Glial changes in atypical
parkinsonian syndromes
Yun Ju Christine Song
A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy
August 2008
University of New South Wales Department of Anatomy
Supervisors: Professor Glenda M Halliday Dr Yue Huang
1
Acknowledgements It feels surreal realising that I have come to the end of this unbelievably challenging but rewarding journey. I could not have come this far without the amazing help and guidance from so many important people and I am deeply grateful to everybody who has contributed to the steps I have taken in completing this journey.
To my supervisor Glenda Halliday, thank you so much for all your encouragement and guidance. I have continuously learnt so much from you and there have been countless times where I have been in constant awe of your drive, passion and knowledge about these movement disorders. Thank you for all your teachings and enthusiasm for my work, and believing that I could achieve this. I could not have come this far without such a first-class supervisor.
To my co-supervisor Yue Huang, your passion for MSA pushed me to search for more and you always helped me to think from a different perspective. I have learnt many things from you and I thank you for your support.
My dearest friend and lab manager Heather, your meticulous training and perfectionism in the lab and has helped me to achieve this much. Thank you for your technical guidance, I have the deepest regard for you, both as a teacher and friend. Karen, my second lab manager, thanks for being so helpful and supportive right to the very end. You have become such a dear friend and I appreciate all that you have done for me. Heidi, I owe so much to you, thank you for your patience and turning my images into artwork. I thank you Farid, Claire and Emma for all your words of wisdom and Fabs for all your technical support.
To my collaborators Professor Poul Henning Jensen and Dr Paul Lockhart, your enthusiasm and interest in these glial proteins is what started this project and I thank you for your guidance and encouragement. I was so fortunate to do part of my PhD at the Queen Square Brain Bank. I owe so much to Professor Tamas
2 Revesz who taught me the beauty of neuropathology. Spending endless hours on the microscope with you and your encouragement and teachings has contributed so much to this journey, thank you. Dr Janice Holton, thank you for your ongoing support and faith in me as a researcher. Thank you to my friend and supervisor Dr Tammaryn Lashley, you are an amazing super-woman that had the answer to everything! To my dearest friends at Queen Square, Sudi, Kate, Hil, Perdi, Dan and Idris, your friendships made my UK experience so much more rewarding. I will always cherish your love and care, thank you!
I am so grateful for my dear friends Jo, Fran and Lol (fellow PhD buddy) who gave me hugs, smiles and cups of tea when needed most. My study room pals Daniel, Dave, Elias, Sarah, Jacob and Fatima who shared my rants and raves, I thank you all. To my support team Nancy, Jo, Narae, Julie, Danbi, Beks, Jen and Kristy, you girls have helped me maintain my sanity through the past years. Special thanks to Beks, Jen and Kristy for your amazing proof-reading skills and Nancy for being my special shoulder to cry on. I am so grateful for all your prayers and endless encouragement, and keeping me focused on the unseen, your friendships have been invaluable to this journey.
My family have put up with so much throughout this journey, I am so deeply grateful. To my mum and brother for believing in me, embracing my breakdowns and your constant prayers and words of comfort has helped me to persevere and continue in running the race. To Jamie, you have been so patient and understanding, I owe alot to you. Thank you for putting up with my tears and struggles, you helped me reach the finish line and I thank you dearly. To my Lord, you showed me that all things are possible through you. Thank you for your grace and guiding me till the very end. I give this and all glory to you.
This doctorate was funded by the Australian Government, GlaxoSmithKline Australia and Parkinson’s NSW and a personal thank you to all the brain donors and the Australian Brain Donor Programs.
3 Abstract
Idiopathic Parkinson’s disease (PD) and the atypical parkinsonian syndromes progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) have substantial overlap in clinical features, with parkinsonian and cerebellar phenotypes identified. Pathologically, reactive glial changes occur in overlapping pathways in these disorders. Recent findings that glia concentrate proteins associated with genetic forms of PD, suggest a more significant role for these cells in the pathogenesis of these disorders.
This study is the first to comparatively assess glial abnormalities in PD, PSP and
MSA. Cases were clinically and pathologically characterised to establish correlates to prominent glial changes. The three main types of glia (astrocytes, oligodendroglia and microglia) were characterised by morphological features and protein expression (using immunohistochemical techniques) for correlations with disease indices. Tissue features measured included subregional volumes, nigral cell loss, characteristic disease inclusions, and the densities of glia. Using these techniques, the parkin co-regulated gene protein was found to be a novel constituent protein in protoplasmic astrocytes, facilitating the assessment of glial subtypes.
The data show that distinct glial abnormalities associate with each parkinsonian syndrome. The most marked differences were observed in the astrocytic
4 reaction in each disorder. In PD, protoplasmic astrocytes accumulated non- fibrillar -synuclein and degenerated over time, relating to a loss of levodopa responsiveness. In PSP, there was a marked protoplasmic astrogliosis (with these reactive glia strongly expressing parkin) that related to PSP-prominent clinical symptoms. In MSA, there was a marked fibrous astrogliosis and a loss of protoplasmic astrocytes in association with early changes in constituent myelin and oligodendroglial proteins. In contrast, similar microglial activation was observed across all disorders, with phagocytes concentrating in the substantia nigra, while non-phagocytic reactive microglia expressed parkin and associated with inclusion formation in each disorder. Overall, the glial reactions were considered to be either contributing to or ameliorating (neuroprotective) the neurodegenerative processes, and the timing of these reactions assessed with respect to indices of disease progression. The novel findings of this thesis show that glial abnormalities are prominent but distinct, and occur early in these parkinsonian syndromes. Suggestions on how these findings may translate into future therapeutic targets are given.
5 Table of Contents
CHAPTER 1: INTRODUCTION...... 22 1.1 Parkinson’s disease and atypical parkinsonian disorders ...... 22 1.1.1 Clinical features and diagnosis ...... 22 1.1.2 Overlapping phenotypes in parkinsonian disorders ...... 25 1.1.3 Genetics...... 27 1.1.4 Core pathologies differentiating Parkinson’s disease, progressive supranuclear palsy and multiple system atrophy ...... 31 1.1.5 Pathological staging and differences between clinical phenotypes. 35 1.1.5.1 Clinicopathological correlates: parkinsonian subtype...... 38 1.1.5.1 Clinicopathological correlates: cerebellar subtype ...... 41 1.1.6 Summary...... 43 1.2 Cell specific protein changes in Parkinson’s disease and atypical parkinsonian disorders ...... 44 1.2.1 Abnormal protein expression in neurons...... 44 1.2.2 Abnormal protein expression in astrocytes ...... 48 1.2.3 Abnormal protein expression in oligodendroglia ...... 49 1.2.4 Abnormal protein expression in microglia ...... 52 1.2.5 Summary...... 53 1.3 Study objectives ...... 54 1.4 Major hypotheses ...... 55
CHAPTER 2: COMMON MATERIALS AND METHODS ...... 56 2.1 Sources of tissue ...... 56 2.2 Case ascertainment and clinical information...... 58 2.3 Standard preparation of brain tissue ...... 61 2.4 General immunohistochemical methods...... 62 2.4.1 Peroxidase immunohistochemistry (counterstained with
6 cresyl violet)...... 62 2.4.2 Double-labelling immunofluorescence ...... 65 2.4.3 Combined peroxidase and immunofluorescence labelling ...... 66
CHAPTER 3: PATHOLOGICAL STAGING OF PROGRESSIVE SUPRANUCLEAR PALSY...... 68 3.1 Introduction...... 68 3.1.1 Aim...... 71 3.2 Methods ...... 71 3.2.1 Cases used...... 71 3.2.1.1 Cases for method development ...... 72 3.2.1.2 Cases for scheme validation ...... 72 3.2.1.3 Cases for clinical correlations...... 73 3.2.2 Development of a pathological staging scheme for progressive supranuclear palsy...... 74 3.2.2.1 Regional tissue sampling ...... 74 3.2.2.2 Feature identification and severity ratings ...... 75 3.2.3 Correlations between tau stage and clinically relevant indices ...... 85 3.3 Results...... 85 3.3.1 Analysis of cohorts...... 85 3.3.2 Analysis of variability in pathological features and the use of this variability in developing the scheme ...... 86 3.3.3 The development of a staging scheme using the variability in pathological features and clinical correlates ...... 90 3.3.4 The pathological staging of progressive supranuclear palsy severity ...... 94 3.3.5 Analysis and validation of the pathological staging of progressive supranuclear palsy...... 95 3.3.6 Correlations between progressive supranuclear palsy pathological severity, pathological tau burden and clinical indices...... 96 3.4 Discussion...... 96
7 3.4.1 Comparison with current diagnostic techniques for progressive supranuclear palsy...... 99 3.4.2 Accuracy and limitations of the staging scheme ...... 100 3.4.3 Comparison with staging schemes for other parkinsonian and neurodegenerative disorders ...... 101
CHAPTER 4: CLINICOPATHOLOGICAL CHARACTERISATION OF CASES FOR COMPARISON...... 103 4.1 Introduction...... 103 4.1.1 Aims and hypothesis...... 103 4.2 Methods ...... 104 4.2.1 Assessment of regional atrophy...... 104 4.2.2 Assessment of pathological staging and severity of core pathologies ...... 105 4.3 Results...... 112 4.3.1 Controls...... 112 4.3.2 Parkinson’s disease diagnosis and characterisation...... 114 4.3.2.1 Case demographics and clinical progression ...... 114 4.3.2.2 Pathology and atrophy ...... 114 4.3.3 Progressive supranuclear palsy diagnosis and characterisation... 117 4.3.3.1 Case demographics and clinical progression ...... 117 4.3.3.2 Pathology and atrophy ...... 118 4.3.4 Multiple system atrophy diagnosis and characterisation ...... 120 4.3.4.1 Case demographics and clinical progression ...... 120 4.3.4.2 Pathology and atrophy ...... 122 4.3.5 Cohort and disease comparisons...... 125 4.3.5.1 Demographic cohort comparisons...... 125 4.3.5.2 Clinical comparisons ...... 126 4.3.5.3 Pathological comparisons of disease severity...... 132 4.3.5.4 Clinicopathological comparisons ...... 134 4.4 Discussion...... 135
8
CHAPTER 5: PATHOLOGICAL CHANGES IN ASTROCYTES ...... 141 5.1 Introduction...... 141 5.1.1 Specific hypotheses to be tested ...... 146 5.2 Methods ...... 146 5.2.1 Case selection ...... 146 5.2.2 Tissue preparation ...... 146 5.2.3 Analyses ...... 148 5.3 Results...... 149 5.3.1 Pathological changes in astrocytes in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 149 5.3.2 Astrocytic parkin and PACRG in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 154 5.3.3 Types of astrocytes affected in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 156 5.3.4 Clinical correlations...... 161 5.4 Discussion...... 161 5.4.1 Astrocytic subtypes affected in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 162 5.4.2 Parkin expression in protoplasmic astrocytes in Parkinson’s disease and progressive supranuclear palsy ...... 164 5.4.3 The severity of these degenerative changes and their relationships...... 167 5.4.4 Conclusions ...... 169
CHAPTER 6: PATHOLOGICAL CHANGES IN OLIGODENDROGLIA ...... 170 6.1 Introduction...... 170 6.1.1 Hypotheses to be tested ...... 173 6.2 Methods ...... 173 6.2.1 Case and tissue preparation ...... 173
9 6.2.2 Protein extractions and western blotting for myelin basic protein and p25...... 174 6.2.3 Immunohistochemistry to assess the distribution of myelin- associated proteins ...... 176 6.2.4 Assessment of axon diameter, fiber diameter and calculation of g ratios ...... 178 6.2.5 Immunohistochemistry for the assessment of morphological changes in oligodendroglia-associated with GCI formation ...... 179 6.2.6 Assessment of oligodendroglia changes associated with GCI and coiled bodies...... 181 6.2.7 Correlations with clinical indices ...... 182 6.3 Results...... 182 6.3.1 Comparative changes in the amount of myelin-associated proteins ...... 182 6.3.2 Comparative changes in the distribution of myelin-associated proteins ...... 185 6.3.3 Affects of myelin changes on axons...... 189 6.3.4 Oligodendroglial cell body changes in multiple system atrophy .... 192 6.3.5 Oligodendroglial changes associated with GCI...... 193 6.3.6 Oligodendroglial changes associated with coiled bodies ...... 198 6.3.7 Correlations with clinical indices ...... 200 6.4 Discussion...... 201 6.4.1 Conclusions ...... 206
CHAPTER 7: MICROGLIAL ACTIVATION...... 208 7.1 Introduction...... 208 7.1.1 Hypotheses to be tested ...... 210 7.2 Methods ...... 211 7.2.1 Cases and tissue preparation ...... 211 7.2.3 Analyses ...... 211 7.3 Results...... 215
10 7.3.1 Microglial activation in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 215 7.3.2 Microglial parkin in Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy ...... 220 7.4 Discussion...... 224 7.4.1 Conclusions ...... 231
CHAPTER 8: DISCUSSION ...... 233
REFERENCES ...... 244
11 List of Tables
Tables Pages
Chapter 2
2.1 General case demographics for control, PD, PSP and MSA 58
2.2 Antigen retrieval methods for different primary antibodies 64
Chapter 3
3.1 Cohort characteristics 73
3.2 Feature assessment in brain regions of interest 85
3.3 Regional severity data for each pathological feature in cohort I 88
3.4 Development scheme 1 of PSP pathological staging based on
feature assessment 92
3.5 Development scheme 2 of PSP pathological staging based on
feature assessment 93
3.6 Refinement of the PSP pathological staging scheme with the
closest two out of three variables required 94
Chapter 4
4.1 Demographic, volumetric and pathological variables for controls 113
4.2 Demographic, volumetric and pathological variables for PD 116
12 4.3 Demographic, volumetric and pathological variables for PSP 119
4.4 Demographic, volumetric and pathological variables for MSA 124
4.5 Clinical features for PD, PSP and MSA 131
4.6 Comparisons of regional atrophy in PD, PSP and MSA 133
Chapter 5
5.1 Regional severity gradings for nigral cell loss, pathological inclusion
formation, and increased astrocytic GFAP, PACRG and parkin 151
Chapter 6
6.1 Group averages of the proportion of myelin proteins assessed
densitometrically and standardised to GAPDH in each case 185
6.2 Semi-quantitative assessment of myelin protein immunoreactivity
within pontine fiber tracts 189
6.3 P25 and -synuclein associated oligodendroglial cell size
measurements in m2 193
Chapter 7
7.1 Regional severity gradings for nigral cell loss, pathological inclusion
formation, and increased HLA-DR-immunoreactive microglial
activation 218
7.2 Mean and standard deviations of parkin-immunoreactive
structures (per mm2) in controls, PD, PSP and MSA 224
13 List of Figures
Figures Pages
Chapter 1
1.1 Core pathological features of PD, MSA and PSP 34
1.2 Braak staging of pathological PD 36
1.3 Neuronal and glial inclusions in PD, MSA and PSP 47
Chapter 3
3.1 Minimal neuron loss in the pons in PSP 77
3.2 Representative grades of neuron loss in PSP 78
3.3 Representative grades of NFT deposition in PSP 81
3.4 Minimal tufted astrocytes in the substantia nigra of PSP 82
3.5 Representative grades of tufted astrocytes in the caudate nucleus
of PSP 83
3.6 The severity of the identified hierarchical pathologies in regions of
interest 91
Chapter 4
4.1 Representative grades of neuronal loss in the substantia nigra 108
4.2 Representative grades of NFT as a core pathological feature of
14 PSP 109
4.3 Representative grades of GCI as a core pathological feature of
MSA 110
Chapter 5
5.1 Astrocytes in control and PD 152
5.2 Astrocytic changes in MSA and PSP 153
5.3 Astrocytic PACRG in control and PD 157
5.4 Astrocytic PACRG and parkin in PSP 158
5.5 Astrocytic PACRG, parkin and tau in PSP 159
5.6 PACRG immunoreactivity in ApoD-immunoreactive protoplasmic
astrocytes 160
Chapter 6
6.1 Western blots of controls, MSA, PD and PSP human brain
extracts 184
6.2 In situ protein localisation in myelinated fiber bundles and
oligodendroglia in controls 187
6.3 Changes in location of myelin-associated proteins in MSA 188
6.4 Loss of p25 without axonal degeneration in MSA 191
6.5 Control and MSA oligodendroglia 197
6.6 Representative grades of coiled bodies in PSP 199
15
Chapter 7
7.1 Different types and representative grades of HLA-DR-immunoreactive
activated microglia 213
7.2 HLA-DR-immunoreactive phagocytic and non-phagocytic
microglia 217
7.3 Parkin-immunoreactive activated microglia 222
16 List of abbreviations
ABDP Australian Brain Donors Programs
ApoD Apolipoprotein D
AR-JP Autosomal recessive-juvenile parkinsonism
CB Coiled bodies
CDR Clinical dementia rating
CNPase 2’3’-cyclicnucleotide 3’-phosphodiesterase
CNS Central nervous system
GAPDH Glyceraldehyde-3-phosphate dehydrogenase
GCI Glial cytoplasmic inclusions
GFAP Glial fibrillary acidic protein
H&Y Hoehn and Yahr
HLA-DR Human leukocyte antigen DR-1
IHC Immunohistochemistry
LB Lewy bodies
L-dopa Levodopa
LRRK2 Leucine-rich repeat kinase 2
MAPT Microtubule associated protein tau
MBP Myelin basic protein
MPTP 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine
MSA Multiple system atrophy
17 MSA-C Multiple system atrophy-cerebellar
MSA-P Multiple system atrophy-parkinsonism
NCI Neuronal cytoplasmic inclusions
NF Neurofilament
NFT Neurofibrillary tangles
NII Neuronal intranuclear inclusions
NINDS-SPSP National Institute of Neurological Disorders and Stroke and
Society for Progressive Supranuclear Palsy
OPCA Olivopontocerebellar atrophy
PACRG Parkin co-regulated gene
PAGE Polyacrylamide gel electrophoresis
PD Parkinson’s disease
PET Positron emission tomography
PINK1 Phosphatase and tensin homolog deleted on chromosome
10 induced kinase 1
PMD Post-mortem delay
PNLA Pallido-nigro-luysial atrophy
POWMRI TRC Prince of Wales Medical Research Institute Tissue
Resource Centre
PSP Progressive supranuclear palsy
PSP-P Progressive supranuclear palsy-parkinsonism
PSP-RS Progressive supranuclear palsy-Richardson’s syndrome
QSBB Queen Square Brain Bank
SABB South Australian Brain Bank 18 SCP Superior cerebellar peduncle
SD Standard deviation
SDS Sodium dodecyl sulfate
SN Substantia nigra
SND Striatonigral degeneration
STN Subthalamic nucleus
TA Tufted astrocytes
TESPA 3-aminopropyltrimethoxysilane
WB Western blotting
19 List of publications arising from this thesis
Publications
JM Taylor, YJC Song, Y Huang, MJ Farrer, M Delatycki, GM Halliday, PJ
Lockhart.
“PACRG is regulated by the ubiquitin-proteasomal system and is present in the pathological features of Parkinsonian diseases.”
Neurobiology of Disease 2007 Aug; 27 (2): 238-47
YJC Song, D Lundvig, Y Huang, WP Gai, PC Blumbergs, P Horjup, D Otzen,
GM Halliday, PH Jensen.
“P25 relocalizes from myelin to cytoplasmic inclusions in multiple system atrophy.”
American Journal of Pathology 2007 Oct; 171 (4): 1291-303
Y Huang, YJC Song, K Murphy, JL Holton, T Lashley, T Revesz, WP Gai, GM
Halliday.
“LRRK2 and parkin immunoreactivity in multiple system atrophy inclusions.”
Acta Neuropathologica 2008 Dec; 1: 16 (6): 639-46
Abstracts
YJC Song, Y Huang, WP Gai, PH Jensen, GM Halliday.
“Selective p25 loss in multiple system atrophy.”
20 Proceedings of the Australian Neuroscience Society, January 2005.
YJC Song, Y Huang, WP Gai, PH Jensen, GM Halliday.
“P25 relocalizes from myelin to cytoplasmic inclusions in multiple system atrophy.”
Parkinsonism and Related Disorders 2007, 13 Supplementary. (2): 63
YJC Song, Y Huang, WP Gai, PH Jensen, GM Halliday.
“Correlations between striatal oligodendroglial abnormalities and neuron loss in multiple system atrophy.”
Movement Disorders 2008, 23 Supplementary. (1): S266
21 Chapter 1: Introduction
1.1 PARKINSON’S DISEASE AND ATYPICAL PARKINSONIAN DISORDERS
1.1.1 Clinical features and diagnosis
Idiopathic Parkinson’s disease (PD) occurs in about 1% of people over 60 years of age (Nussbaum and Ellis, 2003). A clinical diagnosis of PD is given when the patient has the typical features of bradykinesia, resting tremor and/or extrapyramidal rigidity and the diagnosis is made more certain if there is a good response to levodopa (L-dopa) (Brooks, 2002; Gelb et al., 1999; Hald and
Lotharius, 2005; Hoehn and Yahr, 1998). A diagnosis of definite PD is given based on the confirmation of substantia nigra (SN) cell loss and typical Lewy bodies (LB) at autopsy (Gibb and Lees, 1988; Jellinger, 2003). Disorders that present symptoms of rapidly progressing parkinsonism, poor or temporary response to L-dopa or other associated features such as early falls and postural instability are defined as atypical parkinsonian syndromes (Tolosa et al., 2004).
Progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) are defined as sporadic neurodegenerative diseases that vary from typical PD in their clinicopathological presentations, and are thus classified as atypical parkinsonian disorders.
22 PSP is a disorder of unknown etiology with a prevalence of about 6.4 per
100,000 people (Schrag et al., 1999). Diagnostic criteria for PSP are based on consensus statements from the Scientific Issues Committee Task Force
Appraisal and the National Institute of Neurological Disorders and Stroke and
Society for PSP (NINDS-SPSP). For a possible diagnosis, either vertical supranuclear palsy or both postural instability with falls within a year of symptom onset and slowing of vertical saccades must occur. A probable diagnosis includes features of vertical supranuclear palsy and prominent postural instability with falls within the first year of symptom onset. A definite diagnosis of
PSP is given when criteria for possible or probable PSP are met with the pathological confirmation of subcortical neurofibrillary tangles (NFT) at autopsy
(Litvan et al., 1996a; Litvan et al., 2003).
MSA is also a disorder of unknown etiology with a prevalence of about 4-4.5 per
100,000 people (Schrag et al., 1999; Wenning et al., 2004). Diagnostic criteria for MSA are based on four clinical domains, which include autonomic and urinary dysfunction, parkinsonism, cerebellar dysfunction and corticospinal tract dysfunction (Litvan et al., 2003; Schrag et al., 1999; Wenning et al., 2004). A possible diagnosis is given when one domain feature occurs in addition to two features from other domains. A probable diagnosis is given when an autonomic and urinary dysfunction feature occurs with either cerebellar dysfunction or a poor response to L-dopa. A definite diagnosis is given at autopsy following pathological confirmation of widespread glial cytoplasmic inclusions (GCI)
(Trojanowski and Revesz, 2007; Wenning et al., 2004). 23
It has become increasingly recognised that the clinical diversity observed in PD,
PSP and MSA patients causes misdiagnosis (Collins et al., 1995; Dickson et al.,
1999a). In particular, there is substantial clinical overlap across these parkinsonian syndromes in early disease stages (Poewe and Wenning, 2002;
Wenning et al., 2004; Wenning et al., 2003), with a proportion of PSP and MSA patients continuing to have parkinsonian phenotypes throughout their course
(Gilman et al., 1998; Gilman et al., 1999; Wenning et al., 1994; Williams et al.,
2005; Williams et al., 2007a). 32% of PSP patients present with dominant parkinsonism (PSP-Parkinsonism or PSP-P) (Williams et al., 2005) and a larger proportion of MSA patients (80%) also present with dominant parkinsonian features (MSA-P) (Gilman et al., 1999; Wenning et al., 2004; Wenning and
Jellinger, 2005). The more typical clinical features described previously to discriminate PSP occur in up to 54% of PSP patients, now classified as PSP-
Richardson’s syndrome (PSP-RS) (Williams et al., 2005), whereas only 20% of
MSA patients present with features consistent with a probable diagnosis, now classified as MSA-C (Gilman et al., 1999; Wenning et al., 2004; Wenning and
Jellinger, 2005). These data show that two major clinical phenotypes occur across these disorders, a parkinsonian phenotype (PD, PSP-P, MSA-P) and a cerebellar (MSA-C)/Richardson’s syndrome phenotype (PSP-RS). Few studies have assessed these phenotypes across these disorders to determine any pathological correlations or etiological similarities.
24
1.1.2 Overlapping phenotypes in parkinsonian disorders
As described above, resting tremor, rigidity, bradykinesia, postural instability and
L-dopa response are core features of PD (Hald and Lotharius, 2005), but are also commonly identified features in atypical parkinsonian syndromes. In addition, 20-30% of PD patients have atypical parkinsonian syndromes at autopsy (Poewe and Wenning, 2002). 5% of PSP-P patients are misdiagnosed with PD, whereas approximately 50% of MSA-P patients are misdiagnosed with
PD (Litvan et al., 1997). Parkinsonism (progressive akinesia and rigidity) is the primary feature of all these conditions, with jerky postural tremor and tremor at rest as additional prominent presentations even in PSP-P and MSA-P (Wenning et al., 2004; Williams et al., 2005).
Prolonged L-dopa responsiveness is considered one of the main differentiating features for PD (Forno, 1996), although a proportion of patients with atypical syndromes can also respond to L-dopa. Approximately 30-40% of PSP and
MSA patients initially respond to L-dopa, however less than 5% of patients express a marked response after 5 years of treatment (Berciano et al., 2002;
Birdi et al., 2002; Jankovic, 1984; Nieforth and Golbe, 1993; Wenning et al.,
2004; Williams et al., 2005). The PSP-P and MSA-P subtypes are likely to have higher response rates to L-dopa (Constantinescu et al., 2007), with a moderate initial response to L-dopa required for the diagnosis of PSP-P (Williams et al.,
2005). Although the majority of PD patients still respond to L-dopa at 5 years, wearing off and atypical side affects are often problematic, affecting 50% of 25 patients by 5 years and almost all patients by 10 years (Hely et al., 2000; Hely et al., 1994). The similar and prominent initial response to L-dopa in PD, MSA and
PSP (in particular MSA-P and PSP-P) suggests a similar pathological change at this time, followed by differentiating pathologies.
Less recognised is the potential similarities between PSP-RS and MSA-C. This is due to the recency of the concept of PSP-RS (Williams et al., 2005). In particular, a proportion of PSP and MSA cases present with the dominant atypical symptoms of early falls, with oculomotor and cerebellar symptoms and other features, like dysarthria and dysphagia, can not distinguish between them
(Muller et al., 2001). Early falls are thought to be characteristic for PSP, in particular PSP-RS (Wenning et al., 1999; Williams et al., 2006). However, early falls within 3 years of disease onset has also been identified as a “red flag” warning feature of MSA (Muller et al., 2000; Wenning et al., 1999). The overlap of this cerebellar clinical phenotype may explain that 18% of PSP cases are misdiagnosed as MSA (Litvan et al., 1997). Early cerebellar features, such as ataxia, postural instability and falls, dominate the clinical picture in these cases.
Supranuclear vertical down-gaze palsy, axial dystonia and cognitive impairment are features that can help differentiate PSP from PD and MSA (Colosimo et al.,
1995). While these clinical features can be helpful, like vertical supranuclear gaze palsy, the signature sign for PSP, eye signs may also occur in MSA
(Wenning et al., 2004). In MSA-C, cerebellar ataxia is the main clinical presentation and may include other clinical symptoms such as scanning dysarthria and cerebellar oculomotor disturbances (Wenning et al., 2004). MSA- 26 C may therefore be difficult to differentiate from PSP-RS (Dickson et al., 1999a).
Despite this clinical overlap, there have been no comparative pathological studies of PSP-RS and MSA-C. In particular, it is not clear if the initial focus and cell types involved are the same, and there are limited studies on the pathological progression of these phenotypes either independently or comparatively.
1.1.3 Genetics
Historically, PD was thought to be less genetically influenced than other neurodegenerative conditions, with substantial evidence for the involvement of environmental toxicants (Morris, 2005). However, this has not been sustained, with thirteen pathogenic genetic loci established from families with PD and eight genes identified, five of which are found in multiple families with characteristic
PD. The five genes are -synuclein (PARK1), parkin (PARK2), PTEN induced kinase 1 (PINK1) (PARK6), DJ-1 (PARK7) and leucine-rich repeat kinase 2
(LRRK2) (PARK8) (Schiesling et al., 2008). The expression of some of these genetic proteins in human brain tissue has been described. In particular, - synuclein, parkin, PINK1, DJ-1 and LRRK2 are expressed in neurons and glia in controls and patients with PD, PSP and MSA (Bandopadhyay et al., 2004;
Gandhi et al., 2006; Higashi et al., 2007; Miklossy et al., 2006; Neumann et al.,
2004; Spillantini et al., 1998; Wakabayashi et al., 1998; Wenning and Jellinger,
2005; Zarate-Lagunes et al., 2001).
27 -Synuclein was the first PD gene discovered and is found in LB in PD
(McInerney-Leo et al., 2005; Spillantini et al., 1997). -Synuclein is a soluble synaptic protein in the normal human brain (Tu et al., 1998), primarily localised to synaptic terminals (Jakes et al., 1994). -Synuclein mutations are commonly used in mouse models, not only to model PD but other parkinsonian disorders such as MSA (McInerney-Leo et al., 2005). Similar to PD, -synuclein is the major protein localised in the inclusions of MSA but there have been no - synuclein gene mutations identified in MSA, further confirming the non-familial and sporadic presentation of this disease (Wenning and Jellinger, 2005;
Wenning et al., 1993). However, there has been one report of an autosomal dominant inheritance within an MSA family (Wullner et al., 2004). Genetic studies have been carried out in effort to analyse the potential risk factors and inheritability involved in MSA. It has been hypothesised that there are different subsets of genetic susceptibility factors that are different between MSA-P and
MSA-C (Ozawa, 2006). It may be that genes associated with parkinsonism may be linked to MSA-P and genes associated with ataxia could be linked to MSA-C.
Genetic risk factors may therefore also differ depending on the clinical subtype.
Understanding important proteins involved in the pathology of specific clinical
MSA subtypes may aid in elucidating the potential genetic components in relation to clinical presentations.
Parkin is a widely expressed ubiquitin E3 ligase, implicating the ubiquitin- mediated protein degradation pathway in neurodegeneration (Casarejos et al.,
28 2006; Klein et al., 2006; Shimura et al., 1999; Vercammen et al., 2006).
Expression of parkin is neuroprotective and mutations in or loss of parkin protein lead to a hereditary form of PD, called autosomal recessive-juvenile parkinsonism (AR-JP) (Perez and Palmiter, 2005). Several neuropathological studies on cases with AR-JP showed a loss of dopaminergic neurons in the SN and the absence of LB (the pathological hallmark for PD), although there have been few neuropathological studies on parkin mutations (Schiesling et al.,
2008). A gene closely affiliated with parkin called the parkin co-regulated gene
(PACRG) has also been identified (West et al., 2003). This gene is transcriptionally co-regulated with the parkin gene by a shared bi-directional promoter, and despite its close association with parkin, mutations of PACRG are not associated with early-onset parkinsonism (Deng et al., 2005). However, deletion of the shared promoter has been linked to early-onset parkinsonism
(Lesage et al., 2007).
The PINK1 gene was first identified in a large Italian family with an autosomal recessive form of PD (Valente et al., 2004). PINK1 encodes a 581 amino acid protein and thought to have a neuroprotective role (Gandhi et al., 2006; Petit et al., 2005; Valente et al., 2004). To date, there have only been four brains of patients with heterozygous PINK1 mutations that have had neuropathological analyses performed (Gandhi et al., 2006). The pathology in these patients is typical of idiopathic PD with substantial SN cell loss in the presence of LB
(Schiesling et al., 2008). Similar to PINK1, mutations in the DJ-1 gene have also been shown to cause early-onset autosomal recessive PD (Bonifati et al., 29 2003a; Bonifati et al., 2003b). This protein is thought to be associated with oxidative stress (Mitsumoto and Nakagawa, 2001). To date, there have been no studies on the neuropathology of patients with DJ-1 mutations (Schiesling et al.,
2008).
