an ethanol series (70%, 70%, 80%, 90%, 100%, 2 min

each) at 4°C and then placed in a 37°C oven to reach hybridization temperature. 10µl

of probe mixture per slide (1µl LSi 21 probe, 2 µl distilled water, 6µl LSi/WCP

hybridisation buffer) was prepared and denatured in a 79°C water bath for 5mins. 5 µl

of the probe mixture was added to each buccal cytospin spot, cover slipped and

sealed with rubber cement before incubating at 37°C over night (~16hr) in a

humidified box.

Coverslips were removed with forceps before slides were washed in three coplin jars

of 50% formamide/2xSSC at 45°C for 10 mins. Slides were further washed in coplin

jars of 2xSSC and 2XSSC/0.1% Nonidet P40 (Roche No: 1754599) at 45°C for

10mins. The nuclei were counterstained with 4, 6-diamidino-2-phenylindole (DAPI)

(0.05µg/ml in 4XSSC with 0.06% Tween 20) for 1min 20 secs at room temperature


144

and cover-slipped in anti-fade solution the coverslips were sealed with nail varnish

and kept at –20°C in dark.

5.3.8 Scoring Method

A minimum of 1000 buccal cells or hippocampal brain tissue cells were scored for

the presence of one, two or three signals (Figures 2 and 3). Only nuclei with at least

one FISH signal were scored. In the cases of nuclei with more than one signal only

those nuclei in which the signals were of similar size and intensities, and were

separated by a distance of more than half the diameter of one FISH signal were

scored [301]. A Nikon E600 fluorescence microscope was used with a triple band

filter (for DAPI, FITC and Rhodamine) allowing simultaneous visualization of the

signals from both the fluorochrome and the nuclear counterstain.

5.4 Statistical Analyses

One way ANOVA analysis was used to determine the significance of difference

between groups for aneuploidy incidence, whereas pair wise comparison of

significance was determined using Tukey’s test. Gender ratios were tested using the

Chi square test. ANOVA analysis values and cross correlation analysis was

calculated using Graphpad PRISM (Graphpad inc., San Diego, CA). Significance was

accepted at P<0.05.


145

a) b) c)

d) e) f)

Figure 2 : FISH results showing non disjunction events in buccal cells. a) Chromosome 17 monosomy, b) Chromosome 17 disomy,

c) Chromosome 17 trisomy, d) Chromosome 21 monosomy, e) Chromosome 21 disomy, f) Chromosome 21 trisomy


146

a) b) c)

d) e)f)

Figure 3 : FISH results showing non disjunction events in hippocampal brain tissue. a) Chromosome 17 monosomy, b)

Chromosome 17 disomy, C) chromosome 17 trisomy, d) Chromosome 21 monosomy, e) Chromosome 21 disomy, f) Chromosome

21 trisomy.


147

5.5 Results

The results for the incidence of aneuploidy (monosomy and trisomy) for chromosome

17 and 21 in buccal cells for all groups are shown in Figures 4 and 5. The results

showing the incidence of aneuploidy (monosomy and trisomy) for chromosomes 17

and 21 in hippocampal brain tissue from Alzheimer’s and control groups are shown in

Figures 6 and 7. Percentages of aneuploid cells scored in both buccal cells and brain

tissue are outlined in Table 2.

5.5.1 Normal ageing-Aneuploidy in buccal cells Monosomy of chromosome 17 and 21 is increased by 222.2 % (P<0.001), and

91.4% (P<0.001) and trisomy of chromosome 17 and 21 is increased by 89.0%

(P<0.001) and 97.4% (P<0.001) respectively in the old controls relative to the young

controls. The total aneuploidy rate was 13.8% for chromosome 17 and 9.6% for

chromosome 21 in old controls compared to 5.0% and 5.0% respectively in young

controls.

5.5.2 Down’s syndrome-Aneuploidy in buccal cells Monosomy and trisomy of chromosome 17 is increased by 292.7 % (P<0.001) and

79.7% (P<0.001) respectively in DS relative to young controls and were at a level

similar to that observed in old controls. Total aneuploidy rate for chromosome 17 in

DS was 16.0% compared to 5.0% in young controls and 13.8% in old controls.

Results for chromosome 21 aneuploidy could not be meaningfully compared given

that DS is caused by trisomy of chromosome 21. The total aneuploidy rate for


148

chromosome 21 was 92.1% in DS compared to 5.0% in young controls and 9.6% in

old controls. Most DS individuals are cytogenetically determined as having full

trisomy 21. Incomplete hybridisation of the LSI 21 probe to buccal cells may be

responsible for a lower rate of trisomy 21 with cells appearing disomic and therefore

being scored as false negatives. However, It has been shown that DS individuals

tend to exhibit increased disomy 21 with ageing, resulting in various frequencies of

mosaicism for aneuploidy of chromosome 21, which may reflect our findings

[272,302].

5.5.3 Alzheimer’s disease-Aneuploidy in buccal cell s Both chromosome 17 monosomy and trisomy were increased in the younger AD

group by 19.4% (P<0.05) and 16.1% (P<0.001) respectively relative to the old control

group, but there were no differences between the younger and older AD groups. The

total chromosome 17 aneuploidy rate in younger and older AD groups was 15.7%

and 16.4% compared to 13.8% in the old control group. Chromosome 21 trisomy was

increased by 183.3% (P<0.001) in the AD groups relative to the old controls, but

there was no difference in chromosome 21 monosomy. MMSE scores were not

significantly correlated with chromosome 17 or chromosome 21 aneuploidy.

5.5.4 Alzheimer’s disease- Aneuploidy in Brain hipp ocampus Chromosome 17 or chromosome 21 aneuploidy did not differ significantly in

hippocampus tissue of Alzheimer’s cases and controls. Chromosome 17 and 21

aneuploidy rate in hippocampus was 18-18.2% and 11.8-12.8% compared to 13.8-


149

16.4% and 9.6-11.6% in buccal cells of old controls and AD patients respectively,

suggesting a slightly higher aneuploidy rate in brain tissue relative to buccal mucosa.

youn

g co

ntro

ls

Down'

s sy

ndro

me

old

contro

ls

youn

ger A

D

olde r A

D

0102030405060708090

100110120130

P<0.0001

Chromosome 17 monosomy

a

b

cd

bbd

a)

Freq

uenc

y in

100

0 bu

ccal

cel

ls

youn

g cont

rols

Down's

synd

rom

e

old c

ontro

ls

youn

ger

AD

older

AD

05

101520253035404550556065

P<0.0001


aa

bb b

b)

Fre

quen

cy in

100

0 bu

ccal

cel

ls

Figure 4 : Frequency of a) Chromosome 17 monosomy and b) Chromosome 21

monosomy following FISH in 1000 buccal cells of young controls (N=30), Down’s

syndrome (N=21), old controls (N=26), younger AD (N=23) and older AD (N=31).

Groups sharing the same letters are not significant. Error bars indicate SE of the

mean.


150

Chromosome 17 trisomy

you ng C

ont rols

Down 's s ynd rom

e

old cont rols

young er A

D

old er AD

0

10

20

30

40

50

P<0.0001

a

bb

c c

a)

Chr

omos

ome

17 t

riso

my

freq

uenc

y (%

)

young Contro

ls

Down's synd ro

me

old contro

ls

younger A

D

o lder AD

0102030405060

P<0.0001

a

b

c

d d800900

b)


Chr

omos

ome

21 t

riso

my

freq

uenc

y

Figure 5: Frequency of a) Chromosome 17 trisomy and b) Chromosome 21 trisomy

following FISH in 1000 buccal cells of young controls (N=30), Down’s syndrome

(N=21), old controls (N=26), younger AD (N=23) and older AD (N=31). Groups

sharing the same letters are not significant. Error bars indicate SE of the mean.


151

Alzheimer's Controls0

25

50

75

100

125

150

175a a

P=0.8392


a)

Fre

quen

cy in

100

0 br

ain

cells



102030405060708090

100110

P=0.1781

aa

b)

Fre

quen

cy in

100

0 br

ain

cells

Figure 6 : Frequency of a) Chromosome 17 monosomy and b) Chromosome 21

monosomy from 1000 hippocampal brain tissue cells of Alzheimer’s patients (N=13)

and control hippocampal brain tissue (N=9). Groups sharing the same letters are not

significant. Error bars indicate SE of the mean.


152


10

20

30

40

P=0.7343


a a

a)

Frq

uenc

y in

100

0 br

ain

cells



1015202530354045

P=0.753

a a

b)

Frqu

ency

in 1

000

brai

n ce

lls

Figure 7 : Frequency of a) Chromosome 17 trisomy and b) Chromosome 21 trisomy

from 1000 hippocampal brain tissue cells of Alzheimer’s patients (N=13) and control

hippocampal brain tissue (N=9). Groups sharing the same letters are not significant.

Error bars indicate SE of the mean (N=9).


153

Table 2: Percentages of monosomy and trisomic cells for chromosome 17 and 21 in buccal cells of young controls (N=30), Down’s syndrome (N=21), old controls (N=26), younger AD (N=23) and older AD (N=31) and hippocampal brain tissue cells of Alzheimer’s patients (N=13) and control hippocampal brain tissue (N=9). Young

controls

Down’s

syndrome

Old Controls Younger AD Older AD Alzheimer’s Brain Tissue

Control Brain Tissue

Chromosome 17

Monosomy 3.1 12.4 10.1 12.1 11.3 14.6 14.3 Trisomy 1.9 3.6 3.7 4.3 4.4 3.6 3.7 Total aneuploidy

5.0 16.0 13.8 16.4 15.7 18.2 18.0

Chromosome 21

Monosomy 3.1 2.9 5.9 5.5 5.8 8.9 7.9 Trisomy 1.9 89.2 3.7 5.4 5.8 3.9 3.9 Total Aneuploidy

5.0 92.1 9.6 10.9 11.6 12.8 11.8


154

5.6 Discussion

The aim of the study was to test the hypotheses that aneuploidy of chromosomes 17

and 21 in buccal cells a) is a risk factor for neurodegenerative diseases such as AD

and DS and b) increases with ageing.

A significant 1.2 fold increase in aneuploidy for chromosome 17 and a 1.5 fold

increase in aneuploidy 21 was found within the buccal mucosa of AD patients

compared to age and gender matched controls. A 1.8 fold increase in the incidence

of chromosome 17 in DS buccal cells was found compared to the young control

group (P<0.001). The DS values were not significantly different from the old control,

even though the old control group is 50 yrs senior to the DS group. DS aneuploidy

rates are beyond those expected for normal ageing confirming its status as a

premature ageing syndrome. Although a significant increase in aneuploidy rate for

chromosome 17 (P<0.001) and chromosome 21 (P<0.001) occurred in buccal cells

with normal ageing, the data showed that the incidence of chromosome

malsegregation in both the AD and DS groups was significantly increased and

beyond the levels expected for healthy subjects in corresponding age groups. Given

the strong association of trisomy 21 with premature ageing in DS, it is plausible that

elevated trisomy 21 observed in AD may contribute to accelerated ageing in this

condition.

Increased aneuploidy for chromosome 17 and 21, which could lead to altered gene

dosage and expression for tau and App, may be an important contributing factor

leading to the early stages of the development of AD, if critical regions of the brain


155

are enriched in aneuploid cells during early development due to mosaicism. The APP

gene present on chromosome 21 may be over expressed in the small population of

cells that are trisomic and could result in aberrant proteolysis and the accumulation of

the 42 beta amyloid peptide (Aβ42) which is the core component of the senile

plaques found in the brains of both DS and AD patients [52,56,102,246]. This

amyloidogenic pathway has traditionally held the view that the neurotoxic effects of

these peptides contribute to the etiology of the disease. Recently this view has been

challenged suggesting that APP itself may play an important neuronal role leading to

cognitive impairment [252,303,304]. The precise role of these peptides and proteins

and their interaction and potential relationship to the development of AD will need to

be conclusively determined through future studies. App processing is also altered in

terms of the ratio of (Aβ42) compared to the normal 40 amino acid β amyloid peptide

(Aβ40), resulting in an increase of the more neurotoxic and amyloidogenic Aβ42.

Similarly, an individual who is mosaic for trisomy 17 cells could potentially over-

express the microtubule associated protein tau which may lead to an increased

aggregation of the protein; this could in turn result in increased paired helical

filaments known to make up the neurofibrillary tangles. Abnormal accumulation or

deficiency of tau could lead to a breakdown of the microtubule system, causing

chromosomal malsegregation as a result of microtubule disruption. Similarly a

breakdown in the neuronal transport system due to microtubule dysfunction may

result in an apparent micronutrient deficiency affecting certain susceptible areas of

the brain known to be affected in AD.

It is plausible that trisomy 21 mosaicism in brain tissue, particularly within the

hippocampus, may have originated from chromosome malsegregation events early in


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fetal development and may be a possible explanation for some sporadic forms of AD

[99,100]. Low level In utero mosaicism may be the result of non-disjunction caused

by folate deficiency, which has been shown to increase the rate of chromosome 17

and 21 aneuploidy in lymphocytes [103]. Recent studies have shown an increased

predisposition to chromosome malsegregation in the young mothers of Down’s

syndrome individuals (MDS) [305]. Schumpf et al showed a five fold increase in the

risk of AD within this cohort of young mothers and suggested that these individuals

are biologically prematurely aged increasing their susceptibility to aneuploidy events

[305]. Chromosome 21 aneuploidy could predispose these individuals to DS

pregnancies and potentially contribute to an increased risk for developing AD later in

life [305].

The risk of aneuploidy due to chromosome malsegregation is likely to be increased in

cerebral tissues undergoing post-maturation neurogenesis, such as the dentate

gyrus of the hippocampus involved in short term memory and learning and the glial

cells [306]. Both populations of cells have been shown to continue cell division in the

adult brain and so could be potential candidates to accumulate aneuploid cells

throughout an individual’s lifetime [287]. The data shows that mosaicism for

chromosome 17 and 21 occurred within the hippocampus of histopathologically

confirmed Alzheimer’s patients. However, the aneuploidy rate for these two

chromosomes was not significantly different from control hippocampal tissue. This

result suggests that elevated chromosome 17 and 21 aneuploidy is unlikely to be a

causative factor of AD on its own, unless higher rates of aneuploidy of these

chromosomes were present much earlier in the life of AD cases and rates of mitosis

in neural tissue was reduced relative to controls. An alternative possibility is that


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abnormal expression of tau and App occurs to a greater extent in chromosome 17

and 21 aneuploid cells in AD relative to controls. Studies investigating the

relationship between tau and App expression and chromosome 17 and 21

aneuploidy are needed to address this question.

Polymorphisms of Presenilins and APOE genes that are known risk factors for both

AD and DS are likely to play a pivotal role in chromosome malsegregation. Mutated

Presenilin genes that contribute to early onset familial AD, have been shown to

produce proteins localised within the nuclear membrane, centrosomes and

kinetochores indicating a role in chromosome segregation and organisation [106]. An

association has also been shown between polymorphisms within intron 8 of the

Presenilin 1 gene and errors within maternal meiosis II that led to trisomy 21 [307].

This same polymorphism has also been identified as conferring an increased risk for

late onset AD [78,99,308]. It has been shown that certain alleles of APOE influence

the age of onset of dementia in both AD and DS. The APOE4 allele has been shown

to influence the development of sporadic AD and DS. DS individuals with two copies

of this allele develop more severe forms of AD neuropathology compared to DS

individuals lacking the e4 allele [98,309,310]. The APOE4 allele has also been shown

to be significantly more common among young mothers of Down’s syndrome

children, suggesting that this allele may predispose these individuals to chromosome

21 non-disjunction and a potential influential role for this allele on chromosome

malsegregation [311].

Micronutrient deficiency may also have an influence upon chromosome

malsegregation in both AD and DS. It has been shown that AD patients tend to be


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deficient in vitamins such as folate and B12 [138,154]. Folate and B12 play an

important role in DNA metabolism and the maintenance of methylation patterns that

could modify gene expression [140,141]. There is evidence to show that abnormal

folate metabolism, possibly as a result of polymorphisms within genes of the

folate/methionine pathway, may result in a state of DNA hypomethylation in the

centromeric regions of chromosomes leading to abnormal chromosome segregation

[159,312,313]. In addition folate deficiency has been show to increase aneuploidy of

chromosome 17 and 21 [103].

In conclusion the results of this study show that a) aneuploidy of chromosomes 17

and 21 increases with ageing in buccal cells, b) AD patients exhibit an abnormally

high rate of chromosome 17 and 21 aneuploidy in buccal cells compared to controls;

c) DS is associated with increased aneuploidy of chromosome 17 in buccal cells and

d) despite these differences in buccal cell’s, aneuploidy of chromosome 17 and 21 in

hippocampus tissue did not differ between AD cases and controls. These results

suggest that aneuploidy of chromosome 17 and 21 may be caused by genetic factors

that predispose to AD but are unlikely to be a primary cause of brain pathology in AD.

Chapter 6: Folate metabolism and Alzheimer’s diseas e

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6 Chapter 6: Folate metabolism and Alzheimer’s diseas e


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6.1 Abstract The primary aim of this study was to confirm earlier observations that AD individuals

have altered plasma folate, B12 and Hcy levels compared to age matched controls

who have not been clinically diagnosed with AD. Secondly, genotyping studies were

undertaken to determine whether polymorphisms within the genes of the folate

methionine pathway contributed to AD pathogenesis. Lastly, any correlation between

folate, B12 and Hcy status with previously determined buccal micronucleus cytome

assay biomarkers for DNA damage, cell proliferation and cell death markers was

investigated.

6.2 Introduction Folate (vitamin B9) is an essential B vitamin that is crucial to the prevention of

genomic instability and hypomethylation of DNA [314,315]. Folate is required for the

synthesis of deoxythymidine monophosphate (dTMP) from deoxyuridine

monophosphate (dUMP) which is essential for DNA synthesis and repair (Figure 1).

Under conditions of folate deficiency dUMP accumulates resulting in excessive uracil

corporation into DNA leading to single and double strand DNA breaks, chromosome

breakage and ultimately micronucleus formation [142,316,317]. Folate and vitamin

B12 are required in the synthesis of methionine through the remethylation of

homocysteine (Hcy) and in the synthesis of S-adenosylmethionine (SAM). SAM plays

an important role as a methyl donor required for the maintenance of genomic

methylation patterns that determine gene expression, DNA conformation and is

required for the synthesis of myelin, neurotransmitters and membrane phospholipids

[143,318]. Folate deficiency reduces SAM levels resulting in lower DNA cytosine

methylation and elevated levels of Hcy. Additionally, folate deficiency may lead to


161

demethylation of centromeric DNA repeat sequences and centromere dysfunction

leading to abnormal chromosome distribution during nuclear division, resulting in

elevated rates of aneuploidy and altered gene dosage. Folate deficiency has been

shown to increase trisomy for chromosome 17 and 21 leading to the possible over

expression of Alzheimer’s disease (AD) related genes, Tau, MPO and APP

[103,319].

AD is a chronic progressive neurological disorder accounting for more than 50% of all

clinically diagnosed dementia cases. Studies have shown that AD is associated with

lower levels of folate and B12 and elevated levels of plasma Hcy compared to age-

matched non-Alzheimer’s controls [138,139,154]. Hyperhomocysteinemia has been

shown to be a strong independent risk factor for AD [146,320]. Hcy not only promotes

excitotoxicity giving rise to neuronal DNA damage and apoptosis, but enhances β

amyloid production through its interaction with presenilins resulting in the induction of

stress proteins such as Herp [149,321,322]. These findings suggest that Hcy-induced

neuronal damage occurring in areas of the brain, such as the hippocampus which is

involved in short term memory and learning, may result in the cognitive impairment

that is characteristic of AD patients. However, the actual concentration of

homocysteine within the hippocampus of AD patients has yet to be determined.

It is possible that polymorphisms within the folate metabolic pathway may alter the

efficiency of folate metabolism as a result of reduced enzyme activity leading to the

elevated Hcy levels observed in AD patients. Methylenetetrahydrofolate reductase

(MTHFR) converts 5, 10 methylene tetrahydrofolate to 5, methyltetrahydrofolate

which provides a methyl group used in the conversion of Hcy to methionine. A


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common C to T polymorphism at position 677 of MTHFR, results in reduced enzyme

activity of the heterozygote CT by 35% and by 70% in the TT homozygote compared

to the CC genotype, possibly leading to elevated Hcy levels [159]. A second

polymorphism in the MTHFR gene involves an A to C transition at position 1298 and

is thought to play a regulatory role in the activity of the MTHFR enzyme, which when

altered may lead to abnormal folate metabolism [161]. Methionine synthase (MTR)

catalyses the transfer of a methyl group from 5 methyltetrafolate to Hcy utilising

vitamin B12 as a cofactor to produce methionine. Deficiency in vitamin B12 or

reduced MTR enzyme activity as a result of common polymorphisms such as the A to

G transition at the 2756 position in MTR may result in elevated levels of Hcy [164].

Methionine synthase reductase (MTRR) is responsible for maintaining adequate

levels of reduced methyl cob(I)alamin the activated cofactor for methionine synthase.

A common polymorphism involving an A to G transition at position 66 has been

shown to have an association with circulating Hcy concentrations in the blood, with

AA homozygotes having elevated Hcy levels compared to AG heterozygotes and GG

homozygotes [323].

The primary aim of this study was to confirm earlier observations that AD individuals

have altered plasma folate, B12 and Hcy levels compared to age matched controls.

Genotyping studies were undertaken to determine whether polymorphisms within the

genes of the folate methionine pathway are associated with AD pathogenesis. Lastly,

correlations between folate, B12 and Hcy status with previously determined buccal

micronucleus assay cytome biomarkers for DNA damage, cell proliferation and cell

death markers were investigated, to determine the possibility that the buccal cytome

may be influenced by B vitamin status


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DNA synthesis

and repair

B6

MTHFR

Cystathione

Homocysteine

B6

MTRR

5-Methyl THF

dTMP

B12

B12

B12

Folic Acid

SAM

Dietary Folate

CH

DNAmethylation

3

Cob (I)

Cob (II)

Cob (III)

Gene expression

Cell proliferation and protein synthesis

THF

5,10-MethylTHF

DHF

5,10-Methylene THF

dUMP

MTR

Methionine

Figure 1 . A simplified scheme of one carbon metabolism showing the effects of key

enzymes and co factors on DNA methylation, synthesis and repair. DHF,

Dihydrofolate; THF, Tetrahydrofolate; MTHFR, Methylenetetrahydrofolate; MTR,

Methionine Synthase; MTRR, Methionine Synthase Reductase; B12,

Cyanocobalamin (in various oxidative forms). SAM, S-Adenosylmethionine; dUMP,

deoxyuridine monophosphate; dTMP, deoxythymidine monophosphate.

6.3 Methods

6.3.1 Recruitment and characteristics of participan ts Approval for this study was obtained from CSIRO Human Nutrition, Adelaide

University, and Ramsey Health Care Human Experimentation Ethics Committees.

Participants in this study consisted of three distinct groups: 30 young controls (age

18-26yrs), 26 old controls (age 64-75yrs), and 54 clinically diagnosed Alzheimer’s

patients (age 58-93yrs). None of the participants recruited to the study were receiving


164

anti-folate therapy or cancer treatment. Age, gender and MMSE scores of the cohorts

are shown in Table 1. Gender ratio differences between the groups were not

significant (chi square P>0.05). Young and old controls were recruited through the

clinic of CSIRO Human Nutrition. Alzheimer’s patients were recruited at the College

Grove Private Hospital, Walkerville, Adelaide, South Australia following their initial

diagnosis and prior to commencement of therapy. Diagnosis of AD was made by two

experienced clinicians according to the criteria outlined by the National Institute of

Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and

related Disorders Association (NINCDS-AD&DA) [12]. These are well recognised

standards used in all clinical trials. Mini Mental State Examination scores (MMSE)

which are a recognised measure of cognitive impairment were only available for the

Alzheimer’s cohorts. Participants did not receive any remuneration for their

participation. Alzheimer’s patients were separated into two distinct groups. The

younger AD group was age-matched to the old control group, whilst the second older

AD group was classified as an older Alzheimer’s cohort. MMSE scores between the

two AD groups were not significantly different (P>0.05). The age of the old control

group compared to the younger AD group was not significantly different, but the

younger AD group had a significantly lower age relative to the older AD group

(P<0.0001). MMSE scores were not available for the control groups. The young and

old controls were “normal” functioning healthy individuals, who self volunteered,

consented to the study and did not report a family history of cognitive impairment.


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Table 1: Age, gender ratio and MMSE scores in study groups Young

Controls

Old Controls* Younger AD Older AD Alzheimer’s Brain Tissue Group


Blood Plasma N=30 N=26 N=23 N=31 NA NA Age (Mean±S.D)

22.47±2.177 68.7±2.6 70.7±4.1 83.13±4.5 NA NA

Age (Range) 18-26 66-75 58-75 78-93 NA NA Gender Ratio (Male/Female)

15/15 11/15 8/15 8/23 NA NA

MMSE (Mean±S.D)

NA NA 22.52±3.013 22.13±3.6.76 NA NA

MMSE (Range)

NA NA 15-27 12-29 NA NA

Genotyping N=30 N=84 N=23 N=31 N=13 N=9 Age (Mean±S.D)

22.47±2.177 65.47±7.516 70.7±4.1 83.13±4.5 75.75±7.8 74.10±10.95

Age (Range) 18-26 51-98 58-75 78-93 59-88 60-98

* Age and gender matched to younger AD group NA= Not available


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Blood was collected from consented young and old controls by trained nursing staff

at the CSIRO Human Nutrition clinic. Buccal cells were also collected from these

cohorts. Blood was collected from consented clinically diagnosed Alzheimer’s

patients prior to medical treatment by trained nursing staff at College Grove Private

Hospital, Walkerville, Adelaide. Buccal cells were also collected from these cohorts.

Buccal samples were more readily available from the AD cohorts as visits to the clinic

were infrequent and obtaining a fasted blood sample required a second visit within

the study time frame. This was not logistically practical as many individuals lived

outside of the city limits and relied on relatives/friends for transportation to the clinic.

Consequently, this resulted in more buccal cell samples being made available for

analysis compared to the lower numbers for blood samples.

A single fasted 8ml EDTA tube was collected by venapuncture from all consented

individuals, placed on ice and then transported to the laboratory at CSIRO Human

Nutrition. Blood samples were spun for 20 mins at 3000rpm (MSE Mistral 2000). 1ml

of plasma was separated for folate and vitamin B12 evaluation and 0.5ml of plasma

for Hcy determination. All samples were snap frozen in liquid nitrogen and then

stored at -80ºC until analysis could be performed. Prior to buccal cell collection the

mouth was rinsed thoroughly with water to remove any unwanted debris. Small

headed toothbrushes (Supply SA, code 85300012) were rotated 20 times in a circular

motion against the inside of the cheek, starting from a central point and gradually

increasing in circumference to produce an outward spiral effect. Both cheeks were

sampled using separate brushes. The heads of the brushes were individually placed


167

into separate 30ml yellow top containers (Sarstedt code 60.9922.918) containing

buccal cell (BC) buffer (0.01M Tris-HCL (Sigma T-3253), 0.1M EDTA tetra sodium

salt (Sigma E5391), 0.02M sodium chloride (Sigma S5886)) at pH 7.0 and then

transported to the laboratory at CSIRO Human Nutrition.




Flinders University. Control hippocampal brain tissue from histopathologically normal







6.3.3 Quantification of plasma folate

Plasma folate was quantified using the ARCHITECT® folate assay (Abbott

Laboratories, Abbott Park, IL, USA), a chemiluminescent microparticular folate

binding protein assay, on the ARCHITECT® i System. The ARCHITECT® folate assay

exhibits total imprecision of < 10% within the calibration range (0.0 – 20.0 ng/mL).

The analytical sensitivity of the assay is ≤ 0.8 ng/mL. Prior to quantification of the

plasma samples, a calibration curve was generated for the ARCHITECT® folate

assay. Subsequently, every 24 hours, a single sample of all control levels was tested


168

to ensure the control values were within the concentration range as specified by the

manufacturer. The assay was recalibrated when control samples were out of range

or when a new reagent kit with a new lot number was used.

To convert plasma folate to measurable folate a manual pre-treatment is performed.

Two pre-treatment steps mediate the release of folate from endogenous folate

binding protein. First, plasma and a pre-treatment reagent (dithiothreitol in acetic acid

buffer with EDTA) were aspirated and dispensed into a reaction vessel. Second, an

aliquot of the pre-treatment solution and potassium hydroxide were aspirated and

dispensed into a second reaction vessel. An aliquot of the second pre-treatment

solution was mixed with a TRIS buffer with protein stabilisers (human albumin)

containing monoclonal mouse anti-folate binding protein coupled to microparticles

affinity bound with bovine folate binding protein (FBP). Folate present in the plasma

binds to the FBP coated microparticles. After washing with phosphate buffered saline

(PBS) solution, pteroic acid–acridinium labelled conjugate (in MES buffer with

porcine protein stabiliser) was added, which binds to unoccupied sites on the FBP

coated microparticles. Pre-trigger (1.32% w/v hydrogen peroxide) and trigger (0.35 N

sodium hydroxide) solutions were then added, resulting in a chemiluminescent

reaction that can be measured in relative light units (RLUs). An inverse relationship

exists between the amount of folate in the plasma and the RLUs detected by the

ARCHITECT® i optical system. The concentration of folate in plasma was expressed

as nmol/L. Quantification of folate was performed by Division of Clinical Biochemistry,

Institute of Medical and Veterinary Science, Adelaide.


169

6.3.4 Quantification of Vitamin B12 in plasma

Vitamin B12 in plasma was quantified using the ARCHITECT® B12 assay (Abbott

Laboratories, Abbott Park, IL, USA), a chemiluminescent microparticular intrinsic

factor assay, on the ARCHITECT® i System. The ARCHITECT® B12 assay exhibits

total imprecision of < 10% within the calibration range (0.0 – 1476 pmol/L). The

analytical sensitivity of the assay is ≤ 44.27 pmol/L. Prior to quantification of plasma

samples, the ARCHITECT® vitamin B12 assay was calibrated using the test

calibrators supplied by the manufacturer and a calibration curve was generated. A

single sample of all control levels was tested every 24 hours to ensure the control

values were within the manufacturers specified concentration range. The assay was

recalibrated when control samples were out of range or when a new reagent kit with

a new lot number was used.

In a reaction vessel plasma was combined with three pre-treatment reagents,

containing either a) 1.0 N sodium hydroxide with 0.005% potassium cyanide, b) alpha

monothioglycerol and EDTA or c) cobinamide dicyanide in borate buffer with protein

stabilisers (avian). An aliquot of the pre-treatment solution and potassium hydroxide

(KOH) was aspirated and dispensed into a second reaction vessel. An aliquot of the

pre-treatment solution was mixed in a new reaction vessel with assay diluent (borate

buffer with EDTA) and intrinsic factor (porcine) coated microparticles (in borate buffer

with bovine protein stabilisers). Vitamin B12 present in the plasma binds to the

intrinsic factor coated microparticles. After washing with a PBS solution, B12–

acridinium labelled conjugate (in MES buffer) was added, which binds to unoccupied

sites on the intrinsic factor coated microparticles. Pre-trigger (1.32% w/v hydrogen

peroxide) and trigger (0.35 N sodium hydroxide) solutions were then added to the


170

reaction mixture, resulting in a chemiluminescent reaction that can be measured in

relative light units (RLUs). An inverse relationship exists between the amount of

Vitamin B12 in the plasma and the RLUs detected by the ARCHITECT® i optical

system. Vitamin B12 concentrations of the samples were determined from the

standard (calibration) curve by matching the absorbance readings with the

corresponding B12 concentrations. The concentration of vitamin B12 was expressed

as pmol/L. Quantification of Vitamin B12 in plasma was performed by the Division of

Clinical Biochemistry, Institute of Medical and Veterinary Science, Adelaide.

6.3.5 Quantification of plasma total L-homocysteine

L-homocysteine in plasma was quantified using the AxSYM® homocysteine (Hcy)

assay (Abbott, Wiedbaden, Germany), a fluorescence polarisation immunoassay

(FPIA), on the AxSYM ® system. The AxSYM® Hcy assay exhibits total imprecision of

< 6% within the calibration range (0.0 – 50 µmol/L). Prior to quantification of the Hcy

samples, the AxSYM® Hcy assay was calibrated using the test calibrators supplied by

the manufacturer and a calibration curve was generated. A single sample of all

control levels was tested every 24 hours to ensure the control values were within the

manufacturers specified concentration range. The assay was recalibrated when

control samples were out of range or when a new reagent kit with a new lot number

was used.

In the assay homocysteine, mixed disulfide, and protein-bound forms of Hcy are

reduced to form free Hcy by dithiothreitol (DTT). Free Hcy is converted to S-

adenosylHcy (SAH) by SAH hydrolase and excess adenosine. Under physiological


171

conditions, SAH hydrolase converts SAH to Hcy. Excess adenosine in the pre-

treatment solution drives the conversion of Hcy to SAH by SAH hydrolase.

Plasma was pre-treated in a reaction vessel with 0.1 M phosphate buffer, bovine

SAH hydrolase (in phosphate buffer with bovine protein stabilizers) and a pre-

treatment solution containing DTT and adenosine in citric acid. An aliquot of this

solution was mixed with monoclonal mouse anti-S-adenosyl-L-Hcy (in phosphate

buffer with bovine protein stabilisers) and 0.1 M phosphate buffer, and transferred to

the cuvette of the reaction vessel. A second aliquot of the pre-treated plasma solution

was mixed with S-adenosyl-L-cysteine fluorescence tracer (in phosphate buffer with

bovine protein stabiliser) and 0.1 M phosphate buffer, and transferred to the cuvette.

SAH and the labelled fluorescent tracer compete for the sites on the antibody

molecule. The intensity of the resulting polarised fluorescent light was measured by

the FPIA optical assembly. Total L-Hcy concentrations of the samples were

determined from the standard curve by matching the absorbance readings with the

corresponding total L-Hcy concentrations. The concentration of total L-Hcy was

expressed as µmol/L. Quantification of plasma Hcy was performed by the Division of

Clinical Biochemistry, Institute of Medical and Veterinary Science, Adelaide.

6.3.6 DNA isolation for genotyping

The isolation of DNA from buccal cells and brain tissue was performed under

conditions that minimise in vitro oxidation. These conditions are not essential for DNA

isolation for genotyping but were originally performed to investigate telomere length

as outlined in chapter 4. DNA was isolated using the silica-gel membrane based


172

DNeasy blood and tissue kit (Qiagen Cat no 69506), following the manufacturers

instructions. Prior to isolation all buffers were purged for five minutes in nitrogen and

supplemented with 50µM phenyl-tert-butyl nitrone (Sigma B7263) which acts as a

free radical trap and scavenger, the use of phenol and high temperatures (>56 oC)

were avoided.

All samples were quantified using a nanodrop ND-1000 spectrophotometer

(Nanodrop Technologies, Wilmington, U.S.A)

DNA from buccal cells was isolated as follows: Buccal cell pellets were resuspended in 0.5ml of BC buffer and 100µl used for the

DNA isolation. 100µl of the buccal pellet was added to a microtube containing 20µl of

proteinase K and adjusted to 220µl with phosphate buffered saline (PBS). 200µl of

nitrogen purged DNeasy (Qiagen) AL buffer was added and incubated at 37 oC

overnight. 200µl of ethanol was added and vortexed for 10 seconds. The mixture was

pipetted into another microtube housed in a collection tube and spun for 1 min at

8000rpm (Eppendorf, Centrifuge 5415R). The spin column was placed inside another


and spun for 1 minute at 8000 rpm. The spin column was placed inside another


and centrifuged for 3 minutes at 14, 0000 rpm to dry the DNeasy membrane. DNA

was eluted by placing the spin column in a 2ml collection tube and adding 200µl of

nitrogen purged DNeasy (Qiagen) AE buffer and spun at 8000 rpm for 1 minute.


173

Isolation of DNA from brain tissue We used a modified version of the above protocol to isolate DNA from brain tissue.

25 mg of brain tissue was cut into small pieces and placed into a microcentrifuge

containing 180µl of nitrogen purged DNeasy (Qiagen) ATL buffer. After the addition

of proteinase K the samples were incubated at 37 oC for 4hr until completely lysed.

DNA elution occurred as above.

6.3.7 Genotyping

Additional genotype data from age and gender matched healthy controls were used

from historical data bases of our previous studies [324], to increase the number of

older healthy controls (N=84) to achieve comparable numbers when comparing

genotypes with the Alzheimer’s cohort. All additional individuals were recruited

through CSIRO clinic of Human Nutrition after CSIRO ethics committee approval.

Isolated DNA from all cohorts was genotyped for MTHFR C677T, MTHFR A1298C,

MTR A2756G and MTRR A66G polymorphisms using the Applied Biosystems

7900HT Real Time PCR system, and ABI 7300 Sequence detection system with the

SDS Version 1.9 software (Applied Biosystems, Foster City, CA). Each reaction was

performed in duplicate. Control samples for homozygotes and heterozygotes for each

polymorphism were also included to act as internal controls for each reaction. These

genotypes had previously been determined using the PCR Restriction Fragment

Length Polymorphism method.


174

The allelic discrimination assay used in determining genotype is a multiplexed; end

point assay that detects variants within a single nucleic acid sequence. The presence

of two primer/probes that are specific for each allele within a single reaction allows

the detection of the two possible variants at the polymorphic site within the target

template sequence. The primers/probes can be distinguished, as they are labelled

with different fluorescent reporter dyes such as FAM and VIC. During strand

replacement a fully hybridised probe remains bound, resulting in probe cleavage and

release of the reporter dye. A mismatch between primer/probe and the target

sequence reduces probe hybridisation and subsequent cleavage. Increases in the

fluorescence of reporter molecule fluorescence containing FAM or VIC indicate

specific allele homozygosity, or an increase in both signals indicates allele

heterozygosity. (Figure 2)

Figure 2 : Allelic discrimination scatter plot for allele X (G) versus allele Y (A) for

methionine synthase reductase A66G polymorphism


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6.3.8 Allelic discrimination primers for genotype d etection

Primers for MTHFR C677T and MTR A2756G were obtained from Applied

Biosystems as assays on demand (Catalogue numbers: C-1202883-20 and C-

12005959-10 respectively). The primer and reporter sequences for MTHFR A1298C

(Catalogue number: C-850486-20) and MTRR A66G (Catalogue number: C-

3068176-10) which were ordered as assays by design are outlined below.

MTHFR A1298C

Forward primer: 5’-GGAGGAGCTGCTGAAGATGTG-3’

Reverse primer: 5’-CCCGAGAGGTAAAGAACAAAGACTT-3’

Reporter 1: 5’-CCAGTGAAGCAAGTGT-3’ VIC

Reporter 2: 5’-CCAGTGAAGAAAGTGT-3’ FAM (Common Allele A)

MTRR A66G

Forward primer: 5’-AGCAGGGACAGGCAAAGG-3’

Reverse primer: 5’-CCCGAGAGGTAAAGAACAAAGACTT-3’

Reporter 1: 5’-ATCGCAGAAGAAATGTGTGA -3’ VIC

Reporter 2: 5’-TCGCAGAAGAAATATGTGA -3’ FAM (Common Allele A)

6.3.9 PCR conditions and reagents

The PCR master mix for each 20 µl reaction consisted of 10.0 µl Taqman® 2x

Universal PCR Master mix without Amperase® UNG (Applied Biosystems, Foster city,

CA, catalogue number: 4324018), 1.0 µl of each primer contained in 20x assay on

demandTM SNP genotyping assay mix , 6 µl of distilled water and 20ng of genomic

DNA.


176

The thermal cycling conditions for MTHFR C677T and MTR A2756G comprised of 10

mins at 95oC as an initial denaturation followed by 50 cycles at 92oC for 15 seconds

and 60oC for 60 seconds to complete annealing. The thermal cycling conditions for

MTHFR A1298C and MTRR A66G consisted of 10 mins at 95oC followed by 50

cycles at 96oC for 15 seconds and 60oC for 90 seconds to complete annealing.

6.4 Statistics

One way ANOVA analysis was used to determine the significance of difference

between groups for plasma micronutrient and protein levels, whereas pair wise

comparison of significance was determined using Tukey’s test. Gender ratios were

tested using the Chi square test. ANOVA analysis values and cross correlation

analysis was calculated using Graphpad PRISM (Graphpad inc., San Diego, CA).

Significance was accepted at P<0.05. The Chi square test was used to determine

differences in allelic and genotype frequencies between the old control and

Alzheimer’s cohorts for all polymorphisms investigated. The Hardy –Weinberg

equilibrium equation was performed on all genotyping data. Chi square and odds

ratios were calculated using Graphpad PRISM (Graphpad inc., San Diego, CA).

6.5 Results

6.5.1 Folate, B12 and homocysteine

The results for plasma folate, vitamin B12 and Hcy for all cohorts are summarised

and illustrated in Figures 3-5.


177

A significantly lower plasma folate was found in the young cohort compared to both

old controls and the younger AD cohort (P=0.0008), but not with the older AD group.

No significant difference was found between the old controls and both AD groups.

The older AD group showed a slightly reduced plasma folate level compared to both

older controls and the younger AD group but this did not achieve significance (Figure

3). All values are within the normal range for plasma folate (6.9-39nmol/litre).

Concentration of plasma B12 levels did not show significant differences between any

of the four cohorts investigated (P=0.874) (Figure 4). All values are within the normal

range for plasma B12 (133-664 pmol/litre). It has been shown that micronucleus

formation is minimised when B12>300pmol/liter, all subjects achieved this

level.[142,325]

Concentrations of plasma homocysteine showed a significant increase in both AD

groups compared to both control groups (P=0.0003) (Figure 5). All values are within

the normal range for plasma Hcy (5-15µmol/litre). It has been shown that

micronucleus formation is minimised when Hcy<7.5µmol/liter, all subjects exceeded

this level. [142,325]


178

youn

g co

ntro

ls

old co

n trols

youn

ger A

D

older

AD

0

10

20

30

P=0.0008

Plasma folate levels

a

bb

ab

nmol

/litr

e

Figure 3: Plasma folate levels in nmol/litre for young controls (N=30), old controls

(N=26), younger AD (N=23) and older AD (N=31). Groups not showing the same

letter are significantly different from each other. Error bars denote SE of the mean.


179

youn

g con

t rols

old co

ntrols

youn

ger A

D

older A

D

050

100150200250300350400450

P=0.874

Plasma B12

a a

a a

pmol

/litr

e

Figure 4 : Plasma B12 levels in pmol/litre for young controls (N=30), old controls

(N=26), younger AD (N=23) and older AD (N=31). Groups not showing the same

letter are significantly different from each other. Error bars denote SE of the mean.


180

yo

u ng contr

ols

old co

ntrol

s

you nge

r AD

older

AD

0123456789

101112

P=0.0003

Plasma Homocysteine

a a

bb

µµ µµm

ol/li

tre

Figure 5 : Plasma total homocysteine levels in µmol/litre for young controls (N=30),

old controls (N=26), younger AD (N=23) and older AD (N=31). Groups not showing

the same letter are significantly different from each other. Error bars denote SE of the

mean.


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6.5.2 Polymorphisms Genotype frequencies for the four polymorphisms examined were calculated and

found to fit the Hardy-Weinberg equilibrium. The genotype frequencies of MTHFR,

MTR and MTRR in the Alzheimer’s cohorts did not differ significantly from the

genotype frequencies in the old control group (P>0.05) (Table 2).

There were no significant differences in the allelic frequencies between all the

cohorts for all of the polymorphisms examined (P>0.05) (Table 3).

Table 2: Folate metabolism polymorphism genotype frequencies for Alzheimer’s

* Value for chi square test of differences in genotype frequencies between old control and AD cohort.

Polymorphisms Young control (N=30)

Older control (N=84)

Alzheimer’s group (N=64)

Chi-Square P value*

MTHFR C677T CC 13 (0.433) 46 (0.547) 36 (0.562) CT 12 (0.400) 32 (0.380) 24 (0.375) p=0.970 TT 5 (0.166) 6 (0.380) 4 (0.062) MTHFR A1298C

AA 21(0.700) 37 (0.440) 25 (0.390) AC 6 (0.200) 37 (0.440) 32 (0.500) p=0.770 CC 3 (0.100) 10 (0.119) 7 (0.109) MTR A2576G AA 20 (0.666) 53 (0.638) 46 (0.718) AG 9 (0.300) 27 (0.325) 18 (0.281) p=0.306 GG 1 (0.033) 3 (0.036) 0 (0.000) MTRR A66G AA 7 (0.233) 7 (0.083) 14 (0.225) AG 16 (0.533) 57 (0.678) 31 (0.500) p=0.577 GG 7 (0.233) 20 (0.238) 17 (0.274)


182

Table 3 : Folate metabolism polymorphism allele frequencies for Alzheimer’s cohort and controls

Polymorphisms Young Controls (N=30)

Older controls (N=84)

Alzheimer’s cohort (N=64)

Chi square P value*

Odds ratio**

MTHFR C677T C 0.63 0.74 0.75 p=0.871 0.94 T 0.37 0.26 0.25 MTHFR A1298C A 0.80 0.66 0.64 p=0.766 1.09 C 0.20 0.34 0.36 MTR A2756G A 0.82 0.80 0.86 p=0.258 0.65 G 0.18 0.20 0.14 MTRR A66G A 0.50 0.42 0.48 p=0.390 0.78 G 0.50 0.58 0.52

* Value for chi square test of differences in allele frequencies between old control and AD cohort. ** Odds ratio for less common allele relative to common allele


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6.5.3 Correlations Cross correlation analysis between the biomarkers of the buccal cytome assay for

the young controls, old controls and for the combined Alzheimer’s cohorts and levels

of plasma folate, B12 and homocysteine are shown in Tables 4-6. Buccal cytome

analysis for these cohorts had previously been performed and is described in

Chapters 2 and 3.

In the young controls plasma folate, B12 and Hcy showed no significant correlation

with any of the buccal cytome parameters measured.

For the old controls plasma folate showed no significant correlation with any of the

buccal cytome parameters measured. Plasma B12 showed a positive correlation with

pyknosis (r=0.5365, P=0.0047), karyolysis (r=0.5447, P=0.0040) and condensed

chromatin (r=0.5238, P=0.0060). Plasma Hcy showed no significant correlation with

any of the buccal cytome parameters measured.

In the Alzheimer’s cohort plasma folate showed no positive correlation with any of the

buccal parameters measured. Plasma B12 showed a positive correlation with the

number of micronuclei scored in 1000 cells (r= 0.3552, P=0.0425) and with the

number of basal cells (r=0.3448, P=0.0494) scored in the assay. Plasma Hcy showed

a negative correlation with the number of karyorrhectic cells (r=-0.4107, P=0.0176)

scored in the assay.

No significant correlation was found between the MMSE scores and plasma folate,

B12 and Hcy.


184

Table 4 : Cross correlation results between biomarkers of the buccal micronucleus cytome assay and plasma micronutrients for young controls (N=30). Plasma Folate Plasma B12 Plasma

Homocysteine Number of buccal cells with MN

Pearson Correlation Sig. (2-tailed)

-0.0084 0.9646

-0.2732 0.1441

-0.0140 0.9411

Number of MN in 1000 cells


-0.0124 0.9480

-0.2197 0.2433

-0.2173 0.2487

Karyorrhexis


-0.2938 0.1151

-0.3063 0.0997

0.0873 0.6461

Pyknosis


-0.3474 0.0599

0.1005 0.5970

0.1154 0.5436

Binucleates


0.1180 0.5347

0.2521 0.1790

-0.2474 0.1875

Karyolysis


0.0798 0.6750

0.2235 0.2351

-0.0686 0.7185

Nuclear buds


-0.1133 0.5513

-0.2732 0.1441

0.1339 0.4807

Condensed chromatin


-0.0414 0.8277

-0.0923 0.6273

-0.0281 0.8824

Basal cells


0.0926 0.6264

-0.3572 0.0526

-0.0015 0.9936


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Table 5 : Cross correlation results between biomarkers of the buccal micronucleus cytome assay and plasma micronutrients for old controls (N=30). Plasma Folate Plasma B12 Plasma



-0.0234 0.9095

-0.0880 0.6688

-0.1665 0.4163



-0.1828 0.3714

-0.1041 0.6128

0.0183 0.9292

Karyorrhexis


0.1414 0.4907

0.0948 0.6449

-0.3020 0.1337

Pyknosis


-0.0330 0.8727

0.5365 0.0047**

-0.2053 0.3144

Binucleates


-0.0887 0.6663

0.0715 0.7284

-0.0958 0.6413

Karyolysis


0.2308 0.2566

0.5447 0.0040**

-0.0422 0.8376

Nuclear buds


-0.2463 0.2251

0.1320 0.5202

-0.2221 0.2754

Condensed chromatin


0.1212 0.5554

0.5238 0.0060**

-0.2808 0.1646

Basal cells


-0.0390 0.8500

-0.0113 0.9559

0.1106 0.5906

** Correlation is significant at the 0.01 level (2-tailed).


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Table 6 : Cross correlation results between biomarkers of the buccal micronucleus cytome assay and plasma micronutrients for Alzheimer’s cohort (N=54). Plasma Folate Plasma B12 Plasma



-0.0975 0.5893

0.2120 0.2363

-0.1189 0.5098



-0.2361 0.1860

0.3552 0.0425*

-0.0963 0.5938

Karyorrhexis


0.0810 0.6537

0.2808 0.1134

-0.4107 0.0176*

Pyknosis


0.0171 0.9244

0.0918 0.6112

-0.2431 0.1728

Binucleates


0.1507 0.4025

-0.1013 0.5749

0.1382 0.4433

Karyolysis


-0.1847 0.3036

-0.0181 0.9203

0.0419 0.8165

Nuclear buds


0.2468 0.1733

0.1977 0.2781

-0.3142 0.0799

Condensed chromatin


0.0553 0.7596

-0.1477 0.4122

0.1110 0.5385

Basal cells


-0.0201 0.9113

0.3448 0.0494*

-0.1473 0.4133

MMSE


0.2359 0.1862

0.0035 0.9844

-0.0664 0.7134

* Correlation is significant at the 0.05 level (2-tailed).


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6.6 Discussion One of the aims of the study was to investigate levels of plasma folate, vitamin B12

and homocysteine in Alzheimer’s patients compared to non-clinically diagnosed

control groups. It has been well documented that Alzheimer’s patients often have

reduced levels of folate, making them susceptible to genomic instability events [326-

328]. The results of the study showed only a slight non significant reduction in

plasma folate levels for the Alzheimer’ cohorts compared to the age-matched old

control group. However, it is possible that that although plasma levels appear to be

adequate, bioavailability of folate may still be impaired as many physiological and

biochemical processes are required to effectively deliver dietary folate from plasma

into the cells [329]. Furthermore, defects in uptake and storage of folate could result

in an apparent increase in plasma folate [330,331]. It is expected that red blood cell

folate should give a more accurate determination of folate status in this cohort and

should be considered for future studies.

Plasma levels for vitamin B12 in this study showed no significant differences between

any of the cohorts investigated. Vitamin B12 is an essential cofactor for methionine

synthase, but in order to be biologically effective it needs to be in a reduced state

[332]. AD has been shown to be associated with oxidative stress [134,137,333]. It is

possible that under such conditions oxidative stress could lead to deactivation of

cob(I)alamin by its subsequent oxidation to cob(II)alamin resulting in a functional B12

deficiency [332]. This in turn would lead to reduced methionine synthase activity

leading to Hcy accumulation following failure to be converted to methionine, and an

inability to convert 5-Methyltetrahydrofolate to tetrahydrofolate the form of folate that

is polyglutamated and stored [334,335]. Such changes in the oxidation state were not


188

determined in the analysis but would be of great interest in any future studies

undertaken given the evidence for increased oxidative stress in AD [44,127-129].

Alternatively, as with folate, the plasma B12 levels do not reflect the bioavailability of

B12 at the cellular level. Physiologically in order to deliver B12 from the gut to the

tissues at least five peptides are necessary, (R binder, intrinsic factor, ileal receptors,

transcobalamin I, transcobalamin II), and a further four enzymes are required to

obtain the reduced state for effective methionine synthase function (cbIF, cbIC/D,

cbIE/G and microsomal reductase [142]. It is possible that any changes in these

biological components may lead to functional B12 deficiency which would not be

reflected in plasma B12 analysis. Measurement of transcobalamin II and Methyl

malonyl CoA are considered to be better biomarkers of functional B12 status and

should be considered for future studies [336,337].

Plasma Hcy was found to be significantly increased in both the Alzheimer’s cohorts

compared to age matched controls confirming earlier studies with these findings

[145,338,339]. There is substantial evidence to show that total Hcy is an independent

vascular risk factor, and subjects with such risk factors and cerebrovascular disease

have an increased risk for developing AD [146,320]. It has been shown that

hyperhomocysteinemia sensitises nervous tissue to increased glutamate toxicity via

activation of N-methyl-D-aspartate receptors and damages neuronal DNA giving rise

to apoptosis. There is evidence that elevated levels of Hcy are also associated with

increased β amyloid peptide generation, impairment of DNA repair and sensitization

of neurons to amyloid toxicity [149,340]. It has been proposed that such findings

result in neuronal damage within the hippocampus leading to cognitive impairment

which is characteristic of AD.


189

A second aim of the study was to determine whether polymorphisms within the folate

methionine pathway contribute to AD pathogenesis. AD patients within this study

were found to have elevated levels of homocysteine compared to age-matched

controls. The remethylation of Hcy to methionine is regulated by the effective activity

of certain enzymes involved in folate metabolism. The genotypic and allelic

frequencies were determined for MTHFR C677T, MTHFR A1298C, MTR A2756G,

and MTRR A66G. Genotype frequencies for the four polymorphisms examined were

found to fit Hardy-Weinberg equilibrium and did not deviate substantially from

previously reported frequencies for these polymorphisms [161,164,341-343]. The

genotypic frequencies for the AD cohort did not differ significantly from those

reported for the older control groups, inferring that these particular polymorphisms do

not play a critical role in AD pathology in the cohorts studied. It is possible that these

polymorphisms may not be directly responsible for the observed elevated Hcy levels

but their enzymatic efficiency may be compromised by inadequate levels of cofactors

which are required for efficient enzyme activity. Changes in the oxidative state of B12

resulting from oxidative stress may result in inefficient MTR enzyme activity leading

to the observed elevation in Hcy in the Alzheimer’s cohorts. Only further studies

investigating the relationship between cofactor enzyme activity and polymorphism

status and its relation to AD folate metabolism may answer this question.

Alternatively Hcy can also be catabolised via the transulphuration pathway. This

pathway involves the condensation of Hcy with serine through the action of the B6

dependent cystathionine β synthase (CBS) to form cystathionine [152]. Cystathionine

is then metabolised to cysteine through the action of the B6 dependent cystathionine-


190

γ-lysase that can then be utilised for glutathione synthesis. It is possible that

polymorphisms within the CBS gene such as C699T, C1080T or the short tandem

repeat -5697, or deficiency in B6 as an effective cofactor could lead to reduced CBS

activity resulting in elevated levels of Hcy.

Finally, cross correlation analysis was performed between the biomarkers of the

buccal cytome assay and levels of folate, B12 and Hcy for the young, old and

combined AD cohorts. In the young controls no association was apparent between

buccal cytome parameters and any of the micronutrient levels investigated (Table 4).

The results from the old control cohort showed a positive correlation for vitamin B12

with the cell death parameters pyknosis (r=0.5365. P=0.0047), karyolysis (r=0.5447,

P=0.004) and condensed chromatin (r=0.5238, P=0.006), no significant correlation

was evident for either folate or Hcy (Table 5). This may suggest that B12 may in

some way facilitate the cell death process in normal buccal mucosa, and could

explain the association of B12 with lower MN frequency observed in previous studies

involving smokers [344]. However, no association with MN was observed in this

study.