Mutations in the LRRK2 gene are currently the most frequent genetic cause of idiopathic and familial PD, with more than 50 variants identified as responsible for approximately 2-10% of idiopathic and 10-40% of familial PD (Berg et al.,
2005; Di Fonzo et al., 2005; Mata et al., 2006; Schiesling et al., 2008). However,
LRRK2 is distinct from the other PD-related genes in that the clinical phenotype can vary widely (atypical parkinsonism and dementia phenotypes) even within one family (Zimprich, Biskup, Leitner, Farrer et al 2004; Funayama, Hasegawa,
Kowa et al 2002). In addition to the heterogeneity in clinical phenotype, the pathology in these patients can also be highly variable, including brainstem LB, diffuse LB disease pathology and pure nigral degeneration without distinctive histopathology and PSP-like pathology (Zimprich et al., 2004).
PSP has been described as a sporadic tauopathy, as there has been no direct causative genes identified, however there is a strong genetic association with the microtubule associated protein tau (MAPT) gene (Albers and Augood, 2001;
Morris et al., 1999). An extended 5’-MAPT haplotype, Haplotype A, has been noted in 98% of PSP cases and has been recognised as a good indicator for sporadic PSP (Higgins et al., 2000). However, this haplotype has also been identified in 33% of controls, suggesting that there may be additional 30 environmental and genetic factors associated with the disease (Albers and
Augood, 2001). Haplotype H1 was found to have a strong affiliation with PSP
(Pittman et al., 2004), although recent subtyping of PSP into clinical phenotypes has found that haplotype H1 has a stronger affiliation for PSP-RS than PSP-P
(Williams et al., 2005). Additionally, there have been reports of families with PSP
(Pastor and Tolosa, 2002; Rojo et al., 1999). A silent mutation in exon 10 of the
MAPT gene has been discovered in an Australian family member with PSP-like pathology (Stanford et al., 2000). Another mutation in the MAPT gene was also found to cause a tauopathy with dementia and supranuclear palsy (Delisle et al.,
1999). These MAPT gene mutations increase the inclusion of exon 10 in the mature messenger RNA thus causing a surplus of 4-repeat tau over the 3-repeat tau isoforms, a feature found in PSP (Goedert et al., 1998; Mailliot et al., 1998).
1.1.4 Core pathologies differentiating PD, PSP and MSA
SN cell loss is a key pathological feature of both typical (PD) and atypical (PSP and MSA) parkinsonian syndromes. However, cell loss in PSP and MSA is more extensive, affecting other basal ganglia, cerebellar and spinal structures (Bak et al., 2005). The definitive diagnosis of different parkinsonian disorders is based on the type and distribution of pathological inclusions. In PD, the core LB inclusion is present in neurons (Figure 1.1A) and consists primarily of the - synuclein protein. PD is therefore categorised as an -synucleinopathy
(Geddes, 2005). In -synucleinopathies, insoluble -synuclein is phosphorylated, nitrated and often ubiquitinated (Duda et al., 2000a). Like PD,
31 -synuclein is the dominant abnormal protein expressed in the core GCI inclusions found in oligodendroglia in MSA (Figure 1.1B). However in LB, filaments are orientated in a radiating fashion in the periphery of the inclusions and less heavily coated by amorphous material (Forno, 1996). Whereas in GCI, the filaments are heavily coated by amorphous material and are arranged in parallel bundles towards the processes of the oligodendroglia (Gai et al., 2003).
MSA is also classified as a -synucleinopathy. Previously, three pathological forms of MSA were identified as either striatonigral degeneration (SND) (Adams et al., 1964), olivopontocerebellar atrophy (OPCA) (Geary et al., 1956) or Shy-
Drager syndrome (Shy and Drager, 1960). The first description of GCI in oligodendroglia (Papp et al., 1989) helped to unify MSA pathologically, although
MSA stands out among other neurodegenerative diseases in that its core inclusion pathology (the GCI) are localised in oligodendroglia rather than neurons.
The neuronal and glial pathologies found in PSP are composed of hyperphosphorylated tau, classifying PSP as a tauopathy (Gibb et al., 2004).
Tau is a microtubule associated protein related to axonal transport and in the normal brain is located predominantly in the axons (Komori, 1999). Tau proteins support the assembly and stabilise microtubules in a polymerised state. In the brain there are 6 tau isoforms generated by alternative splicing of exons 2, 3 and
10 in the MAPT gene (Tolosa et al., 2004). The accumulation of selective hyperphosphorylated tau isoforms that contain four microtubule binding domains
32 (4 repeat tau, 64 and 69kDa in molecular weight) is observed in PSP, and this accumulation of hyperphosphorylated tau disrupts microtubule function and interferes with axonal transport (Komori, 1999). AT8 is a robust immunoreaction marker commonly used to identify hyperphosphorylated tau protein (Braak et al.,
2006). PSP is also a distinct disorder in that it is associated with abnormal tau deposition in three main types of cells – neurons, astrocytes and oligodendroglia
(Takahashi et al., 2002). Neuronal NFT (Figure 1.1C) are the core inclusion used for the pathological diagnosis of PSP (Hauw et al., 1994; Litvan et al.,
1996b). In addition to NFT in neurons, glial inclusions are also considered important pathological markers for PSP (Burn and Lees, 2002). In PSP, glial inclusions are in the form of tufted astrocytes (TA) and coiled bodies (CB) in the oligodendroglia. TA contain hyperphosphorylated tau and are considered part of the degenerative process in PSP (Togo and Dickson, 2002).
33 Figure 1.1 Core pathological features of PD, MSA and PSP
Representative brightfield photomicrographs of 5m thick, paraffin-embedded sections taken at x400 magnification, immunoperoxidase labelled and counterstained with cresyl violet. Scale in C is equivalent for all photomicrographs.
A A dopaminergic neuron in the substantia nigra of a PD case containing an
-synuclein-immunoreactive Lewy body (LB).
B -Synuclein-immunoreactive glial cytoplasmic inclusions (GCI) in the
pons of a MSA case.
C Tau (AT8)-immunoreactive neurofibrillary tangles (NFT) in the pons of a
PSP case.
34
A
B
C
50μm 1.1.5 Pathological staging and differences between clinical phenotypes
The severity of -synuclein-immunopositive LB and Lewy neurites are graded to pathologically stage the progression of PD (Braak et al., 2003; Braak et al.,
2004) (Figure 1.2). The staging scheme is divided into 6 stages dependent on the progression of regions affected. Stages 1 and 2 reflects a confinement of pathology to olfactory regions, the medulla oblongata and pontine tegmentum, with stage 3 including regions affected in the lower and upper midbrain, and the anteromedial temporal mesocortex additionally affected in stage 4. End-stages 5 and 6 include all areas affected in stages 1 to 4 with additional neocortical areas affected. Therefore, the core LB pathology in PD can be used to stage the progression of pathology in PD.
The progression of pathology in some tauopathies can be staged based on the degrees of progressive atrophy divided into four stages (Broe et al., 2003).
Stage 1 reflects mild atrophy in the orbital and superior medial frontal cortices and hippocampus. Stage 2 progresses to include atrophy of other anterior frontal regions, temporal cortices and basal ganglia. Stage 3 involves all remaining tissue in coronal slices and stage 4 reflects overall marked atrophy in all areas. However, only limited atrophy is observed in PSP and this staging scheme for atrophy cannot be applied to PSP (Schofield et al., 2005).
35 Figure 1.2 Braak staging of pathological PD
A schematic diagram of the pathological staging of PD based on the deposition of Lewy bodies and Lewy neurites, courtesy of Heiko Braak.
A Pathological Braak stages 1 and 2 initially affecting the medulla oblongata
and pontine tegmentum.
B In addition to pathology in stages 1 and 2, pathological Braak stages 3
and 4 also affects the midbrain, basal prosencephalon and mesocortex.
C In addition to the pathological regions affected in stages 1-4, the
neocortex and premotor areas including primary sensory areas and the
primary motor field are affected in stages 5 and 6.
36
A Braak Parkinson’s disease stage 1&2 Preclinical Parkinson’s disease
B Braak Parkinson’s disease stage 3&4 Clinical Parkinson’s disease
C Braak Parkinson’s disease stage 5&6 Cognitive impairment
Courtesy of Heiko Braak The division of clinical subtypes in PSP and MSA has lead to the establishment of novel pathological grading systems for PSP and MSA that differ in the regions examined and the pathologies assessed, although there is some overlap. The clinical subtypes in PSP can be distinguished based on the recently published pathological tau severity scale (Williams et al., 2007a). A 12-tiered grading system has been established based on grading the severity of CB and associated threads in the SN, caudate nucleus and dentate nucleus. Four severity grades (grades 1-4) of CB and threads were used to evaluate the 3 selected regions. The grades for all 3 regions were summed to provide a total score ranging from a minimum of 0 to a maximum of 12. PSP-RS was consistently graded higher than PSP-P, as no PSP-P case was scored higher than 5. In addition, tau burden was topographically more restricted in PSP-P, with tau burden significantly greater in PSP-RS in all regions except for the putamen and SN. More recently, the differentiation of PSP clinical subtypes based on this pathological tau severity scheme (Williams et al., 2007a) was validated in another cohort to confirm the distinguishable PSP clinical subtypes based on tau burden (Jellinger, 2008).
In MSA, the pathological grading system is based on rating atrophy, neuronal loss, gliosis and GCI, separating MSA-P and MSA-C (Jellinger et al., 2005).
MSA-P and MSA-C can be divided into four grades ranging from grade 0 to 3.
Briefly, MSA-P grade 1 represents similarities to minimal change MSA, whereby the SN is significantly degenerated and the striatum preserved with minimal GCI and gliosis in the posterior putamen. MSA-P grade 2 features neuronal loss, 37 gliosis and GCI in the SN and putamen. MSA-P grade 3 reflects greater GCI severity in the SN and putamen than grade 1 and 2, and additional neuronal loss in the caudate nucleus and globus pallidus (Jellinger et al., 2005; Wenning et al.,
2002). In contrast, MSA-C grade 1 reflects widespread GCI with minimal atrophy, neuronal loss and gliosis, except for neuronal loss in the SN. MSA-C grade 2 represents widespread GCI, minimal atrophy, mild neuronal loss and gliosis in the pons and inferior olives but a variable severity of neuronal loss in the SN. MSA-C grade 3 features substantial atrophy of the cerebellum and pons, Purkinje cell loss and demyelination in the cerebellum, neuron and fiber loss in the pons and severe atrophy and gliosis in the inferior olives of the medulla. At grade 3, the SN often includes severe neuronal loss and gliosis, and
GCI severity can decrease with LB accumulation (Jellinger et al., 2005). It is also important to note that in addition to pure MSA-P or MSA-C grades, cases can present with varying combinations (Jellinger et al., 2005; Ozawa et al., 2004).
1.1.5.1 Clinicopathological correlates: parkinsonian subtype
The progressive loss of dopaminergic neurons in the SN is a key pathological feature in PD leading to the clinical and pharmacological abnormalities observed in the disease (Schulz and Falkenburger, 2004). However, all atypical parkinsonian syndromes have this feature, which may explain their initial early response to L-dopa (Berciano et al., 2002; Williams et al., 2005). Imaging studies have shown that midbrain atrophy (hummingbird sign) is worse in PSP than MSA-P and PD (Cosottini et al., 2007; Groschel et al., 2006; Kato et al.,
2003; Yekhlef et al., 2003). The SN is a consistently affected region in PSP 38 (Fearnley and Lees, 1991; Halliday et al., 2000; Oyanagi et al., 2001), but whether this is more prominent in PSP-P is yet to be determined. In MSA-P, the degree of degeneration in the SN correlates with the severity of parkinsonism
(Jellinger et al., 2005; Wenning et al., 2002), with the severity of akinesia correlating with the severity of cell loss in the putamen and SN, while more severe rigidity correlates with greater SN loss (Wenning et al., 1997). For MSA-
P, the L-dopa response is transient due to prominent subsequent putaminal degeneration (90% have loss of putamen at autopsy). Only 5% of patients with
MSA-P have long-term benefits from L-dopa (Burn and Jaros, 2001). In contrast in PSP-P, putamen loss is not a key pathological feature and all PSP-P patients have substantive benefit from L-dopa (Williams et al., 2005).
Despite the clinical similarities between these parkinsonian conditions, both
PSP-P and MSA-P have additional and more global regions of degeneration, although the timing of this additional degeneration has not been identified. Due to the recent division of PSP subtypes, patterns of degeneration have not been well studied for the different clinical groups. The major study defining pathological PSP subtypes used tau burden as a marker of disease severity
(Williams et al., 2007a). In this study, gaze palsy was absent from PSP-P cases along with less severe tau burden (Williams et al., 2007a; Williams et al., 2008).
Regions of degeneration correlating with parkinsonian symptoms in PSP are the thalamus (Henderson et al., 2000), striatum (Burn and Lees, 2002; Schulz et al.,
1999; Warren et al., 2005), globus pallidus (Hardman and Halliday, 1999) as well as the SN (Halliday et al., 2000; Hardman et al., 1997; Kluin et al., 2001). In 39 particular, degeneration of the external globus pallidus appears to be related to increased thalamic inhibition through the basal ganglia output nuclei, as observed in PD (Hardman and Halliday, 1999).
Regional changes have been confirmed at autopsy for MSA-P patients. These patients present, with an overall discolouration and atrophy of the putamen
(Konagaya et al., 1994; Schulz et al., 1999), increased hypointensities in or slit- like hyperintense bands lateral to the putamen (Konagaya et al., 1994; Schulz et al., 1999), with neuronal loss largely confined to the striatum and midbrain
(Kume et al., 1993). Detailed studies of the striatum and SN reported marked loss in the caudal putamen and SN, supporting a region-specific cell loss (Kume et al., 1993; Sato et al., 2007; Wenning et al., 1997).
In the majority of MSA cases, neuronal loss is quite marked at autopsy, independent of clinical subtype. Regions affected include the basal ganglia, brainstem and cerebellar regions. Several semi-quantitative studies have shown neuron loss in the caudate, putamen, pallidum, SN, brainstem reticular formation, pontine base and cranial motor nuclei (Papp and Lantos, 1994;
Tsuchiya et al., 2000; Wenning et al., 1997; Wenning et al., 1996). Quantitative studies (Benarroch et al., 2003; Benarroch et al., 2001; Benarroch et al., 1998) have demonstrated the selective neuronal loss in subnuclei of the pons and medulla oblongata, including one study correlating catecholaminergic neuron loss in the medulla with autonomic failure in MSA. Autonomic failure is observed in both clinical subtypes of MSA. Most studies have not correlated these 40 pathological changes with atrophy and have not compared degenerative changes across the parkinsonian phenotypes PD, PSP-P and MSA-P.
1.1.5.2 Clinicopathological correlates: cerebellar subtype
In PSP, atrophy of the superior cerebellar peduncle (SCP) appears to differentiate PSP from other parkinsonian conditions (Blain et al., 2006; Kataoka et al., 2008; Paviour et al., 2005; Price et al., 2004; Quattrone et al., 2008). The
SCP is involved in the cerebellar output pathway from the dentate nucleus targeting the ventrolateral nucleus of the thalamus and the red nucleus (Nolte,
1999). Comparatively, there is striking atrophy of the cerebellum, middle cerebellar peduncles, pontine basis and olivary nuclei in vivo in MSA-C
(Wenning and Jellinger, 2005), with T2-weighted images showing signal hyperintensities known as the “hot cross bun” signal within the pons and middle cerebellar peduncles in some cases (Scherfler et al., 2005; Schrag et al., 1998).
The middle and inferior cerebellar peduncles are associated with the cerebellar input pathways from the pons and spinal cord (Nolte, 1999). This suggests that different cerebellar systems (superior versus middle and inferior cerebellar systems) are involved in PSP-RS compared with MSA-C. Possible differences in cerebellar pathway involvement in PSP-RS and MSA-C may implicate different cerebellar motor presentations and pathology, however this needs to be further studied in detail.
Despite the cerebellar focus observed in these atypical parkinsonian syndromes, degeneration in the cerebellar system has not been well studied pathologically in 41 either PSP-RS or MSA-C. Neuronal loss is observed in the pons (Hirsch et al.,
1987; Kasashima and Oda, 2003; Malessa et al., 1991; Zweig et al., 1987) and cerebellar dentate nucleus (Matsumoto et al., 1998) in PSP. In contrast, clinical correlations to histopathology link cerebellar ataxia with neuronal loss in the inferior olives and cerebellar cortex in MSA-C (Wenning et al., 1997) and may be related to the degeneration of cerebellar input pathways. It will be important to determine if this pattern of degeneration is limited to these clinical subtypes, as well as to determine the type and timing of pathological degeneration within these cerebellar pathways.
As discussed previously, both PSP-RS and MSA-C subtypes can have significant eye signs, particularly as these diseases progress. The pathological substrate for these clinical features has not been determined for MSA-C.
However, studies have shown that the severity of tau deposition and neuronal loss in the SN pars reticulata (Halliday et al., 2000), mesencephalon (Juncos et al., 1991) and the pontine nucleus raphe interpositus (Revesz et al., 1996) are increased in PSP patients with gaze palsy. Cerebellar pathways involved in the motor control of eye movements may be disrupted in both PSP-RS and MSA-C and correlates to specific eye signs may help differentiate these phenotypes.
Although substantive cortical atrophy is not a feature of these atypical parkinsonian conditions, mild frontal lobe atrophy is well known to correlate with both the severity of NFT pathology and behavioural changes in PSP-RS
(Cordato et al., 1997; Cordato et al., 2002). In MSA-C, supratentorial volume 42 loss has been found in the orbitofrontal and mid-frontal regions as well as in temporomesial and insular areas of both hemispheres (Brenneis et al., 2005).
However, there are limited studies on correlations to the clinical symptoms of both PSP-RS and MSA-C with atrophy and neuronal loss.
1.1.6 Summary
In summary, the clinical subtypes of PSP-P and MSA-P present similar clinical symptoms, closely mimicking PD. In contrast, PSP-RS and MSA-C pathologically differ from PD but are similar to each other in their clinical presentations. In PD, PSP-P and MSA-P, the SN is a region that is consistently affected with correlates to parkinsonian features. The atrophy of the putamen is marked in MSA-P, whereas clinicopathological correlates to PSP-P have not been well characterised. The middle cerebellar peduncles appear to be affected in MSA-C, whereas in PSP, the atrophy of the SCP is used as a differentiating marker. Histopathological studies in cerebellar regions have shown correlates to eye signs in PSP-RS and ataxia in MSA-C, however these cerebellar clinical subtypes have not been well studied. Despite the similarities in clinical features and pathways affected, there have been no comparative studies of pathological comparisons across these disorders. The similarities in the PSP and MSA clinical subtypes and their differentiation based on glial pathology suggest that the cell types in particular pathways may be related to specific clinical subtypes.
The similar and more global regions/pathways affected warrants further investigation of the glial changes across these clinically overlapping parkinsonian disorders. 43
1.2 CELL SPECIFIC PROTEIN CHANGES IN PD AND ATYPICAL
PARKINSONIAN DISORDERS
1.2.1 Abnormal protein expression in neurons
Both PD and MSA are defined as -synucleinopathies with neuronal -synuclein inclusions featured in both disorders. In PD, the core pathological feature is localised in neurons in the form of -synuclein-immunoreactive LB (Figure
1.3A). The distribution of LB in PD is in both subcortical and cortical regions, as well as in the periphery (Hughes et al., 1993; Ohama and Ikuta, 1976;
Takahashi and Wakabayashi, 2005). In contrast, -synuclein-immunoreactive inclusions in neurons are less prominently observed in MSA (Burn and Jaros,
2001). This is also in contrast to the core -synuclein-immunoreactive GCI pathology observed in MSA. Both neuronal cytoplasmic inclusions (NCI) and neuronal intranuclear inclusions (NII) occur in MSA (Figure 1.3B), largely in the pontine and olivary nuclei (Nishie et al., 2004; Papp and Lantos, 1992)
The deposition of -synuclein has not been studied in detail in PSP, but there are reports of -synuclein-immunopositive LB in pathologically proven PSP cases (Fearnley et al., 1991; Gearing et al., 1994; Judkins et al., 2002; Mori et al., 2002; Tsuboi et al., 2003b). These rare reports of PSP and PD combined cases present a predominance of LB in neurons in the SN and dorsal motor nucleus, and at times in the cerebral cortex. In addition, another study has shown that the anterior olfactory nucleus of PSP patients have mild -synuclein
44 pathology (Tsuboi et al., 2003b). In addition to neuronal inclusions, one report has shown that the C-terminus of -synuclein was immunoreactive in glial inclusions of PSP following pre-treatment with proteinase K (Takeda et al.,
1998).
In PSP, NFT is the core neuronal pathological feature and can be either globose or flame-shaped in morphology (Figure 1.3C) (Tellez-Nagel and Wisniewski,
1973). NFT are tau-immunoreactive, with the 4R isoform predominating. The distribution of NFT in PSP concentrates in the basal ganglia, diencephalon and brainstem (Dickson et al., 1999a; Dickson et al., 2007). The current neuropathologic criteria for PSP requires a high degree of NFT and neuropil threads in at least three of the following regions: pallidum, subthalamic nucleus
(STN), SN, or pontine basis. In addition to this, a low to high density of these pathological features is required in any one or more of the following regions: the striatum, oculomotor complex, medulla or dentate nucleus.
In addition to -synuclein, a number of other proteins associated with genetic forms of PD are normally expressed in neurons. The dominant constituent expression of parkin is thought to be neuronal (Zarate-Lagunes et al., 2001) and there are varying reports of parkin expression in LB in typical PD
(Schlossmacher et al., 2002; Zarate-Lagunes et al., 2001). PINK1 protein is expressed in mitochondria in neurons and in glial cells and is unchanged in PD, although 5-10% of brainstem LB also contains PINK1 immunoreactivity (Gandhi
45 et al., 2006). In contrast, the normal expression of DJ-1 is weak in neurons, although NFT in PSP are DJ-1 immunopositive (Rizzu et al., 2004). -Synuclein- immunopositive LB in PD do not contain DJ-1 (Rizzu et al., 2004). Similarly,
LRRK2 is not a major component of LB in idiopathic PD, however it is expressed in neurons of the dopaminergic nigrostriatal pathway (Higashi et al., 2007;
Melrose et al., 2007). LRRK2 is also expressed in neuronal inclusions in a number of neurodegenerative conditions including Alzheimer’s disease, Pick’s disease, amyotrophic lateral sclerosis and Huntington’s disease (Miklossy et al.,
2006). Therefore, LRRK2 is strongly associated with pathological inclusions in several neurodegenerative conditions and is not confined to the core pathologies associated with parkinsonian conditions.
46 Figure 1.3 Neuronal and glial inclusions in PD, MSA and PSP
Representative brightfield photomicrographs of 5m thick, paraffin-embedded sections immunoperoxidase labelled with -synuclein or tau (AT8) and counterstained with cresyl violet. Scale in D is equivalent for photomicrographs
A-C. Scale in G is equivalent for photomicrographs E & F.
A An -synuclein-immunoreactive Lewy body (LB) in a dopaminergic
neuron of the substantia nigra in a PD case.
B An -synuclein-immunoreactive neuronal cytoplasmic inclusion (NCI) in
the pons of a MSA case.
C A tau (AT8)-immunoreactive neurofibrillary tangle (NFT) adjacent to a
normal neuron in the pons of a PSP case.
D A tau (AT8)-immunoreactive tufted astrocyte (TA) in the motor cortex of a
PSP case.
E -Synuclein-immunoreactive glial cytoplasmic inclusions (GCI) in the
pons of a MSA case.
F A tau (AT8)-immunoreactive coiled body adjacent to a normal neuron in
the pons of a MSA case.
G HLA-DR-immunoreactive activated microglia in the pons of a MSA case.
47
A B
C D
25μm E FG
50μm 1.2.2 Abnormal protein expression in astrocytes
Astrocytes provide essential support to neurons, including roles in synapse formation, maintenance and plasticity, and regulation of cerebral blood flow
(Lobsiger and Cleveland, 2007). The importance of astrocytes has begun to emerge with the growing knowledge that they are involved in almost every task the brain performs (Ransom et al., 2003). In neurodegenerative diseases, astrocytic changes are associated with the upregulation of glial fibrillary acidic protein (GFAP), an intermediate filament found in all astrocytes (Teismann and
Schulz, 2004). Astrogliosis is observed across all parkinsonian disorders and in addition some of these disorders accumulate inclusions in astrocytes.
In PD, reactive astrogliosis is thought to be minimal (Hirsch et al., 2005; Mirza et al., 2000), however, GFAP expression of astrocytes is observed primarily in the
SN (Hirsch et al., 2005; Vila et al., 2001). In addition, -synuclein- immunoreactive astrocytes are also observed in PD and shown to correlate with neuronal inclusion pathology (Braak et al., 2007; Wakabayashi et al., 2000). In contrast to PD, although severe astrogliosis is commonly observed in MSA
(Ozawa et al., 2004), there have been no reports of -synuclein-immunoreactive astrocytic inclusions. In PSP, increased reactive astrogliosis is observed with additional tau-immunoreactive TA (Figure 1.3D). These TA are thought to contribute to degeneration, rather than participating in a reactive process in PSP
(Togo and Dickson, 2002).
48 Many of the pathogenic proteins associated with genetic forms of PD (parkin,
PINK1 and DJ-1) are normally expressed in glia in the human brain
(Bandopadhyay et al., 2004; Gandhi et al., 2006; Neumann et al., 2004; Zarate-
Lagunes et al., 2001). Parkin immunoreactivity is observed in glial cells (Zarate-
Lagunes et al., 2001) and in a large proportion of GFAP-negative astrocytes in rat brain tissue (D'Agata et al., 2000). In PSP and MSA, PINK1 protein is present in upregulated reactive astrocytes (Gandhi et al., 2006). Similarly, DJ-1 immunoreactivity is also observed in reactive astrocytes in PD, PSP and MSA
(Bandopadhyay et al., 2004; Neumann et al., 2004). In addition to DJ-1 immunoreactivity in reactive astrocytes, tau-immunoreactive TA in PSP also express DJ-1 (Kumaran et al., 2007).
1.2.3 Abnormal protein expression in oligodendroglia
The distinguishing and core pathological feature in MSA is the -synuclein- immunoreactive GCI in oligodendroglia (Figure 1.3E) (Papp et al., 1989;
Trojanowski and Revesz, 2007). However, some reports have also shown - synuclein-immunoreactive oligodendroglia in PD (Campbell et al., 2001;
Wakabayashi et al., 2000). GCI are described as non-membrane bound cytoplasmic inclusions composed of loosely aggregated filaments/tubular structures (Burn and Jaros, 2001). A large number of GCI are identified using - synuclein in MSA (Burn and Jaros, 2001; Wakabayashi et al., 1998) even though -synuclein is a synaptic protein not normally found in oligodendroglia
(Culvenor et al., 2002; Duda et al., 2000b; Richter-Landsberg, 2000). No
49 increase in -synuclein mRNA occurs in MSA (Miller et al., 2005; Ozawa et al.,
2001). This suggests -synuclein aggregation within these oligodendroglia may result from an imbalance of multi-protein interactions (Gai et al., 1999).
CB are argyrophilic and tau-immunoreactive (Arima et al., 1997) (Figure 1.3F) occurring in oligodendroglia as fine bundles of filaments around a nucleus and extending into the proximal part of the cell process (Chin and Goldman, 1996).
CB are commonly found in the precentral cortex, internal capsule, pencil fibers in the lenticular nuclei, midbrain and the tegmentum of the pons and medulla oblongata (Komori, 1999). As described above, tau-immunoreactive CB and associated threads have also been used to grade tau burden and differentiate
PSP subtypes (Williams et al., 2007a) with the degree of CB thought to decline with disease duration (Josephs et al., 2006; Williams et al., 2007a). However,
CB is also thought to be strongly associated with regions of severe neuronal loss (Jin et al., 2006). Tau immunoreactivity has also been observed in oligodendroglial GCI in MSA (Cairns et al., 1997; Giasson et al., 2003; Takeda et al., 1997). One study has reported the expression of insoluble PINK1 in GCI in MSA (Murakami et al., 2007). The oligodendroglial pathologies of GCI in MSA and CB in PSP are also immunoreactive for DJ-1 (Kumaran et al., 2007;
Neumann et al., 2004).
There have been very few studies on oligodendroglia-associated changes in PD and although PSP or MSA are not recognised as gross demyelinating diseases
50 using routine myelin stains, the significant involvement of oligodendroglia in both disorders suggests some disruption to this cell type. In PSP, the dentate hilus and SCP are regions that are associated with demyelination (Ishizawa and
Dickson, 2001). Such changes have been associated with grumose degeneration (abnormalities in Purkinje cell synapses) in the dentate nucleus
(Cruz-Sanchez et al., 1992; Ishizawa and Dickson, 2001; Suyama et al., 1997).
Myelin disruption has been observed in the pons, caudate, putamen and globus pallidus of MSA cases using antibodies sensitive to abnormalities in myelin basic protein (MBP) (Matsuo et al., 1998). Few other studies have been performed identifying disease effects on myelin in MSA and PSP. In particular, there have been no studies on changes in constituent oligodendroglial proteins in these disorders. In MSA, GCI are thought to represent the primary change and neuronal pathology is considered secondary to oligodendroglial pathology
(Armstrong et al., 2006; Wenning and Jellinger, 2005). Furthermore, the implementation of CB as a measure of tau burden in PSP subtyping also suggests the importance of oligodendroglial pathology in PSP. Therefore, it would be of interest to identify changes in constituent oligodendroglial and myelin proteins to determine if such changes occur in both PSP and MSA.
51
1.2.4 Abnormal protein expression in microglia
Microglia comprise 10-20% of the total glial cell population and are evenly distributed throughout the normal brain, with their processes close together, but not touching each other (Gerhard et al., 2003). Using their processes, resting microglia constantly evaluate their surroundings under normal conditions, however with the slightest alteration in their micro-environment or as a consequence of pathological changes, they rapidly activate and express a morphological change (Hald and Lotharius, 2005). Microglial activation as a response to tissue injury is a feature of many neurodegenerative disorders, whereby the cell surface expression of the Human Leukocyte Antigen DR-1
(HLA-DR) can be used as a marker for tissue degeneration as activated microglia respond to tissue injury (Figure 1.3G) (Gerhard et al., 2003).
In PD, similar to astrocytic activation, microglial activation occurs with the loss of dopaminergic neurons (Hirsch et al., 2005). Animal models and in vitro culture studies of PD are indirect, but they do illustrate that the dopaminergic cells in the
SN are highly vulnerable to inflammatory attack and that microglial cells can be activated to mount such an attack (McGeer and McGeer, 2008). 1-methyl-4- phenyl-1,2,3,6-tetrahydropyridine (MPTP) models of PD have been used to produce a sustained microglial inflammatory reaction in the SN, although LB are not formed (Barcia et al., 2004; McGeer et al., 2003). Furthermore, studies have shown that -synuclein is an inflammatory stimulant for microglia that contribute
52 to the death of dopaminergic cells (Esposito et al., 2007; Gao et al., 2003; Lee et al., 2005; McLaughlin et al., 2006; Shavali et al., 2006; Zhang et al., 2005).
The pathological changes in microglia have been less studied in post-mortem brain tissue of the atypical parkinsonian disorders PSP and MSA. However, the use of the in vivo activated microglial marker [11C] (R)-PK11195 positron emission tomography (PET) in parkinsonian disorders have shown a pattern of increased microglial activation in regions of neuropathological alterations in PD,
PSP and MSA (Gerhard et al., 2003; Gerhard et al., 2006). In PSP, tau pathology correlates with microglial activation in all regions except for the brainstem, suggesting that in the brainstem, microglial activation is not related to tau deposition alone (Ishizawa, Dickson et al 2001). In MSA, the transformation of microglia into HLA-DR-immunopositive antigen presenting cells correlates with GCI burden (Ishizawa et al., 2004). The suggested role of microglial activation in these neurodegenerative conditions is to arbitrate neuronal loss
(Gerhard et al., 2003).