In the AD cohort folate showed no significant correlation with any of the buccal

parameters measured. Plasma B12 showed a slight positive correlation with the

number of basal cells (r=0.3448, P=0.04) showing an association with the

proliferative index of these cells. Plasma B12 also showed a slight positive

correlation with the number of MN scored (r=0.3552, P=0.04) indicating an

association with chromosomal instability and proliferation rate in basal cells possibly

via association with reduced apoptosis (Table 6). Dose response experiments


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involving vitamin B12 are necessary in order to determine the relationship between

B12 and these cytome measures. Plasma Hcy showed a negative correlation with

the number of karyorrhectic cells (r=-0.4107, P=0.017) indicating a suppressive effect

on cell death under conditions of high Hcy. In the AD cohort plasma Hcy was

elevated and the number of karyorrhectic cells scored in the buccal cytome assay

was significantly reduced compared to age matched controls with a lower Hcy level.

These results suggest that a) the buccal cytome of AD subjects exhibits a different

relationship to B12 and Hcy compared to the relationship seen in normal controls,

and b) a low B12 and high Hcy status could be an underlying cause of the low basal

cell and low karyorrhectic cell frequency seen in AD relative to matched and healthy

controls.

Chapter 7: Ageing and polyphenols

192

7 Chapter 7: Ageing and polyphenols in a transgenic

mouse model for Alzheimer’s disease


193

7.1 Abstract The study set out to determine a) whether DNA damage is elevated with time in mice

that carry mutations that predispose to Alzheimer’s disease (AD) relative to non

transgenic control mice, and b) whether increasing the intake of dietary polyphenols

curcumin and grape seed extract could reduce genomic instability events in a

transgenic mouse model for AD. Micronuclei (MN) frequency was recorded in both

buccal mucosa and whole blood. After 9 months a non-significant 2 fold increase in

buccal MN frequency and a non-significant 1.3 fold increase in whole blood MN

frequency were found in the AD control group compared to the WT control group. A

significant 91% decrease (P=0.04) in absolute buccal telomere length and a non-

significant 2 fold decrease in absolute olfactory lobe telomere length was evident

between the AD control and WT control group. A significant 10 fold decrease in

buccal micronucleus (MN) frequency (P=0.01) was found for both curcumin and

microencapsulated grape seed extract (MGSE) and a 7 fold decrease (P=0.02) for

the grape seed extract (GSE) AD cohorts compared to the AD group on control diet.

Similarly, within whole blood a non-significant reduction in MN frequency was found

for the curcumin (49.5%), GSE (33.3%) and MGSE (62.5%) AD groups when

compared to the AD group on control diet. A non-significant 2 fold increase in buccal

cell telomere length was evident for the curcumin, GSE and MGSE groups compared

to the AD control group. Olfactory lobe telomere length was found to be non-

significantly 2 fold longer in mice fed on an enriched curcumin diet compared to

controls. These results suggest potential protective effects of polyphenols against

genomic instability events in different somatic tissues of a transgenic mouse model

for AD.


194

7.2 Introduction Alzheimer’s disease (AD) is associated with elevated rates of oxidative stress that

contribute to increased rates of genomic instability such as micronuclei,

chromosomal aberrations, telomere length and apoptosis [96,127-129,345]. The

characteristic hallmarks of AD involve the deposition of proteins leading to amyloid

plaques and neurofibrillary tangles in areas of the brain that are associated with

reduced cognitive function [10,62,346-348]. These proteins have also been linked

with oxidative stress [43,349]. It has been suggested that both plaques and tangles

are produced in order to protect sensitive areas of the brain from the effects of

oxidative related injury [349]. However, other studies have shown that plaques may

produce reactive oxygen species when they form complexes with metals such as

copper and iron [200,259]. Free radical generation is the result of normal metabolic

processes, whereby the levels are maintained within normal homeostatic boundaries

by an elaborate endogenous antioxidant system. However, when levels of free

radicals exceeds the normal clearing capacity of the cells oxidative stress follows

resulting in potential cellular damage [350]. It has recently been shown that

individuals with mild cognitive impairment (MCI) and more advanced AD have a 2

fold increase in DNA damage levels and oxidized bases in their leucocytes compared

with age matched controls not clinically diagnosed with AD [134]. This is suggestive

that oxidative stress occurs in the early stages of the disease, as MCI individuals

progress to AD with an estimated probability of 50% within 4 years [134,135],

suggesting MCI may be representative of early AD and that oxidative stress may

directly contribute to disease pathology. It has also been shown that within the post

mortem Alzheimer’s brain that there is an increase in mitochondrial and nuclear

oxidative damage [44].


195

Recently, a number of studies have suggested the positive effects of dietary

antioxidants as an aid in potentially reducing somatic cell and neuronal damage by

free radicals [43,175,176,184,351]. Curcumin is the yellow phenolic compound in the

Indian curry spice turmeric. This spice is used as a food preservative in India where

the incidence of AD in individuals aged between 70 and 79 years of age is 4.4 fold

less than that in the United States [352]. It has been shown to act as an antioxidant

through modulation of glutathione levels [353] and possesses anti- inflammatory

properties possibly mediated by inhibition of IL-8 release [353] as well as the ability to

reduce Aβ42 toxicity by preventing the formation of β42 oligomers leading to amyloid

plaque formation [178,351,354,355]. It has further been shown to block the

aggregation of the β fibrils that comprise the structure of the amyloid plaque

[180,354,356]. Curcumin may also contribute to reducing amyloid plaque formation

by acting as a chelator, binding metals such as copper and iron that have been

shown to form complexes with Aβ42 resulting in oxidative stress, free radical

formation that leads to oxidative neurotoxicity [181]. Curcumin has also been shown

to be a significantly more potent free radical scavenger than vitamin E and to protect

the brain from the effects of lipid peroxidation [357,358].

Grape Seed Extract (GSE) contains a number of polyphenols Including

proanthocyanidins and procyanidins [359-361]. They have been shown to be

powerful free radical scavengers, possess anti-inflammatory properties, reduce

apoptosis and prevent H202 induced chromosomal damage in human lymphoblastoid

cells [362-364]. It has been shown that their free radical scavenging capacity is 20

times more effective than vitamin E and 50 times more effective than vitamin C [185].


196

It has also been shown in rat models that cells are protected against β amyloid

toxicity when treated with GSE compared to unprotected neurons, possibly as a

result of the antioxidant or chelating properties [186,187].

The aims of this study were a) to investigate whether DNA damage events increase

with time to a greater extent in AD mice relative to controls and b) to determine the

potential protective effects of natural products rich in polyphenols on genomic

instability events in a transgenic mouse model for AD. We investigated the effects of

curcumin and GSE polyphenols on DNA damage by testing the mice over a 9 month

period utilizing a buccal micronucleus cytome assay, an erythrocyte micronucleus

assay and by determining telomere length in both buccal cells and olfactory lobe

tissue from the brain.

7.3 Materials and methods

7.3.1 Mouse model

The study involved the use of a double transgenic mouse model (Jackson

Laboratory, Maine, USA) that expresses a chimeric mouse/human amyloid precursor

protein (Mo/Hu APP695swe) and a mutant presenilin 1 (PSEN1-dE9) that are both

directed to CNS neurons (Figure 1). These mutations are both associated with early

onset AD. The “humanized” Mo/HuAPP695swe transgene allows the mice to secrete

a human A-beta amyloid peptide. The transgenic peptide and holoprotein can be

detected through immunohistochemistry using antibodies specific for the human

sequence within this region (monoclonal 6E10 antibody, Signet laboratories, Cat No:

Sig-39320). The included “swedish” mutations (K595N/M596L) elevate the amount of


197

A-beta peptide produced from the transgene by favoring processing through the

beta-secretase pathway. The Mo/HuAPP695swe protein and the transgenic mutant

human presenilin protein (PSEN1-dE9) are both immunodetected in whole brain

homogenates [365,366].

Figure 1 : B6C3-Tg (APPswePSEN1dE9)85Dbo/J transgenic mouse model for AD.

The strain was developed by using two expression plasmids (Mo/HuAPP696swe and

PSEN1-dE9) that were designed to each be controlled by independent mouse prion

promoter elements, directing transgene expression predominantly to CNS neurons.

The Mo/HuAPP695swe transgene expresses a “humanized” mouse amyloid

precursor gene modified at three amino acids to reflect the human residues, and

further modified to contain the K595N and M596L mutations that are linked to familial

AD [367]. The PSEN1-dE9 transgene expresses a mutant human presenilin 1

carrying the exon 9 deleted variant (PSEN1dE9) which is also associated with

familial AD. These constructs were co-injected into B6C3HF2 pronuclei and insertion

of the transgenes occurred at a single locus. Founder line 85 was obtained and the

resulting colony was maintained as a hemizygote by crossing transgenic mice to

B6C3F1/J mice [368,369].


198

These transgenic mice develop amyloid plaques in the hippocampus and cortex at

four months and in the thalamus at 6 months. At 9 months there is significant amyloid

present in the cortex, hippocampus and thalamus [369,370]. At 12 months the plaque

area accounts for 10.5±2.9% of the total cortex, 4.1±1.6% in the hippocampus and

2.3±1.3% in the thalamus [371]. The plaques consist of diffused β amyloid alone or

with the thioflavine S positive compact core. The amyloid plaques were of a compact

core nature surrounded with dilated dystrophic neurites and associated with

aggregated microglia and astrocytes.

7.3.2 Genotyping

All animals prior to receipt were genotyped at the Jackson laboratory for Tg(PSEN1)

and Tg(APPswe). The protocols used are outlined below.

7.3.2.1 Tg(PSEN1) protocol 20µl reactions used 5-20ng of DNA per reaction. The reaction components for the

amplification of the PSEN 1 transgene consisted of 10x PCR buffer, 25mM MgCl2,

2.5mM dNTP, 20µM o1MR 1644 (forward primer for PSEN 1, 5’-AAT AGA GAA CGG

CAG GAG CA-3’), 20µM o1MR 1645 (reverse primer for PSEN 1, 5’-GCC ATG AGG

GCA CTA ATC AT-3’) 5u/µl Taq polymerase and distilled water. The cycling

conditions consisted of 94oC for 3 mins and 35 cycles of 94oC for 30 seconds, 67oC

for 1 min and 72oC for 2 mins with a final annealing step of 72oC for 2 mins. The PCR

products were separated by gel electrophoresis on a 1.5% agarose gel at 67V for 30

mins. The reaction amplifies a 608 bp product from the PSEN 1Tg.


199

A second reaction involving the amplification of the PrP gene was performed to act

as an internal control. 20µl reactions used 5-20ng of DNA per reaction. The reaction

components for the amplification of the PrP transgene consisted of 10x PCR buffer,

25mM MgCl2, 2.5mM dNTP, 20µM o1MR 1588 (forward primer for PrP 5’-GTG GAT

AAC CCC TCC CCC AGC CTA GAC C-3’), 20µM o1MR 944 (reverse primer for PrP

5’-CCT CTT TGT GAC TAT GTG GAC TGA TGT CGG-3’), 5u/µl Taq polymerase

and distilled water. The cycling conditions consisted of 94oC for 3 mins and 35 cycles

of 94oC for 30 seconds, 70oC for 1 min and 72oC for 2 mins with a final annealing

step of 72oC for 2 mins. The PCR products were separated by gel electrophoresis on

a 1.5% agarose gel at 67V for 30 mins. The reaction amplifies a 750 bp product from

the PrP gene.

7.3.2.2 Tg(APPswe) protocol 20µl reactions used 5-20ng of DNA per reaction. The reaction components for the

amplification of the APPswe transgene consisted of 10x PCR buffer, 25mM MgCl2,

2.5mM dNTP, 20µM o1MR 1597 (forward primer for APPswe 5’-GAC TGA CCA CTC

GAC CAG GTT CTG-3’), 20µM o1MR 1598 (reverse primer for APPswe 5’-CTT GTA

AGT TGG ATT CTC ATA TCC G-3’), 5u/µl Taq polymerase and distilled water. The

cycling conditions consisted of 94oC for 3 mins and 35 cycles of 94oC for 30 seconds,

69oC for 1 min and 72oC for 2 mins with a final annealing step of 72oC for 2 mins.

The PCR products were separated by gel electrophoresis on a 1.5% agarose gel at

67V for 30 mins. The reaction amplifies a 350 bp product from the APPswe Tg.


200

7.4 Study design

Approval for this 9 month study was obtained from CSIRO Human Nutrition and

Flinders University Animal Ethics committees. The experimental design is a parallel

dietary intervention involving four different dietary treatments using the B6C3-

Tg(APPswePSEN1dE9)85Dbo/J mouse starting at an age of 3-4 months. The design

of the study is intended to determine whether grape seed extract is as effective as

curcumin in reducing the AD related genomic instability pathology observed in

Alzheimer’s patients and whether micro-encapsulation of GSE enhances the observed

effects. Normal mice with the same genetic background, but lacking defective APP and

PSEN1 genes were included as an added control to identify the point in time when

buccal and blood differences between normal and Alzheimer’s mice become evident,

and to test the hypothesis that the Alzheimer’s prone mice exhibited elevated DNA

damage. Double the numbers of normal mice relative to Alzheimer’s mice were used

because it was necessary to practice the buccal sampling procedure on half of these

mice. The mice used for buccal sampling practice were kept in the study on a normal

control diet and were otherwise treated in the same way as the other normal mice. The

mice used in the pilot buccal sampling were also used as additional controls. The

design is summarised below.


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* Control groups

** DNA damage biomarkers (Micronucleus and telomere length)

# Mice will be sacrificed at this point

Figure 2 : Shows dietary groups, schedule and sampling points.AIN-93G denotes

control diet.

The mice were randomly grouped with good balance in age, sex and breeding pairs

(Table 1). All animals were housed in the Flinders Medical Centre animal holding

facility, 2-3 per cage in standard cages ~600cm2 (150-200cm2 per animal) and were

genotyped prior to the commencement of the study following breeding from the

originally acquired transgenic model. All groups were kept in the same room on a

14/10hr light dark cycle and had free access to food and water ad libitum. Food

consumption and bodyweight data was collected by the staff at the animal facility at 3

and 9 months.

AIN-93G N=20 Normal*

AIN-93G N=10 AD Mice*

AIN-93G+ 500pp Curcumin N=10 AD Mice

AIN-93G+ 20,000pp GSE N=10 AD Mice

AIN-93G+ 20,000pp MGSE N=10 AD Mice

Buccal samples taken at 3 and 6 months dietary intervention. Blood samples taken at 3 months**

Brain, buccal and blood samples taken at 9 month dietary intervention**#


202

Table1 : Age and gender of study cohort mice

WT Control AD Control Curcumin GSE MGSE

N=20 N=10 N=10 N=10 N=10

AGE (days)

(Mean ±SD)

119.9±21.04 116.1±25.15 111.5±21.04 119.9±21.04 119 .9±21.04

Gender Ratio

(male: female)

10:10 6:4 5:5 5:5 6:4

There were no significant differences in gender ratio or age between cohorts

7.5 Diets

All diets were prepared by Specialty Feeds, Glen Forrest, Western Australia. The

control diet consisted of 95% standard AIN-93G rodent diet comprising of 39.7% corn

starch, 20% casein (vitamin free), 13.2% dextrin, 10% sucrose, 7% soybean oil, 5%

powdered cellulose, 3.5% AIN-93G mineral mix, 1% AIN-93G vitamin mix, 0.3% L-

cysteine, 0.25% Choline bitartrate, 0.001% t-Butylhydroquinone and 5% maize

starch. Diet 2 consisted of 95% AIN-93G, 4.93% maize starch and 0.07% Curcumin

(Sigma, Cat No: C1386, Australia). Diet 3 consisted of 95% AIN-93G, 3% maize

starch and 2% free grape seed extract. Diet 4 consisted of 95% AIN-93G and 5%

encapsulated grape seed extract. Enough diet was ordered for the duration of the

study and housed at the Flinders Medical Centre animal holding facility.


203

7.6 Animal welfare

Mice were observed daily and checked weekly for symptoms as outlined in the

attached clinical assessment form (Appendix 1). Daily monitoring occurred if a mouse

displayed 2 or more symptoms at Grade 1 level. Euthanasia was performed if a

mouse displayed 2 or more symptoms at Grade 2 level or above. An animal that

showed a sustained loss in body weight over consecutive weighings and demonstrated

signs of distress as indicated within the appendix were also killed.

7.7 Buccal cell collection

Buccal cells were collected from all animals at 3, 6 and 9 months. Prior to sample

collection the mouse was anaesthetized by placing 2mls of isoflurane (Veterinary

companies of Australia Pty Ltd, NSW, Australia) on a tissue inside a bell jar that the

mouse is free to move around in. After 1 min the mouse came to rest and was free to

be handled. The mice were held using a firm grip of the neck skin which keeps the

mouth of the mouse open and accessible to allow inner cheek scraping. The buccal

cells were collected by swabbing the inner cheeks with a thin cotton-tipped stick with

2mm diameter buds (aluminium shaft 0.9mm x 150mm, Applimed SA, Chatel St

Denis, Switzerland). Both cheeks were sampled and the head of the applicator

placed inside a 1.5ml eppendorf containing 1ml of buccal cell buffer (0.01M Tris-HCL


chloride (Sigma S5886)) and revolved to dislodge the cells. Once all samples were

collected they were harvested at the CSIRO Human Nutrition laboratories as

described below.


204

Cells were spun in a microfuge (Centrifuge 5415R, eppendorf) at 1800rpm for 10

mins. The supernatant was removed leaving approximately 150µl and replaced with I

ml of buccal cell buffer. The cells were spun and washed twice more to remove

DNAses and bacteria which may hamper scoring. Cells were not homogenised or

filtered so as not to lose cells unnecessarily. Buffer was removed leaving ~120µl. 6µl

of DMSO (5%) was added to the cell suspension, agitated and added to cytospin

cups and spun at 600rpm for 5 mins in a cytocentrifuge (Shandon cytospin 3). Slides

were then air dried for 10 mins and fixed in ethanol: acetic acid (3:1) for 10 mins prior

to staining. The nuclei were counterstained with Propidium Iodide (Sigma P-4170)

(0.05µg/ml in 4XSSC (Standard saline citrate, 0.15 M sodium chloride, Sigma

S9888/0.015 M sodium citrate, Sigma S4641)/with 0.06% Tween 20, Sigma P1379)

for 3 min at room temperature in the dark and cover-slipped in anti-fade solution and

kept at –20°C until analysis could be performed. Slides were scored using a Nikon

E600 microscope equipped with a triple band filter (Dapi, FITC and rhodamine) at

1000x magnification.

7.7.1 Scoring criteria for murine buccal micronucle us assay

The various distinct populations used in the murine buccal micronucleus cytome

assay were determined based on criteria outlined in the two previous human studies

(Chapter 2 and 3). These criteria are intended to classify buccal cells into categories

that distinguish between “normal” cells and cells that are considered “abnormal”,

based on nuclear morphology. These abnormal nuclear morphologies are thought to

be indicative of DNA damage or cell death. Images showing distinct cell populations

as scored in assay are shown in Figure 3.


205

Basal Cells (Figure 3a): These are the cells from the basal layer. The nuclear to cytoplasm ratio is larger than

that in typical normal differentiated buccal cells. Basal cells are smaller in size when

compared to differentiated buccal cells and may occasionally contain micronuclei.

Normal differentiated Cells (Figure 3b): These cells have a uniformly stained nucleus which is usually oval or round in shape

and a nuclear to cytoplasmic ratio smaller than that of basal cells. No other DNA

containing structures apart from the nucleus are observed in these cells.

Basal and differentiated cells with micronuclei (Figure 3c): These cells are characterized by the presence of both a main nucleus and one or





may have the morphology of normal cells or that of dying cells (ie karyolytic cells).

The micronuclei must be located within the cytoplasm of the cells. The presence of

micronuclei is indicative of chromosome loss or fragmentation occurring during

previous nuclear division. Micronuclei were scored only in basal and normal

differentiated cells. Those cells undergoing any forms of cell death (three

characterized stages of karyolysis) were not scored for micronuclei.


206

Karyolytic cells (Figure 3d-f): Early karyolysis (Figure 3d): These cells show the first signs of nuclear disintegration

and appear to resemble the early stages of apoptosis. It is unclear at this time

whether this group is representative of early apoptotic or necrotic pathways. This

would need to be determined in future studies using specific cell surface markers.

Mid karyolysis (Figure 3e): This group appears to still have the final stages of a

nuclear membrane but the staining in these cells is very faint.

Late karyolysis (Figure 3f): In these cells the nucleus is completely depleted of DNA

and apparent as a ghost-like image that has weak to negative fluorescent staining.

These cells may also appear to have no nucleus. Karyolitic cells may be in the late

stages of apoptosis.

7.7.2 Scoring method

1000 cells were scored per mouse for all the various cells types outlined in the buccal

cytome assay. These consisted of nucleated differentiated cells, basal cells, and the

three stages of karyolysis. Only basal and normal differentiated cells were scored for

micronuclei and their scores were combined to give the overall incidence.


207

3a) Basal cell 3b) Normal differentiated Cell

3c) Basal with MN 3C) Differentiated with MN

3d) Early karyolytic 3e) Mid karyolytic

3f) late karyolytic

Figure 3 : Types of cells scored in the buccal micronucleus cytome assay. Cells were

stained with propidium iodide. Images shown under represent cytoplasmic staining in

cells scored because cytoplasm is actually clearly visible when viewed through

microscope.


208

7.8 Blood collection for micronucleated erythrocyte assay

Blood was collected from the tail at 3 months and from the right atrium during post

mortem at 9 months. The cell preparation for this assay was the same at both time

points. 500ul of RPMI-1640 media was added to a multivette tube (Sarstedt ref No:

15.1673). As mouse blood coagulates more so than human an additional 20 units of

heparin was added to each tube. 10,000 lyophilized heparin (Sigma, cat no H3393-

10KU) was reconstituted with 1 ml of 0.9% saline and 2µl (20 units) added to each

multivette tube. The mouse was anaesthetized with isoflurane and the end of the tail

is removed (~1mm), 50µl of blood is acquired and added to the heparinised media.

The blood sample was then thoroughly mixed to prevent clotting. Within a biosafety

hazard cabinet 30µl was pipetted onto a clean slide and a blood film prepared by

running a coverslip along the length of the slide. The slide is air dried for 10 mins and

then fixed in methanol for 10 mins.

7.8.1 Acridine orange staining

A stock solution of Acridine orange (Sigma A-6014) was prepared in phosphate

buffer saline (120 mM sodium chloride, 2.7 mM pottasium chloride, 10 mM potassium

phosphate monobasic, 10 mM sodium phosphate dibasic, pH 7.4) at a concentration

of 10mg/ml. A 1:250 dilution was prepared in 4xSSC to give a final concentration of

40µg/ml (200µl of 10mg/ml Acridine orange in 50 mls of 4xSSC). Slides were stained

for 4 mins, rinsed briefly in 2xSSC and coverslipped prior to analysis using a

fluorescent microscope. Immature erythrocytes i.e. polychromatic erythrocytes (PCE)

were identified by their orange–red color, mature erythrocytes by their green-brown

color and micronuclei by their yellow color. The frequency of PCE’s in a total of 2000


209

erythrocytes was determined as well as the number of micronucleated PCE’s in 1000

PCE’s scored. Figure 4 outlines the different cell types scored in the assay.

a) Polychromatic erythrocyte with micronuclei

b) Polychromatic erythrocyte with micronuclei

c) Mature erythrocytes with micronuclei

d) Polychromatic erythrocyte (bright orange) and mature erythrocyte.

PCE

Micronuclei in Mature and immature erythrocytes

Figure 4 : a,b) Showing immature polychromatic erythrocytes with micronucleus, c)

mature erythrocyte with micronucleus, d) Polychromatic erythrocyte and mature

erythrocyte without micronuclei in same field if view. Cells were stained with acridine

orange.

7.9 DNA isolation for telomere length determination

The isolation of DNA from buccal cells and olfactory lobes of the mouse brain were

performed under conditions that minimise in vitro oxidation. We therefore used a

modified version of the protocol outlined by Lu et al [276]. DNA was isolated using

the silica-gel membrane based DNeasy tissue kit (Qiagen Cat no 69506), following

the manufacturer’s instructions. Prior to isolation all buffers were purged for five


210

minutes in nitrogen and supplemented with 50µM phenyl-tert-butyl nitrone (Sigma

B7263) which acts as a free radical trap and scavenger, the use of phenol and high

temperatures (>56oC) were avoided. Each of the tissues was isolated separately.

7.9.1 DNA isolation of buccal cells

100µl of suspended buccal cells was added to a microtube containing 20µl of

proteinase K and adjusted to 220µl with phosphate buffered saline (PBS). 200µl of

nitrogen purged manufacturer’s AL buffer was added and incubated at 37 oC

overnight. 200µl of ethanol was added and vortexed for 10 seconds. The mixture was

pipetted into another microtube housed in a collection tube and spun for 1 min at

8000rpm (Eppendorf, Centrifuge 5415R). The spin column was placed inside another

collection tube and 500µl nitrogen-purged manufacturer’s AW1 buffer was added and

spun for 1 minute at 8000 rpm. The spin column was placed inside another collection

tube and 500µl nitrogen purged manufacturer’s AW2 buffer was added and

centrifuged for 3 minutes at 14, 0000 rpm to dry the DNeasy membrane. DNA was

eluted by placing the spin column in a 2ml collection tube and adding 200µl of

nitrogen purged manufacturer’s AE buffer and spun at 8000rpm for 1 minute.

7.9.2 DNA isolation of Brain tissue

The above protocol was followed using the entire olfactory lobe sample (<4mg) which

was cut into small pieces and placed into a microcentrifuge where 180µl of nitrogen

purged manufacturer’s ATL buffer was added. After the addition of proteinase K the


211

samples were left at 37 oC for 4 hrs until completely lysed. DNA elution occurred as

above.

DNA in all samples was quantitated using a nanodrop ND-1000 spectrophotometer

(Biolab, Australia).

7.10 Real time PCR for absolute quantitation for te lomere length

The quantitative Real-Time amplification of the telomere sequence was performed as

described by Cawthon (2002) with the following modifications. A standard curve was

established by dilution of known quantities of a synthesised 84mer oligonucleotide

containing 14 TTAGGG repeats. The number of repeats in each standard was

calculated using standard techniques, as follows: the oligomer is TTAGGG repeated

14 times, 84bp in length (MW= 26667.2). The highest concentration standard

(standard 1) contained 1.9 x1010 telomere hexamer repeats units in 60pg which is

equivalent to 1.18 x108 kb of telomere sequence. Assays on serial dilutions were

performed to determine a standard curve for measuring kb of telomeric sequence

(Figure 1). Plasmid DNA (pBR3222) was added to each standard to maintain a

constant 20ng of total DNA per reaction tube.

All samples were run on an ABI 7300 Sequence Detection System with the SDS Ver.

1.9 software (Applied Biosystems, Foster City, CA). After the reaction is completed

the AB system produces a value that is equivalent to telomere sequence length (kb)

per 20ng of total genomic DNA which is equivalent to telomere sequence length (kb)

per 3472 mouse diploid genomes. The telomere sequence length (kb) per diploid


212

genome can then be derived from this value by dividing by 3472. A standard curve

was generated in each assay run. Each sample was analysed in duplicate. 36B4

amplification for every sample was also performed to verify accurate quantification of

the amount of template in each well. If the results for duplicate samples differed by

more than one CT value, the results were discarded and the assay repeated. Each

20µl reaction was performed as follows: 20ng DNA, 1xSYBR Green master mix,

100nM telo1 forward (CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT),

100nM telo2 reverse (GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT)

[273,277]. Cycling conditions (for both telomere and 36B4 amplicons) were: 10min at

95oC, followed by 40 cycles of 95oC for 15sec, 60oC for 1min. Primers for the 36B4

reaction consisted of (forward primer, 5’-ACT GGT CTA GGA CCC GAG AAG-3’)

and (reverse primer, 5’-TCA ATG GTG CCT CTG GAG ATT-3’ geneworks, Adelaide,

Australia). DNA from the 1301 lymphoblastoid cell line was used as a control in each

plate run. Using the 1301 data we estimated that the inter-experimental variability

was ≤ 7 % (N=34) and the intra-experimental variability ±1.1 % (N=17).


One way ANOVA analysis was used to determine the significance of differences

between groups for all measurements, whereas pair wise comparison of significance

was determined using the parametric Tukey’s test if distribution of values is

Gaussian, or the non-parametric Kruskal wallis if values were not Gaussian. 2 way

ANOVA was performed to investigate the effect of time on each of the parameters

measured. Comparisons between the two control groups were performed using the

Mann-Whitney non parametric t-test if values were not Gaussian or parametric t-test


213

if values were found to be Gaussian in distribution (Graphpad PRISM (Graphpad inc.,

San Diego, CA)). P values <0.05 were considered to be significant.

7.12 Results

7.12.1 Food consumption

Food consumption data was measured at 3 and 9 months over a period of 1 week.

Data was collected and averaged for these two time points and is shown in Figure 5.

There was no significant difference in the amount of food consumed between the AD

control and the WT control group. No significant differences in food consumption

occurred between the AD control group and any of the polyphenol cohorts.

7.12.2 Bodyweight Bodyweight data for all groups at 3, 6 and 9 months is shown in Figure 6. There was

a significant increase in bodyweight for the AD control group compared to the WT

control group at the 3 month (P=0.04), 6 month (P=0.009) and 9 month (P=0.02) time

points. A significant increase in bodyweight occurred in the curcumin and free GSE

cohorts between months 3 and 9. A significant decrease between AD control and the

GSE cohort occurred at 3 months.


214

W

T co

ntro

l

AD Con

trol

Curcu

min

GSE

MGSE

0

10

20

30

40

50

P=0.7838

Food Consumption

gram

s/w

eek

Figure 5 : Food consumption data for average of 3 and 9 month time points for wild

type control (N=20), AD control (N=10), AD Curcumin (N=10), AD GSE (N=10) and

AD MGSE (N=10). Groups were not significantly different from each other. Error bars

denote SE of the mean.


215

3 6 9 3 6 9 3 6 9 3 6 9 3 6 905

10152025303540455055

WT Control

AD/Control diet

AD/ Curcumin

AD/GSE

AD/MGSE

Time in months

Bodyweight

ab

b

ab

b1 1 12

Bod

ywei

ght

in g

ram

s

Source of Variation % of total variation P valu e

Interaction 5.19 0.0823

Diet group 12.15 P<0.0001

Time 16.11 P<0.0001

Figure 6 : Bodyweight data at 3, 6 and 9 month time points for wild type control

(N=20), AD control (N=10), AD Curcumin (N=10), AD GSE (N=10) and AD MGSE

(N=10). Letters denote comparisons within the same group. Time points not showing

the same letter are significantly different from each other. Numbers denote

comparisons between all the cohorts for the same time point. Time points not

showing the same number are significantly different from each other. Error bars

denote SE of the mean.


216

7.12.3 Buccal micronucleus cytome assay

The results for the buccal micronucleus cytome assay are summarized and illustrated

in Figures 7a-f.

7.12.3.1 Basal cells The results for basal cell frequency are shown in Figure 7a. There were no significant

differences in basal cell frequency between the AD control group and the WT control

at any of the sample points. There were no significant differences in basal cell

frequency between any of the polyphenol cohorts and the AD control group at the

three time points sampled.


217

Basal cells

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90.0

0.5

1.0

1.5

2.0

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSE

Time in months

% o

f to

tal c

ells

sam

pled

Source of Variation % of total variat ion P value


Diet group 4.56 0.0672

Time 1.06 0.3546

Figure 7a : Basal cell frequency sampled as a percentage of total cells sampled for

WT Control (N=20), AD control (N=10), AD curcumin (N=10), AD GSE (N=10) and

AD MGSE (N=10) at 3, 6 and 9 months. Error bars denote SE of the mean.

7.12.3.2 Differentiated cells

The results for differentiated cell frequency are shown in Figure 7b. There were no

significant differences in differential cell frequency between the AD and WT control

groups or between the AD control and polyphenol cohorts for any of the time points

sampled. There was a significant increase (P<0.001) in the frequency of


218

differentiated cells in all cohorts between 3 and 6 months (average increase in value

of 353.8%). There was a significant decrease (P<0.001) in the frequency of

differentiated cells in all cohorts between months 6 and 9 (average decreased value-

72.9%).

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90

1

2

3

4

5

6

7

8

Differentiated Cells

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSE

a a a a a aa

aa

a

b bb b

b

Time in Months

% o

f to

tal c

ells

sam

pled

Source of Variation % of total variation P value



Time 66.36 P<0.0001

Figure 7b : Frequency of differentiated cells sampled as a percentage of total cells

sampled for WT Control (N=20), AD control (N=10), AD curcumin (N=10), AD GSE

(N=10) and AD MGSE (N=10) at 3, 6 and 9 months. Groups not sharing the same

letter are significantly different. Error bars denote SE of the mean.


219

7.12.3.3 Micronucleated cells (combined basal and d ifferentiated micronucleated cells)

The results for combined micronucleus frequency for all cohorts are shown in Figure

7c. A non-significant 2 fold increase in micronucleated buccal cells occurred in the

AD control compared to the WT control group over the 9 month duration of the study.

A decrease in micronuclei occurred within the curcumin group between months 6 and

9, although this decrease did not achieve significance. A non-significant decrease in

micronuclei occurred in both the GSE and MGSE groups compared to the AD control

over the 9 month duration of the study.


220

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90.000.050.100.150.200.250.300.350.400.450.500.550.600.65

Micronucleated cells

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSE

Time in months

% o

f to

tal c

ells

sam

pled




Time 0.33 0.7329

Figure 7c : Combined frequency of micronuclei for both basal and differentiated cells

in WT Control (N=20), AD control (N=10), AD curcumin (N=10), AD GSE (N=10) and

AD MGSE (N=10) at 3, 6 and 9 months. Error bars denote SE of the mean.


221

7.12.3.4 Early Karyolytic cells

The result for early karyolitic cell frequency is shown in Figure 7d. There were no

significant differences in the frequencies of early karyolitic cells between the AD

control and the WT control groups at each of the 3, 6 and 9 month time points. In

each cohort studied there was a significant increase (P<0.001) in the frequency of

early karyolytic cells between the 3 month and 6 month time points. An average

increase in the control groups was 284.30% whereas the curcumin, GSE and MGSE

had an average increase of 394.40%. There was a significant decrease (P<0.001) in

early karyolytic frequency between the 6 month and 9 month time points for all study

cohorts. The average decrease in the control groups was -82.25% whereas the

curcumin, GSE and MGSE cohorts had an average decrease of -87.40%. At month 6

inter group comparisons showed a significant increase (P<0.01) in curcumin early

karyolitic frequency compared to the AD control and MGSE cohorts.


222

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90

1

2

3

4

5

6

7

8

Early karyolytic cells

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSE

a

b

a a

b

a a

b

aa

b

a a

b

a

Time in Months

% o

f tot

al c

ells

sam

pled




Time 60.80 P<0.0001

Figure 7d : Early karyolytic frequencies for WT Control (N=20), AD control (N=10),

AD curcumin (N=10), AD GSE (N=10) and AD MGSE (N=10) at 3, 6 and 9 months.

Groups not sharing the same letter are significantly different. Error bars are SE of the

mean.


223

7.12.3.5 Mid Karyolysis

The results for mid karyolytic cells for all the cohorts sampled are shown in Figure 7e.

There was no significant difference in mid karyolytic cell frequency between the AD

and WT control groups at the three time points sampled. There was a significant

increase (P<0.05) in the frequency of mid karyolytic cells in both the WT control and

the MGSE cohorts between the 3 month and 6 month time points. A significant

decrease (P<0.05) in mid karyolytic cell frequency occurred between the 6 month

and 9 month time points for both the WT control and the MGSE cohort. Similar trends

occurred for the AD control and GSE cohorts over the 3, 6 and 9 month period but

these changes did not achieve significance.


224

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90.0

0.5

1.0

1.5

2.0

2.5

Mid Karyolytic cells

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSE

a

b

a

a

b

a

1 1

2

1

1

Time in Months

% o

f to

tal c

ells

sam

pled




Time 16.40 P<0.0001

Figure 7e : Mid karyolytic frequencies for WT Control (N=20), AD control (N=10), AD

curcumin (N=10), AD GSE (N=10) and AD MGSE (N=10) at 3, 6 and 9 months.

Letters denote intra group comparisons whereas numbers denote inter group

comparisons Groups not sharing the same letter or number are significantly different.

Error bars are SE of the mean.


225

7.12.3.6 Late Karyolysis

Results for the late karyolytic frequencies for all sample cohorts at 3, 6 and 9 month

time points are shown in Figure 7f. There was no significant difference in late

karyolytic cell frequency between the AD and WT control group. There was no

significant difference in late karyolytic cell frequency between the AD control group

and any of the polyphenol cohorts at any of the time points measured. There was a

significant reduction (P<0.001) in late karyolytic cells for all cohorts inclusive of

controls between the 3 month and 6 month sample points. A significant increase

(P<0.001) in the number of late karyolytic cells sampled at 9 months compared to the

6 month sample occurred for all study cohorts.


226

3 6 9 3 6 9 3 6 9 3 6 9 3 6 90

25

50

75

100

Late Karyolytic cells

WT Control

AD Control

AD Curcumin

AD GSE

AD MGSEa ab

a a a a a a a ab b b b

Time in Months

% o

f to

tal c

ells

sam

pled




Time 72.28 P<0.0001

Figure 7f : Late karyolytic frequencies for WT Control (N=20), AD control (N=10), AD

curcumin (N=10), AD GSE (N=10) and AD MGSE (N=10) at 3, 6 and 9 months.

Letters denote intra group comparisons; groups not sharing the same letter are

significantly different. Error bars are SE of the mean.


227

7.12.4 Whole blood micronucleus erythrocyte assay

Results for this assay are shown in Table 2.

7.12.4.1 Micronucleated PCE

There were no significant differences in the frequency of micronucleated

polychromatic erythrocytes between the WT control and AD control groups for both

the 3 and 9 month sampled time points. A non-significant increase in micronucleated

PCE’s occurred between month 3 and 9 for the WT control group (24.25%), whereas

for the AD control cohort a non-significant 50% increase was measured at the 9

month timeframe compared to the 3 month sample point. Non-significant reductions

were apparent for the curcumin cohort (49.5%), GSE (33.3%) and MGSE (62.79%)

for measured micronucleated PCE frequency at the 3 month and 9 month sampled

time points. No significant difference in micronuclei frequency was apparent at 3

months when all polyphenol cohorts were compared to the AD control group. At 9

months each of the polyphenol cohorts had significantly lower micronucleated PCE’s

(P<0.001) when compared to the AD control.

7.12.4.2 Micronucleated Non polychromatic erythrocy tes

No significant differences occurred in the micronucleated non-polychromatic

erythrocyte frequency between the AD and WT control groups when compared to

each other at the 3 and 9 month time point. No significant differences occurred

between the AD control and the polyphenol cohorts at both the 3 and 9 month for

measured non PCE micronucleus frequency.


228

7.12.4.3 Polychromatic erythrocyte percentage

No Significant difference in polychromatic frequency occurred between the WT

control and the AD control groups when compared at the 3 and 9 month time points.

Intragroup comparisons between the 3 and 9 month PCE frequency showed a

significant increase (P<0.05) for the curcumin group (49.99%), a significant increase

(P<0.001) for the GSE group (60.71%) and the MGSE group (P<0.05) which had an

increased frequency of (43.75%).


229

Table 2: Frequencies of micronuclei in 1000 polychromatic (MN-PCE) and nonpolychromatic (MN-NCE) erythrocytes and PCE/ NCE relationship in control and polyphenol treated mice. Treatment group MN-PCE

(Mean ± SD) MN-NCE (Mean ± SD)

PCE/2000 NCE (%) (Mean ± SD)

WT Control

3 month* 4.33±1.44 6.62±3.31 3.07±0.51

9 Month* 5.38±3.24 6.29±2.54 3.54±0.69

AD Control

3 Month* 4.60±1.17 6.30±3.86 3.30±0.81

9 Month* 6.90±2.02 5.60±1.84 3.96±0.84

AD Curcumin

3 Month* 3.91±1.97 5.36±1.50 2.61±0.34

9 Month* 2.81±1.32** 5.45±1.91 3.96±0.66a

AD GSE

3 Month* 3.00±1.55 5.90±1.92 2.82±0.31

9 Month* 2.00±1.18** 4.36±1.86 4.54±1.78b

AD MGSE

3 Month* 4.30±1.76 5.60±2.76 3.24±0.49

9 Month* 1.60±1.17** 4.00±1.76 4.56±15.57a * Months on assigned diet ** P<0.001 when compared to the AD control group of the same month. a P<0.05 comparing values for 3 and 9 months on diet within the same cohort. b P<0.001 comparing values for 3 and 9 months on diet within the same cohort. 2 way analysis results for micronucleated polychromatic erythrocytes Source of Variation % of total variation P value Interaction 12.12 0.0004 Diet groups 23.46 P<0.0001 Time in months 0.33 0.4377


230

7.12.5 Correlation between micronuclei in buccal ce lls and polychromatic erythrocytes

Combined data for all cohorts showed no significant correlation (r=0.09, P=0.28)

between the combined MN for basal and differentiated buccal cells and micronuclei

in the polychromatic erythrocytes (Figure 8).

0.0 0.5 1.0 1.5 2.0 2.50.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

MN in Buccal cells

Correlation between MN in buccal Cells and PCE

r=0.09, P=0.28

MN

in P

CE

Figure 8: Graph showing correlation data between MN in buccal cells and

polychromatic erythrocytes.


231

7.12.6 Telomere length at 9 months

7.12.6.1 Olfactory lobe brain tissue

The results for absolute telomere length for all the cohorts sampled are shown in

Figure 9. A non significant 2 fold decrease in absolute olfactory lobe telomere length

was evident between the AD control and WT control groups. The polyphenol

curcumin cohort had non-significantly longer telomeres compared to the AD control

and both grape seed extract cohorts (P>0.05).

W

T Con

trol

AD Con

trol

AD Cur

cumin

AD GSE

AD MGSE

0

10

20

30

40

50

Absolute brain telomere length

P=0.22

a

a

a

aa

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 9 : Absolute telomere length in olfactory lobes of WT controls (N=20), AD controls (N=10), AD curcumin (N=10), AD GSE (N=10), AD MGSE (N=10).Groups not sharing the same letter are significantly different. Error bars are SE of the mean.


232

7.12.6.2 Buccal cell absolute telomere length

The results for absolute telomere length in buccal cells for all the cohorts sampled

are shown in Figure 10. A significant decrease (P=0.04) in absolute buccal telomere

length was evident in the AD control when compared to the WT control. All

polyphenol cohorts had a non-significant increase in telomere length when compared

to AD controls.

W

T Con

trol

AD Con

trol

AD Cur

c umin

AD GSE

AD MGSE

0.0

2.5

5.0

7.5

Absolute buccal telomere length

a

a

a aa

P=0.09

Abs

olut

e te

lom

ere

leng

th(K

b pe

r di

ploi

d ge

nom

e)

Figure 10: Absolute telomere length in buccal cells of WT controls (N=20), AD controls (N=10), AD curcumin (N=10), AD GSE (N=10), AD MGSE (N=10).Groups not sharing the same letter are significantly different. Error bars are SE of the mean.

There were no significant gender effects within any of the cohorts for any of the

parameters investigated.


233

7.12.7 Correlation between buccal cell and olfactor y lobe telomere length

Combined data for all cohorts showed a non significant inverse correlation

(r=-0.12, P=0.23) between buccal cell and olfactory lobe telomere length (Figure 11).

Correlation between buccal cell and olfactory lobe telomere length

0.01 0.1 1 10 1000.01

0.1

1

10

100

1000

r=-0.15, P=0.24

Buccal cell telomere length (log scale)

Olfa

ctor

y lo

be t

elom

ere

leng

th(l

og s

cale

)

Figure 11: Graph showing correlation between buccal cell and olfactory lobe

telomere length.

7.13 Discussion Oxidative stress has been accepted as playing a key role in AD pathology. It results

from an imbalance between free radical formation, and the counteractive

endogenous antioxidant defense systems such as superoxide dismutase (SOD),

catalase (CAT) and glutathione peroxidase (GPx). Reactive oxygen species (ROS)

are damaging to cells leading to the oxidation of essential cellular components such


234

as proteins and lipids, leading to eventual genomic instability events such as MN

formation and telomere shortening [96,345]. The aim of the study was to a)

determine whether DNA damage events are increased to a greater extent with time

in carriers of mutations that predispose to AD relative to controls and b) to investigate

whether increasing the intake of dietary polyphenols such as curcumin and GSE

prevent the onset and severity of genomic instability biomarkers in a transgenic

mouse model for AD.

Results from the study show differences in biomarkers for DNA damage between the

transgenic AD control group and the WT control groups. Both were confined to the

same AIN-93G diet for the duration of the study. MN frequency was determined in

both buccal cells and whole blood. Buccal cell analysis showed an increase in MN

frequency for both control groups over the duration of the 9 month study. WT controls

showed an 8% increase whereas the AD control group showed an increase in MN

frequency of 20%. After 9 months a non significant 2 fold increase in MN frequency

was apparent in the transgenic AD buccal mucosa compared to the WT group.

Similarly in whole blood a 24% increase in micronucleated polychromatic

erythrocytes occurred in the WT control group compared to a 50% increase in the AD

controls. After 9 months the AD control had a non significant 1.3 fold increase in MN

frequency compared to the WT control. Taken together, the data suggest that the AD

control cohorts have an increased rate of DNA damage in different tissues beyond

the rate of normal ageing. It is possible that had sampling occurred later these initial

trends may prove to be significantly different. These findings are similar to the results

in human buccal mucosa which show a similar trend for increased MN frequency in

the younger AD group and age matched controls (Chapter 3).


235

Differences were apparent in biomarkers for DNA damage, cell proliferation and cell

death parameters between AD control mice and those cohorts with an increased

dietary polyphenol intake. MN were scored in both buccal cells and whole blood. The

results suggest a potential protective effect from a polyphenol enriched diet as the

MN frequency in both buccal and whole blood was reduced compared to the control

diets. The curcumin cohort showed a non-significant decrease of 72% whereas the

GSE and MGSE cohorts showed an overall decrease of 9 and 84% respectively.

There was a significant ten fold decrease (P=0.01) in MN frequency at 9 months

between the AD control group and both the curcumin and MGSE cohorts and a

significant seven fold decrease for the GSE cohort (P=0.02). This is the first time that

buccal cells have been used to investigate the effects of polyphenols on MN

frequency in a transgenic mouse model for AD. Similarly in whole blood differences

were apparent between the AD control and polyphenol diet groups. All the

polyphenol groups saw a reduction in MN frequency between the 3 and 9 month

sample points. Curcumin showed a reduction of 49.5% and the GSE and MGSE

cohorts showed an overall reduction of 33.3% and 62.5% respectively. However, no

significant positive correlation for MN frequency between these tissues was evident

(r=0.09, P=0.28) (Figure 8). These results suggest that the polyphenol diets may be

protective in reducing the MN frequency in both buccal mucosa and whole blood, at

the levels investigated confirming the results of earlier studies involving human

lymphocytes [364,372-374].

It has previously been shown that both curcumin and GSE are effective antioxidants

and have contributory roles in protecting cells from oxidative stress and the resulting

DNA damage [363,375]. It is thought that the effectiveness of these compounds as


236

free radical scavengers can be directly attributed to their structural characteristics.

The phenolic and methoxy groups on the curcumin benzene rings and the 1,3-

diketone system are thought to be important structures for effective oxygen free

radical scavenging [376,377] . GSE has been shown to have a high number of

conjugated structures between the B-ring catechol groups and the 3-OH free groups

of the polymeric skeleton allowing these compounds to be effective free radical

scavengers and metal chelators [372,378]. As GSE scavenges for free radicals, the

resulting aroxyl radical formed has been shown to be more stable than those

generated from other polyphenolic compounds [379] potentially aiding in preventing

further DNA damage.

Further mechanisms that have been attributed to both curcumin and GSE that

enhance their effectiveness as powerful antioxidants involve the enhanced synthesis

of the endogenous antioxidant enzymes SOD, CAT and GPx [373,380,381].

Reduced glutathione (GSH) is another endogenous antioxidant that regulates the

expression of antioxidant genes [353,382-384]. GSH levels and subsequent activity

is maintained by the enzyme γ-glutamylcysteine ligase catalytic subunit (GCLC)

which in turn is regulated by oxidative stress [385]. It has been shown that both

curcumin and GSE protect against GSH depletion by sequestering ROS and

increases GSH synthesis by enhancing GCLC expression [353,386].

Telomere length was investigated as a biomarker of genomic instability in both

buccal cells and olfactory lobe brain tissue, as telomere length has been shown to be

compromised in AD and under conditions of oxidative stress [112,267]. In buccal

cells a significant (P=0.04) 11 fold reduction in telomere length was found in the AD


237

control group compared to the WT control. This reduction in buccal telomere length in

the AD control cohort may be due to increased levels of oxidative stress, or a higher

turnover rate of cells. These results are in agreement with the findings from the

human study (chapter 4) where telomere length was found to be shorter in AD buccal

cells compared to age and gender matched controls. All polyphenol cohorts showed

a non-significant 2 fold increase in buccal cell telomere length compared to the AD

control cohort and a non-significant 4.3 fold decrease compared to the WT cohort.

This would suggest that polyphenols through their effective scavenging of ROS and

activation of endogenous defense mechanisms, may provide some degree of

protection towards telomere maintenance in the buccal mucosa at the levels

investigated.

Telomere length within the olfactory lobe brain tissue of AD controls was found to be

non-significantly reduced by 2 fold compared to the WT control group. Both the GSE

and MGSE polyphenol group were found to have a 34% and 25% reduction in brain

telomere length compared to the AD control group. AD mice that were fed a curcumin

rich diet were found to have a 2 fold increase in brain telomere length compared to

the AD control group, and were found to be only 4% shorter than the WT control

cohort. It has been shown that curcumin has the ability to induce expression of genes

involved in the cellular stress response network. Curcumin can activate Heme

oxygenase-1 (HO-1) which increases cellular resistance to oxidative stress and

phase II enzyme expression in neural tissue through the activation of the

transcription factor Nrf2, affording significant protection to neurons exposed to

oxidative stress [387-390]. Furthermore, curcumin and GSE have been shown to

inhibit the formation of amyloid oligomers and prevents fibril formation that lead to the


238

formation of amyloid plaques [180,186,351,354]. Beta amyloid has been shown to

form complexes with copper and iron to produce hypochlorous acid that increase the

levels of oxidative stress within the brain [200,259]. Both Curcumin and GSE have

been shown to act as a metal chelator binding these metals and possibly reducing

amyloid levels resulting in lower levels of oxidative stress [181,391].

A weak non-significant inverse correlation was found between telomere length in

brain tissue and buccal mucosa (r=-0.15, P=0.24) (Figure 11). At this stage it is

uncertain the contribution made by each cellular population to overall telomere

length. It has been shown in this study that a high proportion of buccal cells are

under going various stages of karyolysis which may distort the true telomere length of

the progenitor basal cells by over representing senescent cells that would be

expected to contain shorter telomeres. Only future studies on progenitor cells will be

able to determine whether a stronger correlation exists between these two tissues,

which if proven may lead to buccal cells potentially being used as a noninvasive

biomarker reflecting physiological changes within telomere length in the brains of

premature ageing mouse models for AD.

The buccal cytome micronucleus assay also provided measures of potential cell

proliferation and cell death in relation to potential genotoxicity of the polyphenols at

the levels investigated. Basal cell frequency within both the control groups showed a

slight but non-significant decrease over the three time points measured. After 9

months the basal cell frequency in the AD control group had decreased by 7%

possibly indicating the initial stages leading to the flattening of the rete pegs which

are associated with advancing age. It would have been interesting to have sampled


239

the buccal mucosa at later time points, in order to determine whether similar changes

in basal cell frequency reflect those observed in the earlier human study. The

curcumin cohort showed a slight but non- significant decrease between months 6 and

nine whereas both GSE groups showed a slight non-significant increase over the last

three months of the study. All of the polyphenol cohorts did not show any marked

changes in the cell proliferation rate of basal cells compared to controls suggesting

that polyphenols at the dose used in the study had no cytotoxic or cytostatic effects.

Similarly, differences were evident in the frequencies of differentiated cells measured

between all of the cohorts. A significant increase (P<0.001, average increase

353.8%) in differential cell frequency occurred in all groups between months 3 and 6

suggesting a higher turn over of cells at this time point whilst a significant decrease

(P<0.001, average decrease 72.9%) occurred in all groups between months 6 and 9 .

These marked changes in proliferative rates at 6 months may reflect changes in the

cellular kinetics of the buccal mucosa during growth and need to be further

investigated in future studies.

The three stages of cell death characterized in the assay represent over 95% of the

cells sampled. This would indicate that the stratum corneum or keratinized layer of

the murine buccal mucosa is significantly thickened and may be necessary to offset

excessive sloughing off during mastication and to maintain the structural profile of the

mouse’s buccal mucosa. At this stage it is uncertain whether these stages of

karyolysis may represent specific forms of cell death such as apoptosis. Only future

studies using cell death markers will determine their true origin. Early karyolysis was

significantly increased (P<0.0001, average increase 286.96%) in both the control

cohorts whereas the polyphenol cohorts had an average increase of 393.69%.


240

Similarly after 9 months the control groups showed a significant decrease (P<0.001,

average decrease 82.25%) in early karyolysis and the polyphenol cohorts showed a

decrease of 87.40%. These changes in cell death parameters exhibited similar trends

in all the groups of the study indicating that these changes did not arise from dietary

genotoxicity. There were no significant inter-group changes for both the mid and late

karyolitic parameters measured.

In conclusion, these results suggest a potential protective effect of a polyphenol

enriched diet in terms of reducing DNA damage events, such as micronuclei and

telomere length in different somatic tissue types, with no adverse effects on cell

proliferation rates or cell death markers. This is reflected in that bodyweight and food

consumption were also not significantly different between any of the cohorts

suggesting that unpalatability of the diet at the doses investigated was not a variable

affecting the observed results. This confirms earlier findings that increased dietary

intake of polyphenols had no adverse effect on bodyweight [187,392]. However, due

to multiple comparisons, the study was underpowered to demonstrate significant

effects for some of the comparisons made. The results suggest that replication of this

study with more mice per group, would be required to conclusively verify the possible

protective effects of curcumin, GSE and MGSE in this model of AD. Further studies

designed to elucidate the underlying molecular mechanisms for the observed

protective effects should also be performed.


241

7.14 Appendix 1: Clinical morbidity assessment for AD Mice performed weekly

• Switch to daily monitoring when mouse displays 2 or more symptoms at Grade1 or above

• Perform euthanasia when mouse displays 2 or more sy mptoms Grade 2 or above.

Signs Grade 0 Grade 1 Grade 2 Grade 3

*Chronic weight loss compared with mean of aged matched normal controls

Normal weight

5-10% 11-15% >15%

*Acute body weight loss compared to animal’s weight 7 days earlier

No change 5-10% 11-15% >15%

Degree of anaemia Normal Slightly pale eyes, ears, tail

Obvious pale extremities

Very pale extremities, blood apparent in stools; cool extremities

Behaviour/posture/ activity

Normal Slightly hunched, sometimes on own; transiently dull; occasional lurch when disturbed

Quiet and often on own; sometimes hunched; dull; occasional lurch.

Often hunched or curled posture; isolated, does not interact with others; significantly dull; frequent lurch.