1.2.5 Summary
The abnormal protein expression in neurons differs across parkinsonian disorders, however, some similarities occur in the pathological changes in glia.
The role of glia has long been underestimated, with accumulating evidence suggesting that glial cells may represent a primary target of degenerative disease processes (Ransom, Behar, Nedergaard 2003; Croisier & Graeber
2006). It is still unclear how glial abnormalities facilitate degeneration in these 53 disorders and in particular, the earliest intracellular abnormalities associated with these conditions have not been identified and therefore, the mechanism of degeneration remains poorly understood. To determine early changes, it may be useful in initially studying the constituent glial proteins and how they are associated with other core pathological features observed in these disorders.
Many of the pathogenic proteins associated with genetic forms of PD appear to be expressed in glial cells and even in some of the glial inclusions observed in parkinsonian disorders. Despite this knowledge, there have been no comparative studies of how these glial proteins are affected in different parkinsonian disorders. The prominent glial-related inflammatory processes and inclusion pathology in PD, PSP and MSA warrants further studies of these glial changes across these parkinsonian disorders.
1.3 STUDY OBJECTIVES
The current literature suggests that there is substantial clinical overlap between typical PD and the atypical parkinsonian disorders. The overlap in clinical phenotypes suggests that similar pathways and cell types are affected in these disorders. There has been growing evidence of the significant degree of overlap between neurodegenerative diseases (Feany & Dickson 1996; Armstrong,
Cairns, Lantos 2001; Armstrong, Cairns, Lantos 2005; Galpern & Lang 2005;
Armstrong, Cairns, Lantos 2008). In particular, Armstrong & colleagues have suggested that although there are differences in morphology and molecular diversity, pathological lesions often express similar spatial patterns in several neurodegenerative disorders, implying a degree of overlap between different 54 disorders and shared pathological mechanisms (Armstrong, Cairns, Lantos
2001). Despite this, there have been no comparative studies on the pathological changes in these overlapping parkinsonian disorders. Pathologically, the loss of dopaminergic neurons in the SN is a key feature observed in PD, PSP and
MSA, although a comparison of glial changes in protein expression and deposition warrants further studies.
1.4 MAJOR HYPOTHESES
Clinical subtype is related to pathological regions and cell type/s affected rather than the type of inclusion pathology.
Astrocytic dysfunction occurs early in PSP or the cerebellar/Richardson’s syndrome phenotypes of PSP and MSA.
Oligodendroglial dysfunction occurs early in MSA or in the parkinsonian phenotypes of MSA and PSP.
Microglial activation occurs globally across all parkinsonian disorders and different forms of microglia relate to the pattern of pathological severity and degeneration.
55
Chapter 2: Common materials and methods
2.1 SOURCES OF TISSUE
Cases were sourced from different brain banks, which used the same diagnostic criteria (refer to chapter 1). Controls were matched for age and were without neurological or neuropathological disease. All tissue, and clinical and pathological information was collected with appropriate consent from brain donors and their next-of-kin, and the collections were approved by appropriate institutional Human Ethics Committees. Cases were longitudinally assessed by clinicians associated with each brain bank.
The Prince of Wales Medical Research Institute Tissue Resource Centre
(POWMRI TRC) provided fresh frozen and formalin-fixed brain tissue samples from longitudinally studied PD (n=10), PSP (n=17), MSA (n=12) and age- matched control (n=13) cases (Table 2.1) as requested through the Australian
Brain Donor Programs (ABDP) coordinated by Associate Professor Jillian Kril.
Neuropathological diagnoses for these cases were performed by Professor
Glenda Halliday and Associate Professor Jillian Kril. The POWMRI TRC tissue was used for both immunohistochemistry (IHC) and western blotting (WB).
56 The Queen Square Brain Bank (QSBB) provided formalin-fixed brain tissue samples from prospectively-studied PD (n=5), PSP (n=19), MSA (n=17) and control (n=5) cases (Table 2.1) as requested through the QSBB coordinated by
Professors Andrew Lees and Tamas Revesz. Neuropathological diagnoses for these cases were performed by Dr Janice Holton and Professor Tamas Revesz.
The QSBB tissue was used for IHC.
As the supply of fresh frozen brain tissue for MSA cases was limited from these brain banks, a further request for fresh frozen MSA tissue (n=5) was granted from the South Australian Brain Bank (SABB) coordinated by Professor Peter
Blumbergs. Neuropathological diagnoses for these cases were performed by
Professor Peter Blumbergs. This tissue was used for WB.
57
Table 2.1 General case demographics for control, PD, PSP and MSA cases
Case cohorts Sex Age at death PMD
(M/F) (Years, Mean SD) (Hours, Mean SD)
Control POWMRI TRC cohort 1 4M : 4F 72 8 16 10
Control POWMRI TRC cohort 2 4M : 1F 71 7 14 6
Control QSBB TRC cohort 3 2M : 3F 78 14 64 29
PD POWMRI TRC cohort 4 6M : 2F 75 5 17 16
PD POWMRI TRC cohort 5 2M : 0F 83 7 4 4
PD QSBB cohort 6 4M : 1F 79 4 70 45
PSP POWMRI TRC cohort 7 12M : 3F 74 8 10 7
PSP POWMRI TRC cohort 8 2M : 0F 76 2 12 11
PSP QSBB cohort 9 12M : 7F 76 9 27 13
MSA POWMRI TRC cohort 10 7M : 5F 69 8 13 12
MSA QSBB cohort 11 9M : 8F 68 7 34 23
MSA SABB cohort 12 1M: 4F 72 7 10 7
PMD= post-mortem delay, M= male, F= female, SD= standard deviation, POWMRI
TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB=
Queen Square Brain Bank, PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy, SABB= South Australian Brain Bank.
2.2 CASE ASCERTAINMENT AND CLINICAL INFORMATION
Information regarding the following clinical features was provided for all prospectively-studied cases, with some exceptions. Standard clinical information
58 available for all cases included age at onset and disease duration (determined from the earliest clinical presentation as assessed by medical practitioners from patient and informant information).
The clinical indices chosen for correlation studies were based on dominant clinical features and key differentiating markers of PD, PSP or MSA. Akinesia and rigidity are considered to be the core clinical features observed across these parkinsonian disorders (Brooks, 2002; Poewe and Wenning, 2002). Whereas resting tremor, rigidity, bradykinesia and postural instability are the major clinical features in PD (Hald and Lotharius, 2005). The clinical diagnosis of PD is certain if subjects have good clinical improvement with L-dopa therapy (Gelb et al.,
1999). Therefore, all these features were assessed to evaluate the parkinsonian signs in PD, PSP and MSA. The neurological examinations also involved Hoehn and Yahr (H&Y) staging (Hoehn and Yahr, 1998), which describes the progression of parkinsonian symptoms from stages 0 (no signs or symptoms) to
5 (severely affected). The last H&Y stage recorded for each patient was used for parkinsonism-associated clinical correlations.
Dysarthria refers to speech impairment and dysphagia is associated with swallowing difficulties. These features are more commonly associated with atypical parkinsonian disorders, in contrast to typical PD. In addition to these parkinsonian-related features, cognitive impairment is also commonly observed in neurodegenerative disorders, particularly with disease progression. The
Clinical Dementia Rating (CDR) scale (Morris, 1993) for the severity of dementia 59 was assessed, and the last CDR stage prior to death was used for clinical correlations associated with cognitive dysfunction. The CDR consists of five stages ranging from 0, 0.5, 1, 2 and 3.
As described in chapter 1, a possible diagnosis of PSP is given when either slow vertical saccades, vertical supranuclear gaze palsy or postural instability with falls occurs within a year of onset of symmetric akinesia or rigidity (Burn and
Lees, 2002). A probable PSP diagnosis includes all these symptoms with no evidence of other diseases that could explain them (Burn and Lees, 2002).
Supporting features for the diagnosis of PSP include postural abnormalities, poor response to L-dopa therapy and early dysphagia or dysarthria (Litvan et al.,
1996a; Litvan et al., 2003). Early falls, postural instability and eye signs were assessed as clinical indices related to PSP.
As described in Chapter 1, the Minneapolis Consensus Conference identified four clinical domains and a response to L-dopa to differentiate cases into possible and probable MSA in the absence of autopsy confirmation (Wenning et al., 2004) as 1) parkinsonism, 2) autonomic and urinary dysfunction, 3) cerebellar dysfunction and 4) corticospinal tract dysfunction. Therefore, autonomic dysfunction, postural hypotension and ataxia were primary features assessed to evaluate symptoms associated with MSA.
60 2.3 STANDARD PREPARATION OF BRAIN TISSUE
Brains from donors were obtained with consent at autopsy from the POWMRI
TRC, QSBB and the SABB. Brains were fixed for at least two weeks in 15% buffered formalin (39% aqueous solution of formaldehyde). Following fixation, the cerebellum and brainstem were separated from the cerebrum by sectioning through the cerebral peduncles. The weight and volume of the cerebrum was determined and the length of each hemisphere measured. The cerebrum was embedded in 3% agarose and cut into coronal slices. The cutting surface was perpendicular to the fronto-occipital axis and cut at 3mm intervals on a rotary slicer and examined macroscopically (Cullen and Halliday, 1998; Harding et al.,
2002). Standard blocks and blocks from regions of interest were taken from coronal slices including the midbrain (taken at the transverse level including the red nucleus), the putamen (dorsolateral level) and the pontine basis (taken at the transverse level including the SCP).
Blocks of all tissue regions of interest for each case were paraffin-embedded using a Tissue Tek automatic processor (Sakura Inc., Torrance, USA). Blocks were processed through graded ethanols and xylene and then infiltrated with paraffin wax under vacuum pressure. Paraffin-embedded blocks were then cut at 5-8m on a rotary microtome (HM 325 Microm). To ensure good adhesion of all brain tissue sections, slides for mounting the tissue sections were coated with gelatin or 3-aminopropyltrimethoxysilane (TESPA) (Sigma, St Louis, USA).
Gelatinised slides were coated with a 1% gelatin solution, then coated with a 4%
61 formaldehyde solution and dried to make ready for use. TESPA-coated slides were first coated with absolute ethanol for 10 seconds and then with TESPA for
5 minutes. The slides were then rinsed in dry acetone, followed by distilled water for 10 seconds each and then dried overnight in an oven at 40 C. Tissue sections were mounted onto gelatinised or TESPA-coated slides in preparation for IHC.
2.4 GENERAL IMMUNOHISTOCHEMICAL METHODS
2.4.1 Peroxidase immunohistochemistry (counterstained with cresyl violet)
Standard protocols for peroxidase IHC were utilised to identify the proteins of interest in all cases, as previously described (Halliday et al., 2005b). Firstly, sections were deparaffinized and rehydrated in xylene (twice, 3 minutes each),
100% ethanol (twice, 3 minutes each), 95% ethanol (3 minutes), 70% ethanol (3 minutes) and distilled water (3 minutes). Appropriate antigen retrieval methods were utilised depending on the primary antibody used (Table 2.2), followed by incubation in a 3% hydrogen peroxide and 50% ethanol solution (40 minutes, room temperature) to quench endogenous peroxidases. Following two washes in distilled water and 0.1M tris buffer (pH 7.4), a blocking step was performed by incubating slides in a 20% normal horse serum solution (1 hour, room temperature). Primary antibody incubations varied depending on the antibody
(Table 2.2) and were followed by three 0.1M tris buffer washes (5 minutes).
Sections were then incubated in rabbit or mouse biotinylated secondary antibody (1:200; 30 minutes at 37 C; Vector Laboratories Inc., Burlingame,
62 USA), followed by three 0.1M tris washes. The tertiary antibody incubation required an avidin-biotin-peroxidase tertiary complex (1:500; 30 minutes at room temperature; Vectastain, Vector Laboratories Inc., Burlinghame, USA).
Visualisation was achieved by incubation with 0.7% hydrogen peroxide in 0.15% diamniobenzidine tetrahydrochloride (Sigma, St Louis, USA) for 15 minutes at room temperature, followed by several 0.1M tris buffer and distilled water washes.
Following the completion of the peroxidase immunohistochemical procedure, sections were counterstained with cresyl violet (0.5%) or Mayer’s haemotoxylin to visualise Nissl substance. Sections were placed in cresyl violet for 30-60 seconds and then rinsed with water, and differentiated using 70% ethanol to obtain optimal histological intensity. Sections were then placed in 95% ethanol
(1 minute), 100% ethanol (twice, for 3 minutes each) and xylene (twice, for 3 minutes each). Slides were then coverslipped using DPX neutral mounting medium (Ajax Finechem, Taren Point, Australia) to make ready for analysis.
63
Table 2.2 Antigen retrieval methods for different primary antibodies
Primary antibodies Antigen retrieval method Primary antibody
incubation time
AT8, GFAP (anti- None 1 hour at 37 C rabbit), III-tubulin
-Synuclein, GFAP 99% formic acid (3 minutes) 1 hour at 37 C
(anti-mouse)
PACRG 99% formic acid (3 minutes) 1.5 hours at 37 C
Parkin 99% formic acid (10 minutes) and 1 hour at room
pressure cooking temperature
P25 0.2M citrate buffer, pH6.0 (15 minutes) Overnight at 4 C
MBP, CNPase, 0.2M citrate buffer, pH 6.0 (5 minutes) Overnight at 4 C
MAP1B
Neurofilament 0.2M citrate buffer, pH 6.0 (10 minutes) 1 hour at 37 C
Apolipoprotein D, 4% aluminium chloride (3 minutes) Overnight at 4 C degraded MBP,
HLA-DR
GFAP = glial fibrillary acidic protein, PACRG = parkin co-regulated gene, MBP = myelin basic protein, CNPase = 2’3’-cyclicnucleotide 3’phosphodiesterase, MAP1B = microtubule associated protein 1B, HLA-DR = human leukocyte antigen-DR1.
64 2.4.2 Double-labelling immunofluorescence
Double-labelling immunofluorescence was performed using previously established methods (Baker et al., 2006), including appropriate antigen retrieval methods depending on the different primary antibodies used (Table 2.2).
Paraffin sections were dewaxed through xylene, graded ethanols (twice in xylene, twice in 100% ethanol, 95% ethanol, 75% ethanol, for 3 minutes each) and lastly in distilled water (3 minutes). All appropriate antigen retrieval methods were carried out for both primary antibodies used for double-labelling immunofluorescence. Slides were then washed in distilled water and 0.1M tris buffer and placed in a solution of 3% hydrogen peroxide and 50% ethanol for 40 minutes at room temperature, then placed in a 20% normal horse serum solution for 1 hour at room temperature. Primary antibodies were then incubated at different times depending on the primary antibodies used (Table 2.2) and visualised with a cocktail of an anti-rabbit secondary antibody conjugated to
Alexa 568 (1:250; Molecular Probes, Invitrogen, Carlsbad, US) and anti-mouse secondary antibody conjugated to Alexa 488 (1:400; Molecular Probes,
Invitrogen, Carlsbad, USA) for 2 hours at room temperature. Slides were then washed in 0.1M tris (3 times in 5 minutes) and coverslipped with Vectashield mounting medium (Vector Laboratories Inc., Burlingame, USA). To test the specificity and ensure non-cross reactivity of secondary fluorescent probes, a section without primary antibodies was included for each staining procedure as a negative control. In addition, a cocktail of the secondary antibodies were applied to sections with only one primary antibody incubated on each section.
65 2.4.3 Combined peroxidase and immunofluorescence labelling
For the purpose of using same species-derived primary antibodies, a combined method of peroxidase visualisation and immunofluorescence was used. Firstly, the standard peroxidase protocol was performed as described above, with all appropriate antigen retrieval methods carried out for all primary antibodies included in the experimental procedure (Table 2.2) (Baker et al., 2006; Halliday et al., 2005b). Briefly, slides were incubated with the first primary antibody, and then incubated with a rabbit or mouse biotinylated secondary antibody (1:200,
Vector Laboratories Inc., Burlingame, USA) for 30 minutes at 37 C. The tertiary complex involved the incubation with an avidin-biotin-peroxidase tertiary complex (1:500, Vectastain, Vector Laboratories, Burlinghame, USA) for 30 minutes at room temperature. Visualisation was achieved by incubation with
0.7% H2O2, in 0.15% diaminobenzidine tetrahydrochloride (Sigma, St Louis,
USA) for 15 minutes at room temperature, followed by several 0.1M tris washes.
This was then followed by the immunofluorescent labelling step, either using one fluorescent probe (method used in chapter 5) or a cocktail of two fluorescent probes (method used in chapter 6). Prior to the second primary antibody incubation, slides were incubated in a 20% normal horse serum solution for 1 hour at room temperature. Sections were then incubated with the second same species-derived primary antibody for 1 hour at 37 C. Following several 0.1M tris washes (3 times in 5 minutes) sections were incubated with one or a cocktail of secondary antibodies (anti-mouse conjugated to Alexa 568, Molecular Probes,
Invitrogen, Carlsbad, USA or anti-rabbit conjugated to Alexa 488, Molecular
66 Probes, Invitrogen, Carlsbad, USA) for 2 hours at room temperature. Slides were then washed in 0.1M tris (3 times in 5 minutes) and coverslipped with
Vectashield mounting medium (Vector Laboratories Inc., Burlingame, USA). To ensure specificity of the immunohistochemical technique, a positive and negative (with no primary antibody incubation) control was included in each experiment.
67
Chapter 3: Pathological staging of Progressive Supranuclear
Palsy
3.1 INTRODUCTION
As described in chapter 1, PSP is a progressive neurodegenerative disorder with a variety of tau-immunoreactive neuropathologies occurring in association with fibrillary gliosis and neuronal loss predominantly in subcortical regions (Jin et al., 2006; Komori, 1999; Steele et al., 1964). Despite thorough knowledge of the distribution and type of pathology, the pathological progression of PSP has not been clearly defined. This emphasises the necessity of a severity scale for the progression of PSP based on tissue histopathology.
The most consistent types of histopathology in PSP are well described. The presence of intraneuronal fibrillised tau in the form of NFT establishes a definitive diagnosis for PSP (Hauw et al., 1994; Litvan et al., 1996b), with current criteria requiring a high degree of NFT and neuropil threads in at least three of the following regions: pallidum, STN, SN, or pontine basis and a low to high density of these pathological features in at least one of the following regions: striatum, oculomotor complex, medulla or dentate nucleus. This concentration has recently been confirmed using more modern IHC (Dickson et al., 2007;
Williams et al., 2007a). Neuronal loss is thought to be variable, and tau-
68 immunopositive astrocytes or processes in these regions help to confirm the neuropathological diagnosis.
The two major clinical phenotypes, PSP-P and PSP-RS, relate to significantly different quantities and distributions of pathological tau (AT8-immunoreactive CB and threads), with more restricted and milder tau pathology occurring in PSP-P compared with PSP-RS (Williams et al 2007). As described in chapter 1, a histopathological grading system has been developed to assess pathology that can distinguish these clinical subtypes using overall tau burden in the SN, caudate and dentate nucleus (Williams et al., 2007a). A similar approach has been used to distinguish another rare clinical phenotype, pallido-nigro-luysial atrophy (PNLA), which has less pathological tau in the motor cortex, striatum, pontine nuclei and cerebellum (Ahmed et al., 2008). These grading systems enable the overall evaluation of pathological tau to distinguish clinical phenotypes of PSP. However, all cases have similar core pathological PSP features, and the progression of these core pathologies is still poorly understood.
An interesting finding in PSP is that, as the disease progresses over time, there is a negative rather than positive correlation between the burden of pathological tau in subcortical and cortical regions and disease duration (Halliday et al.,
2000; Josephs et al., 2006; Rub et al., 2002; Williams et al., 2007a). This negative relationship, in association with the differences observed between clinical phenotypes, limits the usefulness of tau deposition alone as an indicator 69 of disease severity. Furthermore, in addition to tau pathology, Ahmed and colleagues also evaluated the degree of neuronal loss in the SN, STN and dentate nucleus. A correlation between neuronal loss and disease duration in these regions was not identified in either the PSP or PSP-PNLA groups (Ahmed et al., 2008). This suggests that the assessment of neuronal loss alone is also a poor indicator of disease severity and progression in PSP.
Most other neurodegenerative tauopathies can be staged by their progressive atrophy into 5 stages (0-4) (Broe et al., 2003). This staging scheme is not applicable for PSP due to the limited atrophy observed (refer to chapter 1)
(Schofield et al., 2005), indicating a substantive difference in the consequence of the tau abnormality and regional deposition in this disorder. The staging scheme developed for MSA may be a useful template, as MSA also has two major phenotypes (MSA-P and MSA-C) with progression determined by grading several pathological features (Jellinger et al., 2005) including the assessment of atrophy, neuronal loss, astrogliosis and abnormal protein deposition in GCI.
Using this concept for PSP, the STN, SN and globus pallidus are the most consistently affected and are suggested to be the earliest regions affected
(Verny et al., 1996; Williams et al., 2007a). While it has been suggested that the pattern of NFT topography commences subcortically then spreads cortically in
PSP (Armstrong et al., 2006; Armstrong et al., 2007b; Bergeron et al., 1997), this concept has been challenged by recent findings suggesting the motor cortices are affected early, followed by other subcortical pathways (cerebellum and pons, caudate nucleus) and finally extending into prefrontal and parietal 70 cortical regions (Williams et al., 2007a). The loss of neurons and atrophy in cerebellar relay pathways have been identified as contributors to early falls in
PSP (Halliday et al., 2005a), with atrophy of the SCP potentially diagnostic for
PSP (Paviour et al., 2005; Tsuboi et al., 2003a). The severity of neuronal loss in the SN has been correlated with the later clinical features of gaze palsy (Halliday et al., 2000) and dysarthria (Kluin et al., 2001). Establishing the pathological staging of PSP will assist in determining its pathogenesis.
3.1.1 Aim
To establish a staging scheme, by grading different core pathological features of
PSP.
3.2 METHODS
3.2.1 Cases Used
In order to develop and validate a staging scheme for PSP that reflects disease progression over time, several cohorts are required, some of which need to include prospectively collected cases ranging from extremely early in the disease to end stage. As the fortuitous death of PSP cases at early disease stages are extremely rare, a collaborative approach between major collections of pathological specimens was instigated in order to assemble sufficient cases with adequate clinical follow-up at both early and late stages of disease analysis.
Further validation of the staging scheme was performed on an independent sample. Therefore, several cohorts were used to 1) develop the scheme and 2) validate the scheme. Consent for all tissue samples was provided and approved 71 by the Human Ethics Committees associated with all institutions. Clinical details of age at death, age at onset and disease duration from the time of diagnosis was collated for all cases. Duration of clinical symptoms (early falls and slow or absent supranuclear gaze) were established from the first symptom onset through to death. Cases used were pure PSP cases and did not have any coexisting Alzheimer’s disease, therefore Braak NFT staging (Braak et al., 2006) was used to stage tangle pathology. Additionally, Williams’s PSP stages
(Williams et al., 2007a) and widths of the SCP (Tsuboi et al., 2003a) were analysed for cases included in correlation studies.
3.2.1.1 Cases for method development
13 prospectively followed cases with clinical and pathologically diagnosed PSP from the ABDP processed through the POWMRI TRC (cohort I - POWMRI TRC,
Table 3.1) were used for method development.
3.2.1.2 Cases for scheme validation
To validate the PSP staging scheme, a separate cohort was used, which included 16 prospectively followed cases with clinical and pathological PSP
(excluding those from cohort I) from the POWMRI TRC (cohort II - POWMRI
TRC, Table 3.1).
72
Table 3.1 Cohort characteristics
Cohort I Cohort II Cohort III POWMRI POWMRI International TRC TRC cases Gender ratio M:F 10:3 10:6 15:6 PSP-P:PSP-RS ratio 3:10 0:16 5:16
Age at onset (y) 68± 9 63± 8 69± 9
Age at death (y) 75± 7 70± 6 74± 8 Post-mortem delay (h) 10± 7 18± 21 11± 7 Disease duration (y) 7± 3 7± 3 5± 4 Duration of falls (y) 4± 3 5± 2 3± 3 Duration of eye signs (y) 2± 1 3± 2 1± 1** Brain weight (g) 1235± 158 1171± 151 1242± 150 Braak neuritic stage (/6) 1± 1 2± 2 1± 1 Williams PSP stage (/12) 4± 2 - 4± 2 Width of SCP (mm) 4.2± 0.6 3.8± 0.8 4.2± 0.6 POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, M= male, F= female, PSP-P= progressive supranuclear palsy – parkinsonism, PSP- RS= progressive supranuclear palsy – Richardson’s syndrome, y= years, h= hours, g= grams, SCP= superior cerebellar peduncle. ** from both groups using one-way analysis of variance p<0.05 followed by posthoc t least-square-difference test p<0.05.
3.2.1.3 Cases for clinical correlations
To determine correlations to clinical measures, 11 prospectively followed PSP cases were identified through international collaborators as dying with early disease indicators not reaching end-stage PSP including three from the QSBB, three from the Harvard Brain Bank and five from the ABDP (cohort III -
73 international cases). These cases were matched with 10 end-stage cases from cohort I and were included in cohort III to determine pathological changes over the disease and establish correlations to clinical indices.
3.2.2 Development of a pathological PSP staging scheme
3.2.2.1 Regional tissue sampling
Based on the current understanding of the distribution of PSP pathology (see chapter 3 introduction) combined with knowledge of the MSA staging scheme
(Jellinger et al., 2005), a number of regions were chosen. From those regions consistently affected early in both PSP phenotypes, the SN (transverse level including the red nucleus) the STN (coronal level including the mammillothalamic tract) were chosen. The anterior caudate nucleus (coronal level including the nucleus accumbens) was selected, as it is also a subcortical region consistently affected in both PSP phenotypes. From the cerebellar pathways likely to be involved early in PSP-RS, the pontine basis (transverse level including the SCP) the dentate nucleus (parasagittal level through the middle of the nucleus) were chosen. In addition, the primary motor cortex
(coronal level including the pulvinar of the thalamus) was chosen.
Tissue blocks from these regions were sampled from 3mm - 1cm formalin-fixed brain slices, then paraffin-embedded and cut at 5-8m on a microtome. Sections were mounted on gelatinised slides and immunohistochemically stained with and AT8 antibody (1:10,000; MN1020 Endogen, Rockford, USA), a robust
74 marker for hyperphosphorylated tau (as described in chapter 1), using standard peroxidase visualisation and counterstained with 0.5% cresyl violet as previously described (Halliday et al., 2005b) (refer to chapter 2). The reliability of staining was ensured, by using positive and negative controls in all staining procedures.
3.2.2.2 Feature identification and severity ratings
Based on the dominant types of PSP according to the NINDS-SPSP (Litvan et al., 1996b) and the current MSA and PSP staging schemes (Jellinger et al.,
2005; Williams et al., 2007a), four features of interest were identified using brightfield microscopes (Leica, Leitz Labourlux S) - neuron loss, tau-positive
NFT formation, tau-positive TA and overall tau burden. To maximise the potential use of the scheme in routine pathological practice, a semi-quantitative analysis of pathology was used for each feature of interest rather than more unbiased and laborious sterological methods of quantitation. Using semiquantitative analysis is consistent with routine diagnostic practice, with other staging schemes and previous assessments of these histopathological features in PSP (Ahmed et al., 2008; Bergeron et al., 1997; Josephs et al., 2006;
Paviour et al., 2004; Williams et al., 2007a). To assist with the development of rating the severity of neuron loss, an additional cohort of age-matched controls without neurological or neuropathological disease was identified from the
POWMRI TRC (age at death = 74 ± 8 years, post-mortem delay = 11 ± 7 hours, brain weight = 1235 ± 158 grams, and Braak neuritic stage = 1 ± 1). Preliminary assessment by the candidate and a PhD research student at the Mayo Society for PSP Brain Bank was used to determine reliability of feature identification and 75 rating in each region of interest, ratified by Professors Glenda Halliday
(POWMRI TRC) and Dennis Dickson (Mayo Society for PSP Brain Bank).
Neuron loss - Feature evaluation was performed by scanning at x40 magnification in 3 random regions to determine the overall loss of neurons in each region of interest. This was followed by the evaluation at x100 magnification to determine a final grade for each case. All visible neurons with nucleoli, both tau positive and tau negative, were evaluated. Preliminary examination revealed inconsistent or limited overall neuron loss in the pontine basis, dentate nucleus, anterior caudate and motor cortex tissue samples compared with controls (Figure 3.1). After preliminary examination, the ventral region of the SN was sampled for neuron loss, as this region was most consistently affected (Fearnley and Lees, 1991). For both the ventral SN and
STN, the variability in overall neuron density was estimated for each case as no overall loss (0, same as control density) (Figure 3.2A), mild overall loss (1, limited neuron loss), (Figure 3.2B) moderate overall loss (2, obvious neuron loss but not marked) (Figure 3.2C) or severe overall loss (3, very few to no neurons remaining without having some tau deposition) (Figure 3.2D) compared to controls (Figure 3.2). Regional atrophy and gliosis were found to be highly variable between cases and therefore were not incorporated into the measure of neuronal loss. The agreement for two raters for the severity of neuron loss was perfect (1.0).
76 Figure 3.1 Minimal neuron loss in the pons in PSP
A representative photomicrograph of 5m thick paraffin-embedded section of the pons, immunohistochemically labelled with tau (AT8) and counterstained with cresyl violet, taken at x100 magnification. As shown, minimal neuron loss in the pons was observed and this was similarly observed in the dentate nucleus, anterior caudate and motor cortex in PSP.
77 100μm Figure 3.2 Representative grades of neuron loss in PSP
Representative photomicrographs of 5m thick paraffin-embedded sections of the subthalamic nucleus, immunoperoxidase labelled with tau (AT8), counterstained with cresyl violet, taken at x100 magnification. Scale in D is equivalent for all photomicrographs.
A A representative grade of none (0), showing no overall loss of neurons.
B A representative grade of mild (1), showing a limited loss of neurons.
C A representative grade of moderate (2), showing an obvious overall loss
of neurons.
D A representative grade of severe (3), showing a substantial and marked
loss of neurons with very few neurons remaining.
78 AB
CD
100μm Tau-positive NFT - Feature evaluation was performed by scanning the entire region of interest at x40 magnification to determine the overall deposition of
NFT. A grade was calculated from sampling the 3-5 fields of view of tau- immunoreactive NFT at x100 magnification. For all regions, the variability in NFT density was estimated for each case in proportion to the remaining neurons as none/rare (grade 0, <5%) (Figure 3.3A), mild (grade 1, ~25%) (Figure 3.3B), moderate (grade 2, ~50%) (Figure 3.3C) or severe (grade 3, all remaining neurons are tau-immunoreactive) NFT (Figure 3.3D). The agreement for two raters for the severity of NFT was perfect (1.0)
Tau-positive TA - Feature evaluation was performed by scanning at x40 magnification in 3-5 randomly selected areas in the region of interest to determine an average grade for tau-immunopositive TA. Only characteristic tau- immunopositive TA was evaluated with the final severity grading performed at x100 magnification. Preliminary examination revealed limited to no TA per field in the ventral SN, STN, dentate nucleus and pontine basis tissue samples
(Figure 3.4). After preliminary examination, tau-immunopositive TA were graded in the samples of the anterior caudate nucleus and motor cortex (average of a number of cortical strips perpendicular to the cortical surface and avoiding sulcal depths and heights). This is consistent with previous studies identifying TA as the pathological feature as most prominent in these regions (Dickson et al.,
2007; Iwasaki et al., 2004; Takahashi et al., 2002). For both the anterior caudate nucleus and motor cortex, the variability in tau-positive TA was estimated for
79 each case as none (0) (Figure 3.5A), mild numbers (1, a sparse distribution)
(Figure 3.5B), moderate numbers (2, present in approximately half the field of view) (Figure 3.5C) or severe numbers (3, dense tau deposition throughout the field of view) (Figure 3.5D) of TA. The agreement for two raters for the severity of tau positive TA was almost perfect (0.81).
80 Figure 3.3 Representative grades of NFT deposition in PSP
Representative photomicrographs of 5m thick, paraffin-embedded sections of the subthalamic nucleus immunoperoxidase labelled with tau (AT8) and counterstained with cresyl violet, taken at x100 magnification. Scale in D is equivalent for all photomicrographs.
A A representative grade of none (0), showing no tau-immunoreactive NFT.
B A representative grade of mild (1) NFT, showing tau-immunoreactive NFT
in a few neurons, in proportion to the number of neurons remaining.
C A representative grade of moderate (2) NFT, indicating half the number of
neurons remaining contain tau-immunoreactive NFT.
D A representative grade of severe (3) NFT, showing all remaining neurons
contain tau-immunoreactive NFT.
81 AB
CD
100μm Figure 3.4 Minimal tufted astrocytes in the substantia nigra of PSP
A representative photomicrograph of a 5m thick paraffin-embedded section of the substantia nigra, immunoperoxidase labelled with tau (AT8) and counterstained with cresyl violet, taken at x100 magnification. As shown, although substantial neuron loss and tau-immunoreactivity in remaining neurons are evident, no tau-immunoreactive tufted astrocytes are observed in this field of view in the substantia nigra.
82 100μm Figure 3.5 Representative grades of tufted astrocytes in the caudate nucleus of PSP
Representative photomicrographs of 5m thick paraffin-embedded sections of the caudate nucleus, immunoperoxidase labelled with tau (AT8) and counterstained with cresyl violet, taken at x100 magnification. Scale in D is equivalent for all photomicrographs.
A A representative grade of none (0), showing no tau-immunoreactive
tufted astrocytes in the caudate nucleus.
B A representative grade of mild (1) severity of tufted astrocytes, showing a
sparse distribution of tau-immunoreactive tufted astrocytes in the caudate
nucleus.
C A representative grade of moderate (2) severity of tufted astrocytes,
showing tau-immunoreactive tufted astrocytes distributed throughout half
the field of view in the caudate nucleus.
D A representative grade of severe (3) severity of tufted astrocytes,
showing tau-immunoreactive tufted astrocytes densely spread throughout
the caudate nucleus.
83 AB
CD
100μm Overall tau burden - Feature evaluation was performed by scanning at x40 magnification to determine 5-7 fields of view containing tau-immunopositive pathology in the region of interest. Final grading of the severity of tau- immunopositive pathologies included all types of tau deposition at x100 magnification. Sampling for the ventral SN, STN, anterior caudate nucleus and motor cortex are as described above. The sampling of the dentate nucleus was performed in 3 random fields, while in the pontine basis a number of horizontal strips parallel to the pontocerebellar fibers were examined. For all regions, the density of tau-immunopositive pathologies (overall tau burden) was estimated for each case as none (0, no tau-immunopositive pathology), mild tau deposition
(1, sparse), moderate tau deposition (2, patchy tau deposition in at least half the field of view) or severe tau deposition (3, dense tau deposition dominating most of the field of view) (Figures 3.3 & 3.5). The agreement for two raters for the severity of tau-positive pathologies was perfect (1.0)
To identify the most informative measures for staging PSP pathology using the minimum number of regions, the severity of each pathological feature was graded in each case using the algorithms shown in Table 3.2. Paired t-tests were initially used to determine differences within and between regions in the severity of pathologies. Features were considered informative if they showed hierarchical variability across the cohort and correlated with clinical indices
(Spearman’s rank correlations; SPPS Inc., Illinois, USA). A staging scheme was developed based on the different regional patterns of pathologies identified.
84
Table 3.2 Feature assessment in brain regions of interest
Pathological feature Neuron NFT Tufted Tau burden loss astrocytes Ventral substantia nigra grade* grade* - grade*
Subthalamic nucleus grade* grade* - grade* Pontine basis - grade* - grade* Dentate nucleus - grade* - grade* Anterior caudate - grade* grade* grade* Motor cortex - grade* grade* grade* NFT= neurofibrillary tangles.
*score 0= none, 1= mild, 2= moderate, or 3= severe.
3.2.3 Correlations between tau stage and clinically relevant indices
To establish any correlations between the pathological staging, Williams PSP staging, and clinical indices (Table 3.1), factor analysis and Spearman’s rank correlations (SPPS Inc., Illinois, USA) were performed. Clinically relevant indices were considered to be those related to time or potentially simple measures of pathological severity. The indices identified were age at death, age at onset, disease duration (from the time of diagnosis), duration of falls, duration of eye signs (supranuclear gaze palsy) and SCP width.
3.3. RESULTS
3.3.1 Analysis of cohorts
In all cohorts studied, there were more males than females, with no significant differences between the cohorts studied in age at onset, age at death, disease
85 duration, post-mortem delay (PMD), brain weight, Braak stage of neuritic pathology or SCP width. The duration of eye signs in patients of cohort III was on average significantly shorter, when compared with cohorts I and II (Table 3.1) and consistent with the selection of this cohort for earlier disease durations.
In all cohorts studied, more cases had the clinical features of PSP-RS than those of PSP-P (Table 3.1). Cases with PSP-RS had a significantly younger age of onset of PSP (66±8 versus 76±11 years, p=0.01) and age at death (72±7 versus 80±9 years, p=0.01) compared with cases of PSP-P. Despite their younger average age, cases with PSP-RS had higher average Braak neuritic stages compared with the PSP-P cases studied (1.6±1.5 versus 0±0, p=0.03).
3.3.2 Analysis of the variability in pathological features and the use of this variability in developing the scheme
The average, standard deviation (SD) and range of scores for each pathological feature assessed for cohort I are given in Table 3.3. Only one of the regions evaluated had consistently severe pathology in most cases, the ventral SN. In this region neuronal loss was more severe than NFT or overall tau burden (t>5, p<0.0001), whilst there was no difference between the severity of NFT and overall tau burden (t=0, p=1). Overall severity of nigral cell loss and NFT did not show a hierarchical pattern across the cohort. For the STN, the severity of neuronal loss was more severe than the severity of NFT (t=2.5, p=0.03) whilst
NFT severity and overall tau burden were similar (t=1.8, p=0.11). Overall severity of subthalamic NFT showed a hierarchical pattern across the cohort. 86 For the pontine basis, NFT density reflected the overall tau burden (t=0, p=1), with the severity of NFT appearing hierarchical. CB and threads reflected the overall tau burden in the dentate region of the cerebellum, although the severity scores for these pathologies were not hierarchically varied across the cohort. In the caudate nucleus, the overall tau burden was reflected in the density of TA
(t=1.9, p=0.08) found in significantly greater quantities than NFT (t>6, p<0.0001) and variable across the cohort. In the motor cortex the tau burden was also mainly reflected in the density of TA (t=0.6, p=0.58) rather than NFT (t=1.9, p=0.08), and the variability in the severity of TA was greater than that for NFT.
87
Table 3.3 Regional severity* data (average, standard deviation and [range]) for each pathological feature in cohort I (N=13)
Pathological feature Neuron NFT Tufted Tau burden loss astrocytes Ventral substantia nigra 3±0.5¶ 2±1.0 - 2±0.9 [2-3] [0-3] [0-3] Subthalamic nucleus 2±0.7¶ 2±1.0§ - 2±0.9 [1-3] [0-3] [0-3] Pontine basis - 1±1.0§ - 1±1.0 [0-3] [0-3] Dentate nucleus - 0±0.6¶ - 1±1.1 [0-1] [0-3] Anterior caudate - 0±0.6¶ 1±0.8§ 1±0.8 [0-1] [0-3] [0-3] Motor cortex - 0±0.5¶ 1±0.8§ 1±0.7 [0-1] [0-2] [0-2] N= number of cases, NFT= neurofibrillary tangles. *Severity score rated as 0-3 for each case. ¶Statistically different from other pathologies in the same region. §Hierarchical across regions.
The region with the most severe neuron loss was consistently the ventral SN when compared with the STN (t=2.9, p=0.01) (Figure 3.6). 69% of all cases were graded as having severe nigral neuron loss, with the remaining 31% having moderate neuron loss. In the STN, 46% of all cases were graded as severe and moderate, and 8% were mild (Figure 3.6). This suggests that the ventral SN and STN may be consistently affected regions at all stages of PSP, with the greatest variability in neuron loss observed in the STN.
88
The severity of NFT was not significantly different (t<1.4, p>0.20) across the three core regions required for NINDS diagnosis of PSP (Hauw, Daniel Dickson et al 1994; Litvan, Agid, Calne et al 1996), the SN, the STN and the pontine basis. NFT density was quite variable between cases, although there were no cases that presented with an absence of NFT in the ventral SN and STN. In the
NINDS recommendations for PSP diagnosis, it is acknowledged that the dentate nucleus, caudate nucleus and motor cortex have a more variable and lower density of NFT pathology than the core regions analysed above (Hauw et al.,
1994; Litvan et al., 1996b), which is also consistent with the present study
(t>3.5, p>0.01). In these regions, NFT densities were similar (t<0.5, p>0.60) and were never scored as severe, with many cases (69-77%) having no NFT and
15-31% of cases graded as having mild NFT pathology in these regions.
Tau burden was primarily reflected by NFT density or TA in all regions studied, except for the dentate nucleus. CB and neuropil threads predominantly reflected the overall tau burden in the dentate nucleus, as shown previously (Williams et al., 2007a). In this region, 8% of cases were graded as severe, 38% of cases were moderate and 8% had mild pathology, while almost half of the cases (46%) had no pathology in the dentate nucleus sections sampled.
Tau-positive TA was the most dominant tau pathological feature observed in the anterior caudate nucleus and motor cortex, although the greatest pathology found subcortically (t=6.3, p<0.001, severe in 8% of cases). In the majority of 89 cases, TA were either mild (23-62%) or moderate (15-24%) in these regions, with only 8% of the cases having no TA in the anterior caudate nucleus. 62% of cases were graded as having no TA in the motor cortex.
3.3.3 The development of a staging scheme using the variability in pathological features and clinical correlates
For cohort 1, disease duration negatively correlated with brain weight (Rho=-
0.33, p=0.03) and the SCP width (Rho=-0.38, p=0.03). Only an increasing severity of TA in the caudate nucleus negatively correlated with brain weight
(Rho=-0.58, p=0.04) and SCP width (Rho=-0.68, p=0.04). For the other regions a non-linear hierarchy using the most severe and/or variable feature assessed was used. Figure 3.6 shows the hierarchical pattern of these pathologies across these regions, with the SN (neuron loss) > STN (neuron loss) > STN (NFT) > pontine basis (NFT) > anterior caudate nucleus (TA) > dentate nucleus (tau burden) > motor cortex (TA) (see also Figure 3.2).
90 Figure 3.6 The severity of the identified hierarchical pathologies in regions of interest
100%
90%
80%
70%
60% none mild 50% mod severe 40%
30%
20%
10%
0% SN_NL STN_NL STN_NFT Pons_NFT Caudate_TA Dentate_Tau MTR_TA
SN_NL= ventral substantia nigra neuron loss, STN_NL= subthalamic nucleus neuron loss, Pons_NFT= neurofibrillary tangles in the pontine basis, Caudate_TA= tufted astrocytes in the anterior caudate nucleus, Dentate_Tau= tau burden in the dentate nucleus, MTR_TA= tufted astrocytes in the motor cortex.
Based on this data, a severity scheme with six stages (1-6) was trialled (Table
3.4). As moderate to severe neuronal loss was consistently observed in the ventral SN, a moderate or severe degree of neuronal loss in this region was considered a mandatory feature.
91 Table 3.4 Development scheme 1 of PSP pathological staging based on feature assessment. Moderate to severe SN cell loss is a mandatory feature.
STN Dentate Motor STN Pons NFT / STAGE neuron nucleus cortex NFT Caudate TA loss Tau TA Stage 1 1 0 0 0 0
Stage 2 2 1 0/1 0/1 0/1
Stage 3 2/3 1/2 1/2 0/1 0/1
Stage 4 3 1/2 2 2 1/2
Stage 5 3 2 3 2 2
Stage 6 3 3 3 3 3
STN= subthalamic nucleus, NFT= neurofibrillary tangles, TA= tufted astrocytes.
Applying this development scheme 1 (Table 3.4) to cohort I revealed that only
15% of the cases fitted into the stages identified. To determine which features could be used to optimise the scheme, each pathological feature was individually excluded and the proportion of cases that fitted into these variant schemes determined. Due to the most non-hierarchical pattern observed being in the dentate nucleus (as shown in Figure 3.6), the variant of the dentate was excluded and this significantly improved the proportion of cases that fitted the scheme (46%). Therefore, a new scheme (development scheme 2, Table 3.5) was applied with the exclusion of dentate tau burden. To improve the effectiveness of the scheme, further features were excluded for optimisation as explained below.
92
Table 3.5 Development scheme 2 of PSP pathological staging based on feature assessment. Moderate to severe SN cell loss is a mandatory feature.
STN neuron Pons NFT / Motor STAGE STN NFT loss Caudate TA cortex TA Stage 1 1 0 0 0
Stage 2 2 1 0/1 0/1
Stage 3 2/3 1/2 1/2 0/1
Stage 4 3 1/2 2 1/2
Stage 5 3 2 3 2
Stage 6 3 3 3 3
STN= subthalamic nucleus, NFT= neurofibrillary tangles, TA= tufted astrocytes.
Exclusion of the motor cortex TA did not significantly change the proportion that could fit this variant scheme (54%). Exclusion of the pons NFT / caudate TA significantly improved the proportion of cases that could fit this variation of the scheme (77%). However, the most successful variation for PSP staging was to exclude the evaluation of NFT pathology in the STN. All thirteen cases could be staged using this variation. Therefore, a refined version of development schemes 1 and 2 was established for the pathological staging of PSP (Table
3.6).
93 Table 3.6 Refinement of the PSP pathological staging scheme with the closest two out of three variables required. Moderate to severe SN cell loss is a mandatory feature.
Pons NFT/ Motor cortex STAGE STN neuron loss Caudate tufted tufted astrocytes astrocytes Stage 1 0 0 0
Stage 2 1 0/1 0
Stage 3 2 0/1 0/1
Stage 4 2/3 1/2 0/1
Stage 5 2/3 2/3 2/3
STN= subthalamic nucleus, NFT= neurofibrillary tangles.
3.3.4 The pathological staging of PSP severity
Stage 1 represents loss of neurons in the SN without visible loss of subthalamic neurons. Due to the tau deposition in the SN, STN and globus pallidus not being used in this staging scheme, these cases still fulfil pathological diagnosis for
PSP (Hauw et al., 1994; Litvan et al., 1996b).
Stage 2 represents moderate to severe loss of the SN, a mild loss of neurons in the STN, and none or mild pathology in the pons and/or caudate nucleus.
Stage 3 represents moderate to severe loss of the SN, moderate loss of neurons in the STN, and none or mild degree of tau pathology in the pons
94 and/or caudate nucleus. None or mild tau-immunoreactive TA in the motor cortex.
Stage 4 indicates moderate to severe loss of the SN, a moderate or severe loss of neurons in the STN, with a mild or moderate degree of tau pathology in the pons and/or caudate nucleus but mild or no pathology in the motor cortex.
Stage 5 is the most severe, with all regions moderately or severely affected.
There is moderate to severe loss of the SN and STN, with the degree of tau pathology moderate to severe in all fields of view of the pons and/or caudate and the motor cortex.
3.3.5 Analysis and validation of the pathological staging of PSP
For cohort I, common factor analysis of stage, disease duration, brain weight and SCP width revealed these variables were all related to a single dominant factor explaining 52% of the variance (loading for duration=0.75, pathological stage= 0.64, brain weight=-0.70, SCP width=-0.78). This suggests that the pathological stage in this cohort is positively related to disease duration and negatively related to brain weight and SCP width.
Cohort II contained only the PSP-RS phenotype and, as may then be expected, presented a greater disease severity overall (n=14, 88% at stages 4-5).
However, common factor analysis of stage, disease duration, brain weight and
SCP width revealed that stage, disease duration and brain weight were related 95 to a dominant factor explaining 38% of the variance (loading for duration=0.65, pathological stage=0.82, brain weight=-0.65). This confirms that pathological stage is positively related to disease duration and negatively related to brain weight.
3.3.6 Correlations between PSP pathological severity, pathological tau burden and clinical indices
Half the cases in cohort III were selected to have non-end stage disease so that correlations with clinical variables could be more effectively tested. For the PSP-
RS group there was a bimodal distribution with 36% of cases having pathological stage 2 and 3 disease and 18% having stage 4 disease. The PSP-
P cases had a unimodal distribution with pathological stages 2-4. The clinical indices tested in this cohort were age at death, age at onset, disease duration, duration of falls, duration of eye signs, and SCP width. The pathological stage of disease positively correlated with disease duration (Rho=0.75, p<0.001), the duration of falls (Rho=0.59, p=0.005) and the duration of eye signs (Rho=0.60, p=0.004) but not with the other variables assessed in this cohort. There was no significant difference between the pathological progression of patients with PSP-
RS versus PSP-P using this staging scheme (2=0.19, p=0.67), possibly indicating a similar disease mechanism.
3.4 DISCUSSION
96 By using some invariant and other highly variant pathologies in PSP, the present study has been able to devise a progressive pathological staging scheme that correlates with disease duration. This scheme aims to identify a common underlying pathological mechanism not dependent on clinical phenotype or tau burden. The use of this scheme should be considered in tandem with other similar staging schemes to address the concept of pathological progression in
PSP.
Neuronal loss in the STN varies with the presence of the gaze palsy in PSP
(Halliday et al., 2000), whereas the SN is consistently severely affected in PSP
(Halliday et al., 2000; Oyanagi et al., 2001). The current staging scheme has included the depletion of nigral neurons in the SN as a mandatory feature, whereas neuronal loss in the STN has been included as a more variant feature that appears to play an early role in the pathological progression of PSP. This is consistent with the somewhat delayed clinical onset of the gaze palsy in PSP, which often contributes to difficulties with early differential diagnosis (Tolosa et al., 1994). It should be noted that the inclusion of SN cell loss suggests a pre- clinical phase of PSP, which has not been factored into this disease staging.
Midbrain atrophy on magnetic resonance imaging (MRI) (hummingbird sign) has been used to differentiate PSP from PD, MSA-P and normal aging (Kato et al.,
2003; Oba et al., 2005), with atrophy of the midbrain positively correlating with disease duration (Oba et al., 2005). These studies confirm that tissue loss in the midbrain is a diagnostic feature of PSP and suggests that it is affected pre-
97 clinically in PSP. These studies further support the inclusion of the SN as a mandatory region in the current PSP staging scheme.
In addition to STN neuron loss, NFT in the pons as well as TA in the caudate nucleus and motor cortex assisted with predicting the progression of disease over time. In PSP, abnormal tau deposition variably related to disease duration and in certain regions, decreased with disease duration (Halliday et al., 2000;
Rub et al., 2002; Williams et al., 2007a), yet poorly correlates with disease duration in most regions (Armstrong et al., 2007a), whilst in the lower brainstem does not correlate with disease duration at all (Rub et al., 2002). In the cohorts studied, abnormal tau deposition did not decline in the pons or caudate nucleus with longer disease durations, although in larger cohorts there is a slight non- significant trend to do so (Ahmed et al., 2008). This reflects that the severity of tau-positive NFT in the pons and TA in the caudate nucleus may be useful for
PSP staging, as they may reflect disease stage in these anatomical regions. The caudate nucleus has previously been included as one of the regions to assess tau burden for distinguishing clinical phenotypes (along with tau deposition in the
SN and dentate nucleus, (Williams et al., 2007a). It was found that overall tau burden in these regions declines with increasing durations (Williams et al.,
2007a), suggesting that tau deposition in the SN and cerebellum also declines over time. For both regions, this decline is likely to be associated with increasing neuron loss.
98 TA in the motor cortex is considered to be a prominent pathological feature in
PSP (Dickson et al., 2007). It has been previously established that there are no correlations between the density of TA in cortical and subcortical regions
(Armstrong et al., 2007a). In the cohorts studied, more variable numbers of tau- positive TA in the motor cortex were observed between cases at all stages, although this may relate to sampling of this region to some degree. The use of
TA in the motor cortex correlated best with the late spreading of pathology observed in PSP (Josephs et al., 2006).
Overall, the developed pathological staging scheme for PSP attempts to combine the evaluation of core pathologies associated with PSP. Previous reports have shown that tau burden or neuronal loss alone poorly correlates with disease duration (Ahmed et al., 2008; Armstrong et al., 2007a; Halliday et al.,
2000; Rub et al., 2002; Williams et al., 2007a). Therefore, combining the pathological features of STN neuronal loss, NFT deposition in the pons and tau burden in more ancillary regions such as the caudate nucleus and motor cortex seems to reflect a common underlying progression of pathology in PSP. Further evaluation of this scheme in larger cohorts is now warranted.
3.4.1 Comparison with current diagnostic techniques for PSP
The current neuropathologic criteria for PSP requires a high degree of NFT and neuropil threads in at least three of the following regions: pallidum, STN, SN, or pontine basis. In addition to this, a low to high density of these pathological features is required in any one or more of the following regions: the striatum, 99 oculomotor complex, medulla or dentate nucleus (Hauw et al., 1994; Litvan et al., 1996b). The current staging scheme utilises all of the core regions from the neuropathologic criteria for PSP including the SN, STN, pons, and in addition, the caudate nucleus and motor cortex. The aim of the staging scheme was to utilise the known core regions affected in PSP and use this knowledge to identify the progressive changes in pathology. The neuropathologic criteria for PSP is based on the severity of NFT and neuropil threads, whereas the current staging scheme combines the primary pathologies of neuronal loss in core regions (SN and STN), NFT in the pons and TA in ancillary regions (caudate nucleus and motor cortex). Therefore, the current neuropathologic criteria (Hauw et al., 1994;
Litvan et al., 1996b) form the basis for the current staging scheme that aims to grade the progression of pathology in PSP.
An increasingly accepted diagnostic marker for PSP is atrophy of the SCP
(Hauw et al., 1994; Litvan et al., 1996b), whereby the SCP appears to be less affected in PSP-PNLA compared with PSP (Ahmed et al., 2008). Therefore, in addition to disease duration, the width of the SCP was correlated with the histopathological variables used to stage disease severity. In cohort I, pathological stage negatively correlated with SCP width, however, this was not shown in cohort II (an end-stage cohort) or in cohort III (this measure was not available in ~50% of early cases in this cohort). These data suggest that SCP atrophy is a useful feature and warrants further examination.
3.4.2 Accuracy and limitations of the staging scheme 100 The current staging scheme was applicable to all cohorts used for the development and validation processes. No significant differences were observed between the pathological stages of patients with PSP-RS versus PSP-P. This may be due to the relatively small number of PSP-P cases and its unimodal distribution of pathological severity. The application of this scheme to cohorts with larger variability of PSP phenotypes, including PSP-P, PSP-RS and PSP-
PNLA (Ahmed et al., 2008; Williams et al., 2007a), is required to further validate any common core progression of pathology across these different clinical phenotypes.
The inclusion of a rare cohort of early PSP cases was a crucial factor in devising a scheme that reflects the pathological progression of PSP. Williams and colleagues have suggested that without early PSP cases, the topographical changes of tau pathology could not be identified (Williams et al., 2007a).
Although our cohort included only a small number of cases, the current scheme positively correlated with disease duration in these PSP cases.
3.4.3 Comparison with staging schemes for other parkinsonian and neurodegenerative diseases
As described in chapter 1, the Braak staging scheme for typical PD is based on the main pathological feature of -synuclein immunoreactive LB and Lewy neurites, graded into 6 progressive stages (Braak et al., 2003; Braak et al.,
2004). Unlike PD, the atypical parkinsonian disorders PSP and MSA have proven difficult to grade disease severity based on one pathological feature.
101 Using a similar strategy to that employed for the MSA staging scheme (Jellinger et al., 2005), a PSP staging scheme was developed using more than one pathological feature. Previous studies have shown that PSP has several clinical phenotypes (PSP-P, PSP-RS and pure akinesia with gait freezing) that can be distinguished by the severity of tau pathology (Ahmed et al., 2008; Williams et al., 2007a; Williams et al., 2007b). The MSA staging scheme has a separate progression scheme for each clinical subtype. The current PSP staging scheme uses core common features for all clinical phenotypes, identifies features that appeared to have a hierarchical progression and has determined the best combination that related to disease duration and therefore, forming a measure of pathological progression in PSP.
102
Chapter 4: Clinicopathological characterisation of cases for
comparisons
4.1 INTRODUCTION
As detailed in chapter 1, although characteristic pathological features can definitively diagnose patients with idiopathic PD, PSP and MSA, there can be extensive overlap between the clinical features at presentation and during the disease course. In particular, the identification of PD-overlapping clinical phenotypes in autopsy-proven PSP and MSA cases suggests that the destruction of similar anatomical systems by different pathological processes is likely. In addition, each of these diseases has considerable pathological variability in different anatomical regions depending on the stage of the disease process in which the patient dies (Braak et al., 2003; Braak et al., 2004; Broe et al., 2003; Jellinger et al., 2005). This chapter describes the variability in clinical features and pathological severity for the cases evaluated in this thesis.
4.1.1 Aims and Hypothesis
Hypothesis: Clinical and pathological features related to specific regions/pathways are associated with clinical subtype.
103 Aim: To clinically and pathologically characterise case groups from different cohorts by assessing clinical indices, core pathologies and atrophy to determine overlapping and differentiating features.
4.2 METHODS
As described in chapter 2, cases used were provided by the POWMRI TRC,
QSBB, and SABB. The assessment of clinical information is described in chapter 2.
4.2.1 Assessment of regional atrophy
To assess the degree of regional atrophy between disease groups, a point- counting method was utilised, as previously described (Double et al., 1996a;
Double et al., 1996b; Halliday et al., 2003). The degree of atrophy in disease groups was determined as a proportion of the control mean volume. Tissue processing for this method was only suitable for the POWMRI TRC cohorts 1, 4,
7 and 10, and no data was presented for other cohorts.
Brains were weighed at autopsy and the volume of the brain measured by fluid displacement. Following a period of 14 days fixation, the weight and volume of the brain were remeasured to calculate formalin-induced shrinkage, found to be less than 1% in all cases. The cerebellum and brainstem were detached from the cerebrum and then the weight and volume of the cerebrum were determined.
Each cerebrum was embedded in 3% agarose and sliced into 3mm coronal slices, photographed and the photographs were printed in black and white at 1 x 104 magnification. Each brain slice photograph was randomly overlayed with a grid of 1961 points (area: 141 x 200mm), and the number of points falling on each region of interest identified. The subcortical regions of interest included the caudate nucleus, putamen, the globus pallidus (not differentiating between external and internal segments), the entire midbrain and the entire pons. The volume of each region was calculated by multiplying the sum of points measured for each structure of interest (which may appear in more than one slice) by the volume represented by each point. The proportional volume was determined by dividing the volume of each region by the cerebrum volume. Repeated measurements and interrater error was less than 5%.
Correlations between regional volumes for each disease type were performed using non-parametric Spearman’s rank tests (SPPS Inc., Illinois, USA).
Significant differences between groups were statistically identified using
ANOVA, followed by posthoc least square difference tests (SPPS Inc., Illinois,
USA).
4.2.2 Assessment of pathological staging and severity of core pathologies
-Synuclein-immunoreactive LB are the pathological hallmark for PD (refer to chapter 1), and the Braak LB staging scheme (Braak et al., 2003; Braak et al.,
2004) uses this pathology to stage disease progression. Tau-immunoreactive
NFT are the main pathological features of PSP (refer to chapter 1), although other disease pathologies are used for the pathological staging of PSP (refer to
105 chapter 3). -Synuclein-immunoreactive GCI are the histological hallmark of
MSA (refer to chapter 1), although other disease pathologies are used for the pathological staging of MSA (Jellinger et al., 2005). In addition to identifying the pathological disease stages, the severity of the core pathologies for PD, PSP and MSA were evaluated to correlate with other pathological changes of interest.
Separate sections of the medulla oblongata, pons, midbrain, lateral cerebellum, anterior and posterior basal ganglia, anterior cingulate, hippocampal, frontal, temporal and motor cortices were immunohistochemically stained for - synuclein or tau (AT8) (refer to chapter 2), and counterstained with cresyl violet to grade the neuropathological stages of PD, PSP and MSA. Degeneration of the pigmented neurons in the SN is a consistent feature of all parkinsonian disorders, and the severity of nigral cell loss was graded in a randomised method, as none (0), mild (1), moderate (2) or severe (3) (Figure 4.1), as previously described in chapter 3. The severity of LB, GCI and NFT in the SN, putamen and pons were evaluated in a semi-quantitative and randomised manner. The putamen and pons were selected to evaluate the severity of core pathologies in addition to the SN, as these regions concentrate pathology in the parkinsonian and cerebellar subtypes of PSP and MSA. For the evaluation of
NFT (Figure 4.2) and GCI (Figure 4.3), a grade was calculated from sampling 3-
5 fields of view at x100 magnification. Lesion severity was graded as none/rare
(0), mild (1, a sparse distribution), moderate (2, in close to half the field of view)
106 or severe (3, densely spread throughout the field of view). LB severity was graded in a different manner by sampling the whole region of interest at x100 magnification and grading as none (0), mild (grade 1, 1 LB), moderate (grade 2,
2-6 LB) and severe (grade 3, 7 or more LB).
107 Figure 4.1 Representative grades of neuronal loss in the substantia nigra in PD, PSP and MSA
Representative photomicrographs of 5m thick, paraffin-embedded sections of the substantia nigra, histologically stained with cresyl violet, taken at x250 magnification. The scale bar in D is equivalent for all photomicrographs.
A A representative grade of none (0), indicating no loss of the dopaminergic
neurons in the substantia nigra.
B A representative grade of mild (1) neuron loss, indicating a limited and
mild loss of dopaminergic neurons in the substantia nigra.
C A representative grade of moderate (2) neuron loss, indicating a
substantial and obvious loss of dopaminergic neurons in the substantia
nigra.
D A representative grade of severe (3) neuron loss, indicating very few to
no neurons remaining in the substantia nigra.
108 AB
CD
500μm Figure 4.2 Representative grades of NFT as a core pathological feature of
PSP
Representative photomicrographs of 5m thick, paraffin-embedded sections of the pons in PSP. Sections are immunoperoxidase labelled with tau (AT8), counterstained with cresyl violet and taken at x100 magnification. Scale in D is equivalent for all photomicrographs.
A A representative grade of none (0), showing no tau-immunoreactive NFT
in the neurons.
B A representative grade of mild (1), showing approximately 25% of the
remaining neurons containing tau-immunoreactive NFT.
C A representative grade of moderate (2), showing almost half the
remaining neurons containing tau-immunoreactive NFT.
D A representative grade of severe (3), showing all the remaining neurons
consist of tau-immunoreactive NFT.
109 AB
CD
100μm Figure 4.3 Representative grades of GCI as a core pathological feature of
MSA
Representative photomicrographs of 5m thick, paraffin-embedded sections of the putamen in MSA. Sections are immunoperoxidase labelled with -synuclein, counterstained with cresyl violet and taken at x200 magnification. Scale in D is equivalent for all photomicrographs.
A A representative grade of none (0), indicating no -synuclein
immunoreactive GCI in the oligodendroglia.
B A representative grade of mild (1) GCI, indicating a sparse distribution of
-synuclein-immunoreactive GCI.
C A representative grade of moderate (2) GCI, indicating -synuclein-
immunoreactive GCI distributed in approximately half the field of view.
D A representative grade of severe (3) GCI, indicating a dense distribution
of -synuclein-immunoreactive GCI.
110 AB
CD
100μm As described in chapter 1, the pathological staging of PD has been well established and utilises the anatomical distribution and severity of -synuclein- positive Lewy pathology in six pathological disease stages (Braak et al., 2003;
Braak et al., 2004). Stages 1 and 2 are presymptomatic disease stages, whereby inclusion pathology is confined to the medulla oblongata and olfactory bulb and patients do not have the clinical features characteristic of PD. Stages 3 and 4 refer to the subtle to severe changes in the SN and other grey matter regions of the midbrain and the basal forebrain, with these stages reflecting the typical onset and progression of idiopathic PD. Stages 5 and 6 additionally affect regions of the telencephalic cortex and reflect progression of disease symptoms to include later developing cortical features.