Appearance Normal Slight porphyrin staining

Moderate porphyrin staining; mild failure to groom

Severe porphyrin staining; moderate failure to groom

Vocalisation Normal Squeals when palpated

Squeals when handled

Struggles and squeals loudly when handled/palpated

*If a study involves the use of growing animals the reduction in growth rate compared to healthy aged matched controls should be assessed rather than weight loss.


242

Weekly Animal monitoring sheet

AEC Project Number:

Investigator Name & Contact:

Animal ID Number:

Diet:

Comments:

• Each animal is examined (am) for abnormalities weekly if normal and switch to daily

monitoring when mouse displays 2 or more symptoms at Grade1 or above.

� Observations are recorded in the table below.

� Normal clinical signs are recorded as “N”

� Abnormalities are recorded as “A” and severity is scored in brackets eg. Appearance: A

(2) where score is derived from clinical assessment form

� Comments concerning abnormalities are recorded in the comments section of the table

� Additional observations tailored to the monitoring requirements for each animal

experiment are to be added at “Other”


243

Weekly Animal monitoring sheet

Clinical Observation (N or A)

Date

Chronic weight loss compared with aged matched controls

Acute body weight loss

Anaemia

Behaviour/posture

Appearance

Vocalisation reaction to Handling/gait

Other:

Comments

Initials of assessor

Signature of (responsible) Investigator: Date:

Chapter 8: Conclusions and future directions

244

8 Chapter 8: Conclusions and future directions


245

The aim of this thesis was to investigate changes in buccal genomic instability

biomarkers in relation to normal ageing as well as in premature ageing syndromes

such as AD and DS. A buccal cytome micronucleus assay was developed involving

cellular/nuclear classification specific for DNA damage, potential cell proliferation and

cell death markers. The assay was validated in cohorts of young, old and

prematurely aged DS individuals to determine age-related changes. It was found that

micronuclei, basal cells, karyorrhectic cells and condensed chromatin cells increased

significantly with normal ageing (P<0.0001). Micronuclei and binucleated cells

increased (P<0.0001) and condensed chromatin, karyorrhectic, karyolytic and

pyknotic cells decreased (P<0.002) significantly in DS individuals relative to young

controls. These changes show distinct differences between the cytome profile of

normal ageing relative to that for a premature ageing syndrome, and highlights the

diagnostic value of the cytome approach for measuring changes in genome damage,

cell death and cell proliferative effects with normal and accelerated ageing.

The buccal cytome assay was then used to investigate a cohort of individuals that

had been clinically diagnosed with AD, to determine if specific changes in the buccal

profile could also be identified in this cohort. It was found that frequencies of basal

cells (P<0.0001), condensed chromatin (P<0.0001) and karyorrhectic cells

(P<0.0001) were significantly lower in Alzheimer’s patients. These changes may

reflect alterations in the cellular kinetics or structural profile of the buccal mucosa,

and may be useful as potential biomarkers in identifying individuals with a high risk of

developing AD. The odd’s ratio of being diagnosed with AD for those individuals with

a basal plus karyorrhectic cell frequency <41 per 1000 cells is 140, with a specificity

of 97% and sensitivity of 82%.


246

Although encouraging these preliminary results need to be performed in larger

cohorts to determine the accuracy and reproducibility of these findings. Future

studies are important to determine if these changes are specific to AD or whether

they reflect alterations in the cellular kinetics of the buccal mucosa that can be linked

to non-specific pathological situations. Thus, the same parameters need to be

measured in mucosal cells from patients affected by other neurodegenerative

dementia disorders such as vascular dementia or Huntingdon’s disease to determine

specificity to AD. Furthermore, it is important to determine whether patients who have

different genetic forms of familial AD exhibit the same changes and whether these

changes can be identified presymptomatically. The proposed models (Chapter 3

Figures 8a-c) derived from the studies that reflect potential structural profile changes

can only be validated through further research involving histopathological sections

and biopsies. Once this has been established more accurate models can be

proposed for future testing. Testing for concentrations of micronutrients such as zinc

may be important in explaining the changes in the structural mucosa of AD patients

and may eventually be useful as a non-invasive model for individual micronutrient

status. It may also be possible to culture buccal cells which would allow a wide range

of in vitro experiments to be performed to investigate genotoxicity due to

micronutrient deficiency or excess and identify the nutritional requirements for the

reduction of genomic instability events. Further improvements in methodology

involving image analysis and flow cytometry should be investigated and subsequently

validated, to allow the development of an automated system that could potentially

allow for scoring larger numbers of cells, in order to more accurately define changes

in cellular kinetics and genomic instability events within the buccal mucosa.


247

A quantitative RTm-PCR method was developed and validated in order to determine

absolute telomere length (in Kb per diploid genome) in a number of somatic tissues

from AD patients. A significantly lower telomere length was observed in white blood

cells (P<0.001) and buccal cells (P<0.01), and a significantly greater telomere length

was found in hippocampus cells from AD patients relative to healthy age-matched

controls. It was also observed that telomere length in buccal cells was 52.2%-74.2%

shorter than in the corresponding white blood cells from the same cohorts

investigated. The odds ratio for AD diagnosis was 4.6 (95% CI 1.22-17.66) if buccal

cell telomere length was less than 40Kb per diploid genome with a sensitivity of

72.7% and a specificity of 63.1%. It is not evident from these preliminary findings

which cells from the heterogeneous populations investigated contribute to the

observed changes in telomere length. Future studies need to be performed using

flow cytometry to accurately determine the contribution from each cellular subset.

Q FISH could be implemented to determine if there is uniform telomere shortening

amongst chromosomes or whether shortening occurs in a select few chromosomes.

As AD is associated with oxidative stress the integrity of the telomere sequence may

be compromised if oxidized bases or abasic sites accumulate within the telomere

sequence. A RTm-PCR method that would allow us to determine oxidized bases in

the telomere sequence may provide a more accurate risk assessment of AD.

The buccal cytome assay was also used to investigate aneuploidy events for both

chromosome 17 and 21. An age related increase in both chromosome 17 and 21

monosomy and trisomy occurred between the young and old cohorts investigated.

The study showed a 1.5 fold increase in trisomy 21 (P<0.001) and a 1.2 fold increase

in trisomy 17 (P<0.001) in buccal cells of AD patients compare to age matched


248

controls, which was beyond the effects of normal ageing. DS individuals also showed

a significant increase in chromosome 17 monosomy and trisomy within their buccal

cells compared to age-matched controls. It is possible that the observed increase in

aneuploidy status for chromosome 17 and 21 in both AD and DS patients may lead

to altered gene dosage and expression for both tau and APP. Through the utilization

of specific fluorescently labeled antibodies for both these proteins, it may be possible

to quantify the amount of protein present within individual aneuploidy cells, allowing

us to determine the significance of aneuploidy as a contributing factor for altered

gene expression of tau and APP in the early stages of AD. It is possible that

micronutrient deficiency (e.g. folate deficiency) may have influenced the observed

elevated chromosomal malsegregation frequencies for the chromosomes

investigated [103,319]. Folate and B12 are important in the maintenance of

methylation patterns that could potentially modify gene expression. Abnormal folate

and methyl metabolism may result in a state of DNA hypomethylation leading to

abnormal chromosome malsegregation and altered gene expression

[140,141,143,171,172].

The levels of plasma folate, B12 and Hcy in AD individuals compared to age-

matched controls were investigated. Results from previous studies were confirmed

showing that AD patients have higher levels of plasma Hcy (P<0.0003), however no

significant difference in folate or B12 status was found suggesting the possibility of

differences in folate/methionine metabolism due to genetic factors. However,

genotypic frequencies for common polymorphisms for genes coding for key enzymes

in folate and methionine metabolism in AD cases did not differ significantly from

those for the older control group. Future studies could explore other possibilities such


249

as defects in folate uptake and storage which may be a more accurate predictor for

Hcy status in AD patients. Similarly, the oxidative state of B12 and its impact as an

effective cofactor for methionine synthase in the remethylation of Hcy should also be

investigated, and measurements of methylmalonyl COA and transcobalamin (II)

should also be considered in order to determine whether either may be a more

informative biomarker in relation to B12 status. Elevated levels of Hcy may also be

accounted for as a result of deficiencies in vitamins B2 and B6 which act as cofactors

for MTHFR and cystathionine β synthase respectively. Therefore, it would be of

interest to determine B2 and B6 levels and the polymorphism status of other

enzymes that may affect Hcy metabolism.

The last investigation involved a dietary study of the effects of antioxidants in relation

to somatic genomic instability events in a transgenic mouse model of AD. It was

found that animals fed on a diet rich in curcumin and GSE had a positive effect in

reducing micronuclei frequency within the blood and buccal cells compared to control

animals on normal diets. Curcumin also appeared to have a protective effect on

olfactory lobe telomere length compared to control animals. The effects of

phytonutrient antioxidants, in particular curcumin, need to be further investigated to

determine their effectiveness as potential agents in reducing oxidative stress and

genomic instability events associated with AD. It may also be reasonable to consider

using Immunohistochemistry to determine whether levels of specific Alzheimer’s

proteins in buccal cells are correlated with levels of the same protein within brain

tissue from areas of the brain primarily affected by AD. This would then allow testing

the possibility of using buccal cells as a potential surrogate tissue that may reflect the

pathophysiological changes that occur within the brain of AD individuals.


250

In conclusion, changes within the buccal micronucleus cytome assay may be useful

as potential biomarkers to gauge both normal ageing and in the identification of

individuals associated with premature ageing syndromes such as AD and DS.

Through further studies it may be possible to overlay data from tau and APP

measurements together with the genomic instability events already investigated to

increase the sensitivity, specificity, NPV, PPV and odds ratio to give a more precise

and sensitive assay. In the future the buccal cytome may form the basis of a non-

invasive diagnostic test that may eventually be used to identify presymptomatically

those individuals with an increase risk of developing AD. It may then be possible to

develop and implement potential prophylactic measures based on dietary

intervention studies that may result in a cessation or reversal of the changes that are

characteristic of the disease. Buccal cytome changes may eventually be used to

reflect disease severity or as a within subject biomarker to gauge the effectiveness of

preventative interventions aimed at slowing down the progression of the disease.

References

251

9 References [1] K. Maurer, S. Volk and H. Gerbaldo Auguste D and Alzheimer's disease,

Lancet 349 (1997) 1546-1549.

[2] A. Alzheimer Uber Einen eigenartigen schweren Erkrankungsprozeb der

Hirnrinde., Neurologisches cenrealblatt 23 (1906) 1129-1136.

[3] A. Burns, E.J. Byrne and K. Maurer Alzheimer's disease, Lancet 360 (2002)

163-165.

[4] C.P. Ferri, M. Prince, C. Brayne, H. Brodaty, L. Fratiglioni, M. Ganguli, K. Hall,

K. Hasegawa, H. Hendrie, Y. Huang, A. Jorm, C. Mathers, P.R. Menezes, E.

Rimmer and M. Scazufca Global prevalence of dementia: a Delphi consensus

study, Lancet 366 (2005) 2112-2117.

[5] A. Wimo, B. Winblad, H. Aguero-Torres and E. von Strauss The magnitude of

dementia occurrence in the world, Alzheimer Dis Assoc Disord 17 (2003) 63-

67.

[6] A.J. Henderson, AF Dementia n Australia, Aged and community care service

development and evaluation report No 35, AGPS,Canberra (1998).

[7] A. economics delaying the onset of Alzheimer's disease, (August 2004).

[8] C.H. Kawas Clinical practice. Early Alzheimer's disease, N Engl J Med 349

(2003) 1056-1063.

[9] K. Ritchie and S. Lovestone The dementias, Lancet 360 (2002) 1759-1766.

[10] P.H. St George-Hyslop Piecing together Alzheimer's, Sci Am 283 (2000) 76-

83.

[11] R.J. Lederman What tests are necessary to diagnose Alzheimer disease?,

Cleve Clin J Med 67 (2000) 615-618.

References

252

[12] G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price and E.M.

Stadlan Clinical diagnosis of Alzheimer's disease: report of the NINCDS-

ADRDA Work Group under the auspices of Department of Health and Human

Services Task Force on Alzheimer's Disease, Neurology 34 (1984) 939-944.

[13] G.W. Small, Rabins,P.V, Barry P.P Diagnosis and treatment od ALzheimer

disease and related disorders, jama 278 (1997) 1363-1371.

[14] K.S. Santacruz and D. Swagerty Early diagnosis of dementia, Am Fam

Physician 63 (2001) 703-713, 717-708.

[15] Z. Khalil Early diagnosis of dementia, melbourne Health Research week

(2004).

[16] Z. Khalil, H. Poliviou, C.J. Maynard, K. Beyreuther, C.L. Masters and Q.X. Li

Mechanisms of peripheral microvascular dysfunction in transgenic mice

overexpressing the Alzheimer's disease amyloid Abeta protein, J Alzheimers

Dis 4 (2002) 467-478.

[17] M. Higuchi, N. Iwata, Y. Matsuba, K. Sato, K. Sasamoto and T.C. Saido (19)F

and (1)H MRI detection of amyloid beta plaques in vivo, Nat Neurosci (2005).

[18] K. Iqbal, I. Grundke-Iqbal, A.J. Smith, L. George, Y.C. Tung and T. Zaidi

Identification and localization of a tau peptide to paired helical filaments of

Alzheimer disease, Proc Natl Acad Sci U S A 86 (1989) 5646-5650.

[19] M. Goedert, M.G. Spillantini, R. Jakes, D. Rutherford and R.A. Crowther

Multiple isoforms of human microtubule-associated protein tau: sequences

and localization in neurofibrillary tangles of Alzheimer's disease, Neuron 3

(1989) 519-526.

References

253

[20] K. Iqbal, A.C. Alonso, C.X. Gong, S. Khatoon, J.J. Pei, J.Z. Wang and I.

Grundke-Iqbal Mechanisms of neurofibrillary degeneration and the formation

of neurofibrillary tangles, J Neural Transm Suppl 53 (1998) 169-180.

[21] A. Gomez-Ramos, M.A. Smith, G. Perry and J. Avila Tau phosphorylation and

assembly, Acta Neurobiol Exp (Wars) 64 (2004) 33-39.

[22] A.D. Cash, G. Aliev, S.L. Siedlak, A. Nunomura, H. Fujioka, X. Zhu, A.K.

Raina, H.V. Vinters, M. Tabaton, A.B. Johnson, M. Paula-Barbosa, J. Avila,

P.K. Jones, R.J. Castellani, M.A. Smith and G. Perry Microtubule reduction in

Alzheimer's disease and aging is independent of tau filament formation, Am J

Pathol 162 (2003) 1623-1627.

[23] G.D. Schellenberg Genetic dissection of Alzheimer disease, a heterogeneous

disorder, Proc Natl Acad Sci U S A 92 (1995) 8552-8559.

[24] M. Hogg, Z.M. Grujic, M. Baker, S. Demirci, A.L. Guillozet, A.P. Sweet, L.L.

Herzog, S. Weintraub, M.M. Mesulam, N.E. LaPointe, T.C. Gamblin, R.W.

Berry, L.I. Binder, R. de Silva, A. Lees, M. Espinoza, P. Davies, A. Grover, N.

Sahara, T. Ishizawa, D. Dickson, S.H. Yen, M. Hutton and E.H. Bigio The

L266V tau mutation is associated with frontotemporal dementia and Pick-like

3R and 4R tauopathy, Acta Neuropathol (Berl) 106 (2003) 323-336.

[25] C.F. Lippa, V. Zhukareva, T. Kawarai, K. Uryu, M. Shafiq, L.E. Nee, J.

Grafman, Y. Liang, P.H. St George-Hyslop, J.Q. Trojanowski and V.M. Lee

Frontotemporal dementia with novel tau pathology and a Glu342Val tau

mutation, Ann Neurol 48 (2000) 850-858.

[26] L. Buee, T. Bussiere, V. Buee-Scherrer, A. Delacourte and P.R. Hof Tau

protein isoforms, phosphorylation and role in neurodegenerative disorders,

Brain Res Brain Res Rev 33 (2000) 95-130.

References

254

[27] M. Hutton, C.L. Lendon, P. Rizzu, M. Baker, S. Froelich, H. Houlden, S.

Pickering-Brown, S. Chakraverty, A. Isaacs, A. Grover, J. Hackett, J.

Adamson, S. Lincoln, D. Dickson, P. Davies, R.C. Petersen, M. Stevens, E. de

Graaff, E. Wauters, J. van Baren, M. Hillebrand, M. Joosse, J.M. Kwon, P.

Nowotny, P. Heutink and et al. Association of missense and 5'-splice-site

mutations in tau with the inherited dementia FTDP-17, Nature 393 (1998) 702-

705.

[28] E.H. Koo The beta-amyloid precursor protein (APP) and Alzheimer's disease:

does the tail wag the dog?, Traffic 3 (2002) 763-770.

[29] D.R. Howlett, D.L. Simmons, C. Dingwall and G. Christie In search of an

enzyme: the beta-secretase of Alzheimer's disease is an aspartic proteinase,

Trends Neurosci 23 (2000) 565-570.

[30] B.D. Bennett, P. Denis, M. Haniu, D.B. Teplow, S. Kahn, J.C. Louis, M. Citron

and R. Vassar A furin-like convertase mediates propeptide cleavage of BACE,

the Alzheimer's beta -secretase, J Biol Chem 275 (2000) 37712-37717.

[31] D.J. Selkoe Alzheimer's disease: genes, proteins, and therapy, Physiol Rev 81

(2001) 741-766.

[32] G. Periz and M.E. Fortini Proteolysis in Alzheimer's disease. Can plasmin tip

the balance?, EMBO Rep 1 (2000) 477-478.

[33] R. Vassar, Citron,M. Ab-Generating enzymes:Recent advances in beta and

gamma secretase research, Neuron 27 (2000) 419-422.

[34] D.J. Selkoe Alzheimer disease: mechanistic understanding predicts novel

therapies, Ann Intern Med 140 (2004) 627-638.

[35] C.L. Masters, G. Multhaup, G. Simms, J. Pottgiesser, R.N. Martins and K.

Beyreuther Neuronal origin of a cerebral amyloid: neurofibrillary tangles of

References

255

Alzheimer's disease contain the same protein as the amyloid of plaque cores

and blood vessels, Embo J 4 (1985) 2757-2763.

[36] A.M. Cataldo, S. Petanceska, N.B. Terio, C.M. Peterhoff, R. Durham, M.

Mercken, P.D. Mehta, J. Buxbaum, V. Haroutunian and R.A. Nixon Abeta

localization in abnormal endosomes: association with earliest Abeta elevations

in AD and Down syndrome, Neurobiol Aging 25 (2004) 1263-1272.

[37] C. Haass, E.H. Koo, A. Mellon, A.Y. Hung and D.J. Selkoe Targeting of cell-

surface beta-amyloid precursor protein to lysosomes: alternative processing

into amyloid-bearing fragments, Nature 357 (1992) 500-503.

[38] S. Tomita, Y. Kirino and T. Suzuki Cleavage of Alzheimer's amyloid precursor

protein (APP) by secretases occurs after O-glycosylation of APP in the protein

secretory pathway. Identification of intracellular compartments in which APP

cleavage occurs without using toxic agents that interfere with protein

metabolism, J Biol Chem 273 (1998) 6277-6284.

[39] O. Wirths, G. Multhaup and T.A. Bayer A modified beta-amyloid hypothesis:

intraneuronal accumulation of the beta-amyloid peptide--the first step of a fatal

cascade, J Neurochem 91 (2004) 513-520.

[40] L.M. Billings, S. Oddo, K.N. Green, J.L. McGaugh and F.M. Laferla

Intraneuronal Abeta causes the onset of early Alzheimer's disease-related

cognitive deficits in transgenic mice, Neuron 45 (2005) 675-688.

[41] D.T. Loo, A. Copani, C.J. Pike, E.R. Whittemore, A.J. Walencewicz and C.W.

Cotman Apoptosis is induced by beta-amyloid in cultured central nervous

system neurons, Proc Natl Acad Sci U S A 90 (1993) 7951-7955.

[42] G. Forloni beta-Amyloid neurotoxicity, Funct Neurol 8 (1993) 211-225.

References

256

[43] Y. Christen Oxidative stress and Alzheimer disease, Am J Clin Nutr 71 (2000)

621S-629S.

[44] P. Mecocci, U. MacGarvey and M.F. Beal Oxidative damage to mitochondrial

DNA is increased in Alzheimer's disease, Ann Neurol 36 (1994) 747-751.

[45] K.-F. Lin, R.C.-C. Chang, K.-C. Suen, K.-F. So and J. Hugon Modulation of

calcium/calmodulin kinase-II provides partial neuroprotection against beta-

amyloid peptide toxicity, Eur J Neurosci 19 (2004) 2047-2055.

[46] m.p. Mattson Pathways towards and away from Alzheimer's disease, Nature

430 (2004) 631-639.

[47] D.C. Lu, S. Rabizadeh, S. Chandra, R.F. Shayya, L.M. Ellerby, X. Ye, G.S.

Salvesen, E.H. Koo and D.E. Bredesen A second cytotoxic proteolytic peptide

derived from amyloid beta-protein precursor, Nat Med 6 (2000) 397-404.

[48] K.J. Ivins, P.L. Thornton, T.T. Rohn and C.W. Cotman Neuronal apoptosis

induced by beta-amyloid is mediated by caspase-8, Neurobiol Dis 6 (1999)

440-449.

[49] T. Nakagawa, H. Zhu, N. Morishima, E. Li, J. Xu, B.A. Yankner and J. Yuan

Caspase-12 mediates endoplasmic-reticulum-specific apoptosis and

cytotoxicity by amyloid-beta, Nature 403 (2000) 98-103.

[50] M.P. Mattson, J.N. Keller and J.G. Begley Evidence for synaptic apoptosis,

Exp Neurol 153 (1998) 35-48.

[51] J. Hardy, K. Duff, K.G. Hardy, J. Perez-Tur and M. Hutton Genetic dissection

of Alzheimer's disease and related dementias: amyloid and its relationship to

tau, Nat Neurosci 1 (1998) 355-358.

[52] J. Hardy and D. Allsop Amyloid deposition as the central event in the aetiology

of Alzheimer's disease, Trends Pharmacol Sci 12 (1991) 383-388.

References

257

[53] J. Hardy Amyloid, the presenilins and Alzheimer's disease, Trends Neurosci

20 (1997) 154-159.

[54] B. Schonheit, R. Zarski and T.G. Ohm Scientific progress and a Hardy

paradigm-the 'amyloid cascade hypothesis' revisited, Neurobiol Aging 25

(2004) 743-746.

[55] B. Schonheit, R. Zarski and T.G. Ohm Spatial and temporal relationships

between plaques and tangles in Alzheimer-pathology, Neurobiol Aging 25

(2004) 697-711.

[56] J. Hardy and D.J. Selkoe The amyloid hypothesis of Alzheimer's disease:

progress and problems on the road to therapeutics, Science 297 (2002) 353-

356.

[57] J. Hardy The genetic causes of neurodegenerative diseases, J Alzheimers Dis

3 (2001) 109-116.

[58] D. Scheuner, C. Eckman, M. Jensen, X. Song, M. Citron, N. Suzuki, T.D. Bird,

J. Hardy, M. Hutton, W. Kukull, E. Larson, E. Levy-Lahad, M. Viitanen, E.

Peskind, P. Poorkaj, G. Schellenberg, R. Tanzi, W. Wasco, L. Lannfelt, D.

Selkoe and S. Younkin Secreted amyloid beta-protein similar to that in the

senile plaques of Alzheimer's disease is increased in vivo by the presenilin 1

and 2 and APP mutations linked to familial Alzheimer's disease, Nat Med 2

(1996) 864-870.

[59] K.E. Wisniewski, H.M. Wisniewski and G.Y. Wen Occurrence of

neuropathological changes and dementia of Alzheimer's disease in Down's

syndrome, Ann Neurol 17 (1985) 278-282.

References

258

[60] D.M. Mann, P.O. Yates, B. Marcyniuk and C.R. Ravindra The topography of

plaques and tangles in Down's syndrome patients of different ages,

Neuropathol Appl Neurobiol 12 (1986) 447-457.

[61] D.M. Mann and M.M. Esiri The pattern of acquisition of plaques and tangles in

the brains of patients under 50 years of age with Down's syndrome, J Neurol

Sci 89 (1989) 169-179.

[62] J. Lewis, D.W. Dickson, W.L. Lin, L. Chisholm, A. Corral, G. Jones, S.H. Yen,

N. Sahara, L. Skipper, D. Yager, C. Eckman, J. Hardy, M. Hutton and E.

McGowan Enhanced neurofibrillary degeneration in transgenic mice

expressing mutant tau and APP, Science 293 (2001) 1487-1491.

[63] K.R. Bales, T. Verina, R.C. Dodel, Y. Du, L. Altstiel, M. Bender, P. Hyslop,

E.M. Johnstone, S.P. Little, D.J. Cummins, P. Piccardo, B. Ghetti and S.M.

Paul Lack of apolipoprotein E dramatically reduces amyloid beta-peptide

deposition, Nat Genet 17 (1997) 263-264.

[64] R.D. Terry The pathogenesis of Alzheimer disease: an alternative to the

amyloid hypothesis, J Neuropathol Exp Neurol 55 (1996) 1023-1025.

[65] M.C. Irizarry, F. Soriano, M. McNamara, K.J. Page, D. Schenk, D. Games and

B.T. Hyman Abeta deposition is associated with neuropil changes, but not with

overt neuronal loss in the human amyloid precursor protein V717F (PDAPP)

transgenic mouse, J Neurosci 17 (1997) 7053-7059.

[66] R. Crook, A. Verkkoniemi, J. Perez-Tur, N. Mehta, M. Baker, H. Houlden, M.

Farrer, M. Hutton, S. Lincoln, J. Hardy, K. Gwinn, M. Somer, A. Paetau, H.

Kalimo, R. Ylikoski, M. Poyhonen, S. Kucera and M. Haltia A variant of

Alzheimer's disease with spastic paraparesis and unusual plaques due to

deletion of exon 9 of presenilin 1, Nat Med 4 (1998) 452-455.

References

259

[67] H. Houlden, M. Baker, E. McGowan, P. Lewis, M. Hutton, R. Crook, N.W.

Wood, S. Kumar-Singh, J. Geddes, M. Swash, F. Scaravilli, J.L. Holton, T.

Lashley, T. Tomita, T. Hashimoto, A. Verkkoniemi, H. Kalimo, M. Somer, A.

Paetau, J.J. Martin, C. Van Broeckhoven, T. Golde, J. Hardy, M. Haltia and T.

Revesz Variant Alzheimer's disease with spastic paraparesis and cotton wool

plaques is caused by PS-1 mutations that lead to exceptionally high amyloid-

beta concentrations, Ann Neurol 48 (2000) 806-808.

[68] H. Braak and K. Del Tredici Alzheimer's disease: intraneuronal alterations

precede insoluble amyloid-beta formation, Neurobiol Aging 25 (2004) 713-718;

discussion 743-716.

[69] H. Braak and E. Braak Frequency of stages of Alzheimer-related lesions in

different age categories, Neurobiol Aging 18 (1997) 351-357.

[70] j.l. Price, Morris,j.c So what if tangles precede plaques?, Neurobiology of

ageing 25 (2004) 721-723.

[71] J.C. Morris, M. Storandt, D.W. McKeel, Jr., E.H. Rubin, J.L. Price, E.A. Grant

and L. Berg Cerebral amyloid deposition and diffuse plaques in "normal"

aging: Evidence for presymptomatic and very mild Alzheimer's disease,

Neurology 46 (1996) 707-719.

[72] W. Silverman, H.M. Wisniewski, M. Bobinski and J. Wegiel Frequency of

stages of Alzheimer-related lesions in different age categories, Neurobiol

Aging 18 (1997) 377-379; discussion 389-392.

[73] J.L. Price Tangles and plaques in healthy aging and Alzheimer's disease.

independence or interaction?, Semin neurosci 6 (1994) 395-402.