The newly developed pathological PSP staging scheme (refer to chapter 3) was used where possible. As described in chapter 3, there are five main stages based on the pathological features of neuronal loss, NFT and TA in specific brain regions. The depletion of neurons in the SN is considered a mandatory feature for all stages. Stage 1 indicates only a loss of neurons in the SN, whereas stage 2 reflects a mild loss of STN neurons, and none or mild pathology in the pons and/or caudate nucleus and motor cortex. Stage 3 requires a moderate loss of neurons in the STN, and none or mild degree of tau pathology in the pons and/or caudate nucleus and motor cortex. Stage 4 indicates a moderate or severe loss of STN neurons, with a mild or moderate degree of tau pathology in the pons and/or caudate nucleus but mild or no
111 pathology in the motor cortex and stage 5 is when all regions are moderately or severely affected.
MSA cases were pathologically staged according to published criteria (Jellinger et al., 2005) (refer to chapter 1) using the grading (0-4) of neuronal loss, astrogliosis and GCI load in five regions of interest: 1) posterior caudate nucleus, putamen and internal globus pallidus, 2) SN, 3) pontine basis, 4) medulla oblongata and 5) the cerebellum. The scores for each region of interest combine to provide a final MSA grade ranging from SND or OPCA grades 1 to 3.
As described in chapter 1, this staging scheme differentiates between cases with MSA-P (SND) and MSA-C (OPCA) predominance (Jellinger et al., 2005).
Correlations between atrophy and indices of pathological severity for each disease type were performed using non-parametric Spearman’s rank tests
(SPPS Inc., Illinois, USA).
4.3 RESULTS
4.3.1 Controls
Controls were assessed in the same manner through the same programmes, and were included if they had no neurological and neuropathological disease and were within 4 years of the age range of the parkinsonian cases. The mean age at death for the POWMRI TRC controls was 71 years of age (Table 4.1).
The main causes of death were cardiac-related problems (6 cases) and cancer
(4 cases) with one case of renal failure and one death due to post-operative 112 complications. The QSBB controls all died due to cancer and had an average age at death of 78 years old (Table 4.1).
Table 4.1 Demographic, volumetric and pathological variables for controls
Cohort 1 Cohort 2 Cohort 3 POWMRI POWMRI QSBB (n=5) TRC (n=8) TRC (n=5) Technique assessed IHC WB IHC Included in chapters 4, 5, 6, 7 6 7 Sex (M/F) 4M : 4F 4M : 1F 2M : 3F Age at death (Years, Mean SD) 72 8 71 7 78 14 PMD (Hours, Mean SD) 16 10 14 6 64 29* Brain volume (Mean SD) 1185 166 1388 102 N/A Disease stage 0 0 0 Caudate volume (ml) 7 2 N/A N/A Putamen volume (ml) 7 2 N/A N/A Globus pallidus volume (ml) 3 1 N/A N/A Midbrain volume (ml) 5 1 N/A N/A Pons volume (ml) 9 2 N/A N/A SN neuronal loss (Mean, range) 0 (0) N/A N/A Pathology in SN (Mean, range) 0 (0) N/A N/A Pathology in putamen (Mean, range) 0 (0) N/A N/A Pathology in pons (Mean, range) 0 (0) N/A N/A POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB= Queen Square Brain Bank, IHC= immunohistochemistry, WB= western blotting, SD= standard deviation, M= male, F=female, PMD= post-mortem delay, SN= substantia nigra, *significantly different.
113
4.3.2 PD diagnosis and characterisation
All PD cases reached clinical criteria for either possible or probable PD and were definitively diagnosed by the presence of -synuclein immunoreactive LB in brainstem pigmented nuclei (Gelb et al., 1999).
4.3.2.1 Case demographics and clinical progression
The PD cases from the POWMRI TRC consisted of 8 males and 2 female patients with an average age of onset of 55-60 years, an average age at death of 75-83 years, and an average disease duration of 15-28 years (Table 4.2). All cases had reached severe clinical disease with H&Y scores of 4 or 5 (Table
4.2). The median CDR score was 0 (range 0-3; Table 4.2).
The PD cases from the QSBB consisted of 4 males and 1 female and the average age of onset was 61 years, age at death was 79 years and the average disease duration was 18 years (Table 4.2).
4.3.2.2 Pathology and atrophy
Based on Braak’s staging scheme, -synuclein deposition in the medulla oblongata, pons, midbrain, limbic (hippocampus, entorhinal and anterior cingulate) and neo- (frontal and temporal association) cortices were assessed to grade the degree of Lewy pathology in the PD cases. Braak LB staging was not available for the QSBB cohort. The POWMRI TRC PD cohort consisted of four
114 stage 4 and four stage 5 cases (Table 4.2), suggesting that all PD cases had similar degrees of disease severity at the time of death.
The assessment of the volume of regional structures in PD showed that the pons was largest in volume, followed by the putamen, caudate nucleus and midbrain, with the globus pallidus the smallest structure assessed (Table 4.2).
The volume of the caudate nucleus correlated with the volume of the putamen, globus pallidus and pons (all Rho>0.89, all p values <0.01), but not with the midbrain in PD (p=0.22).
As expected for diagnosis, neuronal loss in the SN in PD was severe (Table
4.2). LB severity was assessed as the core pathology for PD, and a moderate severity of LB was observed in the SN, a mild severity in the pons, with this pathology being absent in the putamen (Table 4.2). The severity of LB in the SN correlated with the severity of LB in the pons (Rho=0.82, p<0.05).
Despite the lack of variability in the pathological stages for the PD cases assessed, the Braak LB stage correlated with the volume of the caudate nucleus, putamen and globus pallidus (all Rho>0.87, all p values <0.01). There were no correlations between Braak LB stage and the severity of LB deposition
(all p values >0.05), or between LB severity and regional volume measures (all p values >0.05).
115 Table 4.2 Demographic, volumetric and pathological variables for PD
Cohort 4 Cohort 5 Cohort 6 POWMRI TRC POWMRI QSBB (n=5) (n=8) TRC (n=2) Technique assessed IHC WB IHC Included in chapters 4, 5, 6, 7 6 5, 7 Sex (M : F) 6M : 2F 2M : 0F 4M : 1F Age at onset (Years, Mean SD) 60 6 55 18 61 9 Age at death (Years, Mean SD) 75 5 83 7 79 4 Disease duration (Years, Mean SD) 15 5 28 11 18 7 H&Y (Mean, range) 5.0 (4 – 5) N/A N/A CDR (Mean, range) 0.5 (0 – 3) N/A N/A PMD (Hours, Mean SD) 17 16 4 4 70 45* Brain volume (ml, Mean SD) 1188 155 N/A N/A Braak LB stage (Mean, range) 5 (4-5) 6 (6) N/A Caudate volume (ml) 6 1 N/A N/A Putamen volume (ml) 7 9 N/A N/A Globus pallidus volume (ml) 3 1 N/A N/A Midbrain volume (ml) 6 2 N/A N/A Pons volume (ml) 11 3 N/A N/A SN neuronal loss 3 (2-3) N/A N/A SN LB severity (Mean, range) 2 (0-3) N/A N/A Putamen LB severity (Mean, range) 0 (0-1) N/A N/A Pons LB severity (Mean, range) 1 (0-1) N/A N/A POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB= Queen Square Brain Bank, IHC= immunohistochemistry, WB= western blotting, M= male, F= female, SD= standard deviation, H&Y= Hoehn & Yahr (Hoehn and Yahr, 1998), CDR= Clinical Dementia Rating (Morris, 1993), PMD= post-mortem delay, SN= substantia nigra, LB= Lewy bodies, N/A= not available, *significantly different.
116
4.3.3 PSP diagnosis and characterisation
All PSP cases reached clinical criteria for either possible or probable PSP and were definitely diagnosed according to NINDS-SPSP guidelines by the presence of significant numbers of tau-immunoreactive NFT in basal ganglia and pontine nuclei with no other neurodegenerative pathologies of note (Litvan et al., 1996b).
4.3.3.1 Case demographics and clinical progression
The POWMRI TRC cases with PSP consisted of 12 males and 3 female patients with an average age of onset of 67 years, average age at death of 74 years and an average disease duration of 7 years (Table 4.3). Their average H&Y score was 4 (Table 4.3), while their average CDR was 1 (highest score of 3 in two cases with the remaining cases ranging from 0-2, Table 4.3).
The QSBB PSP cases included 12 males and 7 females and the average age of onset and death was 69 and 76 years old, respectively (Table 4.3). The average disease duration was 7 years (Table 4.3). H&Y and CDR scores were not documented for the QSBB cohort.
As described in chapter 1, PSP cases can be further subtyped into a parkinsonian phenotype, PSP-P, and a more globally impaired PSP-RS phenotype (Williams et al., 2005). PSP-P is diagnosed when the patient has an asymmetric onset with resting tremor as the dominant clinical feature. These cases often have some benefit from L-dopa therapy. A diagnosis of PSP-RS is 117 given when there is an early onset of postural instability and falls often progressing to cognitive dysfunction. PSP-RS cases consistently have supranuclear vertical gaze palsy during their disease course. 71% of the
POWMRI TRC PSP cases were of the PSP-RS subtype (12 cases, Table 4.3) and 29% were PSP-P cases (5 cases, Table 4.3), similar to previously described distributions of these phenotypes (54% PSP-RS versus 32% PSP-P, Williams et al 2005). The QSBB cohort had a more equal distribution of PSP phenotypes,
58% being PSP-RS and 42% PSP-P (Table 4.3).
4.3.3.2 Pathology and atrophy
The pathological PSP staging scheme was not available for the QSBB cohort but was applied to the POWMRI cases (refer to chapter 3). The majority of cases (60%) had stage 4 disease and 13% of cases had stage 2, 20% of cases with stage 5 disease. The smallest proportion (7%) of cases had stage 3 disease.
The assessment of the volume of regional structures in PSP showed that the pons was largest, followed by the putamen and caudate nucleus, while the midbrain and globus pallidus were the smallest structures assessed (Table 4.3).
The volume of the putamen and globus pallidus correlated (Rho=0.73, p=0.04), as did the volume of the caudate nucleus and whole brain (Rho=0.71, p=0.047).
The caudate nucleus, putamen and globus pallidus volumes correlated with the volume of the midbrain (all Rho>0.77, all p values <0.05), suggesting associated changes in PSP. 118 Table 4.3 Demographic, volumetric and pathological variables for PSP
Cohort 7 Cohort 8 Cohort 9 POWMRI POWMRI QSBB (n=19) TRC (n=15) TRC (n=2) Technique assessed IHC WB IHC Included in chapters 3,4,5,6,7 6 5,7 Sex (M : F) 12M : 3F 2M : 0F 12M : 7F Age at onset (Years, Mean SD) 67 9 70 0 69 9 Age at death (Years, Mean SD) 74 8 76 2 76 9 PSP subtype (P or RS) 5 PSP-P : 10 0 PSP-P : 2 8 PSP-P : 11 PSP-RS PSP-RS PSP-RS Disease duration (Years, Mean 7 4 6 1 7 4 SD) H&Y (Mean, range) 4 (3 – 5) 3 (0-5) N/A CDR (Mean, range) 1 (0 – 3) 1 (0.5-1) N/A PMD (Hours, Mean SD) 10 7 12 11 27 13* Brain volume (ml, Mean SD) 1198 146 1193 9 N/A PSP stage (Mean, range) 4 (2-5) 3 (2-4) N/A Caudate volume (ml) 7 2 N/A N/A Putamen volume (ml) 8 1 N/A N/A Globus pallidus volume (ml) 3 1 N/A N/A Midbrain volume (ml) 3 1 N/A N/A Pons volume (ml) 9 3 N/A N/A SN neuronal loss (Mean, range) 3 (2-3) N/A N/A SN NFT severity (Mean, range) 2 (0-3) N/A N/A Putamen NFT severity (Mean, 0 (0-1) N/A N/A range) Pons NFT severity (Mean, range) 1 (0-3) N/A N/A POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB= Queen Square Brain Bank, IHC= immunohistochemistry, WB= western blotting, M= male, F= female, PMD= post-mortem delay, SD= standard deviation, PSP= progressive supranuclear palsy, P= parkinsonism, RS= Richardson's syndrome, H&Y= Hoehn & Yahr (Hoehn and Yahr, 1998), CDR= Clinical Dementia Rating (Morris, 1993), SN= substantia nigra, NFT= neurofibrillary tangles, N/A= not available, *significantly different
119
As expected for diagnosis, neuronal loss in the SN in PSP was severe (Table
4.3). The severity of NFT was evaluated as the core pathology (Table 4.3), with a moderate severity in the SN (ranging from none to severe), mild severity in the pons (ranging from none to severe) and less pathology in the putamen (ranging from none to mild, Table 4.3). The severity of NFT pathology in these different regions was not correlated (all p values >0.05).
Correlations between other pathologies revealed that neuronal loss in the SN was correlated with the severity of NFT in this region (Rho=0.64, p=0.01). There was no correlation between the stage of disease and the severity of subcortical
NFT, as already indicated in chapter 3. There were also no correlations between the severity of subcortical NFT pathology or nigral cell loss and any regional volumes.
4.3.4 MSA diagnosis and characterisation
All MSA cases reached clinical criteria for either possible or probable MSA and were definitely diagnosed by the widespread presence of -synuclein- immunoreactive GCI in basal ganglia and cerebellar pathways with no other neurodegenerative pathologies of note (Wenning et al., 2004).
4.3.4.1 Case demographics and clinical progression
The POWMRI TRC MSA cases consisted of 7 male and 5 female patients with an average age of MSA onset of 65 years, an average age at death of 69 years
120 and an average disease duration of 4 years (Table 4.4). The average H & Y score was 4, while their CDR score was 0 (all cases being 0, Table 4.4).
In the QSBB cases, there were 9 male and 8 female patients and the average age at onset was younger at 60 years old, but they had a similar age at death of
68 years old (Table 4.4). A longer disease duration of 8 years was observed in this cohort. The H&Y and CDR scores were not available for the QSBB MSA cases.
The SABB WB cohort consisted of 1 male and 4 females with the average age of onset being 67 years, age at death was 72 years and disease duration was 7 years (Table 4.4). The H&Y and CDR scores were not available for the SABB
MSA WB cohort.
As described in Chapter 1, MSA is divided into two phenotypes based on the presence of cerebellar or parkinsonian features (Wenning et al., 2004). MSA-P is diagnosed when parkinsonian motor signs are prominent at onset and parkinsonism is poorly responsive to L-dopa. MSA-C is diagnosed when features of cerebellar ataxia, pyramidal signs, early postural instability and falls within 3 years of disease onset is observed. 67% of POWMRI MSA cases were of the MSA-P phenotype (8 cases, Table 4.4) and 33% were of the MSA-C phenotype (4 cases, Table 4.4). The QSBB MSA cases had equal proportions of both the MSA-P (50%) and MSA-C (50%) phenotypes, with one case being
121 unclassifiable due to a dual parkinsonian and cerebellar predominant phenotype. The phenotype of the SABB cases was not known.
4.3.4.2 Pathology and atrophy
The pathological stages were not available for the QSBB and SABB MSA cohorts. The application of the MSA pathological grading scale (Jellinger et al.,
2005) to the POWMRI MSA cases revealed that of the MSA-P cases, 37% had
SND-grade 1, 25% had SND-grade 2 and 50% had SND-grade 3. Of the MSA-C cases, 25% of cases had OPCA-grade 1 and OPCA-grade 2 and the remaining had OPCA-grade 3. Regardless of subtype, the majority of MSA cases had a severe pathological stage of disease (Table 4.4).
Assessment of the volume of regional structures (Table 4.4) showed that the largest volume was observed in the pons, followed by the caudate, midbrain, then putamen and globus pallidus. The volume of globus pallidus correlated with that of the caudate nucleus (Rho=0.86, p=0.007) and the whole brain
(Rho=0.82, p=0.02).
As expected for diagnosis, neuronal loss in the SN in MSA was moderately severe (Table 4.2). The core pathology assessed was the severity of GCI, with a mild and related severity in the SN and pons (ranging from none to severe,
Rho=0.61, p=0.04), and a moderate severity in the putamen (Table 4.4).
122 Correlations between other pathologies revealed a relationship between the loss of nigral neurons and midbrain volume in MSA (Rho=0.79, p=0.03). There were no associations between nigral cell loss and the severity of GCI, or between disease stage, cell loss or GCI (all p values >0.05). Other regional volumes were also not related to any of these variables (all p values).
123
Table 4.4 Demographic, volumetric and pathological variables for MSA
Cohort 10 Cohort 11 Cohort 12 POWMRI TRC QSBB (n=17) SABB (n=5) (n=12) Technique assessed IHC IHC WB Included in chapters 4,5,6,7 5,7 6 Sex (M/F) 7M : 5F 9M : 8F 1M : 4F* Age at onset (Years, Mean SD) 65 9 60 8 67 8 Age at death (Years, Mean SD) 69 8 68 7 72 7 MSA subtype (P or C or U) 8P : 4C: 0U 8P : 8C : 1U* N/A Disease duration (Years, Mean SD) 4 2 8 4* 5 3 H&Y (Mean, range) 4 (3 – 5) N/A N/A CDR (Mean, range) 0 (0) N/A N/A PMD (Hours, Mean SD) 13 12 34 23 10 7 Brain volume (ml, Mean SD) 1189 84 N/A N/A MSA stage (Mean, range) 2 (1-3) N/A N/A Caudate volume (ml) 6 1 N/A N/A Putamen volume (ml) 4 2 N/A N/A Globus pallidus volume (ml) 2 1 N/A N/A Midbrain volume (ml) 5 2 N/A N/A Pons volume (ml) 8 2 N/A N/A SN neuronal loss (Mean, range) 3 (2-3) N/A N/A SN GCI severity (Mean, range) 1 (0-3) N/A N/A Putamen GCI severity (Mean, range) 2 (0-3) N/A N/A Pons GCI severity (Mean, range) 1 (0-3) N/A N/A POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB= Queen Square Brain Bank, SABB= South Australian Brain Bank, IHC= immunohistochemistry, WB= western blotting, M= male, F= female, PMD= post-mortem delay, SD= standard deviation, MSA= multiple system atrophy, P= parkinsonism, C= cerebellar, U= unclassifiable, H&Y= Hoehn & Yahr (Hoehn and Yahr, 1998), CDR= Clinical Dementia Rating (Morris, 1993), SN= substantia nigra, GCI= glial cytoplasmic inclusions, N/A= not applicable, *significantly different.
124 4.3.5 Cohort and disease comparisons
Cohort comparisons between the POWMRI and QSBB control, PD, PSP and
MSA cohorts were assessed separately to ensure similar case cohorts were utilised for analysis. Unpaired t-tests (SPPS Inc., Illinois, USA) were used to identify differences between demographics including sex, age at onset, age at death, disease duration, PMD and disease subtype. Differences between the frequencies of clinical indices between cohorts and subtypes were assessed using Chi-square distribution tests (SPPS Inc., Illinois, USA), and consistent clinical features were identified across cohorts.
To determine clinicopathological similarities and differences between PD, PSP and MSA, Kruskal-Wallis H tests (SPPS Inc., Illinois, USA) were used to assess demographic differences and variations in pathological stage, atrophy and core pathologies across the POWMRI TRC cohorts. Spearman rank correlations
(SPPS Inc., Illinois, USA) were used to determine any relationships between pathological severities across all cases examined. Logistic linear regression modelling (SPPS Inc., Illinois, USA) was used to determine any pathological variables associated with specific clinical features or phenotypes.
4.3.5.1 Demographic cohort comparisons
Assessment of the POWMRI and QSBB control cohorts revealed no significant differences in sex and age at death. Significant differences were observed in
PMD when comparing between the control, PD and PSP cohorts (p<0.01). This is due to the QSBB cases having significantly longer PMD than the POWMRI 125 cases (Tables 4.1, 4.2 & 4.3). Disease duration was similar between cohorts, except for the MSA cohorts where QSBB cases had significantly longer durations (p=0.001, Table 4.4). No other significant differences in clinical demographic indices were observed when comparing the POWMRI and QSBB cohorts.
The POWMRI and QSBB PD, MSA and PSP cohorts were combined and compared across disease groups to identify any disease-specific demographic differences. Significant differences were observed in the age of onset (p=0.009), with the PSP cohort having a later average age of onset (69 years old) compared to PD (61 years old) and MSA (62 years old). A significant difference in the age at death (p=0.005) was also observed. MSA cases had a younger average age at death (68 years old), compared to PD (76 years old) and PSP
(75 years old) cases. As expected, disease duration was another feature significantly different across groups (p<0.001). PD cases had a longer average disease duration (15 years) compared to PSP (7 years) and MSA (8 years) cases.
4.3.5.2 Clinical comparisons
Variability in clinical indices was observed between the POWMRI and QSBB cohorts. This variation may reflect some differences in collection of the clinical data. Importantly, the core clinical features for each disease were similar between cohorts.
126 As expected, the core parkinsonian clinical indices were strongly present across all diseases, particularly in PD. Akinesia and rigidity were present in all PD and
PSP cases in both cohorts. This feature was present in all cases in the
POWMRI MSA cohort, whereas 91% of cases in the QSBB MSA cohort had this feature (Table 4.5). Resting tremor was present in 80-88% of both PD cohorts, but there was a larger variability between the PSP cohorts. 67% of POWMRI
PSP cases while only 32% of QSBB PSP cases had resting tremor (Table 4.5).
A similar proportion of MSA cases had resting tremor between cohorts (33-48
%) (Table 4.5).
All the PD cases were L-dopa responsive (Table 4.5), as required for a PD diagnosis. As expected, a smaller proportion of the PSP cases (24-47%) in both cohorts had a variable response to L-dopa treatment ranging from mild to good or only initial responsiveness, consistent with previous studies (Brooks 2002;
Williams et al., 2005) (Table 4.5). 57-69% of both MSA cohorts had some initial responsiveness to L-dopa treatment, ranging from poor to mild (Table 4.5).
Significant cognitive impairment was another feature assessed, and 63-67% of the PSP cases in both cohorts, a minority of the POWMRI PD cases (25%) and no POWMRI MSA cases had significant cognitive impairment prior to death
(Table 4.5). In contrast, a large proportion of the QSBB PD cases (80%) and a smaller proportion (19%) of the QSBB MSA cohort had measurable cognitive impairment prior to death.
127 PSP related clinical features were also evident in a substantial proportion of the
MSA cases. A large proportion of the PSP cases (67-93%) in both cohorts had early falls (Table 4.5). Early falls were also common in the POWMRI MSA cohort
(67%), but only 14% of the QSBB MSA cases presented with early falls (Table
4.5), possibly contributing to the longer disease durations. In contrast, only 13% of the POWMRI PD cases and none of the QSBB PD cohort had early falls
(Table 4.5). As expected, gaze palsy was observed in 73-79% of the PSP cases in both cohorts. A large proportion of the MSA cases in the QSBB cohort (71%) also had eye signs. However, only 25% of the POWMRI MSA cases had this symptom (Table 4.5). Gaze palsy is the most common eye sign observed in
PSP, whereas this is uncommon in MSA (Warren and Burn, 2007). In MSA, sustained gaze-evoked nystagmus is the commonly observed eye sign
(Wenning et al., 2004). These eye signs were not clinically distinguished due to differential evaluation sites. In contrast, eye signs were not notable in either PD cohorts (Table 4.5).
Postural instability was observed in 83-93% of the PSP cases of both cohorts, but also in 79 - 83% of the MSA cases and 50-88% of the PD cases in both cohorts (Table 4.5). Dysarthria was observed in 60-84% of PSP and 75-95% of the MSA cases, whereas dysphagia was seen in 67% of both PSP cohorts and
58-85% of the MSA cohorts (Table 4.5). These features were less frequent in both PD cohorts, with 38-60% of cases having dysarthria and 38-40% dysphagia
(Table 4.5).
128 Autonomic and urinary dysfunction primarily consists of urogenital and orthostatic dysfunction. In MSA the criteria includes features of urinary incontinence, micturition and constipation (Wenning et al., 2004), whereas in
PSP early unexplained dysautonomia is a mandatory exclusion criteria (Warren and Burn 2007). In PD, micturition appears earlier and more severely in MSA, whereas constipation occurs equally in PD and MSA (Wenning et al., 2004).
Autonomic dysfunction was observed in 75-91% of the MSA cases in both cohorts. In the POWMRI PSP cohort, 47% of cases had autonomic dysfunction, whereas a smaller proportion (11%) of QSBB PSP cases had this feature (Table
4.5). 20-50% of PD cases presented with autonomic dysfunction in both cohorts
(Table 4.5). Postural hypotension occurs when there is a drop in blood pressure due to a change in posture. In PD (Matinolli et al., 2009) and MSA (Wenning et al., 2004) this is a commonly observed feature. However, in PSP this feature is considered part of the exclusion criteria (Warren and Burn 2007). This feature was variable between the PD cohorts. 20% of the QSBB PD cohort as compared to 63% of the POWMRI PD cohort had postural hypotension. This clinical feature was observed in 0-13 % of the PSP cases and 43-50% of MSA cases (Table 4.5). Ataxia is the most classic cerebellar sign with patients having severe difficulties with gait and co-ordination. In MSA, gait ataxia, ataxic dysarthria and limb ataxia are the most common forms of ataxia (Wenning et al.,
2004). However, the different forms of ataxia were not clinically evaluated for the
POWMRI TRC cohorts and ataxia was not evaluated for the QSBB cohorts. In the POWMRI cohorts, ataxia was observed in 67% of the MSA cases, a smaller proportion (40%) of PSP cases and in none of the PD cases assessed (Table 129 4.5). The clinical indices associated with MSA were most dominantly present in the MSA cohorts, however these features were not completely absent from any of the PD and PSP cohorts.
To determine the relevance of clinical subtype, an assessment of clinical features across disease groups was also performed combining all parkinsonian subtypes (PD, PSP-P and MSA-P) and all cerebellar subtypes (PSP-RS and
MSA-C). This analysis revealed that the response to L-dopa was subtype dependent, and associated with a parkinsonian phenotype (2=11.69, p=0.001), as expected. In contrast, resting tremor was not associated with either subtype
(p=0.78) and therefore can be considered more disease specific. Some clinical features were found to be associated with the RS phenotype. These were the presence of eye signs (2=14.46, p<0.001) and early falls (2=7.63, p=0.006).
Early falls is a clinical feature found in both PSP-RS and MSA-C, but eye signs are considered more PSP-RS specific. Autonomic dysfunction (p=0.49) and ataxia (p=0.78) were not associated with either subtype and therefore can be considered more disease specific.
130 Table 4.5 Clinical features for PD, PSP and MSA
Clinical Cohort 4 Cohort 6 Cohort 7 Cohort 9 Cohort 10 Cohort 11 feature POWMRI QSBB POWMRI QSBB POWMRI QSBB TRC (n=8) (n=5) TRC (n=15) (n=19) TRC (n=12) (n=17) Diagnosis PD PD PSP PSP MSA MSA Akinesia & 100% 100% 100% 100% 100% 91% rigidity Resting 88% 80% 67% 32% 33% 48% tremor Postural 88% 50% 93% 83% 83% 79% instability LDR 100% 100% 47% 24% 69% 57% Cognitive 25% 80% 67% 63% 0% 19% dysfunction Early falls 13% 0% 93% 67% 67% 14% Eye signs 0% 0% 73% 79% 25% 71%
Dysarthria 38% 60% 60% 84% 75% 95% Dysphagia 38% 40% 67% 67% 58% 85% PH 63% 20% 13% 0% 50% 43% AD 50% 20% 47% 11% 75% 91% Ataxia 0% N/A 40% N/A 67% N/A POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, QSBB= Queen Square Brain Bank, PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy, LDR= levodopa response, PH= postural hypotension, AD= autonomic dysfunction, N/A= not available. p values < 50% of the cohort in bold.
131 4.3.5.3 Pathological comparisons of disease severity
There were no significant differences in age, sex and PMD between the
POWMRI TRC PD, PSP, MSA and control groups, thus any differences in disease severities were not due to these factors.
Due to the differences between the scales of the staging schemes for PD (6 stages), PSP (5 stages) and MSA (3 stages), stage was converted to a proportion of the maximum stage for each disease. The average Braak LB stage for the POWMRI PD cohort was stage 83% of maximum severity (Table 4.2) with cases ranging from 67-83% severity. This pattern of severity was also observed in the POWMRI PSP cohort, with an average of 80% of maximum severity, however greater variability in pathological severity was observed in these cases (40-100%) (Table 4.5). The POWMRI MSA cohort reflected the greatest variability in neuropathological stage, with the average being 67% of maximum severity and all cases graded with all stages (0-100%) (Table 4.7).
Therefore, the MSA and PSP cohorts reflect a more variable range of neuropathological stages at death, whereas the PD cohorts are mostly end- stage disease at death.
132
Table 4.6 Comparisons of regional atrophy in PD, PSP and MSA
% of control values Cohort 4 Cohort 7 Cohort 10 POWMRI POWMRI POWMRI TRC TRC TRC Diagnosis PD PSP MSA Caudate volume 99 20 114 27 94 21 Putamen volume 112 22 119 33 59 23** Globus pallidus volume 126 31 93 32 82 25 Midbrain volume 121 35 60 20** 96 30 Pons volume 126 36 104 32 94 27 POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre, PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy ** significantly different from groups using one-way analysis of variance p<0.05 followed by a posthoc test p<0.05
To compare regional atrophy between disease groups, the volume measures were converted to a proportion of control values. Despite no significant differences between total brain weight, brain volume or cerebrum volume between disease groups, there were significant differences in regional atrophy
(Table 4.6). In particular, two different regions were atrophic in two different disease groups. In MSA, there was a significant reduction in the volume of the putamen when compared to controls (p = 0.005), PD (p<0.001) and PSP
(p<0.001) cohorts. In PSP, the midbrain region was significantly atrophic when compared to controls (p = 0.008), PD (p<0.001) and MSA (p = 0.008) cohorts.
The severity of core pathologies for PD, MSA and PSP was evaluated in the SN, putamen and pons. As expected, the SN has consistent cell loss and was
133 consistently affected with pathology in all disease groups. In the putamen, PD and PSP had limited pathology, whereas severe pathology was observed in the putamen in many MSA cases. In the pons, there was limited PD pathology, whereas more severe pathology was observed in this region in both the PSP and MSA cohorts.
Correlations between the different pathologies across groups revealed no relationships between disease stage, nigral cell loss and volumes (all p values
>0.05).
4.3.5.4 Clinicopathological comparisons
Akinesia and rigidity were clinical features found in all disease groups, cohorts and phenotypes, as was moderate to severe neuronal loss in the SN.
Other clinical features used for diagnosing PD include L-dopa responsiveness and tremor. As previously found, L-dopa responsiveness was associated with all parkinsonian phenotypes/subtypes (see above). Logistic regression analysis revealed that L-dopa responsiveness was associated with larger globus pallidus volumes (=0.49, p=0.04), suggesting that globus pallidus atrophy occurs in L- dopa resistant atypical cases. Assessment of pathological associations to a parkinsonian phenotype/subtype revealed that these cases have larger midbrain volumes than their cerebellar counterparts (=0.53, p=0.02). Resting tremor was a common feature in PD but also present in some cases of PSP and MSA
134 (Table 4.5). The presence of this clinical feature associated with less severe core pathology in the putamen (=-0.49, p=0.04).
Several clinical features are used in the diagnosis of MSA, with autonomic features and cerebellar signs being prominent. No pathological features were correlated with autonomic dysfunction, but logistic regression analysis revealed that the presence of ataxia was associated with greater atrophy of the putamen
(=-0.67, p=0.002). As cerebellar volumes were not evaluated in this study, this could suggest that greater overall atrophy of subcortical structures occurs in
MSA.
No pathological associations were found for typical PSP clinical features using logistic regression analyses, however, both eye signs and early falls were previously related to cerebellar subtypes across disease groups (see above).
Assessment of pathological associations to cerebellar subtypes revealed that these cases have smaller midbrain volumes than their parkinsonian counterparts
(=-0.53, p=0.02). This relationship is likely to be driven by the midbrain atrophy associated with PSP (Table 4.6).
4.4 DISCUSSION
The cases assessed in this thesis represent typical disease cases fulfilling current clinicopathological disease criteria for PD, PSP and MSA, with average demographic features similar to those described in the literature (Burn and Lees,
135 2002; de Lau and Breteler, 2006; Hely et al., 1999; Warren and Burn, 2007;
Wenning et al., 2004). The average age of onset is in the sixth decade and there are no gender differences, consistent with previous findings (de Lau and
Breteler, 2006; Warren and Burn, 2007; Wenning et al., 2004). PD has a typically longer duration (~15 years) than PSP and MSA (7-8 years) (Burn and
Lees, 2002; Hely et al., 1999; Wenning et al., 2004). While there have been many studies assessing differences in phenotypes between clinical cohorts, very few comparative analyses have had pathological confirmation of disease or assessed pathological severity measures across these disorders. In addition, there have been no previous validation studies that pathological cohorts selected through different recruitment programmes identify cases of similar type.
Evaluating pathological parameters across disease groups revealed a number of correlations. The severity of -synuclein deposition in the SN and pons was correlated in both the PD and MSA groups, as may be expected based on the staging of pathology in these disorders (Braak et al., 2003; Braak et al., 2004;
Jellinger et al., 2005). The severity of PSP pathology in these regions was not correlated, but the loss of neurons in the SN correlated with the severity of NFT pathology within this region, showing that many remaining neurons contain these pathological inclusions. It was found that tau burden in this region declines with increasing durations (Williams et al., 2007a), suggesting that tau-deposition in the SN declines over time and is likely to be associated with increasing cell loss (refer to chapter 3). Unexpectedly, increasing pathological stage of PD
136 correlated with larger basal ganglia volumes (caudate, putamen and globus pallidus), despite many studies showing significant remodelling pathology in these regions even early in PD (Mori et al., 2008), and previous studies identifying significant glial cell infiltration into the basal ganglia in PD (Ouchi et al., 2005; Reynolds et al., 2008). Overall, this data suggests that there is not a substantial loss of tissue volume in the basal ganglia in PD, even though there is a loss of dopaminergic axons, due to pathological deposition in the axonal structures and glial infiltration.
Cases were selected by their pathology and clinical phenotype. Despite considerable differences in the PMD in tissue processing observed between the
POWMRI and QSBB cohorts, this delay did not affect identification of the main pathological variables assessed for diagnosis and severity. The difference in
PMD was due to the collection of remote brain tissue by QSBB from across the
United Kingdom, including Ireland, Scotland and Wales. In contrast, POWMRI
TRC brain tissue is from local donations. Comparison of the pathological staging of disease across PD, MSA and PSP cohorts identified that PD cases had the least variability and were consistently the most severe at the time of death. This is also consistent with the differences in average disease durations observed.
This data suggests that PD is a pathologically more benign disease process compared with PSP and MSA. The progression of pathology appears to be more rapidly progressive in the atypical parkinsonian syndromes MSA and PSP compared to PD.
137 When cohorts are selected by clinicopathological criteria, and then their clinical features compared, there is significant clinical overlap between typical end-stage
PD and the atypical parkinsonian syndromes of PSP and MSA. This suggests that similar anatomical systems in the brain may be affected by different pathological processes in these parkinsonian disorders. Only MSA could be differentiated by the high prevalence of autonomic and cerebellar signs, as predicted (Wenning et al., 2004), and was distinguished by atrophy of the putamen, as previously identified (Minnerop et al., 2007; von Lewinski et al.,
2007). These variables were related using logistic regression analysis (note that cerebellar volumes were not assessed). For end-stage PD and PSP, an absence of certain features was more informative. Over time, PD was distinguished from PSP and MSA by a complete absence of eye signs and ataxia and a low frequency of cases with dysphagia, whereas PSP was distinguished from PD and MSA by a relative lack of L-dopa responsiveness and an absence of postural hypotension. This supports a previous report showing significantly larger number of MSA patients responsive to L-dopa compared to
PSP (O'Sullivan et al., 2008). Furthermore, it is of interest that atrophy of the midbrain differentiated PSP from PD and MSA cases, as previously found (Kato et al., 2003; Oba et al., 2005), and more significant midbrain atrophy is likely to impact on L-dopa responsiveness.
Comparing the core clinical features for PD, PSP and MSA between the different
POWMRI TRC and QSBB cohorts provided validation that akinesia and rigidity are the dominant features in these disorders (Brooks, 2002; Poewe and 138 Wenning, 2002). For many of the other core differentiating features, there was variability between cohorts or overlap between disease types. Resting tremor was not found in all cases of PD, and was also observed in some MSA-P and
PSP-P cases. However, resting tremor was identified as more PD-specific and associated with a lack of pathology in the putamen, supporting the known association of this clinical feature with intact and overactive (loss of dopamine modulation) basal ganglia circuits (Otsuka et al., 1996). For the diagnosis of typical PD, a response to L-dopa therapy is necessary (Gelb et al., 1999) and this feature was observed in all PD cases selected, but was also observed in a majority of pathologically-proven MSA cases from both cohorts (57-69%), particularly those with a MSA-P phenotype (Wenning, Colosimo, Geser, Poewe
2004). This was confirmed by the correlation between L-dopa responsiveness and parkinsonian phenotypes across disease groups (Wenning et al., 2004;
Williams et al., 2005). Interestingly, a lack of atrophy of the globus pallidus was associated with L-dopa responsiveness, identifying the preservation of this basal ganglia output structure as important for mediating this response. Over time L- dopa-induced dyskinesias can occur and are associated with overactivity of the globus pallidus, with pallidotomy a common method used to treat dyskinesias
(Lozano et al., 1995).
Eye signs are one of the key clinical features of PSP (Morris et al., 1999) and were observed in a high proportion of both the POWMRI PSP (73%) and QSBB
PSP (79%) cohorts, but also in 71% of pathologically-proven MSA cases from the QSBB. Gaze palsy is the primary eye sign for PSP (Warren and Burn, 2007), 139 whereas in MSA it is sustained gaze-evoked nystagmus (Wenning et al., 2004).
The specificity of the eye signs may assist in differentiating PSP and MSA.
Overall, early falls and eye signs were associated with a cerebellar subtype across disease groups, and also associated with greater midbrain atrophy, as observed in the PSP cohort. Loss of midbrain oculomotor regions and cerebellar pathways may be involved (Duvoisin et al., 1987; Revesz et al., 1996).
Characterisation of the standard clinical and pathological attributes in PD, PSP and MSA is important in utilising these characteristics to understand the progression of disease in these overlapping disorders. Akinesia and rigidity was a clinical feature with substantive overlap across all parkinsonian disorders.
Clinical features associated with clinical subtype included L-dopa responsiveness, associated with a parkinsonian phenotype (PD, PSP-P and
MSA-P), whereas early falls and eye signs were related to a cerebellar clinical phenotype (PSP-RS and MSA-C). However, pathologically the sole overlapping feature was the involvement of the SN, which appears to occur early (perhaps preclinically) in all diseases. As these diseases progress, PD is more pathologically benign compared to PSP and MSA. For PSP and MSA, there seems to be greater overlap over time in many clinicopathological parameters.
Determining the most significant differences to distinguish these disorders as early as possible is paramount.
140
Chapter 5: Pathological changes in astrocytes
5.1 INTRODUCTION
Based on current literature and as described in chapter 1, it was hypothesised that astrocytic dysfunction could be an early indicator of degeneration in the atypical parkinsonian syndromes PSP and MSA. As previously described in chapter 4, in addition to the core intracellular pathologies, pathological changes in astrocytes are observed in all parkinsonian disorders. In neurodegenerative diseases, astrocytes undergo a complex phenotypic change referred to as astrogliosis. Astrogliosis involves an increased expression of GFAP and cell body enlargement (Teismann and Schulz, 2004). GFAP is the structural intermediate filament protein expressed in the brain by astrocytes, and the immunohistochemical localisation of this protein is the most common marker used for studying this cell type (Korzhevskii et al., 2005). In PD, there is an increase in the number of GFAP-immunoreactive astrocytes in the SN (Hirsch et al., 2005; Vila et al., 2001), although substantive reactive astrocytic changes are not a common widespread pathological event (Hirsch et al., 2005; Mirza et al.,
2000) and remain relatively confined in PD, even within the SN. In contrast, substantial widespread reactive astrogliosis is common to both the atypical parkinsonian syndromes PSP and MSA (Matsusaka et al., 1998; Ozawa et al.,
141 2004). In these syndromes, the glia are considered to be equally and sometimes more affected than the neurons.
In PSP in particular, tau protein that is not normally found within astrocytes and abnormally accumulates within these cells, forming one of the characteristic lesions of this disease, TA (Armstrong et al., 2007a; Togo and Dickson, 2002).
Studies of the density of TA in cortical areas suggest that these abnormal structures correlate with many of the clinical features typical of this disorder
(Iwasaki et al., 2004), while subcortically TA are related to the core pathological feature of PSP, neuronal NFT (Ito et al., 2008). In contrast to the reactive gliosis identified with GFAP, tau-immunoreactive TA relate to a degenerative rather than a reactive process, as previously shown ((Ito et al., 2008; Togo and
Dickson, 2002); refer to chapters 1 and 3).
In MSA, astrocytic changes are largely considered only reactive and secondary to other pathologies. This is due to the more prominent oligodendroglial inclusions and animal oligodendroglial models recapitulate this progression of pathology (Stefanova et al., 2005). In MSA, the reactive astrogliosis correlates with neuronal loss and not GCI load (Ishizawa et al., 2008) and is due to cell stress as these astrocytes express one of the heat shock protein molecular chaperones, heat shock protein 70 (Kawamoto et al., 2007), as well as the neurotrophic factor, brain-derived neurotrophic factor (Kawamoto et al., 1999), indicative of a reactive change. Further studies directly correlating the degree of astrogliosis to other pathological changes in MSA have not been performed. 142
Until recently, astroglial changes were not considered to be significant in PD, due to the lack of widespread astrogliosis in this disorder. However, this view has changed as more recent studies show that -synuclein abnormally accumulates in astrocytes throughout the brain in PD (Shoji et al., 2000;
Wakabayashi et al., 2000), even though this change does not provoke the classic astrocytic reactivity. In PD, the -synuclein-immunoreactive astrocytes are thought to closely parallel the formation of LB, with the theory that they directly take up -synuclein released by terminal axons of affected neurons
(Braak et al., 2007). As previously noted in PD (Mirza et al., 2000), this astrocytic pathology appears to be a unique process as it is directly associated with the progression of disease pathology but occurs without evidence of typical astrogliosis.
Of particular interest is that a number of proteins demonstrated through genetic studies to be important in the pathogenesis of autosomal recessive PD (parkin,
DJ-1 and PINK-1) concentrates in astrocytes (Bandopadhyay et al., 2004;
Gandhi et al., 2006; Ledesma et al., 2002). In many instances these proteins increase in astrocytes undergoing typical reactive changes, contrasting with the changes described for -synuclein above. In particular, DJ-1 and PINK1 are constitutively expressed in astrocytes in the human brain (Bandopadhyay et al.,
2004; Gandhi et al., 2006) with fewer adequate studies on the localisation of parkin. There is one report showing parkin immunoreactivity in glia in control and
143 PD human brain tissue using an antibody to a specific epitope of parkin located at 295-311 amino acids (Zarate-Lagunes et al., 2001). Unfortunately, the identity of the glia was not specified. Consistent with a lack of reactive gliosis, the distribution of astrocytic DJ-1 and PINK1 are similar in PD to controls
(Bandopadhyay et al., 2004; Gandhi et al., 2006). In PSP, a small proportion of tau-immunoreactive TA colocalise DJ-1 with considerable upregulation of DJ-1 in reactive astrocytes (Kumaran et al., 2007; Neumann et al., 2004). The expression of DJ-1 in tau-immunoreactive glia has been linked to oxidative stress (Kumaran et al., 2007). PINK1-immunoreactive astrocytes also increase in PSP and MSA (Gandhi et al., 2006). In contrast to DJ-1, PINK1 is not found in tau-immunoreactive TA in PSP, and is therefore considered to have a more reactive neuroprotective role (Gandhi et al., 2006). These studies directly link parkin, DJ-1 and PINK1 to glial changes occurring in these parkinsonian disorders, although much less is known about astrocytic parkin.
More information on the role parkin may play in astrocytes has been generated under experimental conditions. Cell culture studies have shown increased parkin expression in astrocytes under stress conditions (Ledesma et al., 2002). In cell culture experiments, such stress conditions cause degeneration of the astrocytes from parkin-null mice (Solano et al., 2008) supporting an important role for parkin in both astrocytic survival and the normal reactive astrocytic change to stress. Recent studies have also shown that parkin is coregulated with another protein through a shared bi-directional promoter, PACRG (West et al., 2003). The coregulation of PACRG and parkin suggests it may also be 144 important for astrocytic function, although there have been no studies on the location of this protein in human brain tissue.
Overall, the above literature suggests that there are significant astrocytic changes that differ between the parkinsonian disorders. A non-reactive change directly associated with -synuclein accumulation in PD, a reactive change directly associated with tau accumulation in PSP, and a secondary less specific reactive change in MSA. Intriguingly, these abnormalities appear to be associated with changes in the astroglial concentration of parkin, DJ-1 and
PINK1, although more data on parkin in particular is required. The differences between disorders may not only be due to the different types of intracellular changes that occur, but may be influenced by the type of astrocyte the changes occur in. There are two main types of astrocytes that can be distinguished by their morphology, distribution and protein content (Navarro et al., 2004).
Protoplasmic astrocytes have a mossy appearance with radiating branched processes and are mainly found in the grey matter. They contain Apolipoprotein
D (ApoD) which is a lipid transport protein involved in central nervous system
(CNS) repair and regeneration (Navarro et al., 2004). Fibrous astrocytes have longer processes with less branched processes and do not express ApoD.
These fibrous astrocytes are localised in the white matter along myelinated axons. The differences in the astrocytic changes observed in the different parkinsonian disorders could relate to reactions occurring in these two types of astrocytes.
145
5.1.1 Specific hypotheses to be tested
The different reactive changes in astrocytes in PD, MSA and PSP are related to:
1. the severity of the degenerative changes observed;
2. changes in the expression of gene products identified as important for PD pathogenesis (parkin and PACRG), and/or
3. the type of astrocyte affected.
The following experiments will test these hypotheses.
5.2 METHODS
5.2.1 Case selection
As described in chapters 2 and 4, cases used were controls, PD, PSP and MSA cases from the POWMRI TRC cohorts 1, 4, 7, 10 and the QSBB cohorts 3, 6, 9 and 11. The clinical and pathological characterisation of these cases are as described in chapter 4.
5.2.2 Tissue preparation
Sections of the SN, putamen and the pontine basis were used (refer to chapter 2 for tissue preparation). Routine protocols for peroxidase IHC with appropriate pre-treatment for antigen retrieval (refer to chapter 2) was used to identify GFAP
(1:1000, DAKO, Ely, UK), -synuclein (1:1000, Autogen Bioclear, Calne, UK;
1:200, BD Biosciences, San Jose, USA), AT8 (1:600, Autogen Bioclear, Calne,
146 UK; 1:10 000 Pierce, Rockford, USA), PACRG (1:100, kindly provided by Dr
Paul Lockhart) and parkin (1:200, Biosensis, Adelaide, Australia) and the sections were counterstained with cresyl violet (0.5%) or Mayer’s haematoxylin histological stains for Nissl substance.
For protein colocalisation, double immunofluorescence labelling was performed.
Anti-GFAP was mixed with either anti--synuclein (1:200 dilution) or anti-AT8
(1:10 000 dilution). Rabbit anti-PACRG (1:100) or anti-parkin (1:200 dilution) was mixed with either mouse anti-GFAP (1:10 000, Chemicon, Billerica, USA), anti-ApoD (1:50; Vector Laboratories, Burlingame, USA), anti--synuclein
(1:1000 dilution) or anti-AT8 (1:600 dilution). Appropriate secondary fluorescent probes were used as described in chapter 2.
For primary antibodies from the same-species (parkin and PACRG), a combined method of immunofluorescence and peroxidase visualisation was utilised, as previously described (refer to chapter 2) and published (Song et al., 2007). Pre- treatment methods and standard peroxidase IHC was carried out with the incubation of anti-PACRG (1:100) as the first primary antibody. Following peroxidase visualisation, slides were then incubated with anti-parkin (1:200) as the second primary antibody and then incubated with the secondary anti-rabbit antibody conjugated to Alexa 568, as described in chapter 2.
5.2.3 Analyses
147 The peroxidase sections from all cases were viewed using Zeiss Axioskop
MC80 DX or Olympus BX51 microscopes to evaluate the morphology of astrocytic changes across all groups. The severity of reactive GFAP, PACRG- and parkin-immunoreactive astrocytes were semi-quantitatively analysed in 3 random x100 magnification fields in each section from each case. Astrocytic immunoreactivity was graded as none or rare (0), mild (1, a sparse distribution), moderate (2, in close to half the field of view) or severe (3, densely spread throughout the field of view) compared with the pattern of protein localisation in controls.
To assess the degree of protein colocalisation, double-labelled sections were viewed and photographed using Zeiss Axioskop MC80 DX or Olympus BX51 microscopes (Axiovision camera and software) and confocal images were taken using a Leica TCS4D confocal microscope with a 3-channel scan head and argon/krypton laser (University College London confocal imaging unit). The proportion of GFAP-immunoreactive astrocytes colocalising with other proteins were determined in 10 random photographs of each section for each case taken at x200 magnification.
Spearman’s rank tests (SPPS Inc., Illinois, USA) were performed to determine any relationships between the degree of astrocytic reactivity and core pathological indices. Stepwise logistic linear regression modelling (SPPS Inc.,
Illinois, USA) was performed to determine whether astrocytic changes related to any clinical variables. 148
5.3 RESULTS
5.3.1 Pathological changes in astrocytes in PD, MSA & PSP
As expected and previously described (Sofroniew, 2005), GFAP- immunoreactive astrocytes in controls had a stellate morphology with finely branching processes. Astrocytic abnormalities were observed in all types of parkinsonian disorders, although these changes were highly variable.
In PD, the overall morphology of GFAP-immunoreactive astrocytes was similar to controls (Figure 5.1A & 5.1B), although there was increased GFAP immunoreactivity in PD (Table 1), indicative of a reactive astrogliosis. This was most consistently observed in the pons (moderate severity) and was highly variable in the SN (none to severe). The degree of reactive astrogliosis did not correlate with either the severity of SN cell loss or the severity of LB formation in either the SN or pons (Table 1, p values >0.05). There was no increase in GFAP immunoreactivity in the putamen in PD and no significant LB formation in this region (Table 1). In addition to increased reactivity, colocalisation studies revealed that approximately 45% of GFAP-immunoreactive astrocytes in the PD cases also contained -synuclein immunoreactivity (Figure 5.1C-E).
In MSA, the putamen had the most marked reactive astrogliosis with an increase in GFAP immunoreactivity (Table 5.1) and changes in their morphology
149 (enlarged cell bodies and distorted processes, Figure 5.2A). Markedly reduced astrogliosis was observed in the SN and pons of the MSA cases examined, with only a mild increase in the severity of GFAP immunoreactivity (Table 1) and few morphological changes. The increased severity of GFAP-immunoreactive astrocytes in the putamen positively correlated with an increased number of - synuclein-immunoreactive GCI in the pons (Rho=0.73, p=0.007) and MSA pathological stage (Rho=0.67, p=0.02). In contrast to PD, and as previously identified (Wakabayashi et al., 2000), double-labelling immunofluorescence showed no deposition of -synuclein in GFAP-immunopositive astrocytes in
MSA cases.
150
Table 5.1 Regional severity gradings for nigral cell loss, pathological inclusion formation, and increased astrocytic GFAP, PACRG and parkin
Mean severity grade (range) Control PD MSA PSP
Substantia nigra
Cell loss 0 3 (2 – 3) 3 (2 – 3) 3 (2 – 3)
Inclusion formation 0 2 (0 – 3) 1 (0 – 3) 2 (0 – 3)
GFAP increase 1 (0 – 1) 1 (0 – 3) 1 (0 – 3) 2 (1 – 3)
PACRG increase 0 (0 – 1) 1 (0 – 3) 0 (0 - 2) 2 (0 - 3)
Parkin increase 0 0 0 2 (0 - 3)
Putamen
Inclusion formation 0 0 (0 – 1) 2 (1 – 3) 0 (0 -1)
GFAP increase 1 (0 – 2) 0 (0 – 1) 2 (0 – 3) 1 (0 – 2)
PACRG increase 1 (0 – 1) 1 (0 – 2) 1 (0 – 2) 2 (0 – 3)
Parkin increase 0 0 0 2 (1 - 3)
Pons
Inclusion formation 0 1 (0 – 1) 1 (0 – 3) 1 (0 – 3)
GFAP increase 1 (0 – 1) 2 (2 – 3) 1 (0 – 2) 1 (0 – 2)
PACRG increase 0 (0 – 1) 2 (1 – 2) 0 (0 – 1) 1 (0 – 2)
Parkin increase 0 0 0 1 (0 - 2)
PD= Parkinson’s disease, MSA= multiple system atrophy, PSP= progressive supranuclear palsy, GFAP= glial fibrillary acidic protein, PACRG= parkin co-regulated gene.
151 Figure 5.1 Astrocytes in controls and PD
Representative photomicrographs of 5m thick, paraffin-embedded sections of control and PD cases.
A&B Brighfield photomicrographs of typical stellate astrocytes with finely
branching processes immunohistochemically labelled with GFAP and
counterstained with cresyl violet in the putamen of a control (A) and PD
case (B), were morphologically similar. Scale in B is equivalent for A.
C-E Immunofluorescent images of a typical stellate GFAP-immunoreactive
(Alexa 568, red, C) astrocyte colocalising with -synuclein (Alexa 488,
green, D), shown in the merge image (E) in the pons of a PD case. Scale
in E is equivalent for C and D.
152 AB
20μm CDE
20μm Figure 5.2 Astrocytic changes in MSA and PSP
Representative photomicrographs of 5m thick, paraffin-embedded sections of the basal ganglia in MSA and PSP.
A A brightfield photomicrograph of astrocytes with enlarged cell bodies and
distorted processes in MSA, immunoperoxidase labelled with GFAP and
counterstained with cresyl violet. Scale in B is equivalent for A.
B A brightfield photomicrograph of enlarged and stellate reactive astrocytes
in PSP, immunoperoxidase labelled with GFAP and counterstained with
cresyl violet.
C An immunofluorescent merge image of a GFAP-immunopositive (Alexa
568, red) reactive astrocyte also immunopositive for tau (AT8) (Alexa
488, green) in PSP.
D A brightfield photomicrograph of a tufted astrocyte in PSP,
immunohistochemically labelled with tau (AT8) counterstained with cresyl
violet.
153 A B
100μm C D
25μm 50μm As expected in PSP, obvious reactive astrogliosis was observed, as evidenced by the increase in GFAP-immunoreactive astrocytes with enlarged stellate morphology (Figure 5.2B) in all regions examined (Table 1). The greatest increase in the number of GFAP-immunoreactive astrocytes was observed in the SN (moderate severity, Table 1). An increase in the severity of GFAP- immunoreactive astrocytes in both the SN and putamen positively correlated with increasing SN neuronal loss (Rho>0.53, p<0.04) and SN NFT formation
(Rho>0.56, p<0.03). In all regions examined, approximately 40% of the GFAP- immunoreactive astrocytes in PSP also contained hyperphosphorylated tau- immunoreactivity (Figure 5.2C), although none had the typical morphology of TA
(Figure 5.2D).
5.3.2 Astrocytic parkin and PACRG in PD, MSA and PSP
Despite previous descriptions of parkin-immunoreactive glia (Zarate-Lagunes et al., 2001), in the regions examined, only PACRG immunoreactivity was observed in the typical stellate astrocytes of the controls cases (Figure 5.3A &
5.3B). The lack of parkin in astrocytes is consistent with its distribution in animal studies (Stichel et al., 2000). Colocalisation experiments revealed that approximately 80% of GFAP-immunoreactive astrocytes in controls also contained PACRG immunoreactivity (Figure 5.3C).
There were no morphological changes in PACRG-immunoreactive astrocytes in either PD (as observed with GFAP localisation above) or MSA (in contrast to
GFAP localisation above), and no parkin immunoreactivity. PACRG- 154 immunoreactive astrocytes in PD also contained -synuclein immunoreactivity in double-labelling experiments (Figure 5.3D). In MSA, there was only a mild increase in the density of PACRG-immunoreactive astrocytes in the putamen and no change from controls in the SN and pons (Table 1). The significant atrophy of the putamen in MSA (refer to chapter 4) suggests that there is a loss of PACRG-immunoreactive astrocytes in this region. There was no correlation between the increased severity of GFAP immunoreactivity and PACRG- immunoreactive astrocytes in MSA (p=0.84). This suggests that PACRG- negative astrocytes are selectively affected in MSA.
In contrast to PD and MSA, enlarged reactive parkin-immunoreactive astrocytes were observed in PSP (Figure 5.4A). Double-labelling experiments showed that approximately 50% of GFAP-immunoreactive astrocytes in PSP also contained parkin immunoreactivity (Figure 5.4B-D). Reactive astrocytes in PSP with similar morphology also contained PACRG immunoreactivity and double-labelling experiments showed that approximately 80% of GFAP-immunoreactive astrocytes also contained PACRG immunoreactivity (Figure 5.4E-G). To confirm that PACRG and parkin were expressed in the same astrocytes in PSP, double- labelling experiments were performed and revealed that approximately 90% of
PACRG-immunoreactive astrocytes also contained parkin immunoreactivity
(Figure 5.5A & 5.5B). The SN and putamen had the greatest upregulation of astrocytic PACRG and expression of parkin compared with the pons in PSP
(Table 1). The severity of PACRG/parkin immunoreactive astrocytes in the
155 putamen positively correlated with the PACRG/parkin astrocytes in the pons
(Rho=0.55, p<0.03) and neuronal loss in the SN (Rho=0.56, p=0.04). The severity of PACRG/parkin-immunoreactive astrocytes in the SN correlated with increasing NFT in the pons (Rho=0.72, p=0.006). Tau-immunoreactivity was observed in approximately 25% of PACRG-immunoreactive and in approximately 20% of parkin-immunoreactive astrocytes (Figure 5.5C-E). These astrocytes did not have the morphological appearance of TA.
5.3.3 Type of astrocytes affected in PD, MSA and PSP
ApoD is selectively expressed in protoplasmic astrocytes (Navarro et al., 2004).
In controls, 75% of ApoD-immunoreactive astrocytes were also immunoreactive for PACRG (Figure 5.6A-C), with the distribution of ApoD-immunoreactive astrocytes not significantly different in MSA or PD (~75% of PACRG- immunoreactive astrocytes also contained ApoD immunoreactivity). This suggests that protoplasmic astrocytes constituently express PACRG as well as
ApoD. In PD, many of these protoplasmic astrocytes also contained -synuclein immunoreactivity. In PSP, approximately 85% of PACRG-immunoreactive astrocytes also colocalised with ApoD (Figure 5.6D-F), with a proportion of these protoplasmic astrocytes also containing tau. Similar to that observed with
PACRG, these tau-immunoreactive astrocytes had a reactive morphology rather than the typical morphology of TA.
156 Figure 5.3 Astrocytic PACRG in control and PD
Representative photomicrographs of 5m thick, paraffin-embedded sections of control and PD cases.
A&B A double-labelled photomicrograph of a PACRG-immunopositive
(brightfield immunoperoxidase, B) but parkin-immunonegative (Alexa 568,
red immunofluorescence, A) in a control case. Scale in B is equivalent for
A.
C A merged image of a GFAP-immunopositive (Alexa 488, green) astrocyte
colocalising with PACRG (Alexa 568, red) in the putamen of a control
case.
D A merged image of a proportion of PACRG-immunopositive (Alexa 468,
red) astrocytes containing -synuclein (Alexa 488, green)
immunoreactivity in the pons of a PD case.
157 A B
50μm CD
20μm 100μm Figure 5.4 Astrocytic PACRG and parkin in PSP
Representative photomicrographs of paraffin-embedded sections of the putamen in PSP cases.
A A brightfield photomicrograph of enlarged, stellate reactive astrocytes
immunoperoxiodase labelled with parkin and counterstained with Mayer’s
haemotoxylin.
B-D Immunofluorescent photomicrographs of parkin-immunoreactive (Alexa
568, red, B) astrocytes colocalising with GFAP (Alex 488, green, C), as
shown in merge image (D). Scale in D is equivalent for B and C.
E-G Immunofluorescent photomicrographs of PACRG-immunoreactive (Alexa
568, red, E) astrocytes colocalsing with GFAP (Alexa 488, green, F) as
shown in merge image (G). Scale in G is equivalent for E and F.
158 A
10μm B C D
E F G
10μm Figure 5.5 Astrocytic PACRG, parkin and tau in PSP
Representative photomicrographs of paraffin-embedded sections of the putamen in PSP cases.
A&B Double-labelled photomicrographs of a PACRG-immunoreactive
(brightfield immunoperoxidase, A) astrocyte also containing parkin (Alexa
568, red, B) immunoreactivity. Scale in B is equivalent for A.
C-E Immunofluorescent photomicrographs of a parkin-immunoreactive (Alexa
568, red, C) astrocyte, also colocalising with tau (AT8) (Alexa 488, green,
D), shown in the merge image (E). Scale in E is equivalent for C and D.
159 A B
10μm CDE
20μm Figure 5.6 PACRG immunoreactivity in ApoD-immunoreactive protoplasmic astrocytes
Representative immunofluorescent photomicrographs of 5m thick paraffin- embedded sections of the putamen in control and PSP cases. The scale in F is equivalent for all photomicrographs.
A-C Double-labelled immunofluorescent photomicrographs of PACRG-
immunoreactive (Alexa 568, red, A) astrocytes, colocalising with ApoD
(Alexa 488, green, B), shown in the merge image (C) in a control case.
D-F Double-labelled immunofluorescent photomicrographs of enlarged
PACRG-immunoreactive (Alexa 568, red, D) stellate astrocytes
colocalising with ApoD (Alexa 488, green, E) as shown in merge image
(F) of a PSP case.
160 AB C
DE F
20μm 5.3.4 Clinical correlations
GFAP- and PACRG-immunoreactive astrocytes were observed in all cases and further analysis was performed to determine any clinical features associated with increased astrocytic reactivity. No correlations were observed between clinical subtype and these astrocytic changes. The increased severity of
PACRG-immunoreactive astrocytes in the putamen was negatively associated with L-dopa responsiveness (=-0.45, p=0.01) across all groups. Increasing
GFAP-immunoreactive astrocytes in the putamen was positively correlated with ataxia (=0.52, p=0.008), which is likely to be associated with atrophy in this region (also associated with this clinical feature, see chapter 4). Interestingly, early falls and eye signs associated with increasing PACRG-immunoreactive astrocytes in the putamen (>0.63, p<0.02) and GFAP-immunoreactive astrocytes in the SN (>0.49, p<0.003).
5.4 DISCUSSION
The present study confirms that distinct astrocytic changes occur in PD, MSA and PSP, and shows that these differences relate to the type of astrocytes affected and their reaction to the severity of degeneration. While this study confirms that the reactive astrogliosis in PSP is directly associated with NFT formation (Ito et al., 2008), it also provides more data in support of both a reactive astrogliosis in PD (in contrast to previous reports, (Hirsch et al., 2005;
Mirza et al., 2000)) and a less secondary and very targeted reactive astrogliosis in MSA. In particular, the results suggest that specific types of astrocytes are
161 affected in these different parkinsonian disorders (protoplasmic in PD and PSP, and fibrous in MSA), and that the different disease mechanisms influence different astrocytic intracellular pathways. Lastly, this study also reveals that some of the astrocytic changes observed relate directly to certain clinical features.
5.4.1 Astrocytic subtypes affected in PD, MSA and PSP
Protoplasmic astrocytes are the dominant glial cell type localised in the grey matter of the CNS, whereas fibrous astrocytes are mainly found in the white matter (Bushong et al., 2002; Korzhevskii et al., 2005). As described above,
ApoD (a lipid transport protein) is found only in protoplasmic astrocytes (Navarro et al., 2004), but so is D-serine (a ligand of the N-methyl-D-asparate (NMDA) receptor found at synapses, (Snyder and Kim, 2000), and now PACRG (present study). In fact, unlike these other ligands, constituently expressed PACRG does not appear to concentrate in other CNS structures. PACRG is a structural component of microtubules, with tubulin binding a basic function of the protein
(Ikeda et al., 2007; Ikeda, 2008). This suggests that PACRG is an important component of the cytoskeleton of protoplasmic but not fibrous astrocytes, and a reason why its expression may increase with morphological changes to this type of astrocyte.