[74] M. Nishimura, G. Yu and P.H. St George-Hyslop Biology of presenilins as

causative molecules for Alzheimer disease, Clin Genet 55 (1999) 219-225.

References

260

[75] J. Hardy The genetic causes of neurodegenerative diseasesi, Joural of

Alzheimer's disease 3 (2001) 109-116.

[76] N. Suzuki, T.T. Cheung, X.D. Cai, A. Odaka, L. Otvos, Jr., C. Eckman, T.E.

Golde and S.G. Younkin An increased percentage of long amyloid beta protein

secreted by familial amyloid beta protein precursor (beta APP717) mutants,

Science 264 (1994) 1336-1340.

[77] J. Theuns, J. Del-Favero, B. Dermaut, C.M. van Duijn, H. Backhovens, M.V.

Van den Broeck, S. Serneels, E. Corsmit, C.V. Van Broeckhoven and M. Cruts

Genetic variability in the regulatory region of presenilin 1 associated with risk

for Alzheimer's disease and variable expression, Hum Mol Genet 9 (2000)

325-331.

[78] M. Wragg, M. Hutton and C. Talbot Genetic association between intronic

polymorphism in presenilin-1 gene and late-onset Alzheimer's disease.

Alzheimer's Disease Collaborative Group, Lancet 347 (1996) 509-512.

[79] A.D. Roses A model for susceptibility polymorphisms for complex

diseases:apolipoprotein E and alzheimer's disease, Neurogenetics 1 (1997) 3-

11.

[80] E.H. Corder, A.M. Saunders, W.J. Strittmatter, D.E. Schmechel, P.C. Gaskell,

G.W. Small, A.D. Roses, J.L. Haines and M.A. Pericak-Vance Gene dose of

apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset

families, Science 261 (1993) 921-923.

[81] R.C. Dodel, Y. Du, K.R. Bales, F. Gao, B. Eastwood, B. Glazier, R. Zimmer, B.

Cordell, A. Hake, R. Evans, D. Gallagher-Thompson, L.W. Thompson, J.R.

Tinklenberg, A. Pfefferbaum, E.V. Sullivan, J. Yesavage, L. Alstiel, T. Gasser,

References

261

M.R. Farlow, G.M. Murphy, Jr. and S.M. Paul Alpha2 macroglobulin and the

risk of Alzheimer's disease, Neurology 54 (2000) 438-442.

[82] D. Blacker, M.A. Wilcox, N.M. Laird, L. Rodes, S.M. Horvath, R.C. Go, R.

Perry, B. Watson, Jr., S.S. Bassett, M.G. McInnis, M.S. Albert, B.T. Hyman

and R.E. Tanzi Alpha-2 macroglobulin is genetically associated with Alzheimer

disease, Nat Genet 19 (1998) 357-360.

[83] L. Bertram, D. Blacker, K. Mullin, D. Keeney, J. Jones, S. Basu, S. Yhu, M.G.

McInnis, R.C. Go, K. Vekrellis, D.J. Selkoe, A.J. Saunders and R.E. Tanzi

Evidence for genetic linkage of Alzheimer's disease to chromosome 10q,

Science 290 (2000) 2302-2303.

[84] N. Ertekin-Taner, N. Graff-Radford, L.H. Younkin, C. Eckman, M. Baker, J.

Adamson, J. Ronald, J. Blangero, M. Hutton and S.G. Younkin Linkage of

plasma Abeta42 to a quantitative locus on chromosome 10 in late-onset

Alzheimer's disease pedigrees, Science 290 (2000) 2303-2304.

[85] M. Takehashi, S. Tanaka, E. Masliah and K. Ueda Association of monoamine

oxidase A gene polymorphism with Alzheimer's disease and Lewy body

variant, Neurosci Lett 327 (2002) 79-82.

[86] O. Combarros, J. Infante, J. Llorca, N. Pena, C. Fernandez-Viadero and J.

Berciano The myeloperoxidase gene in Alzheimer's disease: a case-control

study and meta-analysis, Neurosci Lett 326 (2002) 33-36.

[87] F.C. Crawford, M.J. Freeman, J.A. Schinka, M.D. Morris, L.I. Abdullah, D.

Richards, S. Sevush, R. Duara and M.J. Mullan Association between

Alzheimer's disease and a functional polymorphism in the Myeloperoxidase

gene, Exp Neurol 167 (2001) 456-459.

References

262

[88] U. Byrne, Waldvogel,H. , Dragunow,M. ,Kettle,A., Faull, R. Myeloperoxidase

expression in alzheimer's disease, Experimental neurology 155 (1999) 31-41.

[89] H. Tanahashi, T. Asada and T. Tabira Association between tau polymorphism

and male early-onset Alzheimer's disease, Neuroreport 15 (2004) 175-179.

[90] M.J. Bullido, J. Aldudo, A. Frank, F. Coria, J. Avila and F. Valdivieso A

polymorphism in the tau gene associated with risk for Alzheimer's disease,

Neurosci Lett 278 (2000) 49-52.

[91] S. Mace, E. Cousin, S. Ricard, E. Genin, E. Spanakis, C. Lafargue-Soubigou,

B. Genin, R. Fournel, S. Roche, G. Haussy, F. Massey, S. Soubigou, G.

Brefort, P. Benoit, A. Brice, D. Campion, M. Hollis, L. Pradier, J. Benavides

and J.F. Deleuze ABCA2 is a strong genetic risk factor for early-onset

Alzheimer's disease, Neurobiol Dis 18 (2005) 119-125.

[92] F. Licastro, M. Chiappelli, L.M. Grimaldi, K. Morgan, N. Kalsheker, E.

Calabrese, A. Ritchie, E. Porcellini, G. Salani, M. Franceschi and N. Canal A

new promoter polymorphism in the alpha-1-antichymotrypsin gene is a

disease modifier of Alzheimer's disease, Neurobiol Aging 26 (2005) 449-453.

[93] L. Bertram, M. Hiltunen, M. Parkinson, M. Ingelsson, C. Lange, K. Ramasamy,

K. Mullin, R. Menon, A.J. Sampson, M.Y. Hsiao, K.J. Elliott, G. Velicelebi, T.

Moscarillo, B.T. Hyman, S.L. Wagner, K.D. Becker, D. Blacker and R.E. Tanzi

Family-based association between Alzheimer's disease and variants in

UBQLN1, N Engl J Med 352 (2005) 884-894.

[94] A.L. Mah, G. Perry, M.A. Smith and M.J. Monteiro Identification of ubiquilin, a

novel presenilin interactor that increases presenilin protein accumulation, J

Cell Biol 151 (2000) 847-862.

References

263

[95] M. Baker, I.R. Mackenzie, S.M. Pickering-Brown, J. Gass, R. Rademakers, C.

Lindholm, J. Snowden, J. Adamson, A.D. Sadovnick, S. Rollinson, A. Cannon,

E. Dwosh, D. Neary, S. Melquist, A. Richardson, D. Dickson, Z. Berger, J.

Eriksen, T. Robinson, C. Zehr, C.A. Dickey, R. Crook, E. McGowan, D. Mann,

B. Boeve, H. Feldman and M. Hutton Mutations in progranulin cause tau-

negative frontotemporal dementia linked to chromosome 17, Nature 442

(2006) 916-919.

[96] L. Petrozzi, C. Lucetti, R. Scarpato, G. Gambaccini, F. Trippi, S. Bernardini, P.

Del Dotto, L. Migliore and U. Bonuccelli Cytogenetic alterations in lymphocytes

of Alzheimer's disease and Parkinson's disease patients, Neurol Sci 23 Suppl

2 (2002) S97-98.

[97] L. Migliore, A. Testa, R. Scarpato, N. Pavese, L. Petrozzi and U. Bonuccelli

Spontaneous and induced aneuploidy in peripheral blood lymphocytes of

patients with Alzheimer's disease, Hum Genet 101 (1997) 299-305.

[98] L. Migliore, N. Botto, R. Scarpato, L. Petrozzi, G. Cipriani and U. Bonuccelli

Preferencial occurence of chromosome 21 malsegregation in peripheral blood

lymphocytes of alzheimer disease patients, Cytogenet cell genet 87 (1999) 41-

46.

[99] L.N. Geller and H. Potter Chromosome missegregation and trisomy 21

mosaicism in Alzheimer's disease, Neurobiol Dis 6 (1999) 167-179.

[100] H. Potter Review and hypothesis: Alzheimer disease and Down syndrome--

chromosome 21 nondisjunction may underlie both disorders, Am J Hum Genet

48 (1991) 1192-1200.

References

264

[101] H.M. Wisniewski, A. Rabe and K.E. Wisniewski Neuropathology and dementia

in people with Down's syndrome, Cold spring harbour Laboratory Press, New

York, 1988.

[102] J.K. Teller, C. Russo, L.M. DeBusk, G. Angelini, D. Zaccheo, F. Dagna-

Bricarelli, P. Scartezzini, S. Bertolini, D.M. Mann, M. Tabaton and P. Gambetti

Presence of soluble amyloid beta-peptide precedes amyloid plaque formation

in Down's syndrome, Nat Med 2 (1996) 93-95.

[103] X. Wang, P. Thomas, J. Xue and M. Fenech Folate deficiency induces

aneuploidy in human lymphocytes in vitro-evidence using cytokinesis-blocked

cells and probes specific for chromosomes 17 and 21, Mutat Res 551 (2004)

167-180.

[104] G.D. Schellenberg, T.D. Bird, E.M. Wijsman, H.T. Orr, L. Anderson, E.

Nemens, J.A. White, L. Bonnycastle, J.L. Weber, M.E. Alonso and et al.

Genetic linkage evidence for a familial Alzheimer's disease locus on

chromosome 14, Science 258 (1992) 668-671.

[105] R. Sherrington, E.I. Rogaev, Y. Liang, E.A. Rogaeva, G. Levesque, M. Ikeda,

H. Chi, C. Lin, G. Li, K. Holman and et al. Cloning of a gene bearing missense

mutations in early-onset familial Alzheimer's disease, Nature 375 (1995) 754-

760.

[106] J. Li, M. Xu, H. Zhou, J. Ma and H. Potter Alzheimer presenilins in the nuclear

membrane, interphase kinetochores, and centrosomes suggest a role in

chromosome segregation, Cell 90 (1997) 917-927.

[107] G. Deng, C.J. Pike and C.W. Cotman Alzheimer-associated presenilin-2

confers increased sensitivity to apoptosis in PC12 cells, FEBS Lett 397 (1996)

50-54.

References

265

[108] T. Wisniewski, J. Ghiso and B. Frangione Biology of A beta amyloid in

Alzheimer's disease, Neurobiol Dis 4 (1997) 313-328.

[109] S. Das and H. Potter Expression of the Alzheimer amyloid promoting factor

antichymotrypsin is induced in human astrocytes by IL-1., Neuron 14 (1995)

447-456.

[110] M.J. Ramirez, S. Puerto, P. Galofre, E.M. Parry, J.M. Parry, A. Creus, R.

Marcos and J. Surralles Multicolour FISH detection of radioactive iodine-

induced 17cen-p53 chromosomal breakage in buccal cells from therapeutically

exposed patients, Carcinogenesis 21 (2000) 1581-1586.

[111] J. Surralles, M.P. Hande, R. Marcos and P.M. Lansdorp Accelerated telomere

shortening in the human inactive X chromosome, Am J Hum Genet 65 (1999)

1617-1622.

[112] L.A. Panossian, V.R. Porter, H.F. Valenzuela, X. Zhu, E. Reback, D.

Masterman, J.L. Cummings and R.B. Effros Telomere shortening in T cells

correlates with Alzheimer's disease status, Neurobiol Aging 24 (2003) 77-84.

[113] N. Rufer, T.H. Brummendorf, S. Kolvraa, C. Bischoff, K. Christensen, L.

Wadsworth, M. Schulzer and P.M. Lansdorp Telomere fluorescence

measurements in granulocytes and T lymphocyte subsets point to a high

turnover of hematopoietic stem cells and memory T cells in early childhood, J

Exp Med 190 (1999) 157-167.

[114] X. Wu, C.I. Amos, Y. Zhu, H. Zhao, B.H. Grossman, J.W. Shay, S. Luo, W.K.

Hong and M.R. Spitz Telomere dysfunction: a potential cancer predisposition

factor, J Natl Cancer Inst 95 (2003) 1211-1218.

References

266

[115] R.M. Cawthon, K.R. Smith, E. O'Brien, A. Sivatchenko and R.A. Kerber

Association between telomere length in blood and mortality in people aged 60

years or older, Lancet 361 (2003) 393-395.

[116] V.s. Thomas von Zglinicki, Mario lorenz, Gabriele Saretzki, Romana Lenzen-

grobimlighaus, Reiner Gebner, Angela Risch, Elisabeth Steinhagen-Thiessen

Short telomeres in parients with vascular dementia: An indicator of low

antioxidative capacity and a possible risk factor ?, Laboratory investigation 80

(2000) 1739-1747.

[117] V. Pennaneach and R.D. Kolodner Recombination and the Tel1 and Mec1

checkpoints differentially effect genome rearrangements driven by telomere

dysfunction in yeast, 36 (2004) 612-617.

[118] D. Shore CELL BIOLOGY:Enhanced: Telomeres--Unsticky Ends, Science 281

(1998) 1818-1819.

[119] C. Scheel, K.L. Schaefer, A. Jauch, M. Keller, D. Wai, C. Brinkschmidt, F. van

Valen, W. Boecker, B. Dockhorn-Dworniczak and C. Poremba Alternative

lengthening of telomeres is associated with chromosomal instability in

osteosarcomas, Oncogene 20 (2001) 3835-3844.

[120] M. Fenech and J.W. Crott Micronuclei, nucleoplasmic bridges and nuclear

buds induced in folic acid deficient human lymphocytes-evidence for

breakage-fusion-bridge cycles in the cytokinesis-block micronucleus assay,

Mutat Res 504 (2002) 131-136.

[121] B. McClintock Spotaneous alterations in chromosome size and form in Zea

mays, Cold spring Harb Sym quant Biol 8 (1941) 72-81.

References

267

[122] U. Martens, Zijlmans m,j,m, Poon,s. dragowska, W. Yui,J. Chavez, E.A,

Ward,R,K. Lansdorp,P.M Short telomeres on human chromosome 17p, Nature

genetics 18 (1998) 76-80.

[123] A.W. Lo, L. Sabatier, B. Fouladi, G. Pottier, M. Ricoul and J.P. Murnane DNA

amplification by breakage/fusion/bridge cycles initiated by spontaneous

telomere loss in a human cancer cell line, Neoplasia 4 (2002) 531-538.

[124] N.T. Leach, C. Rehder, K. Jensen, S. Holt and C. Jackson-Cook Human

chromosomes with shorter telomeres and large heterochromatin regions have

a higher frequency of acquired somatic cell aneuploidy, Mech Ageing Dev 125

(2004) 563-573.

[125] R.S. Maser and R.A. DePinho Connecting chromosomes, crisis, and cancer,

Science 297 (2002) 565-569.

[126] T.v. Zglinicki Oxidative stress shorrtens telomeres, Trends in biochemical

sciences 27 (2002) 339-344.

[127] S.P. Gabbita, Lovell,M.A., Markesbery,W.R. Increased nuclear DNA oxidation

in the brain in Alzheimer's disease, J Neurochem 71 (1998) 2034-2040.

[128] M.A. Lovell, S.P. Gabbita and W.R. Markesbery Increased DNA oxidation and

decreased levels of repair products in Alzheimer's disease ventricular CSF, J

Neurochem 72 (1999) 771-776.

[129] P. Mecocci, M.C. Polidori, T. Ingegni, A. Cherubini, F. Chionne, R. Cecchetti

and U. Senin Oxidative damage to DNA in lymphocytes from AD patients,

Neurology 51 (1998) 1014-1017.

[130] M.A. Smith, M. Rudnicka-Nawrot, P.L. Richey, D. Praprotnik, P. Mulvihill, C.A.

Miller, L.M. Sayre and G. Perry Carbonyl-related posttranslational modification

References

268

of neurofilament protein in the neurofibrillary pathology of Alzheimer's disease,

J Neurochem 64 (1995) 2660-2666.

[131] M. Miyata and J.D. Smith Apolipoprotein E allele-specific antioxidant activity

and effects on cytotoxicity by oxidative insults and beta-amyloid peptides, Nat

Genet 14 (1996) 55-61.

[132] J. Poirier Apolipoprotein E in animal models of CNS injury and in Alzheimer's

disease, Trends Neurosci 17 (1994) 525-530.

[133] K. Ramasamy, Krzywokowski, P., Bastianetto,S. Apolipoprotein E, oxidative

stress and EGb 761 in Alzheimer's disease brain, packer, L., Christen, Y., eds

Ginkgo biloba extract (EGb 761) study: lessson from cell biology.

Paris:elsevier, 1998:69-83 (1998).

[134] L. Migliore, I. Fontana, F. Trippi, R. Colognato, F. Coppede, G. Tognoni, B.

Nucciarone and G. Siciliano Oxidative DNA damage in peripheral leukocytes

of mild cognitive impairment and AD patients, Neurobiol Aging 26 (2005) 567-

573.

[135] M. Flint Beal Oxidative damage as an early marker of Alzheimer's disease and

mild cognitive impairment, neurobiology of ageing 26 (2005) 585-586.

[136] P. Mecocci, M.C. Polidori, A. Cherubini, T. Ingegni, P. Mattioli, M. Catani, P.

Rinaldi, R. Cecchetti, W. Stahl, U. Senin and M.F. Beal Lymphocyte oxidative

DNA damage and plasma antioxidants in Alzheimer disease, Arch Neurol 59

(2002) 794-798.

[137] A. Nunomura, G. Perry, G. Aliev, K. Hirai, A. Takeda, E.K. Balraj, P.K. Jones,

H. Ghanbari, T. Wataya, S. Shimohama, S. Chiba, C.S. Atwood, R.B.

Petersen and M.A. Smith Oxidative damage is the earliest event in Alzheimer

disease, J Neuropathol Exp Neurol 60 (2001) 759-767.

References

269

[138] P.S. Aisen, S. Egelko, H. Andrews, R. Diaz-Arrastia, M. Weiner, C. DeCarli,

W. Jagust, J.W. Miller, R. Green, K. Bell and M. Sano A pilot study of vitamins

to lower plasma homocysteine levels in Alzheimer disease, Am J Geriatr

Psychiatry 11 (2003) 246-249.

[139] T.B. Shea and E. Rogers Homocysteine and dementia, N Engl J Med 346

(2002) 2007; author reply 2008.

[140] S. Scarpa, A. Fuso, F. D'Anselmi and R.A. Cavallaro Presenilin 1 gene

silencing by S-adenosylmethionine: a treatment for Alzheimer disease?, FEBS

Lett 541 (2003) 145-148.

[141] T. Suzuki, M. Fujii and D. Ayusawa Demethylation of classical satellite 2 and 3

DNA with chromosomal instability in senescent human fibroblasts, Exp

Gerontol 37 (2002) 1005-1014.

[142] M. Fenech The role of folic acid and Vitamin B12 in genomic stability of human

cells, Mutat Res 475 (2001) 57-67.

[143] J.M. Zingg and P.A. Jones Genetic and epigenetic aspects of DNA

methylation on genome expression, evolution, mutation and carcinogenesis,

Carcinogenesis 18 (1997) 869-882.

[144] R. Clarke, A.D. Smith, K.A. Jobst, H. Refsum, L. Sutton and P.M. Ueland

Folate, Vitamin B12, and Serum Total Homocysteine Levels in Confirmed

Alzheimer Disease, Arch Neurol 55 (1998) 1449-1455.

[145] M.S. Morris Homocysteine and Alzheimer's disease, Lancet Neurol 2 (2003)

425-428.

[146] S. Seshadri, A. Beiser, J. Selhub, P.F. Jacques, I.H. Rosenberg, R.B.

D'Agostino, P.W. Wilson and P.A. Wolf Plasma homocysteine as a risk factor

for dementia and Alzheimer's disease, N Engl J Med 346 (2002) 476-483.

References

270

[147] H.X. Wang, A. Wahlin, H. Basun, J. Fastbom, B. Winblad and L. Fratiglioni

Vitamin B(12) and folate in relation to the development of Alzheimer's disease,

Neurology 56 (2001) 1188-1194.

[148] A. McCaddon, G. Davies, P. Hudson, S. Tandy and H. Cattell Total serum

homocysteine in senile dementia of Alzheimer type, Int J Geriatr Psychiatry 13

(1998) 235-239.

[149] Kruman, II, T.S. Kumaravel, A. Lohani, W.A. Pedersen, R.G. Cutler, Y.

Kruman, N. Haughey, J. Lee, M. Evans and M.P. Mattson Folic acid deficiency

and homocysteine impair DNA repair in hippocampal neurons and sensitize

them to amyloid toxicity in experimental models of Alzheimer's disease, J

Neurosci 22 (2002) 1752-1762.

[150] J.H. Williams, E.A. Pereira, M.M. Budge and K.M. Bradley Minimal

hippocampal width relates to plasma homocysteine in community-dwelling

older people, Age Ageing 31 (2002) 440-444.

[151] T. den Heijer, S.E. Vermeer and R. Clarke Homocysteine and brain atrophy on

MRI of non-demented elderly., Brain 126 (2003) 170-175.

[152] B.E. Dwyer, A.K. Raina, G. Perry and M.A. Smith Homocysteine and

Alzheimer's disease: a modifiable risk?, Free Radic Biol Med 36 (2004) 1471-

1475.

[153] M.P. Mattson and T.B. Shea Folate and homocysteine metabolism in neural

plasticity and neurodegenerative disorders, Trends Neurosci 26 (2003) 137-

146.

[154] T.B. Shea, J. Lyons-Weiler and E. Rogers Homocysteine, folate deprivation

and Alzheimer neuropathology, J Alzheimers Dis 4 (2002) 261-267.

References

271

[155] D. Bunce, M. Kivipelto and A. Wahlin Utilization of cognitive support in

episodic free recall as a function of apolipoprotein E and vitamin B12 or folate

among adults aged 75 years and older, Neuropsychology 18 (2004) 362-370.

[156] M.C. Morris, D.A. Evans, J.L. Bienias, P.A. Scherr, C.C. Tangney, L.E. Hebert,

D.A. Bennett, R.S. Wilson and N. Aggarwal Dietary niacin and the risk of

incident Alzheimer's disease and of cognitive decline, J Neurol Neurosurg

Psychiatry 75 (2004) 1093-1099.

[157] M. Cohen-Armon, L. Visochek, A. Katzoff, D. Levitan, A.J. Susswein, R. Klein,

M. Valbrun and J.H. Schwartz Long-term memory requires polyADP-

ribosylation, Science 304 (2004) 1820-1822.

[158] W. Qin, T. Yang, L. Ho, Z. Zhao, J. Wang, L. Chen, M. Thiyagarajan, D.

Macgrogan, J.T. Rodgers, P. Puigserver, J. Sadoshima, H.H. Deng, S.

Pedrini, S. Gandy, A. Sauve and G.M. Pasinetti Neuronal SIRT1 activation as

a novel mechanism underlying the prevention of Alzheimer's disease amyloid

neuropathology by calorie restriction, J Biol Chem (2006).

[159] S.J. James, M. Pogribna, I.P. Pogribny, S. Melnyk, R.J. Hine, J.B. Gibson, P.

Yi, D.L. Tafoya, D.H. Swenson, V.L. Wilson and D.W. Gaylor Abnormal folate

metabolism and mutation in the methylenetetrahydrofolate reductase gene

may be maternal risk factors for Down syndrome, Am J Clin Nutr 70 (1999)

495-501.

[160] P. Frosst, H.J. Blom, R. Milos, P. Goyette, C.A. Sheppard, R.G. Matthews,

G.J. Boers, M. den Heijer, L.A. Kluijtmans, L.P. van den Heuvel and et al. A

candidate genetic risk factor for vascular disease: a common mutation in

methylenetetrahydrofolate reductase, Nat Genet 10 (1995) 111-113.

References

272

[161] K.J. Lievers, G.H. Boers, P. Verhoef, M. den Heijer, L.A. Kluijtmans, N.M. van

der Put, F.J. Trijbels and H.J. Blom A second common variant in the

methylenetetrahydrofolate reductase (MTHFR) gene and its relationship to

MTHFR enzyme activity, homocysteine, and cardiovascular disease risk, J Mol

Med 79 (2001) 522-528.

[162] T. Brunelli, S. Bagnoli, B. Giusti, B. Nacmias, G. Pepe, S. Sorbi and R. Abbate

The C677T methylenetetrahydrofolate reductase mutation is not associated

with Alzheimer's disease, Neurosci Lett 315 (2001) 103-105.

[163] Y. Wakutani, H. Kowa, M. Kusumi, K. Nakaso, K. Yasui, K. Isoe-Wada, H.

Yano, K. Urakami, T. Takeshima and K. Nakashima A haplotype of the

methylenetetrahydrofolate reductase gene is protective against late-onset

Alzheimer's disease, Neurobiol Aging 25 (2004) 291-294.

[164] K. Beyer, J.I. Lao, P. Latorre, N. Riutort, B. Matute, M.T. Fernandez-Figueras,

J.L. Mate and A. Ariza Methionine synthase polymorphism is a risk factor for

Alzheimer disease, Neuroreport 14 (2003) 1391-1394.

[165] A. McCaddon, P. Hudson, D. Hill, J. Barber, A. Lloyd, G. Davies and B.

Regland Alzheimer's disease and total plasma aminothiols, Biol Psychiatry 53

(2003) 254-260.

[166] L.D. Morrison, D.D. Smith and S.J. Kish Brain S-adenosylmethionine levels

are severely decreased in Alzheimer's disease, J Neurochem 67 (1996) 1328-

1331.

[167] K. Abe, Kimura,H. the possible role of hydrogen sulphide as an endogenous

Neuromodulator, Journal of neuroscience 16 (1996) 1066-1071.

References

273

[168] K. Eto, T. Asada, K. Arima, T. Makifuchi and H. Kimura Brain hydrogen

sulphide is severely decreased in Alzheimer's disease, Biochem Biophys Res

Commun 293 (2002) 1485-1488.

[169] Y. Kimura and H. Kimura Hydrogen sulfide protects neurons from oxidative

stress, Faseb J 18 (2004) 1165-1167.

[170] S. Barbaux, R. Plomin and A. Whitehesd Polymorphisms of genes controlling

honmocysteine/folate metabolism and cognitive function., Neuroreport 11

(2000) 1133-1136.

[171] S.L. Payao, M.D. Smith and P.H. Bertolucci Differential chromosome

sensitivity to 5-azacytidine in Alzheimer's disease, Gerontology 44 (1998) 267-

271.

[172] L.S. Andrea Fuso, Rosaria A. Cavallaro, Fabrizio D'Anselmi, Sifrido Scarpa S-

adenosylmethionine/homocysteine cycle alterations modify DNA methylation

status with consequent deregulation of PS1 and BACE and beta-amyloid

production., Mol.Cell.Neuroscience 28 (2005) 195-204.

[173] R.L. West, J.M. Lee and L.E. Maroun Hypomethylation of the amyloid

precursor protein gene in the brain of an Alzheimer's disease patient, J Mol

Neurosci 6 (1995) 141-146.

[174] G. Perry, A.K. Raina, A. Nunomura, T. Wataya, L.M. Sayre and M.A. Smith

How important is oxidative damage? Lessons from Alzheimer's disease, Free

Radic Biol Med 28 (2000) 831-834.

[175] G. Perry, M.A. Taddeo, A. Nunomura, X. Zhu, T. Zenteno-Savin, K.L. Drew, S.

Shimohama, J. Avila, R.J. Castellani and M.A. Smith Comparative biology and

pathology of oxidative stress in Alzheimer and other neurodegenerative

References

274

diseases: beyond damage and response, Comp Biochem Physiol C Toxicol

Pharmacol 133 (2002) 507-513.

[176] P.P. Zandi, J.C. Anthony, A.S. Khachaturian, S.V. Stone, D. Gustafson, J.T.

Tschanz, M.C. Norton, K.A. Welsh-Bohmer and J.C. Breitner Reduced risk of

Alzheimer disease in users of antioxidant vitamin supplements: the Cache

County Study, Arch Neurol 61 (2004) 82-88.

[177] C. Rota, Rimbach,G., Minnihane,A., Stocecklin,E., Barella,L. Dietary Vitamin E

modulates differential gene expression in the rat hippocampus:Potential

implications for its neuroprotective properties, Nutritional neuroscience 8

(2005) 21-29.

[178] J.M. Ringman, S.A. Frautschy, G.M. Cole, D.L. Masterman and J.L.

Cummings A potential role of the curry spice curcumin in Alzheimer's disease,

Curr Alzheimer Res 2 (2005) 131-136.

[179] L.G. Yang F, Begum AN, Ubeda OJ, Simmons MR, Ambegaokar SS, Chen

PP, and G.C. Kayed R, Frautschy SA, Cole GM. curcumin inhibits formation of

amyloid beta oligomers and fibrils , binds plaques, and reduces amyloid in

vivo, j biol chem 18 (2005) 5892-5901.

[180] K. Ono, K. Hasegawa, H. Naiki and M. Yamada Preformed beta-amyloid fibrils

are destabilized by coenzyme Q10 in vitro, Biochem Biophys Res Commun

330 (2005) 111-116.

[181] L. Baum and A. Ng Curcumin interaction with copper and iron suggests one

possible mechanism of action in Alzheimer's disease animal models, J

Alzheimers Dis 6 (2004) 367-377; discussion 443-369.

References

275

[182] X. Wu, G.R. Beecher, J.M. Holden, D.B. Haytowitz, S.E. Gebhardt and R.L.

Prior Lipophilic and hydrophilic antioxidant capacities of common foods in the

United States, J Agric Food Chem 52 (2004) 4026-4037.

[183] J.A. Joseph, N.A. Denisova, G. Arendash, M. Gordon, D. Diamond, B. Shukitt-

Hale and D. Morgan Blueberry supplementation enhances signaling and

prevents behavioral deficits in an Alzheimer disease model, Nutr Neurosci 6

(2003) 153-162.

[184] J.A. Joseph, B. Shukitt-Hale, N.A. Denisova, D. Bielinski, A. Martin, J.J.

McEwen and P.C. Bickford Reversals of age-related declines in neuronal

signal transduction, cognitive, and motor behavioral deficits with blueberry,

spinach, or strawberry dietary supplementation, J Neurosci 19 (1999) 8114-

8121.

[185] J. Shi, J. Yu, J.E. Pohorly and Y. Kakuda Polyphenolics in grape seeds-

biochemistry and functionality, J Med Food 6 (2003) 291-299.

[186] M.H. Li, J.H. Jang, B. Sun and Y.J. Surh Protective effects of oligomers of

grape seed polyphenols against beta-amyloid-induced oxidative cell death,

Ann N Y Acad Sci 1030 (2004) 317-329.

[187] J. Deshane, L. Chaves, K.V. Sarikonda, S. Isbell, L. Wilson, M. Kirk, C.

Grubbs, S. Barnes, S. Meleth and H. Kim Proteomics analysis of rat brain

protein modulations by grape seed extract, J Agric Food Chem 52 (2004)

7872-7883.

[188] S. Mandel, T. Amit, L. Reznichenko, O. Weinreb and M.B. Youdim Green tea

catechins as brain-permeable, natural iron chelators-antioxidants for the

treatment of neurodegenerative disorders, Mol Nutr Food Res 50 (2006) 229-

234.

References

276

[189] K. Rezai-Zadeh, D. Shytle, N. Sun, T. Mori, H. Hou, D. Jeanniton, J. Ehrhart,

K. Townsend, J. Zeng, D. Morgan, J. Hardy, T. Town and J. Tan Green tea

epigallocatechin-3-gallate (EGCG) modulates amyloid precursor protein

cleavage and reduces cerebral amyloidosis in Alzheimer transgenic mice, J

Neurosci 25 (2005) 8807-8814.

[190] E.J. Okello, S.U. Savelev and E.K. Perry In vitro anti-beta-secretase and dual

anti-cholinesterase activities of Camellia sinensis L. (tea) relevant to treatment

of dementia, Phytother Res 18 (2004) 624-627.

[191] S. Kuriyama, A. Hozawa, K. Ohmori, T. Shimazu, T. Matsui, S. Ebihara, S.

Awata, R. Nagatomi, H. Arai and I. Tsuji Green tea consumption and cognitive

function: a cross-sectional study from the Tsurugaya Project 1, Am J Clin Nutr

83 (2006) 355-361.

[192] A.I. Bush Metals and neuroscience, Curr Opin Chem Biol 4 (2000) 184-191.

[193] S. Assaf and Chungs-h Release of endogenous Zinc from brain tissue, Nature

308 (1984) 734-736.

[194] A. Bush and R. Tanzi The galavanization of b-amyloid in alzheimer's disease,

Proceedings of the National Academy of sciences 99 (2002) 7317-7319.

[195] M.A. Lovell, J.D. Robertson, W.J. Teesdale, J.L. Campbell and W.R.

Markesbery Copper, iron and zinc in Alzheimer's disease senile plaques, J

Neurol Sci 158 (1998) 47-52.

[196] S.W. Suh, K.B. Jensen, M.S. Jensen, D.S. Silva, P.J. Kesslak, G. Danscher

and C.J. Frederickson Histochemically-reactive zinc in amyloid plaques,

angiopathy, and degenerating neurons of Alzheimer's diseased brains, Brain

Res 852 (2000) 274-278.

References

277

[197] C.S. Atwood, R.D. Moir, X. Huang, R.C. Scarpa, N.M. Bacarra, D.M. Romano,

M.A. Hartshorn, R.E. Tanzi and A.I. Bush Dramatic aggregation of Alzheimer

abeta by Cu(II) is induced by conditions representing physiological acidosis, J

Biol Chem 273 (1998) 12817-12826.

[198] X. Huang, C.S. Atwood, M.A. Hartshorn, G. Multhaup, L.E. Goldstein, R.C.

Scarpa, M.P. Cuajungco, D.N. Gray, J. Lim, R.D. Moir, R.E. Tanzi and A.I.

Bush The A beta peptide of Alzheimer's disease directly produces hydrogen

peroxide through metal ion reduction, Biochemistry 38 (1999) 7609-7616.

[199] X. Huang, M.P. Cuajungco, C.S. Atwood, M.A. Hartshorn, J.D. Tyndall, G.R.

Hanson, K.C. Stokes, M. Leopold, G. Multhaup, L.E. Goldstein, R.C. Scarpa,

A.J. Saunders, J. Lim, R.D. Moir, C. Glabe, E.F. Bowden, C.L. Masters, D.P.

Fairlie, R.E. Tanzi and A.I. Bush Cu(II) potentiation of alzheimer abeta

neurotoxicity. Correlation with cell-free hydrogen peroxide production and

metal reduction, J Biol Chem 274 (1999) 37111-37116.

[200] A.I. Bush Metal complexing agents as therapies for Alzheimer's disease,

Neurobiology of aging (2002) 1031-1038.

[201] M.P. Cuajungco, L.E. Goldstein, A. Nunomura, M.A. Smith, J.T. Lim, C.S.

Atwood, X. Huang, Y.W. Farrag, G. Perry and A.I. Bush Evidence that the

beta-amyloid plaques of Alzheimer's disease represent the redox-silencing

and entombment of abeta by zinc, J Biol Chem 275 (2000) 19439-19442.

[202] J.Y. Lee, I. Mook-Jung and J.Y. Koh Histochemically reactive zinc in plaques

of the Swedish mutant beta-amyloid precursor protein transgenic mice, J

Neurosci 19 (1999) RC10.

References

278

[203] S. Gonzalez, J.M. Huerta, J. Alvarez-Uria, S. Fernandez, A.M. Patterson and

C. Lasheras Serum selenium is associated with plasma homocysteine

concentrations in elderly humans, J Nutr 134 (2004) 1736-1740.

[204] D.P. Perl and A.R. Brody Alzheimer's disease: X-ray spectrometric evidence

of aluminum accumulation in neurofibrillary tangle-bearing neurons, Science

208 (1980) 297-299.

[205] P.F. Good, D.P. Perl, L.M. Bierer and J. Schmeidler Selective accumulation of

aluminum and iron in the neurofibrillary tangles of Alzheimer's disease: a laser

microprobe (LAMMA) study, Ann Neurol 31 (1992) 286-292.

[206] S. Duckett, P. Galle, R. Escourolle and F. Grey [Presence of aluminum and

magnesium in the cerebral arteries and parenchyma of patients with

striatonigral syndrome: study by Castaing's microprobe], C R Acad Sci Hebd

Seances Acad Sci D 282 (1976) 2115-2117.

[207] J.P. Landsberg, B. McDonald and F. Watt Absence of aluminium in neuritic

plaque cores in Alzheimer's disease, Nature 360 (1992) 65-68.

[208] L.C. Neri and D. Hewitt Aluminium, Alzheimer's disease, and drinking water,

Lancet 338 (1991) 390.

[209] T.P. Flaten Aluminium as a risk factor in Alzheimer's disease, with emphasis

on drinking water, Brain Res Bull 55 (2001) 187-196.

[210] j. Bayley (Ed.) Elegy for Iris, St Martins, New york, 1999.

[211] C. Bolognesi, C. Lando, A. Forni, E. Landini, R. Scarpato, L. Migliore and S.

Bonassi Chromosomal damage and ageing: effect on micronuclei frequency in

peripheral blood lymphocytes, Age Ageing 28 (1999) 393-397.

[212] Miller the biology of ageing and longevity. in : hazzard wr ed. principles of

geriatric medicine and gerontology., Mcgraw -hill, New york:, 1993.

References

279

[213] M. Fenech Chromosomal damage rate, aging, and diet, Ann N Y Acad Sci 854

(1998) 23-36.

[214] Martin genetic and enviromental modulations of chromosomal stability, Ann

NY Acad Sci 621 (1991) 401-417.

[215] C. Fraga, M. Shigenaga, J. Park, P. Degan and B. Ames Oxidative Damage to

DNA During Aging: 8-Hydroxy-2'-Deoxyguanosine in Rat Organ DNA and

Urine, PNAS 87 (1990) 4533-4537.

[216] D. Goukassian, F. Gad, M. Yaar, M.S. Eller, U.S. Nehal and B.A. Gilchrist

Mechanisms and implications of the age-associated decrease in DNA repair

capacity, FASEB J. 14 (2000) 1325-1334.

[217] M. Fenech and A.A. Morley Cytokinesis-block micronucleus method in human

lymphocytes: effect of in vivo ageing and low dose X-irradiation, Mutat Res

161 (1986) 193-198.

[218] A. Antoccia, C. Tanzarella, D. Modesti and F. Degrassi Cytokinesis-block

micronucleus assay with kinetochore detection in colchicine-treated human

fibroblasts, Mutat Res 287 (1993) 93-99.

[219] H. Norppa and G.C.-M. Falck What do human micronuclei contain?

Mutagenesis 18 (2003) 221-233.

[220] E.E. Visvardis, A.M. Tassiou and S.M. Piperakis Study of DNA damage

induction and repair capacity of fresh and cryopreserved lymphocytes

exposed to H2O2 and gamma-irradiation with the alkaline comet assay, Mutat

Res 383 (1997) 71-80.

[221] N.P. Singh, D.B. Danner, R.R. Tice, L. Brant and E.L. Schneider DNA damage

and repair with age in individual human lymphocytes, Mutat Res 237 (1990)

123-130.

References

280

[222] V.S. Dhillon, P. Thomas and M. Fenech Comparison of DNA damage and

repair following radiation challenge in buccal cells and lymphocytes using

single-cell gel electrophoresis, Int J Radiat Biol 80 (2004) 517-528.

[223] H. Weirich-Schwaiger, H.G. Weirich, B. Gruber, M. Schweiger and M. Hirsch-

Kauffmann Correlation between senescence and DNA repair in cells from

young and old individuals and in premature aging syndromes, Mutat Res 316

(1994) 37-48.

[224] P.E. Tolbert, C.M. Shy and J.W. Allen Micronuclei and other nuclear

anomalies in buccal smears: methods development, Mutat Res 271 (1992) 69-

77.

[225] J.A. Belien, M.P. Copper, B.J. Braakhuis, G.B. Snow and J.P. Baak

Standardization of counting micronuclei: definition of a protocol to measure

genotoxic damage in human exfoliated cells, Carcinogenesis 16 (1995) 2395-

2400.

[226] P.E. Tolbert, C.M. Shy and J.W. Allen Micronuclei and other nuclear

anomalies in buccal smears: a field test in snuff users, Am J Epidemiol 134

(1991) 840-850.

[227] N. Shimizu, N. Itoh, H. Utiyama and G.M. Wahl Selective Entrapment of

Extrachromosomally Amplified DNA by Nuclear Budding and Micronucleation

during S Phase, J. Cell Biol. 140 (1998) 1307-1320.

[228] N. Shimizu, F. Kamezaki and S. Shigematsu Tracking of microinjected DNA in

live cells reveals the intracellular behavior and elimination of

extrachromosomal genetic material, Nucl. Acids Res. 33 (2005) 6296-6307.

[229] J.A. Veiro and P.G. Cummins Imaging of skin epidermis from various origins

using confocal laser scanning microscopy, Dermatology 189 (1994) 16-22.

References

281

[230] B.R. Masters, G. Gonnord and P. Corcuff Three-dimensional microscopic

biopsy of in vivo human skin: a new technique based on a flexible confocal

microscope,1997.d01-624.x, Journal of Microscopy 185 (1997) 329-338.

[231] M. Guttenbach, R. Schakowski and M. Schmid Aneuploidy and ageing: sex

chromosome exclusion into micronuclei, Hum Genet 94 (1994) 295-298.

[232] J.C. Hando, J. Nath and J.D. Tucker Sex chromosomes, micronuclei and

aging in women, Chromosoma 103 (1994) 186-192.

[233] G.J. Gattas, A. Cardoso Lde, A. Medrado-Faria Mde and P.H. Saldanha

Frequency of oral mucosa micronuclei in gas station operators after

introducing methanol, Occup Med (Lond) 51 (2001) 107-113.

[234] Y. Ozkul, H. Donmez, A. Erenmemisoglu, H. Demirtas and N. Imamoglu

Induction of micronuclei by smokeless tobacco on buccal mucosa cells of

habitual users, Mutagenesis 12 (1997) 285-287.

[235] D. Pinto, J.M. Ceballos, G. Garcia, P. Guzman, L.M. Del Razo, E. Vera, H.

Gomez, A. Garcia and M.E. Gonsebatt Increased cytogenetic damage in

outdoor painters, Mutat Res 467 (2000) 105-111.

[236] D.M. Williams, Cruchley,A.T The structural aspects of ageing in the oral

mucosa In: The effect of ageing in oral mucosa and skin, CRC press, 1994.

[237] T. Burns, breathnack,S., Cox,N. Rook's textbook of Dermatology,

Oxford,UK:Blackwell Publishing, 2004.

[238] D.R. Thomas Age-related changes in wound healing, Drugs Aging 18 (2001)

607-620.

[239] N.J. Roizen and D. Patterson Down's syndrome, The Lancet 361 (2003) 1281-

1289.

References

282

[240] J. Korenberg, X. Chen, R. Schipper, Z. Sun, R. Gonsky, S. Gerwehr, N.

Carpenter, C. Daumer, P. Dignan, C. Disteche, J. Graham, Jr, L. Hudgins, B.

McGillivray, K. Miyazaki, N. Ogasawara, J. Park, R. Pagon, S. Pueschel, G.

Sack, B. Say, S. Schuffenhauer, S. Soukup and T. Yamanaka Down

Syndrome Phenotypes: The Consequences of Chromosomal Imbalance

, PNAS 91 (1994) 4997-5001.

[241] S.W. Maluf and B. Erdtmann Genomic instability in Down syndrome and

Fanconi anemia assessed by micronucleus analysis and single-cell gel

electrophoresis, Cancer Genet Cytogenet 124 (2001) 71-75.

[242] M.R. Scarfi, A. Cossarizza, D. Monti, F. Bersani, M. Zannotti, M.B. Lioi and C.

Franceschi Age-related increase of mitomycin C-induced micronuclei in

lymphocytes from Down's syndrome subjects, Mutat Res 237 (1990) 247-252.

[243] Q. Shi and R.W. King Chromosome nondisjunction yields tetraploid rather

than aneuploid cells in human cell lines, Nature 437 (2005) 1038-1042.

[244] D.W. Dickson Neuropathological diagnosis of Alzheimer's disease: a

perspective from longitudinal clinicopathological studies, Neurobiol Aging 18

(1997) S21-26.

[245] H. Braak and E. Braak Evolution of neuronal changes in the course of

Alzheimer's disease, J Neural Transm Suppl 53 (1998) 127-140.

[246] P. Thomas and M. Fenech A review of genome mutation and Alzheimer's

disease, Mutagenesis 22 (2007) 15-33.

[247] F. Trippi, N. Botto, R. Scarpato, L. Petrozzi, U. Bonuccelli, S. Latorraca, S.

Sorbi and L. Migliore Spontaneous and induced chromosome damage in

somatic cells of sporadic and familial Alzheimer's disease patients

Mutagenesis 16 (2001) 323-327.

References

283

[248] C.A. Squier and M.J. Kremer Biology of oral mucosa and esophagus, J Natl

Cancer Inst Monogr (2001) 7-15.

[249] M.W. Hill Epithelial proliferation and turn over in oral epithelia and epidermis

with age. In: the effects of ageing in the oral mucosa and skin, 1994.

[250] A. Moragas, C. Castells and M. Sans Mathematical morphologic analysis of

aging-related epidermal changes, Anal Quant Cytol Histol 15 (1993) 75-82.

[251] M.T. Hull and K.A. Warfel Age-related changes in the cutaneous basal lamina:

scanning electron microscopic study, J Invest Dermatol 81 (1983) 378-380.

[252] R.L. Neve, D.L. McPhie and Y. Chen Alzheimer's disease: a dysfunction of the

amyloid precursor protein(1), Brain Res 886 (2000) 54-66.

[253] H. Hattori, M. Matsumoto, K. Iwai, H. Tsuchiya, E. Miyauchi, M. Takasaki, K.

Kamino, J. Munehira, Y. Kimura, K. Kawanishi, T. Hoshino, H. Murai, H.

Ogata, H. Maruyama and H. Yoshida The tau protein of oral epithelium

increases in Alzheimer's disease, J Gerontol A Biol Sci Med Sci 57 (2002)

M64-70.

[254] M. Sashima, M. Satoh and A. Suzuki Oral senile amyloidosis in senescence

accelerated mouse (SAM), J Oral Pathol Med 19 (1990) 381-384.

[255] J. Hoffmann, C. Twiesselmann, M.P. Kummer, P. Romagnoli and V. Herzog A

possible role for the Alzheimer amyloid precursor protein in the regulation of

epidermal basal cell proliferation, Eur J Cell Biol 79 (2000) 905-914.

[256] S.J. Gerson, J. Meyer and D. Gandor Decreased zinc concentration does not

lead to atrophy of rat oral epithelium, J Nutr 115 (1985) 820-823.

[257] C.E. Joseph, S.H. Ashrafi and J.P. Waterhouse Structural changes in rabbit

oral epithelium caused by zinc deficiency, J Nutr 111 (1981) 53-57.

References

284

[258] D. Hsu, J. Meyer, S. Gerson and J. Daniel Sequence of changes in rat buccal

mucosa induced by zinc deficiency, J Oral Pathol Med 20 (1991) 443-448.

[259] A.I. Bush The metallobiology of Alzheimer's disease, Trends in Neurosciences

26 (2003) 207-214.

[260] P. Kruk, N. Rampino and V. Bohr DNA Damage and Repair in Telomeres:

Relation to Aging, PNAS 92 (1995) 258-262.

[261] J. O'Sullivan, R.A. Risques, M.T. Mandelson, L. Chen, T.A. Brentnall, M.P.

Bronner, M.P. Macmillan, Z. Feng, J.R. Siebert, J.D. Potter and P.S.

Rabinovitch Telomere length in the colon declines with age: a relation to

colorectal cancer?, Cancer Epidemiol Biomarkers Prev 15 (2006) 573-577.

[262] R.C. Allsopp, H. Vaziri, C. Patterson, S. Goldstein, E.V. Younglai, A.B.

Futcher, C.W. Greider and C.B. Harley Telomere length predicts replicative

capacity of human fibroblasts, Proc Natl Acad Sci U S A 89 (1992) 10114-

10118.

[263] J.M. Wong and K. Collins Telomere maintenance and disease, Lancet 362

(2003) 983-988.

[264] M.S. Rao and M.P. Mattson Stem cells and aging: expanding the possibilities,

Mech Ageing Dev 122 (2001) 713-734.

[265] R.J. Hodes Telomere length, aging, and somatic cell turnover, J Exp Med 190

(1999) 153-156.

[266] R.W. Frenck, Jr., E.H. Blackburn and K.M. Shannon The rate of telomere

sequence loss in human leukocytes varies with age, Proc Natl Acad Sci U S A

95 (1998) 5607-5610.

[267] T. Von Zglinicki Role of Oxidative Stress in Telomere Length Regulation and

Replicative Senescence, Ann NY Acad Sci 908 (2000) 99-110.

References

285

[268] J.N. O'Sullivan, M.P. Bronner, T.A. Brentnall, J.C. Finley, W.T. Shen, S.

Emerson, M.J. Emond, K.A. Gollahon, A.H. Moskovitz, D.A. Crispin, J.D.

Potter and P.S. Rabinovitch Chromosomal instability in ulcerative colitis is

related to telomere shortening, Nat Genet 32 (2002) 280-284.

[269] S.E. Artandi, S. Chang, S.-L. Lee, S. Alson, G.J. Gottlieb, L. Chin and R.A.

DePinho Telomere dysfunction promotes non-reciprocal translocations and

epithelial cancers in mice, 406 (2000) 641-645.

[270] N.J. Samani, R. Boultby, R. Butler, J.R. Thompson and A.H. Goodall

Telomere shortening in atherosclerosis, The Lancet 358 (2001) 472-473.

[271] E.C. Jenkins, M.T. Velinov, L. Ye, H. Gu, S. Li, E.C. Jenkins, Jr., S.S. Brooks,

D. Pang, D.A. Devenny, W.B. Zigman, N. Schupf and W.P. Silverman

Telomere shortening in T lymphocytes of older individuals with Down

syndrome and dementia, Neurobiol Aging 27 (2006) 941-945.

[272] M. de Arruda Cardoso Smith, B. Borsatto-Galera, R.I. Feller, A. Goncalves,

R.S. Oyama, R. Segato, E. Chen, G.M. Carvalheira, A.S. Filho, R.R. Burbano

and S.L. Payao Telomeres on chromosome 21 and aging in lymphocytes and

gingival fibroblasts from individuals with Down syndrome, J Oral Sci 46 (2004)

171-177.

[273] R.M. Cawthon Telomere measurement by quantitative PCR, Nucleic Acids

Res 30 (2002) e47.

[274] A. Collins, J. Cadet, B. Epe and C. Gedik Problems in the measurement of 8-

oxoguanine in human DNA. Report of a workshop, DNA oxidation, held in

Aberdeen, UK, 19-21 January, 1997, Carcinogenesis 18 (1997) 1833-1836.

[275] H.J. Helbock, K.B. Beckman, M.K. Shigenaga, P.B. Walter, A.A. Woodall, H.C.

Yeo and B.N. Ames DNA oxidation matters: the HPLC-electrochemical

References

286

detection assay of 8-oxo-deoxyguanosine and 8-oxo-guanine, Proc Natl Acad

Sci U S A 95 (1998) 288-293.

[276] T. Lu, Y. Pan, S.Y. Kao, C. Li, I. Kohane, J. Chan and B.A. Yankner Gene

regulation and DNA damage in the ageing human brain, Nature 429 (2004)

883-891.

[277] R.J. Callicott and J.E. Womack Real-time PCR assay for measurement of

mouse telomeres, Comp Med 56 (2006) 17-22.

[278] P.E. Slagboom, S. Droog and D.I. Boomsma Genetic determination of

telomere size in humans: a twin study of three age groups, Am J Hum Genet

55 (1994) 876-882.

[279] K. Prowse and C. Greider Developmental and Tissue-Specific Regulation of

Mouse Telomerase and Telomere Length, PNAS 92 (1995) 4818-4822.

[280] J.C.Y. Wang, J.K. Warner, N. Erdmann, P.M. Lansdorp, L. Harrington and J.E.

Dick Dissociation of telomerase activity and telomere length maintenance in

primitive human hematopoietic cells, PNAS 102 (2005) 14398-14403.

[281] O. Alvares, M.R. Skougaard, J.J. Pindborg and B. Roed-Petersen In vitro

incorporation of tritiated thymidine in oral homogeneous leukoplakias, Scand J

Dent Res 80 (1972) 510-514.

[282] D. Shemin and D. Rittenberg THE LIFE SPAN OF THE HUMAN RED BLOOD

CELL, J. Biol. Chem. 166 (1946) 627-636.

[283] G.M. Gillespie Renewal of buccal epithelium, Oral Surg Oral Med Oral Pathol

27 (1969) 83-89.

[284] D.C. Dale, W.C. Liles, C. Llewellyn and T.H. Price Effects of granulocyte-

macrophage colony-stimulating factor (GM-CSF) on neutrophil kinetics and

function in normal human volunteers, Am J Hematol 57 (1998) 7-15.

References

287

[285] J.D. Robertson, R.E. Gale, R.F. Wynn, M. Dougal, D.C. Linch, N.G. Testa and

R. Chopra Dynamics of telomere shortening in neutrophils and T lymphocytes

during ageing and the relationship to skewed X chromosome inactivation

patterns, Br J Haematol 109 (2000) 272-279.

[286] H.G. Kuhn, H. Dickinson-Anson and F.H. Gage Neurogenesis in the dentate

gyrus of the adult rat: age-related decrease of neuronal progenitor

proliferation, J Neurosci 16 (1996) 2027-2033.

[287] P.S. Eriksson, E. Perfilieva, T. Bjork-Eriksson, A.M. Alborn, C. Nordborg, D.A.

Peterson and F.H. Gage Neurogenesis in the adult human hippocampus, Nat

Med 4 (1998) 1313-1317.

[288] S. Gonzalo, I. Jaco, M.F. Fraga, T. Chen, E. Li, M. Esteller and M.A. Blasco

DNA methyltransferases control telomere length and telomere recombination

in mammalian cells, Nat Cell Biol 8 (2006) 416-424.

[289] M.A. Blasco The epigenetic regulation of mammalian telomeres, 8 (2007)

299-309.

[290] A.T. Du, N. Schuff, D. Amend, M.P. Laakso, Y.Y. Hsu, W.J. Jagust, K. Yaffe,

J.H. Kramer, B. Reed, D. Norman, H.C. Chui and M.W. Weiner Magnetic

resonance imaging of the entorhinal cortex and hippocampus in mild cognitive

impairment and Alzheimer's disease, J Neurol Neurosurg Psychiatry 71 (2001)

441-447.

[291] V. Haroutunian, D.P. Perl, D.P. Purohit, D. Marin, K. Khan, M. Lantz, K.L.

Davis and R.C. Mohs Regional Distribution of Neuritic Plaques in the

Nondemented Elderly and Subjects With Very Mild Alzheimer Disease

Arch Neurol 55 (1998) 1185-1191.

References

288

[292] A.J. Hunt and J.R. McIntosh The dynamic behavior of individual microtubules

associated with chromosomes in vitro, Mol Biol Cell 9 (1998) 2857-2871.

[293] D.A. Devenny, J. Wegiel, N. Schupf, E. Jenkins, W. Zigman, S.J. Krinsky-

McHale and W.P. Silverman Dementia of the Alzheimer's Type and

Accelerated Aging in Down Syndrome, Sci. Aging Knowl. Environ. 2005

(2005) dn1-.