In MSA, there was limited reactivity of the PACRG-immunoreactive astrocytes, contrasting with the substantial reactive GFAP-immunoreactive astrogliosis in this disease. In this way, MSA appears unique as non-ApoD, non-PACRG 162 fibrous astrocytes appear to be affected. In contrast, ApoD and PACRG colocalising protoplasmic astrocytes were affected in both PD and PSP, but quite differently. A proportion of PACRG-immunoreactive astrocytes contained tau protein in PSP and -synuclein in PD but not MSA. In PD, there was limited upregulation of astrocytes associated with significant accumulation of - synuclein. Previous PD studies have shown -synuclein accumulation in astrocytes, however the subtype of the astrocyte was not specified (Braak et al.,
2007; Wakabayashi et al., 2000). In PSP, significant upregulation of
ApoD/PACRG astrocytes was observed with limited tau accumulation. This data suggests that abnormal protein accumulation in protoplasmic astrocytes (as seen in PD) may limit their ability to react to neurodegeneration (significant reaction was observed in PSP). This is the first study to determine that different astrocytic subtypes and reactions are involved in these different parkinsonian disorders.
The small population of tau/PACRG-immunoreactive astrocytes in PSP did not have tufted morphologies, even though TA are described as protoplasmic based on their morphology and distribution (Arima, 2006). TA have been shown to be
GFAP-negative ((Komori, 1999); present study), in contrast to studies showing that all protoplasmic astrocytes are GFAP-immunoreactive (Bushong et al.,
2002; Korzhevskii et al., 2005), as well as ApoD- and PACRG-immunoreactive
(present study). In the present study, none of these astrocytic markers colocalised in astrocytes with typical tufted morphologies. Although the
163 morphology and locality of TA in grey matter suggest they are protoplasmic, the absence of GFAP, ApoD or PACRG immunoreactivity suggests that they may either represent another subpopulation of astrocyte (as previously suggested,
(Komori, 1999)), or that they have lost the characteristics of protoplasmic astrocytes and could potentially be fibrillary astrocytes (Komori, 1999). An earlier description of TA suggested they were a differentiating form of progenitor cells
(Yamada et al., 1992). NG2 glia are described as precursors of oligodendroglia and protoplasmic astrocytes (Zhu et al., 2008) and concentrate in grey matter
(2-3% of total cells, (Nishiyama et al., 2005)). Like TA, NG2 glia do not express
GFAP but have large, stellate morphologies (Nishiyama et al., 2005). In comparison to GFAP-immunoreactive astrocytes, NG2 glia have a centrally located soma and shorter processes (Nishiyama et al., 2005). Further studies identifying the cell type involved are important, as TA relate to the degenerative rather than reactive processes occurring in PSP ((Ito et al., 2008; Togo and
Dickson, 2002); chapter 3).
5.4.2 Parkin expression in protoplasmic astrocytes in PD and PSP
Although ApoD and PACRG were constituently expressed in protoplasmic astrocytes, the expression of parkin with PACRG in astrocytes was only observed in PSP. PACRG and parkin are co-regulated (Brody et al., 2008) and therefore the upregulation of the constituent PACRG protein in PSP astrocytes may lead to the expression of parkin. PACRG binds and interacts with tubulin and microtubules (Ikeda, 2008) and its levels are regulated by the proteasome
(West et al., 2003), whereas parkin assists in proteasomal protein degradation 164 and stabilising misfolded proteins on microtubules (Yang et al., 2005). The increased upregulation of PACRG and parkin expression in PSP astrocytes is likely to increase tubulin, and microtubule binding activity to potentially assist microtubule stability in these enlarged, upregulated astrocytes. In a relatively small proportion of these astrocytes, significantly increased activity appears to cause tau abnormalities. This is consistent with animal studies using parkin knock-outs that show increased levels of phosphorylated tau (Menendez et al.,
2006) and using mixed parkin/tau vectors to show an absence of tau phosphorylation and accumulation with increased parkin expression (Klein et al.,
2006). These studies suggest that the increased PACRG and parkin in the protoplasmic astrocytes is a normal protective response to reduce abnormal tau phosphorylation. This is also consistent with the proposed role most autosomal recessive PD proteins play in the brain (Canet-Aviles et al., 2004; Clark et al.,
2006; Klein et al., 2006; Meulener et al., 2006), perhaps largely through the activation of protoplasmic astrocytes (Gandhi et al., 2006; Kumaran et al., 2007;
Neumann et al., 2004). As observed for PACRG/parkin (present study), PINK1 is localised to reactive astrocytes (Gandhi et al., 2006), whereas DJ-1 is also found in reactive astrocytes as well as a subpopulation of TA (Kotaria et al.,
2005; Kumaran et al., 2007). This suggests that the PD-mutant proteins PINK1 and parkin have overlapping functional roles (Clark et al., 2006) and further studies on these glial proteins are necessary.
In contrast to PSP, the protoplasmic astrocytes in PD do not upregulate PACRG or parkin but instead accumulate -synuclein. Protoplasmic astrocytes have a 165 functional role in synaptic modulation (Oberheim et al., 2006) and their processes can extend to neuronal cell bodies and a number of synapses
(Oberheim et al., 2006). -Synuclein is a synaptic protein and the abnormal accumulation of -synuclein in protoplasmic astrocytes may indicate a reduction in their synaptic activity. Abnormalities in the parkin gene cause PD (Perez and
Palmiter, 2005; Schiesling et al., 2008; van de Warrenburg et al., 2001) suggesting it plays an important role in PD pathogenesis. In patients with dysfunctional parkin, -synuclein-immunoreactive LB do not accumulate in the
SN (Sasaki et al., 2004; Schiesling et al., 2008; van de Warrenburg et al., 2001) although there is a substantial reactive glial response in these cases (van de
Warrenburg et al., 2001). Functional parkin is thought to be necessary to ubiquitinate -synuclein (Dawson, 2006; Shimura et al., 2001), as LB contain a ubiquitinated form of the fibrillised protein. Even though there is an increased amount of -synuclein in the protoplasmic astrocytes of PD, it does not appear to be fibrillised as assessed using conformational stains. This suggests that the normal role of parkin in these protoplasmic astrocytes may be dysfunctional. The survival of these protoplasmic astrocytes suggests that they have significant alternate protective mechanisms to cope with the abnormal accumulation of non-fibrillised -synuclein.
5.4.3 The severity of these degenerative changes and their relationships
166 As described in chapter 1, GCI are considered the core pathology in MSA and upregulation of GFAP-immunoreactive fibrous astrocytes in MSA was associated with the degree of -synuclein-immunoreactive GCI. Such a relationship may have been expected considering the association between fibrous astrocytes and myelinated fibers, although this relationship did not occur in the same locations, and was not necessarily associated with myelinated regions. The severity of GCI in the pons, a predilection site for GCI in MSA
(Langerveld et al., 2007), was associated with the remote upregulation of fibrous astrocytes in the putamen. While previous studies have suggested a significant difference between the astroglial response in grey and white matter regions in
MSA (Ishizawa et al., 2008), the current data suggests that these responses are related and affect the fibrous astrocytes within both regions. Unexpectedly, this study has shown that the putaminal astrogliosis associates with the presence of ataxia, a cerebellar sign. As described in chapter 4, the presence of ataxia was also associated with greater atrophy of the putamen in MSA, and such atrophy is likely to increase astrocyte density. It would appear to be a selective increase in the fibrous astrocytes, suggesting that the atrophy is associated with oligodendroglia and white matter fiber pathways within the putamen. Loss of critical basal ganglia input in addition to oligodendroglial pathology in cerebellar pathways may be required for this more cerebellar clinical feature.
In PD, the degenerative changes are suggested to associate with the - synuclein-immunoreactive astrocytes as they are thought to parallel core
167 intraneuronal pathologies (Braak et al., 2007; Mori et al., 2008). In the present study, the severity of the astroglial response did not relate to the severity of pathological indices. The more widespread astroglial abnormalities in PD may be important for pathogenesis, as discussed above. The assessment of clinical correlations across the groups revealed that less PACRG-immunoreactive astrocytes in the putamen was associated with L-dopa responsiveness, suggesting that preservation of the basal ganglia is required for a response to L- dopa (refer to chapter 4).
In PSP, the protoplasmic astrogliosis in the SN and putamen were associated with SN neuron loss and NFT formation, and with similar astrogliosis in the pons. This has been previously shown (Togo and Dickson, 2002). The degree of
NFT has also been correlated with the severity of TA in PSP (Ito et al., 2008) with the suggestion that the reactive astrocytes and TA occur independently
(Togo and Dickson, 2002). As discussed above, the protoplasmic astrocytic response observed appears to be protective, and the relationship between such astrogliosis and the core pathologies of PSP suggests a reactive response. In this context it is interesting that the presence of early falls and eye signs
(typically seen in PSP, refer to chapter 4) were also related to more severe protoplasmic astrogliosis in the SN and putamen. As previously described in chapter 4, the SN appears to be an early and consistently affected region in
PSP, and for this reason pathologies in this region are likely to be associated with these typical clinical features. Previous studies have shown that the severity of neuronal loss in the SN correlates with the presence of gaze palsy in PSP 168 (Halliday et al., 2000). The loss of SN input to the putamen may explain the associated astrogliosis between these regions in PSP. Early dopamine dysregulation appears to be a prerequisite for these features to emerge.
5.4.4 Conclusions
This is the first study to identify PACRG as a constituent protein in protoplasmic astrocytes, the first study to show that different types of astrocytes are affected in different parkinsonian disorders, and the first to associate increased expression of PACRG with parkin expression in protoplasmic astrocytes in PSP.
There was an absence of GFAP, ApoD, PACRG and parkin in TA in PSP suggesting that TA are not protoplasmic astrocytes. The prominent astrocytic changes in PSP were associated with the loss of SN neurons, the severity of subcortical NFT and specific clinical features. While protoplasmic astrocytes were not spared in PD, a completely different reaction was observed. The protoplasmic astrocytes in PD abnormally accumulate -synuclein but did not become reactive or degenerate. This suggests that PD has an attenuated astrocytic response, an abnormality that may itself propagate the widespread pathology observed in this disorder over time. In contrast, GFAP-positive and
PACRG-negative fibrous astrocytes were associated with MSA clinical and pathological indices. These studies show very diverse astroglial responses in these different parkinsonian conditions.
169
Chapter 6: Pathological changes in oligodendroglia
6.1 INTRODUCTION
Oligodendroglial pathology characterises the atypical parkinsonian disorders
MSA and PSP, with -synuclein-immunoreactive GCI the dominant pathology in
MSA and tau-immunoreactive CB frequent in PSP (refer to chapter 1). In contrast, -synuclein is primarily expressed in neurons and astrocytes in PD
(McGeer and McGeer, 2008), although some studies report occasional - synuclein-immunoreactive oligodendroglia in PD patients (Campbell et al., 2001;
Hishikawa et al., 2001; Wakabayashi et al., 2000).
Oligodendroglia are the myelinating cells of the CNS, located in close apposition to the plasma membrane of neurons, and responsible for regulating axonal signal propagation and intracellular sorting processes (Richter-Landsberg, 2000;
Richter-Landsberg, 2001). They have a high rate of activity and individually produce vast amounts of myelin (Richter-Landsberg, 2001). Myelin is composed of myelin proteins and lipids produced by oligodendroglia. Protein and lipid transport to myelin is through the biosynthetic pathways located in the cell body and continues at the plasma membrane aided by MBP (Simons and Trotter,
2007). MBP comprises 30% of the total protein in myelin, making it the second major constituent after proteolipid protein (Boggs, 2006). Genetic mutations
170 reducing functional MBP cause neurological movement disorders without overt demyelination, as demonstrated in shiverer mice and shaker rats (Carre et al.,
2002; Readhead et al., 1987). Dysmyelination occurs with disruption to MBP function, rather than the frank leukodystrophy observed with disruption of the major myelin constituent protein proteolipid (Koeppen and Robitaille, 2002;
Koizume et al., 2006; Werner et al., 1998).
In addition to MBP, a number of other proteins appear to be important in oligodendroglial pathology. P25 is an oligodendroglial specific phosphoprotein
(Takahashi et al., 1993; Takahashi et al., 1991). Its normal function is unclear but it copurifies with tau kinases and promotes tubulin polymerisation and the bundling of microtubules (Hlavanda et al., 2002; Takahashi et al., 1991). Its expression initiates at the time of myelination along with MBP (Akiyama et al.,
2002; Skjoerringe et al., 2006). CNPase is a component of myelin with an enzymatic role in lipid metabolism, signalling mechanisms, ion transport, and adhesion (Larocca and Rodriguez-Gabin, 2002). MBP, p25 and CNPase all interact with the oligodendroglial cytoskeleton (Richter-Landsberg, 2000) and are used as markers for myelin. ApoD is also found in oligodendroglia (Navarro, del Valle, Tolivia et al 2004), in addition to neurons and protoplasmic astrocytes
(refer to chapter 5). The expression of ApoD is elicited following any injury in the
CNS, suggesting that ApoD may be involved in the repair process (Navarro et al., 2004). The expression of ApoD has not been investigated in the glial prominent disorders of MSA and PSP. Lastly, astrocytic GFAP is necessary for
171 maintenance of myelination in the CNS (Liedtke et al., 1996; Meyer-Franke et al., 1999) and GCI pathology correlates with increasing astrocytic GFAP in MSA
(refer to chapter 5).
Oligodendroglia are the major cell type affected in MSA (refer to chapters 1 and
4), with -synuclein depositing in oligodendroglial cell bodies as GCI (Dickson et al., 1999a) and GCI linked with myelin abnormalities in MSA (Higuchi et al.,
2005). GCI genesis in MSA remains unclear because oligodendroglial - synuclein mRNA expression has not been demonstrated in vivo, although oligodendroglial cells are able to express -synuclein in culture (Richter-
Landsberg, 2000). Transgenic oligodendroglial specific expression of human - synuclein causes a neurodegenerative phenotype in mice that resembles MSA and clearly demonstrates that neuronal degeneration develops subsequent to a
-synuclein-mediated dysfunction of oligodendroglia (Shults et al., 2005;
Yazawa et al., 2005).
In PSP, the core pathology is reflected by the deposition of tau in neurons in the form of NFT (refer to chapter 1 and 4). However, considerable glial cell pathology also ocurs in PSP. In addition to astrocytic changes (refer to chapter
5), tau-immunoreactive CB in oligodendroglia are prominent in PSP. In contrast to -synuclein, tau is constituently expressed in oligodendroglial cells (Richter-
Landsberg, 2001; Richter-Landsberg and Bauer, 2004). CB are cytoskeletal abnormalities (Arima et al., 1997) found in oligodendroglia in degenerating brain
172 regions (Jin et al., 2006). As described in chapter 3, PSP subtypes can be distinguished based on a grading scale utilising CB as a marker of overall tau burden (Williams et al., 2007a). CB are not thought to be related to myelin dysfunction in PSP.
Despite the prominent oligodendroglial involvement in MSA and PSP, changes in associated myelin and oligodendroglial proteins have not been investigated in these disorders.
6.1.1 Hypotheses to be tested
Changes in the amount and/or distribution of constituent oligodendroglial proteins associate with MSA and PSP pathologies, and are important for disease progression.
6.2 METHODS
6.2.1 Case and tissue preparation
Frozen brain white matter from under the superior precentral gyrus was sampled for WB analysis from POWMRI TRC cohorts 2, 5, 8 and SABB cohort 12 (refer to chapters 2 and 4). This myelinated white matter region was selected, as it does not contribute to clinical presentation and is without substantial cell loss but has GCI (Su et al., 2001).
For IHC, formalin-fixed samples of the pontine basis (transverse level includes the SCP) from POWMRI TRC cohorts 1, 4, 7 and 10 (refer to chapters 2 and 4) 173 were used. The pons was selected as a region rich in oligodendroglia and myelin fibers that contribute to clinical presentation due to variable cell loss.
Tissue samples were paraffin-embedded and cut at 5 - 8m on a microtome, as described in chapter 2.
6.2.2 Protein extractions and western blotting for MBP and p25
Brain proteins were extracted from 1 gram of white matter using previously described protocols (Anderson et al., 2006). Brain tissue was homogenised using a Potter S Homogeniser (B.Braun Biotech Inc., USA) in a homogenisation buffer (0.32M sucrose, 20mM Tris-Cl, 5mM ethylene diamine tetraacetic acid
(EDTA), pH 7.4) that included a protease inhibitor cocktail (Complete, EDTA- free, Roche, Indianapolis, USA), sonicated (2 x 10 seconds), centrifuged (23
500 X g, 10 minutes, 4 C) and the resulting supernatant stored as the soluble fraction. Pellets were resuspended and sonicated (2 x 10 seconds) in a sodium dodecyl sulfate (SDS)-urea solubilisation buffer (6M urea, 1% SDS, 5mM
EDTA)(1:5 w/vol) and centrifuged (23 500 X g, 10 minutes, room temperature) to obtain the SDS-extractable insoluble fraction. All centrifugation were performed using a fixed-angle rotor in a Biofuge Stratos Heraeus centrifuge (Frankfurt,
Germany). Protein quantification for both the soluble and insoluble fractions were determined using the bicinchoninic acid (BCA) protein assay (Pierce,
Illinois, USA), according to manufacturer’s instructions, using bovine serum albumin dilutions as standards. Protein assays were read with the Model 550
Microplate Reader (BioRad Hercules, USA).
174
Prior to reducing SDS-polyacrylamide gel electrophoresis (PAGE), SDS-loading buffer (4% SDS, 40% glycerol, 50 mM Tris-HCl; pH 6.8) was added to the brain protein samples, supplemented with 20 mM 1,4-dithioerythritol (DTE) and heated for 3 minutes at 95 C. Proteins were separated by 10-16% gradient
SDS-PAGE. For WB, SDS-PAGE gels were electroblotted onto polyvinylidene difluoride (PVDF) membranes (BioRad, Hercules, USA). Membranes were blocked with 5% skimmed milk (dissolved in 50 mM NaCl, 0.05% Tween-20, 20 mM Tris-HCl; pH 7.4), followed by incubation with several primary and secondary antibodies depending on the experiments required. To detect p25, polyclonal rabbit anti-p251 antibody raised against recombinant human p25 was used as described previously (Lindersson et al., 2005). Rabbit anti-MBP
IgG (18-0444 1:2000; Zymed Laboratories, San Francisco, USA) was used to detect MBP. For standardisation and internal controls, monoclonal mouse anti- glyceraldehyde-3-phosphate dehydrogenase (GAPDH) IgG (4300 1:4000;
Ambion, Austin, USA) was used. Primary antibodies were incubated overnight at
4 C and followed by tris-0.05%tween (50mM Tris, 125mM NaCl, 5mM EDTA) washes repeated 4 times (10 minutes each). Detection was done with enhanced chemiluminescence (NEL104; Perkin Elmer, Boston, USA) using secondary antibodies conjugated to horseradish peroxidase (1:4000; BioRad, Hercules,
USA or 1:5000, Sigma, St Louis, USA).
175 The relative amounts of MBP, p25 and GAPDH on the western immunoblots were analysed using image analysis software (Quantity One 1D-Analysis software, version 4.6, BioRad). GAPDH (30-40kDa) label intensity was used for standardisation on each blot. Protein bands were identified using a computer mouse for each sample, the average band intensity extracted and standardised against the intensity of the GAPDH protein band for that case in that blot.
Density values for the soluble and SDS-extractable insoluble fractions were added together to assess total protein levels, and changes in solubility identified using ratios. Differences between controls and disease groups were assessed using Mann-Whitney U tests (SPSS Inc., Illinois, USA).
6.2.3 Immunohistochemistry to assess the distribution of myelin- associated proteins
The distribution of myelin-associated proteins was assessed using both single peroxidase and double fluorescence IHC, with double fluorescence IHC also used to visualise associations to other structural tissue elements. Protein antigens assessed were MBP, degraded MBP, CNPase, p25, ApoD, - synuclein, PACRG, parkin, AT8 (tau), NF and III-tubulin.
Routine protocols previously described in chapter 2 and published (Halliday et al., 2005b; Taylor et al., 2007) for peroxidase IHC with appropriate pre-treatment for antigen retrieval were used to identify oligodendroglial and dominant inclusion proteins. Primary antibodies to degraded MBP (AB5864 1:2000;
176 Chemicon International, California, USA), anti-p251 IgG (1:50, kindly provided by Professor Poul Henning Jensen), ApoD (1:50, Vector Laboratories,
Burlinghame, USA), -synuclein (1:200, BD Biosciences, San Jose, USA or
1:1000, kindly provided by Professor Poul Henning Jensen), AT8 (1:10 000
Pierce, Rockford, USA), PACRG (1:100, kindly provided by Dr Paul Lockhart) and parkin (1:200, Biosensis, Adelaide, Australia) were used.
Double fluorescence IHC with antigen retrieval (refer to chapter 2) was used to assess myelin and associated axonal changes. Antibodies against either rabbit anti-MBP IgG (18-0444 1:3000; Zymed Laboratories, San Francisco, USA) or mouse anti-MBP IgG (MCA184S 1:250; Serotec; Oxford, United Kingdom) or
CNPase (C5922 1:400, Sigma, St Louis, USA) and anti-p251 IgG (1:50) or neurofilament (NF) (814342 1:100, Boehringer Mannheim Biochemica, Roche,
Indianapolis, USA) or mouse anti-peptide III-tubulin (1:1000; Promega,
Wisconsin, USA) were used. For double-labelling of these proteins, primary antibodies were incubated overnight at 4 C and visualised with a cocktail of anti- rabbit secondary antibody conjugated to Alexa 568 and anti-mouse secondary antibody conjugated to Alexa 488, as described in chapter 2. Labelled sections were evaluated on a confocal microscope analysis system (Leica TCS SP inverted microscope, Leica TCS software) or an Olympus BX51 fluorescence microscope fitted with specific filter systems and a computerised image analysis system (SPOT camera, Image Pro Plus software).
177 For all cases, double-labelled immunofluorescent sections using MBP, CNPase, or p25 antibodies were graded in five random sites within the pontine basis at x200 magnification. Samples were photographed using standard digital camera settings, and the normal distribution of proteins determined in controls. Disease related changes in protein localisation were graded as either no change from controls (0), mild loss (1), moderate loss (2) or severe loss (3) of immunofluorescence labelling of protein antigens, and any associations between protein loss and clinical indices were determined using Spearman’s rank and
Mann-Whitney U tests (SPSS Inc., Illinois, USA).
6.2.4 Assessment of axon diameter, fiber diameter and calculation of g ratios
Sections of the pons, double-labelled using MBP and NF immunofluorescence, were analysed using merged digital images and Axiovision software (version
4.6, Carl Zeiss Imaging Solutions, USA). Only transversely sectioned pontine fiber tracts were assessed, and in MSA cases these fiber tracts were chosen as those depleted of p25 immunoreactivity (see results). For each axon, axon area and external fiber area were outlined separately and the diameter in m calculated from the area. 40-65 axons per case were analysed and repeated measurements of 10 axons in 3 cases gave less than 10% variability.
Differences between groups in g ratio (axon diameter/fiber diameter) and axon diameter were identified using Mann Whitney U tests (SPSS Inc., Illinois, USA).
178 6.2.5 Immunohistochemistry for the assessment of morphological changes in oligodendroglia associated with GCI formation
GCI were visualised using thioflavin S staining for fibril formation and - synuclein IHC and oligodendroglia were visualised using p25 IHC. As described in chapter 2, a combined method of peroxidase visualisation and double fluorescence labelling was used. Firstly, p25 was visualised using standard peroxidase IHC, as previously described (Baker et al., 2006; Halliday et al., 2005b), and slides were incubated with the anti-p251 IgG (1:50) overnight at 4 C, followed by standard peroxidase IHC procedures (refer to chapter 2). This was then followed by -synuclein immunofluorescence. Pre- treatment included the incubation of 99% formic acid for 3 minutes to ensure maximal -synuclein binding. Following pre-treatment, blocking steps were performed. Slides were incubated in a 50% ethanol/3% H2O2 solution for 40 minutes, followed by distilled water and 0.1M tris washes. Prior to the second primary antibody incubation, slides were incubated in a 20% normal horse serum solution for 1 hour. Sections were then incubated with anti--synuclein
IgG (1:200, BD Biosciences, San Jose, USA) for 1 hour at 37 C. Following 0.1M tris washes, sections were incubated with the secondary antibody (anti-mouse conjugated to Alexa 568, Molecular Probes, Invitrogen, Carlsbad, USA) for 2 hours at room temperature. Thioflavin S staining was then used to determine the protein conformation as it detects -pleated sheets of protein (McLellan et al.,
2003). Briefly, slides were placed in a 1% thioflavin S (Sigma, St Louis, USA) solution for 5 minutes at room temperature, differentiated with 70% ethanol and
179 then coverslipped with Vectashield (Vector Laboratories, Burlinghame, USA). To ensure specificity of the immunohistochemical technique, a positive (section containing LB) and negative (with no primary antibody incubation) control was included in each experiment. Labelled sections were evaluated and photographed using an Olympus BX51 fluorescence microscope fitted with specific filter systems and a computerised image analysis system (SPOT camera, Image Pro Plus software).
To assess the p25 oligodendroglia size changes in MSA (see results), merged digital images of the triple-labelled sections were analysed. Fibrillisation was assessed using thioflavin S fluorescence and oligodendroglial cells categorised into 4 types according to their protein content and the presence of fibrillised thioflavin S-positive inclusions. Oligodendroglia cell types were: 1) those containing only non-fibrillar p25, 2) those colocalising -synuclein and p25 but not thioflavin S, 3) those colocalising fibrillised -synuclein and p25
(thioflavin S-positive), or 4) those containing only fibrillar -synuclein (thioflavin
S-positive). High-magnification (x1000) of 15-20 random sample areas of
13,767m2 in affected regions in each section were photographed using standard digital camera settings. Images were enlarged 2.6 fold and the density of GCI determined and the size of oligodendroglial GCI and entire soma in each image measured using point-counting by randomly overlaying a 121mm x
175mm grid on each image (each point represented 1.826μm2).
180 To ensure adequate in situ visualisation of -synuclein using the fluorescent probe, assessment of the density and size of -synuclein-immunoreactive oligodendroglia was also performed on single immunoperoxidase labelled sections. For all analyses, a total of 40-60 oligodendroglial cells were measured in each control and MSA case. T tests (SPSS Inc., Illinois, USA) revealed no significant differences in the density or size of -synuclein-immunoreactive oligodendroglia when measured within sections prepared using either the triple- labelling or single-labelling procedures (p>0.7).
Repeated measurements by the same or different investigators gave an average variance of less than 10% for all variables. Differences between control and
MSA groups in oligodendroglia density were evaluated using Mann-Whitney U tests (SPPS Inc., Illinois, USA). Differences between control and MSA groups in the distribution of GCI sizes or oligodendroglial cell body sizes were identified using 2 tests.
6.2.6 Assessment of oligodendroglia changes associated with GCI and CB
The severity of -synuclein-immunopositive GCI in MSA and tau- immunopositive CB in PSP were semi-quantitatively assessed. As described in chapter 4, GCI in the pons of MSA cases were graded as none (0), mild (1), moderate (2) or severe (3). For the present analysis, the severity of CB was graded in 3 random fields at x200 magnification in the pontine tegmentum (a predilection site for CB). The three fields were graded and averaged for a final
181 score using a previously published grading scale (Josephs et al., 2006), whereby grades of none (0), mild (1), moderate (2) or severe (3) were used.
Spearman’s rank correlations (SPPS Inc., Illinois, USA) were performed to determine any relationships between the severity of abnormal oligodendroglial changes and pathological indices.
6.2.7 Correlations with clinical indices
Correlations with clinical indices were determined using Spearman’s rank tests and logistic linear regression modelling (SPPS Inc., Illinois, USA).
6.3 RESULTS
6.3.1 Comparative changes in the amount of myelin-associated proteins
To determine any changes in the amount of myelin-associated proteins in human tissue, western blot studies of control, PD, MSA and PSP cases were performed. The proteins assessed were full-length MBP and the constituent p25 protein, with band intensities standardised to GAPDH in each case. Full- length MBP and p25 protein bands were consistently identified in all tissue fractions in all cases (Figure 6.1). The proportion of soluble MBP averaged between 20-36% in all cases, with no significant change with any disease assessed (Table 6.1). As may be expected, the proportion of lipid-associated and insoluble MBP was on average higher (between 55-65% for controls and cases with PD and PSP, Table 6.1) and a significant disease association was found. In MSA, the full-length MBP was significantly reduced in the lipid-
182 associated and insoluble fraction to 35% of corrected GAPDH values (Table 6.1,
Figure 6.1). This change in protein amount appeared to be selective, as there were no significant changes in the relative amounts of p25 across disease or in controls (Table 6.1, Figure 6.1). In all cases, approximately equal amounts of p25 were found in the soluble and less soluble fractions, although MSA and
PD cases had an insignificant increase in lipid-associated and insoluble p25
(60%, Table 6.1).
183 Figure 6.1 Western blots of control, MSA, PD and PSP human brain extracts
Brain protein extracts were analysed by SDS-PAGE and immunoblotted for
MBP, p25 and GAPDH in four controls, four MSA, two PD and two PSP cases.
Molecular weight markers are on the right.
A There were no significant differences of these proteins in soluble SDS-
extractable fractions between controls, MSA, PD and PSP cases.
B The relative amount of MBP protein but not p25 was significantly
reduced in the insoluble SDS-extractable fraction of MSA compared to
controls, PD and PSP.
184 A controls MSAPSP PD MBP 20kDa
p25A 25kDa
50kDa GAPDH 37kDa
B MBP 20kDa
p25A 25kDa
GAPDH 50kDa 37kDa Table 6.1 Group averages (and standard deviation) of the proportion of myelin proteins assessed densitometrically and standardised to GAPDH in each case
Group Soluble Insoluble Soluble Insoluble
MBP (%) MBP (%) p25 (%) p25 (%)
Control (POWMRI TRC cohort 2) 36 17 64 14 52 5 48 22
PD (POWMRI TRC cohort 5) 21 7 60 6 38 7 68 6
PSP (POWMRI TRC cohort 8) 23 1 54 1 47 1 40 10
MSA (SABB cohort 12) 22 11 35 9^ 52 14 60 25
GAPDH= glyceraldehyde-3-phosphate dehydrogenase, MBP= myelin basic protein,
POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre,
PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy, SABB= South Australian Brain Bank.
^ Significant difference from control values in bold (Mann-Whitney U p<0.05).
6.3.2 Comparative changes in the distribution of myelin-associated proteins
Double-labelling immunofluorescence in controls revealed substantial colocalisation of MBP and p25 in the myelinated corticospinal fiber tracts
(Figure 6.2A-C), particularly surrounding NF-immunopositive axons (Figure 6.2D and E). In addition, intense p25 immunoreactivity was also present in the cytosol of oligodendroglial cell bodies (Figure 6.2D), as previously described
(Kovacs et al., 2004; Lindersson et al., 2005). ApoD was also localised in oligodendroglia cell bodies having a prominent granular staining pattern (Figure
6.2F), as previously described (Navarro et al., 2004; Navarro et al., 1998).
185 Further examination of in situ protein localisation revealed no change in the localisation of MBP or CNPase in PD, PSP or MSA, and no gross structural demyelination (Figure 6.3A&B, Table 6.2). Unexpectedly, in MSA cases there was a redistribution of p25 immunoreactivity in the myelin, leaving patchy areas with reduced p25 and an enhancement of staining in the oligodendroglial cell bodies (Figure 6.3C&D). In addition, ApoD immunoreactivity was observed in GCI in MSA (Figure 6.3E). In contrast, the distribution of p25 and ApoD immunoreactivity in PD and PSP was not different from controls (Figure 6.3F).