[294] M. Franceschi, M. Comola, F. Piattoni, W. Gualandri and N. Canal Prevalence

of dementia in adult patients with trisomy 21, Am J Med Genet Suppl 7 (1990)

306-308.

[295] L. Migliore, G. Boni, R. Bernardini, F. Trippi, R. Colognato, I. Fontana, F.

Coppede and I. Sbrana Susceptibility to chromosome malsegregation in

lymphocytes of women who had a Down syndrome child in young age,

Neurobiology of Aging 27 (2006) 710-716.

[296] C.A. Evers, Starr, Lisa Biology:Concepts and Applications, Thompson, United

States, 2006.

[297] I. Dunham, C. Lengauer, T. Cremer and T. Featherstone Rapid generation of

chromosome-specific alphoid DNA probes using the polymerase chain

reaction, Hum Genet 88 (1992) 457-462.

[298] J.S. Waye and H.F. Willard Structure, organization, and sequence of alpha

satellite DNA from human chromosome 17: evidence for evolution by unequal

crossing-over and an ancestral pentamer repeat shared with the human X

chromosome, Mol Cell Biol 6 (1986) 3156-3165.

[299] D.A. Eastmond and D. Pinkel Detection of aneuploidy and aneuploidy-

inducing agents in human lymphocytes using fluorescence in situ hybridization

with chromosome-specific DNA probes, Mutat Res 234 (1990) 303-318.

References

289

[300] D. Pinkel, J. Landegent, C. Collins, J. Fuscoe, R. Segraves, J. Lucas and J.

Gray Fluorescence in situ hybridization with human chromosome-specific

libraries: detection of trisomy 21 and translocations of chromosome 4, Proc

Natl Acad Sci U S A 85 (1988) 9138-9142.

[301] Q. Shi, I.D. Adler, J. Zhang, X. Zhang, X. Shan and R. Martin Incidence of

mosaic cell lines in vivo and malsegregation of chromosome 21 in

lymphocytes in vitro of trisomy 21 patients: detection by fluorescence in situ

hybridization on binucleated lymphocytes, Hum Genet 106 (2000) 29-35.

[302] N.S. Edmund C. Jenkins, Marilyn Genovese, Ling Ling Ye, Deborah Kapell,

Basilisa Canto, Marsha Harris, Darlynne Devenny, Joseph H. Lee, W. Ted

Brown, Increased low-level chromosome 21 mosaicism in older individuals

with Down syndrome, American Journal of Medical Genetics 68 (1997) 147-

151.

[303] I. Nishimoto A new paradigm for neurotoxicity by FAD mutants of betaAPP: a

signaling abnormality, Neurobiol Aging 19 (1998) S33-38.

[304] Y. Senechal, Larmet, Y., Dev,K.K. Unraveling in vivo Functions of Amyloid

Precursor Protein: Insights from Knockout and Knockdown Studies,

Neurodegenerative Diseases 3 (2006) 134-147.

[305] N. Schupf, D. Kapell, J.H. Lee, R. Ottman and R. Mayeux Increased risk of

Alzheimer's disease in mothers of adults with Down's syndrome, Lancet 344

(1994) 353-356.

[306] P. Rakic Limits of neurogenesis in primates, Science 227 (1985) 1054-1056.

[307] M.B. Petersen, G. Karadima, M. Samaritaki, D. Avramopoulos, D.

Vassilopoulos and M. Mikkelsen Association between presenilin-1

References

290

polymorphism and maternal meiosis II errors in Down syndrome, Am J Med

Genet 93 (2000) 366-372.

[308] M. Yamada, N. Sodeyama, Y. Itoh, N. Suematsu, E. Otomo, M. Matsushita

and H. Mizusawa Association of presenilin-1 polymorphism with cerebral

amyloid angiopathy in the elderly, Stroke 28 (1997) 2219-2221.

[309] j. Tyrrel, Cosgrave,M., Hawi, Z., Mcpherson,J., Lawlor, B., Gill,M. A protective

effect of apolipoprotein E e2 allele on dementia in Down's syndrome, Biol

Psychiatr 43 (1998) 397-400.

[310] D.M. Holtzman Alzheimer disease and Down syndrome, Cytogenet Cell Genet

77(Suppl 1) (1997).

[311] D. Avramopoulos, M. Mikkelsen, D. Vassilopoulos, M. Grigoriadou and M.B.

Petersen Apolipoprotein E allele distribution in parents of Down's syndrome

children, Lancet 347 (1996) 862-865.

[312] C.A. Hobbs, S.L. Sherman, P. Yi, S.E. Hopkins, C.P. Torfs, R.J. Hine, M.

Pogribna, R. Rozen and S.J. James Polymorphisms in genes involved in

folate metabolism as maternal risk factors for Down syndrome, Am J Hum

Genet 67 (2000) 623-630.

[313] V.B. O'Leary, A. Parle-McDermott, A.M. Molloy, P.N. Kirke, Z. Johnson, M.

Conley, J.M. Scott and J.L. Mills MTRR and MTHFR polymorphism: link to

Down syndrome?, Am J Med Genet 107 (2002) 151-155.

[314] S.W. Choi and J.B. Mason Folate status: effects on pathways of colorectal

carcinogenesis, J Nutr 132 (2002) 2413S-2418S.

[315] S.W. Choi and J.B. Mason Folate and carcinogenesis: an integrated scheme,

J Nutr 130 (2000) 129-132.

References

291

[316] B.C. Blount and B.N. Ames DNA damage in folate deficiency, Baillieres Clin

Haematol 8 (1995) 461-478.

[317] B.C. Blount, M.M. Mack, C.M. Wehr, J.T. MacGregor, R.A. Hiatt, G. Wang,

S.N. Wickramasinghe, R.B. Everson and B.N. Ames Folate deficiency causes

uracil misincorporation into human DNA and chromosome breakage:

implications for cancer and neuronal damage, Proc Natl Acad Sci U S A 94

(1997) 3290-3295.

[318] E. Calvaresi and J. Bryan B vitamins, cognition, and aging: a review, J

Gerontol B Psychol Sci Soc Sci 56 (2001) P327-339.

[319] S. Beetstra, P. Thomas, C. Salisbury, J. Turner and M. Fenech Folic acid

deficiency increases chromosomal instability, chromosome 21 aneuploidy and

sensitivity to radiation-induced micronuclei, Mutat Res 578 (2005) 317-326.

[320] G. Ravaglia, P. Forti, F. Maioli, M. Martelli, L. Servadei, N. Brunetti, E.

Porcellini and F. Licastro Homocysteine and folate as risk factors for dementia

and Alzheimer disease, Am J Clin Nutr 82 (2005) 636-643.

[321] P.I. Ho, S.C. Collins, S. Dhitavat, D. Ortiz, D. Ashline, E. Rogers and T.B.

Shea Homocysteine potentiates beta-amyloid neurotoxicity: role of oxidative

stress, J Neurochem 78 (2001) 249-253.

[322] X. Sai, Y. Kawamura, K. Kokame, H. Yamaguchi, H. Shiraishi, R. Suzuki, T.

Suzuki, M. Kawaichi, T. Miyata, T. Kitamura, B. De Strooper, K. Yanagisawa

and H. Komano Endoplasmic Reticulum Stress-inducible Protein, Herp,

Enhances Presenilin-mediated Generation of Amyloid beta -Protein, J. Biol.

Chem. 277 (2002) 12915-12920.

[323] D.J. Gaughan, L.A. Kluijtmans, S. Barbaux, D. McMaster, I.S. Young, J.W.

Yarnell, A. Evans and A.S. Whitehead The methionine synthase reductase

References

292

(MTRR) A66G polymorphism is a novel genetic determinant of plasma

homocysteine concentrations, Atherosclerosis 157 (2001) 451-456.

[324] M.F. Fenech, I.E. Dreosti and J.R. Rinaldi Folate, vitamin B12, homocysteine

status and chromosome damage rate in lymphocytes of older men,

Carcinogenesis 18 (1997) 1329-1336.

[325] C. Lasseur, F. Parrot, Y. Delmas, C. Level, C. Ged, I. Redonnet-Vernhet, D.

Montaudon, C. Combe and P. Chauveau Impact of high-flux/high-efficiency

dialysis on folate and homocysteine metabolism, J Nephrol 14 (2001) 32-35.

[326] E. Joosten, E. Lesaffre, R. Riezler, V. Ghekiere, L. Dereymaeker, W.

Pelemans and E. Dejaeger Is metabolic evidence for vitamin B-12 and folate

deficiency more frequent in elderly patients with Alzheimer's disease?, J

Gerontol A Biol Sci Med Sci 52 (1997) M76-79.

[327] H.X. Wang, A. Wahlin, H. Basun, J. Fastbom, B. Winblad and L. Fratiglioni

Vitamin B12 and folate in relation to the development of Alzheimer's disease,

Neurology 56 (2001) 1188-1194.

[328] J. Selhub, L.C. Bagley, J. Miller and I.H. Rosenberg B vitamins, homocysteine,

and neurocognitive function in the elderly1, Am J Clin Nutr 71 (2000) 614s-

620.

[329] B. Fowler Genetic defects of folate and cobalamin metabolism, Eur J Pediatr

157 Suppl 2 (1998) S60-66.

[330] A.C. Antony The biological chemistry of folate receptors, Blood 79 (1992)

2807-2820.

[331] N. Habibzadeh, C.J. Schorah, M.J. Seller, R.W. Smithells and M.I. Levene

Uptake and utilization of DL-5-[methyl-14C] tetrahydropteroylmonoglutamate

References

293

by cultured cytotrophoblasts associated with neural tube defects, Proc Soc

Exp Biol Med 203 (1993) 45-54.

[332] A. McCaddon, B. Regland, P. Hudson and G. Davies Functional vitamin B(12)

deficiency and Alzheimer disease, Neurology 58 (2002) 1395-1399.

[333] R.J. Castellani, P.L. Harris, L.M. Sayre, J. Fujii, N. Taniguchi, M.P. Vitek, H.

Founds, C.S. Atwood, G. Perry and M.A. Smith Active glycation in

neurofibrillary pathology of Alzheimer disease: N(epsilon)-(carboxymethyl)

lysine and hexitol-lysine, Free Radic Biol Med 31 (2001) 175-180.

[334] M. Pogribna, S. Melnyk, I. Pogribny, A. Chango, P. Yi and S.J. James

Homocysteine metabolism in children with Down syndrome: in vitro

modulation, Am J Hum Genet 69 (2001) 88-95.

[335] B. Aguilar, J.C. Rojas and M.T. Collados Metabolism of homocysteine and its

relationship with cardiovascular disease, J Thromb Thrombolysis 18 (2004)

75-87.

[336] J.W. Miller Assessing the association between vitamin B-12 status and

cognitive function in older adults, Am J Clin Nutr 84 (2006) 1259-1260.

[337] C. McCracken, P. Hudson, R. Ellis and A. McCaddon Methylmalonic acid and

cognitive function in the Medical Research Council Cognitive Function and

Ageing Study, Am J Clin Nutr 84 (2006) 1406-1411.

[338] J.W. Miller Homocysteine and Alzheimer's disease, Nutr Rev 57 (1999) 126-

129.

[339] J.W. Miller Homocysteine, Alzheimer's disease, and cognitive function,

Nutrition 16 (2000) 675-677.

References

294

[340] P.I. Ho, D. Ortiz, E. Rogers and T.B. Shea Multiple aspects of homocysteine

neurotoxicity: glutamate excitotoxicity, kinase hyperactivation and DNA

damage, J Neurosci Res 70 (2002) 694-702.

[341] J.A. Schneider, D.C. Rees, Y.T. Liu and J.B. Clegg Worldwide distribution of a

common methylenetetrahydrofolate reductase mutation, Am J Hum Genet 62

(1998) 1258-1260.

[342] N.M. van der Put, F. Gabreels, E.M. Stevens, J.A. Smeitink, F.J. Trijbels, T.K.

Eskes, L.P. van den Heuvel and H.J. Blom A second common mutation in the

methylenetetrahydrofolate reductase gene: an additional risk factor for neural-

tube defects?, Am J Hum Genet 62 (1998) 1044-1051.

[343] P.L. Rady, S. Szucs, J. Grady, S.D. Hudnall, L.H. Kellner, H. Nitowsky, S.K.

Tyring and R.K. Matalon Genetic polymorphisms of methylenetetrahydrofolate

reductase (MTHFR) and methionine synthase reductase (MTRR) in ethnic

populations in Texas; a report of a novel MTHFR polymorphic site, G1793A,

Am J Med Genet 107 (2002) 162-168.

[344] C.J. Piyathilake, M. Macaluso, R.J. Hine, D.W. Vinter, E.W. Richards and C.L.

Krumdieck Cigarette smoking, intracellular vitamin deficiency, and occurrence

of micronuclei in epithelial cells of the buccal mucosa, Cancer Epidemiol

Biomarkers Prev 4 (1995) 751-758.

[345] N. Bresgen, G. Karlhuber, I. Krizbai, H. Bauer, H.C. Bauer and P.M. Eckl

Oxidative stress in cultured cerebral endothelial cells induces chromosomal

aberrations, micronuclei, and apoptosis, J Neurosci Res 72 (2003) 327-333.

[346] J. Gotz, F. Chen, J. van Dorpe and R.M. Nitsch Formation of Neurofibrillary

Tangles in P301L Tau Transgenic Mice Induced by Abeta 42 Fibrils, Science

293 (2001) 1491-1495.

References

295

[347] C. Hock, U. Konietzko, J.R. Streffer, J. Tracy, A. Signorell, B. Muller-

Tillmanns, U. Lemke, K. Henke, E. Moritz, E. Garcia, M.A. Wollmer, D.

Umbricht, D.J.F. de Quervain, M. Hofmann, A. Maddalena, A.

Papassotiropoulos and R.M. Nitsch Antibodies against [beta]-Amyloid Slow

Cognitive Decline in Alzheimer's Disease, Neuron 38 (2003) 547-554.

[348] J. Naslund, V. Haroutunian, R. Mohs, K.L. Davis, P. Davies, P. Greengard and

J.D. Buxbaum Correlation Between Elevated Levels of Amyloid {beta}-Peptide

in the Brain and Cognitive Decline, JAMA 283 (2000) 1571-1577.

[349] P.I. Moreira, M.A. Smith, X. Zhu, K. Honda, H.G. Lee, G. Aliev and G. Perry

Oxidative damage and Alzheimer's disease: are antioxidant therapies useful?,

Drug News Perspect 18 (2005) 13-19.

[350] S.J. van Rensburg, J.M. van Zyl, F.C. Potocnik, W.M. Daniels, J. Uys, L.

Marais, D. Hon, B.J. van der Walt and R.T. Erasmus The effect of stress on

the antioxidative potential of serum: implications for Alzheimer's disease,

Metab Brain Dis 21 (2006) 171-179.

[351] G.P. Lim, T. Chu, F. Yang, W. Beech, S.A. Frautschy and G.M. Cole The curry

spice curcumin reduces oxidative damage and amyloid pathology in an

Alzheimer transgenic mouse, J Neurosci 21 (2001) 8370-8377.

[352] M. Ganguli, V. Chandra, M.I. Kamboh, J.M. Johnston, H.H. Dodge, B.K.

Thelma, R.C. Juyal, R. Pandav, S.H. Belle and S.T. DeKosky Apolipoprotein E

polymorphism and Alzheimer disease: The Indo-US Cross-National Dementia

Study, Arch Neurol 57 (2000) 824-830.

[353] S.K. Biswas, D. McClure, L.A. Jimenez, I.L. Megson and I. Rahman Curcumin

induces glutathione biosynthesis and inhibits NF-kappaB activation and

References

296

interleukin-8 release in alveolar epithelial cells: mechanism of free radical

scavenging activity, Antioxid Redox Signal 7 (2005) 32-41.

[354] F. Yang, G.P. Lim, A.N. Begum, O.J. Ubeda, M.R. Simmons, S.S.

Ambegaokar, P.P. Chen, R. Kayed, C.G. Glabe, S.A. Frautschy and G.M.

Cole Curcumin inhibits formation of amyloid beta oligomers and fibrils, binds

plaques, and reduces amyloid in vivo, J Biol Chem 280 (2005) 5892-5901.

[355] A. Wu, Z. Ying and F. Gomez-Pinilla Dietary curcumin counteracts the

outcome of traumatic brain injury on oxidative stress, synaptic plasticity, and

cognition, Exp Neurol 197 (2006) 309-317.

[356] S.A. Frautschy, W. Hu, P. Kim, S.A. Miller, T. Chu, M.E. Harris-White and

G.M. Cole Phenolic anti-inflammatory antioxidant reversal of Abeta-induced

cognitive deficits and neuropathology, Neurobiol Aging 22 (2001) 993-1005.

[357] B.L. Zhao, X.J. Li, R.G. He, S.J. Cheng and W.J. Xin Scavenging effect of

extracts of green tea and natural antioxidants on active oxygen radicals, Cell

Biophys 14 (1989) 175-185.

[358] S. Martin-Aragon, J.M. Benedi and A.M. Villar Modifications on antioxidant

capacity and lipid peroxidation in mice under fraxetin treatment, J Pharm

Pharmacol 49 (1997) 49-52.

[359] D. Bagchi, M. Bagchi, S.J. Stohs, D.K. Das, S.D. Ray, C.A. Kuszynski, S.S.

Joshi and H.G. Pruess Free radicals and grape seed proanthocyanidin extract:

importance in human health and disease prevention, Toxicology 148 (2000)

187-197.

[360] D. Bagchi, C.K. Sen, S.D. Ray, D.K. Das, M. Bagchi, H.G. Preuss and J.A.

Vinson Molecular mechanisms of cardioprotection by a novel grape seed

References

297

proanthocyanidin extract, Mutation Research/Fundamental and Molecular

Mechanisms of Mutagenesis 523-524 (2003) 87-97.

[361] S.L. Nuttall, M.J. Kendall, E. Bombardelli and P. Morazzoni An evaluation of

the antioxidant activity of a standardized grape seed extract, Leucoselect&reg,

Journal of Clinical Pharmacy and Therapeutics 23 (1998) 385-389.

[362] Y. Feng, Y.M. Liu, J.D. Fratkins and M.H. LeBlanc Grape seed extract

suppresses lipid peroxidation and reduces hypoxic ischemic brain injury in

neonatal rats, Brain Res Bull 66 (2005) 120-127.

[363] M. Balu, P. Sangeetha, G. Murali and C. Panneerselvam Modulatory role of

grape seed extract on age-related oxidative DNA damage in central nervous

system of rats, Brain Res Bull 68 (2006) 469-473.

[364] A. Sugisawa, S. Inoue and K. Umegaki Grape seed extract prevents H(2)O(2)-

induced chromosomal damage in human lymphoblastoid cells, Biol Pharm Bull

27 (2004) 1459-1461.

[365] W.V. Nikolic, Y. Bai, D. Obregon, H. Hou, T. Mori, J. Zeng, J. Ehrhart, R.D.

Shytle, B. Giunta, D. Morgan, T. Town and J. Tan Transcutaneous beta-

amyloid immunization reduces cerebral beta-amyloid deposits without T cell

infiltration and microhemorrhage, Proc Natl Acad Sci U S A 104 (2007) 2507-

2512.

[366] J.L. Jankowsky, D.J. Fadale, J. Anderson, G.M. Xu, V. Gonzales, N.A.

Jenkins, N.G. Copeland, M.K. Lee, L.H. Younkin, S.L. Wagner, S.G. Younkin

and D.R. Borchelt Mutant presenilins specifically elevate the levels of the 42

residue {beta}-amyloid peptide in vivo: evidence for augmentation of a 42-

specific {gamma} secretase, Hum. Mol. Genet. 13 (2004) 159-170.

References

298

[367] D.R. Borchelt, G. Thinakaran, C.B. Eckman, M.K. Lee, F. Davenport, T.

Ratovitsky, C.M. Prada, G. Kim, S. Seekins, D. Yager, H.H. Slunt, R. Wang,

M. Seeger, A.I. Levey, S.E. Gandy, N.G. Copeland, N.A. Jenkins, D.L. Price,

S.G. Younkin and S.S. Sisodia Familial Alzheimer's disease-linked presenilin 1

variants elevate Abeta1-42/1-40 ratio in vitro and in vivo, Neuron 17 (1996)

1005-1013.

[368] J.L. Jankowsky, H.H. Slunt, T. Ratovitski, N.A. Jenkins, N.G. Copeland and

D.R. Borchelt Co-expression of multiple transgenes in mouse CNS: a

comparison of strategies, Biomolecular Engineering 17 (2001) 157-165.

[369] D.R. Borchelt, T. Ratovitski, J. van Lare, M.K. Lee, V. Gonzales, N.A. Jenkins,

N.G. Copeland, D.L. Price and S.S. Sisodia Accelerated Amyloid Deposition in

the Brains of Transgenic Mice Coexpressing Mutant Presenilin 1 and Amyloid

Precursor Proteins, Neuron 19 (1997) 939-945.

[370] D.R. Borchelt, G. Thinakaran, C.B. Eckman, M.K. Lee, F. Davenport, T.

Ratovitsky, C.-M. Prada, G. Kim, S. Seekins, D. Yager, H.H. Slunt, R. Wang,

M. Seeger, A.I. Levey, S.E. Gandy, N.G. Copeland, N.A. Jenkins, D.L. Price,

S.G. Younkin and S.S. Sisodia Familial Alzheimer's Disease-Linked Presenilin

1 Variants Elevate A[beta]1-42/1-40 Ratio In Vitro and In Vivo, Neuron 17

(1996) 1005-1013.

[371] Y.J. Wang, Pollard, A.N, Zhou, H.D, Zhong,J.H, Zhou,X.F Charecterization of

an Alzheimer's disease mouse model bearing mutant genes of amyloid

precursor protein and human presenilin 1, Submitted (2007).

[372] J. Castillo, O. Benavente-Garcia, J. Lorente, M. Alcaraz, A. Redondo, A.

Ortuno and J.A. Del Rio Antioxidant activity and radioprotective effects against

chromosomal damage induced in vivo by X-rays of flavan-3-ols (Procyanidins)

References

299

from grape seeds (Vitis vinifera): comparative study versus other phenolic and

organic compounds, J Agric Food Chem 48 (2000) 1738-1745.

[373] M. Srinivasan, N. Rajendra Prasad and V.P. Menon Protective effect of

curcumin on gamma-radiation induced DNA damage and lipid peroxidation in

cultured human lymphocytes, Mutat Res 611 (2006) 96-103.

[374] R. Parshad, K.K. Sanford, F.M. Price, V.E. Steele, R.E. Tarone, G.J. Kelloff

and C.W. Boone Protective action of plant polyphenols on radiation-induced

chromatid breaks in cultured human cells, Anticancer Res 18 (1998) 3263-

3266.

[375] R.A. Sharma, A.J. Gescher and W.P. Steward Curcumin: the story so far, Eur

J Cancer 41 (2005) 1955-1968.

[376] N. Sreejayan and M.N. Rao Free radical scavenging activity of curcuminoids,

Arzneimittelforschung 46 (1996) 169-171.

[377] Sreejayan and M.N. Rao Nitric oxide scavenging by curcuminoids, J Pharm

Pharmacol 49 (1997) 105-107.

[378] J. Castillo, O. Benavente-Garcia, M.J. Del Bano, J. Lorente, M. Alcaraz and

M.J. Dato Radioprotective Effects Against Chromosomal Damage Induced in

Human Lymphocytes by gamma-Rays as a Function of Polymerization Grade

of Grape Seed Extracts, J Med Food 4 (2001) 117-123.

[379] O. Benavente-Garcia, J. Castillo, F.R. Marin, A. Ortuno and J.A. Del Rio Uses

and Properties of Citrus Flavonoids, J. Agric. Food Chem. 45 (1997) 4505-

4515.

[380] A.C. Reddy and B.R. Lokesh Effect of dietary turmeric (Curcuma longa) on

iron-induced lipid peroxidation in the rat liver, Food Chem Toxicol 32 (1994)

279-283.

References

300

[381] M. Balu, P. Sangeetha, D. Haripriya and C. Panneerselvam Rejuvenation of

antioxidant system in central nervous system of aged rats by grape seed

extract, Neurosci Lett 383 (2005) 295-300.

[382] M. Dikshit, L. Rastogi, R. Shukla and R.C. Srimal Prevention of ischaemia-

induced biochemical changes by curcumin & quinidine in the cat heart, Indian

J Med Res 101 (1995) 31-35.

[383] I. Rahman and W. MacNee Role of transcription factors in inflammatory lung

diseases, Thorax 53 (1998) 601-612.

[384] I. Rahman and W. MacNee Regulation of redox glutathione levels and gene

transcription in lung inflammation: therapeutic approaches, Free Radic Biol

Med 28 (2000) 1405-1420.

[385] I. Rahman and W. MacNee Oxidative stress and regulation of glutathione in

lung inflammation, Eur Respir J 16 (2000) 534-554.

[386] M.C.W. Myhrstad, H. Carlsen, O. Nordstrom, R. Blomhoff and J.O. Moskaug

Flavonoids increase the intracellular glutathione level by transactivation of the

[gamma]-glutamylcysteine synthetase catalytical subunit promoter, Free

Radical Biology and Medicine 32 (2002) 386-393.

[387] V. Calabrese, D. Boyd-Kimball, G. Scapagnini and D.A. Butterfield Nitric oxide

and cellular stress response in brain aging and neurodegenerative disorders:

the role of vitagenes, In Vivo 18 (2004) 245-267.

[388] V. Calabrese, G. Scapagnini, A. Ravagna, R.G. Fariello, A.M. Giuffrida Stella

and N.G. Abraham Regional distribution of heme oxygenase, HSP70, and

glutathione in brain: relevance for endogenous oxidant/antioxidant balance

and stress tolerance, J Neurosci Res 68 (2002) 65-75.

References

301

[389] K.D. Poss and S. Tonegawa Reduced stress defense in heme oxygenase 1-

deficient cells, Proc Natl Acad Sci U S A 94 (1997) 10925-10930.

[390] G. Scapagnini, C. Colombrita, M. Amadio, V. D'Agata, E. Arcelli, M. Sapienza,

A. Quattrone and V. Calabrese Curcumin activates defensive genes and

protects neurons against oxidative stress, Antioxid Redox Signal 8 (2006) 395-

403.

[391] Y. Yilmaz and R.T. Toledo Health aspects of functional grape seed

constituents, Trends in Food Science & Technology 15 (2004) 422-433.

[392] J. Yamakoshi, M. Saito, S. Kataoka and S. Tokutake Procyanidin-rich extract

from grape seeds prevents cataract formation in hereditary cataractous (ICR/f)

rats, J Agric Food Chem 50 (2002) 4983-4988.

Appendix

302

10 Appendix: Paper Reprints

Thomas, P. and Fenech, M. (2007) A review of genome mutation and Alzheimer's disease. Mutagenesis v. 22 (1) pp. 15-33, January 2007

NOTE: This publication is included in the print copy of the thesis

held in the University of Adelaide Library.

It is also available online to authorised users at:

http://dx.doi.org/10.1093/mutage/gel055

http://dx.doi.org/10.1093/mutage/gel055

Thomas, P., Harvey, S., Gruner, T. and Fenech, M. (2007) The buccal cytome and micronucleus frequency is substantially altered in Down's syndrome and normal ageing compared to young healthy controls. Mutation Research, v. 638 (1-2) pp. 37-47, February 2008




http://dx.doi.org/10.1016/j.mrfmmm.2007.08.012

http://dx.doi.org/10.1016/j.mrfmmm.2007.08.012

Thomas, P., Hecker, J., Faunt, J. and Fenech, M. (2007) Buccal micronucleus cytome biomarkers may be associated with Alzheimer's disease. Mutagenesis v. 22 (6) pp. 371-379, November 2007




http://dx.doi.org/10.1093/mutage/gem029

http://dx.doi.org/10.1093/mutage/gem029

changes in buccal cytome biomarkers in relation to ageing ... · changes in buccal cytome...

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