Further assessment of the myelin changes in MSA was performed. A patchy distribution of degraded (not full-length) MBP was found in myelinated fiber bundles and in some oligodendroglia and GCI only in the MSA cases (Figure
6.3G, Table 6.2), as previously shown (Matsuo et al., 1998). This is consistent with the reduction of full length MBP to degraded protein products in MSA myelin (Figure 6.1, Table 6.1). Semi-quantitative assessment of the immunofluorescent labelling of protein antigens confirmed the selective mild to moderate patchy loss of p25 immunoreactivity from myelinated fibers to cell bodies in MSA (Table 6.2). There was no correlation to disease duration or subtype, suggesting an early change that does not progress over time.
186 Figure 6.2 In situ protein localisation in myelinated fiber bundles and oligodendroglia in controls
Representative photomicrographs of 8m thick, paraffin-embedded sections of the pons in a control case.
A-C Immunofluorescent photomicrographs of p25 (Alexa 568, red, A) and
MBP (Alexa 488, green, B) immunoreactivity colocalising in the same
axon bundles and structures as indicated in the merge image shown (C).
Scale in C is equivalent to A and B.
D&E Merged immunofluorescent images of p25 (Alexa 568, red, D) and MBP
(Alexa 568, red, E) with NFM (Alexa 488, green, D&E) immunoreacitivity,
indicating that both proteins (p25 and MBP) colocalise in the myelin
sheaths surrounding the NFM-immunoreactive axons in these myelinated
fiber bundles. D: note the intensely p25-immunoreactive
oligodendroglial cell body.
F Brightfield photomicrograph of ApoD immunoreactivity in oligodendroglial
cell bodies of a control case.
187 ABC
100μm p25A MBP Merge DE F
10μm 10μm 20μm p25ANFM merge MBPNFM merge Figure 6.3 Changes in location of myelin-associated proteins in MSA
Representative photomicrographs of 5m thick, paraffin-embedded sections of the pons from control, MSA and PSP cases.
A Merged immunofluorescent image showing p25 (Alexa 568, red) and
MBP (Alexa 488, green) significantly colocalise in control myelinated fiber
tracts. Scale in C is equivalent for A.
B Merged immunofluorescent image showing that similar to MBP, CNPase
(Alexa 488, green) significantly colocalises with p25 (Alexa 568, red) in
control myelinated fiber tracts. Scale in D is equivalent for B.
C Merged immunofluorescent image showing a reduction of p25 (Alexa
568, red) but not MBP (Alexa 488, green) immunoreactivity in the
myelinated fiber tracts in MSA.
D Merged immunofluorescent image showing a loss of p25 (Alexa 568,
red) but not CNPase (Alexa 488, green) immunoreactivity occurs in MSA.
E&F Brightfield photomicrograph of ApoD immunoperoxidase staining in
enlarged oligodendroglia containing GCI in MSA (E). In PSP, ApoD-
immunoreactivity was observed in normal oligodendroglial cells (F). Scale
in G is equivalent for E.
G Brightfield photomicrograph of degraded MBP immunoperoxidase
staining showing abnormally enlarged oligodendroglia containing GCI and
degenerating myelin.
188 AB
p25α/MBP p25α/CNPase C D
100μm 20μm p25α/MBP p25α/CNPase EGF
40μm 20μm Table 6.2 Semi-quantitative assessment of myelin protein immunoreactivity within pontine fiber tracts
Group MBP* CNPase* P25*
Controls (POWMRI TRC cohort 1) 0 ± 0 0 ± 0 0 ± 0
PD (POWMRI TRC cohort 4) 0 ± 0 0 ± 0 0 ± 0
PSP (POWMRI TRC cohort 7) 0 ± 0 0 ± 0 0 ± 0
MSA (POWMRI TRC cohort 10) 0 ± 0 0 ± 0 1.33 0.49
MBP= myelin basic protein, CNPase= 2’3’-cyclicnucleotide 3’phosphodiesterase,
POWMRI TRC= Prince of Wales Medical Research Institute Tissue Resource Centre,
PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy.
*Mean SD Significant differences from control values are indicated in bold (Mann-
Whitney U p<0.05).
6.3.3 Effects of myelin changes on axons
To determine whether these changes in myelination in MSA had any affect on axons, the in situ location of axonal proteins, axonal size and myelination were assessed. Overall, axon integrity as evaluated by NF and III-tubulin immunoreactivity appeared preserved in the corticospinal or pontocerebellar pathways in MSA (Figure 6.4B & D) compared with controls (Figure 6.4A & C).
This is despite the significant reduction in p25 immunoreactivity in the myelin surrounding these axons (Figure 6.4B & D) and the enlargement of the p25- immunoreactive oligodendroglia observed in MSA (Figure 6.4D). G ratios were calculated, to determine whether the surrounding myelin itself was
189 morphologically changed and could therefore affect axonal function. There was a significant increase in the g ratio in MSA cases compared with controls
(0.63±0.08 in MSA versus 0.59±0.10 in controls, p=0.004), suggesting thinner myelin as identified using MBP immunofluorescence and/or larger axons as identified using NF immunofluorescence. Assessment of the axonal diameter for these cases identified a small but significant increase in diameter of NF- immunoreactive axons in the MSA cases compared with controls (2.6±0.4m in
MSA versus 2.4±0.6m in controls, p<0.03). This was due to a relative loss of small myelinated axons in MSA rather than any overall enlargement in the MSA axons.
190 Figure 6.4 Loss of p25 without axonal degeneration in MSA
Representative merged photomicrographs of immunofluorescently labelled paraffin-embedded sections of the pons in control and MSA cases. Scale in D is equivalent for all photomicrographs.
A P25 immunoreactivity (Alexa 568, red) concentrates in myelin
surrounding NFM-immunoreactive (Alexa 488, green) axons in controls.
B There is a significant loss of p25 immunoreactivity (Alexa 568, red) in
MSA myelin without the loss of NFM-immunoreactive (Alexa 488, green)
axons.
C&D Similar to NFM, III-tubulin immunoreactivity (Alexa 488, green)
concentrated in the axons in both controls and MSA. In areas of reduced
p25 immunoreactivity (Alexa 568, red) in MSA myelin, axonal III-tubulin
immunoreactivity remained preserved (D) and enlarged p25-
immunoreactive oligodendroglia were obvious.
191 AB
p25ANFM p25ANFM CD
20μm p25ABIIItubulin p25ABIIItubulin 6.3.4 Oligodendroglial cell body changes in MSA
MBP and CNPase are both constituent proteins of oligodendroglia, however they are more commonly utilised as myelin rather than mature oligodendroglial markers. In addition to myelin, p25 is expressed in oligodendroglial cells
(Lindersson et al., 2005; Skjoerringe et al., 2006). As expected and previously described, p25-immunoreactive oligodendroglia in controls had a perinuclear cytoplasmic staining pattern, without labelling of nuclei (Lindersson et al., 2005)
(Figure 6.5A). In controls, only small -synuclein-negative p25-immunoreactive oligodendroglia were observed with an average cell size of 12.9±3.9μm2 (Figure
6.5A; Table 6.3) and an average density of 4.0±0.9/high power field. In MSA, the p25-immunoreactive oligodendroglia were expanded in all cases, and the - synuclein negative but p25-immunoreactive population was significantly reduced in density (average of 1.8±1.1/field, p=0.002). The significant enlargement of their cell size was approximately triple that of controls (Figure
6.5B; Table 6.3).
192 Table 6.3 P25 and -synuclein associated oligodendroglial cell size measurements in µm2 (mean standard deviation)
Group N p25 only p25+-syn p25+-syn + -syn only +
(%N, range) (%N, range) thioflavin S thioflavin S
(%N, range) (%N, range)
Control 377 12.9 ± 3.9 - - -
(100%,
3.7-31)
MSA 689 36 ± 18* 72 ± 29 89 ± 34 44 ± 24
(53%, 11-141) (27%, 22-181) (7%, 22-161) (13%, 13-120.5)
N=number, -syn= -synuclein, MSA= multiple system atrophy.
* Significantly different distribution from controls using 2 test (p < 0.001) with 87% of
MSA p25 only oligodendroglia sampled > 2 standard deviations from control mean value.
6.3.5 Oligodendroglial changes associated with GCI
As described in chapter 4, the average pontine -synuclein-positive GCI severity in the MSA cases was mild, ranging from none to severe. The constituent oligodendroglial proteins p25 and ApoD both colocalised with -synuclein- immunoreactive GCI and degraded but not full-length MBP, also colocalised with
-synuclein-immunoreactive GCI. A high proportion (around 70-75%) of - synuclein-immunoreactive GCI also contained p25-immunoreactivity (Figure
6.5C, Table 6.3), whereas approximately one third contained degraded MBP immunoreactivity (Figure 6.3G) and 15% contained ApoD immunoreactivity
193 (Figure 6.5D). In addition to these constituent proteins, -synuclein- immunoreactive GCI in MSA also contained PACRG (constituently expressed by protoplasmic astrocytes, refer to chapter 5) and parkin immunoreactivity.
Approximately 50% of -synuclein-immunoreactive GCI contained PACRG immunoreactivity (Figure 6.5E), with a smaller proportion (35%) containing parkin immunoreactivity (Figure 6.5F).
As p25 was observed in most oligodendroglia and GCI (see above), triple- labelling experiments (thioflavin S, -synuclein, and p25, Figure 6.5G-I) were performed to quantify the morphological and density changes in oligodendroglia in MSA compared with controls (Table 6.3). In this analysis, the thioflavin S positive fibrillar inclusions measured in cross-section was 45±17m2.
Assessment of oligodendroglia containing -synuclein-immunoreactivity (not seen in controls) revealed a similar number (1.7±1.2/field) to those without - synuclein-immunoreactivity (see above and Table 6.3), with the majority of these colocalising p25 protein (average density of 1.2±0.9/field). However, these double-labelled oligodendroglia had an even larger cell size compared to those without -synuclein-immunoreactivity (average of approximately 80 μm2; Table
6.3), and were of a similar size to MSA oligodendroglia containing degraded
MBP (p=0.29; Figure 6.3G), ApoD, PACRG and parkin immunoreactivity (Figure
6.5D-F). These very large p25- and -synuclein-immunoreactive oligodendroglia could be divided into non-fibrillar (approximately 80%) and thioflavin S positive fibrillar cells with the latter having the largest average size
194 (Figure 6.5G-I, Table 6.3). These larger fibrillar oligodendroglia did not contain degraded MBP, PACRG, parkin or ApoD immunoreactivity. A small proportion of the oligodendroglia sampled contained no p25 immunoreactivity but displayed
-synuclein and thioflavin S positive fibrillar inclusions (average density of
0.5±0.4/field). These cells had a reduced average size compared with those containing both -synuclein and p25 immunoreactivity (Table 6.3) or those containing degraded MBP (p=0.004), PACRG, parkin or ApoD immunoreactivity.
The localisation of these different proteins in different sized oligodendroglia containing either fibrillar or non-fibrillar -synuclein suggests the initial accumulation of p25 in association with the expression of PACRG. Parkin protein expression associates with the degradation of MBP and non-fibrillised - synuclein accumulation in oligodendroglia. At this stage, ApoD expression occurs in a proportion of these oligodendroglia prior to -synuclein fibrillisation and the loss of constituent protein expression.
The size of the GCI did not differ within the different cell types detected and was not different from the oligodendroglia containing only fibrillar -synuclein
(p=0.77). There was no positive correlation between the number of -synuclein- immunopositive and -synuclein-immunonegative oligodendroglia in MSA
(p=0.27). There was a correlation between the size of these highly expanded p25 and -synuclein containing oligodendroglia and those containing only p25 (p=0.03) and those containing only -synuclein immunoreactivity
(p=0.001). However, there was no correlation between the size of p25 only-
195 and -synuclein only-immunoreactive MSA oligodendroglia. The relationship between the size of the expanded oligodendroglia containing only p25 and those also containing -synuclein across the cases suggests that such cell expansion may predispose to abnormal -synuclein deposition. The relationship between the size of the oligodendroglia containing both p25 and -synuclein and the smaller number containing only fibrillised -synuclein suggests further intracellular modifications targeting p25 influences this pathology.
As described in chapters 4 and 5, the pontine -synuclein-immunoreactive GCI in MSA correlated with several other pathological parameters. Increasing GCI in the pons positively correlated with increasing GCI in the SN (Rho=0.61, p=0.04) and increasing GFAP-immunoreactive astrogliosis in the putamen (Rho=0.73, p<0.01). The severity of -synuclein-immunoreactive GCI did not correlate with nigral neuronal loss or regional volume changes, despite the significant reduction of putamen volume in MSA (refer to chapter 4).
196 Figure 6.5 Control and MSA oligodendroglia
Representative photomicrographs paraffin-embedded sections of the pons in a control (A) and MSA (B-I).
A&B The majority of oligodendroglia sampled in both controls (A) and MSA
cases (B) contained only p25 immunoreactivity (-synuclein- and
thioflavin S-negative, brightfield images shown). In controls, p25
immunoreactivity was found surrounding the nucleus in a thin sheet of
cytoplasm, as well as in surrounding myelin (A). In MSA, there was a
reduction of p25 immunoreactivity in surrounding myelin and an obvious
enlargement of the oligodendroglial cytoplasm in the majority of this cell
type (B). Scale in C equivalent for A and B.
C A small proportion of the MSA oligodendroglia sampled contained only
fibrillar -synuclein inclusions (thioflavin S-positive, p25-negative,
merged brightfield and fluorescence image shown).
D-F Merged immunofluorescent images showing -synuclein-immunoreactive
oligodendroglia also containing ApoD (D), PACRG (E) and parkin (F)
immunoreactivity. Scale in E equivalent for D.
G-I A significant proportion of MSA oligodendroglia colocalised p25
(brightfield immunoperoxidase, G) and -synuclein (Alexa 568, red
immunofluorescence, H) immunoreactivity and ~20% of this cell type
contained fibrillised GCI (thioflavin S, green histofluorescence, I; asterisk
indicates the same cell).
197 ABC
5μm p25A p25A p25A A synuclein DE F
25μm 10μm G HI ** *
5μm p25A A synuclein thioflavin S 6.3.6 Oligodendroglial changes associated with CB
The average severity of tau-immunoreactive CB in the pons was mild, ranging from none to moderate in PSP cases (Figure 6.6A-C). In contrast to MSA, none of the constituent oligodendroglial proteins, and none of the other PD-related proteins, were found in pontine CB in PSP. In addition, there was no visible increase in the size of PSP oligodendroglia containing p25 and tau immunoreactivity compared to control p25-immunoreactive oligodendroglia
(Figure 6.5A).
In PSP, the increasing severity of CB in the pons positively correlated with the volume (Rho=0.87, p=0.01) and severity of NFT (Rho=0.59, p=0.02) in the pons, and with increasing densities of PACRG-immunoreactive astrocytes in the SN
(Rho=0.60, p=0.03). No other correlations were observed with cell loss and
NFT in the SN, other regional volume changes or GFAP associated astrocytosis.
198 Figure 6.6 Representative grades of coiled bodies in PSP
Representative brightfield photomicrographs of paraffin-embedded sections of the pons in PSP, immunohistochemically labelled with tau (AT8) and counterstained with cresyl violet. Scale in A is equivalent for all photomicrographs.
A Representative grade of none (0), showing no tau-immunoreactive coiled
bodies.
B Representative grade of mild (1), showing a sparse distribution of tau-
immunoreactive coiled bodies.
C Representative grade of moderate (2), showing a patchy distribution of
tau-immunoreactive coiled bodies in the field of view.
199 A
50μm B
C 6.3.7 Correlations with clinical indices
There were no differences in the severity or type of oligodendroglia changes and clinical phenotype either across or within disease groups. There were no correlations between the severity or type of oligodendroglial changes observed and any clinical symptoms either across or within disease groups.
The most significant morphological oligodendroglial change was observed in the p25-immunoreactive oligodendroglia in MSA. There was no correlation between the oligodendroglia or GCI densities and MSA disease duration, suggesting that tissue volume changes play a significant role in MSA (refer to chapter 4). Correlating MSA disease duration with the average size data revealed a correlation with the cell size of p25- and -synuclein- immunoreactive oligodendroglia (p=0.04) as well as the cell size of those containing only fibrillised -synuclein-immunoreactive GCI (p=0.009) but not those containing only p25 immunoreactivity. As -synuclein-immunoreactive
GCI size was similar across cases, there was no correlation with MSA disease duration.
The severity of CB in the pons did not correlate with disease duration
(Rho=0.08, p=0.77). Previous studies have established negative correlations between the severity of CB and disease duration in the red nucleus and globus pallidus (Josephs et al., 2006) with these measures also used in the PSP tau grading scale (Williams et al., 2007a).
200
6.4 DISCUSSION
As expected, pathological changes in oligodendroglia were only observed in the atypical parkinsonian syndromes MSA and PSP. While characteristic protein deposition occurs in both disorders, substantial cellular and protein changes were only observed in MSA. These significant alterations in constituent myelin and oligodendroglial proteins in MSA were accompanied by gross morphological changes over time leading to degradation. In contrast and perhaps surprisingly, oligodendroglial tau aggregation in PSP CB did not produce any oligodendroglial protein or morphological changes of note, and were associated with the more substantial neuronal and astrocytic changes found in PSP (refer to chapter 5).
This novel data reveals that myelin dysfunction occurs prior to the oligodendroglial inclusions characterising MSA, whereas oligodendroglial inclusions in PSP do not significantly disrupt these functions.
A number of constituent myelin proteins are disrupted early in MSA. In particular, there is a selective degradation of full-length MBP without significant demyelination (CNPase remains unaffected). Similar myelin changes occur in genetic models that reduce MBP (Matsuo et al., 1998; Mikoshiba et al., 1980;
Mikoshiba et al., 1985). The lack of gross myelin disruption in MSA has been noted previously, although similar myelin degradation has been observed using sensitive histochemical and IHC techniques (Matsuo et al., 1998; Papp et al.,
1989). There is also a patchy disappearance of p25 protein from the myelin
201 along with its accumulation in oligodendroglia with expanded cell bodies.
Oligodendroglial cells have an advanced system for intracellular sorting and transport of constituents for the different subdomains in the myelin sheets. This is exemplified for the two major myelin proteins where the proteolipid protein uses the endoplasmic reticulum-Golgi pathway for sorting of membrane proteins
(Boiko and Winckler, 2006), whereas MBP in myelin relies on the transport of its
RNA, which becomes translated within the myelin structure (Barbarese et al.,
1999). The reduction in full-length MBP and relocalisation of p25 from myelin, along with the accumulation of MBP degradation products in the oligodendroglial cell bodies, suggest that the cellular transport system maintaining MBP levels in myelin is perturbed in MSA. The loss of the microtubule stabiliser p25 from myelin in MSA is consistent with animal models showing that reduced MBP leads to the complete suppression of microtubule stability (Galiano et al., 2006) eliciting a delay in myelin synthesis and deposition without affecting the overall myelin content (Roch et al., 1987; Shine et al., 1992). Whether the reduction in full- length MBP and its abnormal proteolysis in MSA (also previously noted by
Matsuo et al 1998) results from an initial problem with MBP mRNA transport from the cell body destabilising its protein associations in myelin, or a direct loss of the stability of these associations due to a change in its interaction with p25, or to some combination of these events, remains to be investigated further.
The present study shows that these changes in myelin proteins in MSA affect the myelination of associated axons. Of relevance, is that the changes appear to
202 target oligodendroglia myelinating smaller (rather than larger) diameter axon fibers in MSA, consistent with previous studies (Mochizuki et al., 2008; Sobue et al., 1987; Tohgi et al., 1982). In shiverer mice, deletion of the MBP gene preserves large calibre axon fibers and their myelin preferentially (Noebels et al.,
1991; Shine et al., 1992). Interestingly, mice overexpressing golli-MBP proteins transcribed from the same MBP gene develop a profound delayed intention tremor in association with a loss of full-length MBP protein but not mRNA
(Jacobs, 2005). Oligodendroglial cells in these mice do not elaborate myelin sheaths and have abnormal morphology (Jacobs, 2005). These cellular changes directly relate to the loss of MBP (Fitzner et al., 2006). The preservation of large calibre axons in these models and in MSA is consistent with the lack of substantive pyramidal tract signs observed. The selective loss of small myelinated fibers in MSA has been associated with the prominent autonomic dysfunction observed in such cases (Tohgi et al., 1982).
The present study suggests that the abnormal accumulation of -synuclein in
GCI is a relatively late event with a number of other additional proteins abnormally accumulating in pre-fibrillar structures. Of the constituent oligodendroglial proteins assessed, p25 was present in most MSA GCI, with the accumulation of this protein within the oligodendroglial cell bodies preceding - synuclein accumulation. The accumulation of p25 in GCI bearing oligodendroglia in MSA is well documented (Kovacs et al., 2007; Kovacs et al.,
2004; Lindersson et al., 2005) with p25 known to stimulate -synuclein
203 aggregation (Lindersson et al., 2005). In addition to the earlier accumulation of p25 in GCI, the presence of degraded MBP (see also (Matsuo et al., 1998)),
PACRG, parkin and ApoD were also observed in early GCI. Neither PACRG or parkin have been previously localised in -synuclein-immunoreactive GCI, but the present study suggests these proteins are involved subsequent to p25 accumulation. The abnormal presence of these proteins in MSA oligodendroglia may relate to the degradation of MBP and the accumulation of p25. As parkin is an E3 ubiquitin ligase in the proteosome degradation pathway (Shimura et al.,
2001; Vercammen et al., 2006) and its expression was observed in association with the degradation of MBP, these two changes may be most directly related. In addition, PACRG and parkin bind to tubulin for greater microtubule stability
(Ikeda, 2008; Yang et al., 2005). These proteins may be increased in MSA oligodendroglia to increase tubulin polymerisation in an effort to stabilise the microtubule system. This expression itself may precipitate abnormal protein fibrillisation. ApoD is a constituent oligodendroglial protein thought to participate in repair processes (Navarro et al., 2004). ApoD immunoreactivity was observed in a small proportion of GCI, suggesting that its accumulation occurs just prior to fibrillisation. This suggests it is upregulated for a short time period in response to the protein abnormalities precipitating oligodendroglial GCI discussed above.
Significant morphological changes to oligodendroglia were only observed in
MSA and preceded GCI formation. In Long Evans Shaker and bouncer rats lacking MBP, oligodendroglia cells are enlarged and develop an accumulation
204 of vesicles and membranous bodies without significant cell death (Kwiecien et al., 2000; Kwiecien et al., 1998). The quantitative measurement of oligodendroglia size in the present study suggests this early morphological change is the relocalisation of p25 to the cell body with subsequent oligodendroglial soma expansion. In MSA, there appears to be a slow, continued p25 accumulation and somal expansion over time until -synuclein accumulates and GCI form (as revealed by thioflavin S positivity). Hereafter, a fraction of the GCI-containing cell bodies compact and loose their p25 immunoreactivity. How the physiological role of p25 is disrupted to initiate these processes remains to be clarified further, but transgenic mice models show that the accumulation of -synuclein in oligodendroglia causes subsequent degeneration of both oligodendroglia and neurons (Shults et al.,
2005; Yazawa et al., 2005). In these transgenic mice models, the expression of human -synuclein in oligodendroglia leads to oligodendroglial pathology with aggregates of human -synuclein and neuronal degeneration displaying aggregates of mouse -synuclein (Shults et al., 2005; Yazawa et al., 2005). It will be important to further understand the earlier pathological changes involving p25 noted in the present study to be able to develop better models of the early pathogenic events and provide potentially preventative therapeutic strategies for this type of degeneration in MSA.
In contrast to MSA, oligodendroglial tau deposition in the form of CB in PSP did not significantly change oligodendroglial or myelin protein composition or
205 morphology. Abnormal accumulations of tau in oligodendroglia have been associated with axonal dysfunction (Yamada and McGeer, 1990), NFT formation and neuronal loss in regions of degeneration (Jin et al., 2006). The present study also found interactions between the severity of CB and astrocytic and NFT pathology in PSP, suggesting that CB may be a reaction to these other more substantive pathologies. While previous reports have shown that the severity of
CB decreases with disease duration in PSP (Josephs et al., 2006), more recent studies suggest that this is largely due to clinical phenotype (Williams et al.,
2007a), supporting a reactive rather than degenerative oligodendroglial pathology. In the present study, the severity of CB in the pons was not related to disease duration or clinical phenotype. This shows that tau-immunoreactive CB does not disrupt myelin and oligodendroglial function in the same way as MSA.
6.4.1 Conclusions
Abnormalities in constituent oligodendroglial and myelin proteins were observed only in MSA and not in PSP or PD. In PSP, oligodendroglial CB associate with other core pathological features and do not relate to myelin dysfunction. In MSA, there is a relocation of p25 from the myelin to expanding oligodendroglial cell bodies, in parallel with a reduction in full-length MBP and demyelination of smaller caliber axons in corticospinal and pontocerebellar pathways. The expansion of the oligodendroglial cell bodies continues in those cells that also accumulate -synuclein, degraded MBP and ApoD, with the induction of
PACRG and parkin expression associated with the subsequent development of
206 fibrillar -synuclein. Therefore, a series of novel, early MSA-specific oligodendroglial changes have been identified, affecting the p25 protein prior to the development of the current disease-specific hallmark, the -synuclein- containing GCI. Overall, MSA is distinguished by abnormalities in constituent oligodendroglial and myelin proteins that theoretically could be utilised as early markers for this disease.
207
Chapter 7: Microglial activation
7.1 INTRODUCTION
As discussed in chapter 1, based on the current literature it was hypothesised that microglial activation occurs in all parkinsonian disorders, however the different forms of microglial activation may be associated with patterns of degeneration. Microglial activation is one of the most characteristic glial reactions to brain pathogens and pathologies. In vivo studies have shown that microglia are never quiescent but continuously extend and retract their processes to examine their surroundings (Nimmerjahn et al., 2005). Fully activated microglia significantly change their morphology by retracting and thickening their processes to interact with specific tissue elements (McGeer and
McGeer, 2008). The signalling molecule to effect this morphological change is
HLA-DR, an antigen presenting glycoprotein expressed by activated microglia
(McGeer and McGeer, 2008) as well as by macrophage cells in the blood. High expression of HLA-DR transforms both these cell types into phagocytes through regulated immune mechanisms (Gehrmann et al., 1993).
Microglial activation is the most commonly recognised and studied inflammatory process in neurodegeneration. This is due to the promise of regulating such inflammation through successful treatments designed for similar mechanisms in
208 peripheral tissues. In PD, microglial activation is associated with LB accumulation only in the SN (Croisier et al., 2005; Imamura et al., 2003), however there is a closer relationship between microglial activation and neuron loss in this region (Imamura et al., 2003; McGeer et al., 1988; Mirza et al.,
2000). HLA-DR-immunoreactive microglia in the SN have been identified phagocytosing dopaminergic neurons in PD patients (Imamura et al., 2003;
McGeer et al., 1988; Mirza et al., 2000) with imaging studies using [11C] (R)-
PK11195 PET as an in vivo microglial marker demonstrating selective microglial activation corresponding to dopaminergic terminal loss in the nigrostriatal pathway in early PD (Ouchi et al., 2005). These studies show that intrinsic microglia activation significantly contributes to the progressive degeneration of
PD (Ouchi et al., 2005). The close relationship between dopaminergic neuron loss in the SN and microglial activation suggests that imaging reactive microglia may be a good biomarker for the cell loss associated with PD (Mosley et al.,
2006; Ouchi et al., 2005).
In contrast, the microglial activation in atypical parkinsonian syndromes closely associates with abnormal protein accumulation. As described in chapter 1, microglial activation in PSP positively correlates with tau pathology in most regions (Ishizawa and Dickson, 2001), confirmed by the use of the in vivo microglial marker [11C] (R)-PK11195 PET showing microglial activation in the basal ganglia, midbrain, frontal lobe and cerebellum (Gerhard et al., 2005). In
MSA, HLA-DR-immunoreactive microglia closely associate with -synuclein-
209 immunopositive GCI (Ishizawa et al., 2004), also confirmed using the in vivo microglial marker [11C] (R)-PK11195 PET (Gerhard et al., 2003). A recent mouse model of MSA has shown that oligodendroglial overexpression of - synuclein induces microglial activation (Stefanova et al., 2007). Similar to PD, the microglial activation in the MSA mouse model directly correlates with dopaminergic neuron loss (Stefanova et al., 2007). Whether the microglial activation in atypical disorders more closely associates with cell loss or protein accumulations remains to be determined.
As described in chapter 1, the pathogenic PD-related proteins parkin, PACRG,
PINK1 and DJ-1 are normally expressed in glial cells and also in some of the astrocytic and oligodendroglial inclusions of PSP and MSA. However, the expression of these proteins has not been assessed in the obviously activated microglia in these parkinsonian disorders. Parkin knock-out models show increased microglial activation in response to a loss of parkin function (Serrano et al., 2005; Solano et al., 2008) suggesting that parkin plays a functional role in microglial activation.
7.1.1 Hypotheses to be tested
The severity of microglial activation in PD, MSA and PSP relates to:
1. the severity of neuron loss,
2. the type and severity of inclusion formation,
3. the type and severity of other glial cell involvement.
210
7.2 METHODS
7.2.1 Cases and tissue preparation
As described in chapter 4, cases used were from the POWMRI TRC cohorts 1,
4, 7 and 10, also including cases from QSBB cohorts 3, 6, 9, and 11. Sections of the SN, putamen and the pontine basis were used (refer to chapter 2 for tissue preparation). As described in chapter 2, routine protocols for peroxidase IHC with appropriate pre-treatment for antigen retrieval was used to identify HLA-DR
(1:100, DAKO, Ely, UK), -synuclein (1:1000, Autogen Bioclear, Calne, UK;
1:200, BD Biosciences, San Jose, USA), AT8 (1:600, Autogen Bioclear, Calne,
UK; 1:10 000 Pierce, Rockford, USA) and parkin (1:200, Biosensis, Adelaide,
Australia) immunoreactive structures and the sections were counterstained with cresyl violet (0.5%) or Mayer’s haematoxylin histological stains.
For protein colocalisation, double immunofluorescence labelling was performed
(refer to chapter 2) using mouse anti-HLA-DR (1:100 dilution) mixed with anti- parkin (1:200 dilution). Procedures used for the detection of primary antibodies using secondary fluorescent antibody probes were as described in chapter 2.
7.2.3 Analyses
The peroxidase sections from all cases were viewed using Zeiss Axioskop
MC80 DX or Olympus BX51 microscopes to evaluate the morphology of microglial changes across all groups. The morphology and severity of HLA-DR-
211 immunoreactive activated microglia were semi-quantitatively analysed in three random x100 magnification fields in each section from each case. HLA-DR- immunoreactive microglia were separated into those considered non-phagocytic with smaller somas and longer processes >2 (Figure 7.1A) versus those considered phagocytic with larger somas and few processes (Figure 7.1B). The degree of activation of each type of microglia was graded as none or rare (0)
(Figure 7.1C), mild (1, a sparse distribution) (Figure 7.1D), moderate (2, in close to half the field of view) (Figure 7.1E) or severe (3, densely spread throughout the field of view) (Figure 7.1F) compared with the pattern and type of microglial activation in controls.
212 Figure 7.1 Different types and representative grades of HLA-DR- immunoreactive activated microglia in PD, PSP and MSA
Representative brightfield photomicrographs of 5m thick, paraffin-embedded sections immunoperoxidase labelled with HLA-DR.
A Typical non-phagocytic activated microglia in the pons of a MSA case.
Scale in B is equivalent for A.
B Typical phagocytic microglia in the substantia nigra of a PD case.
C Representative grade of none (0), showing no HLA-DR-immunoreactive
activated microglia. Scale in F is equivalent for C.
D Representative grade of mild (1), showing a sparse distribution of HLA-
DR-immunoreactive activated microglia. Scale in F is equivalent for D.
E Representative grade of moderate (2), showing a patchy distribution of
HLA-DR-immunoreactive activated microglia. Scale in F is equivalent for
E.
F Representative grade of severe (3), showing a dense distribution of HLA-
DR-immunoreactive activated microglia.
213 A B
20μm FEDC
50μm To further investigate the severity of parkin immunoreactivity in activated microglia, a quantitative stereological method was applied using an imaging analysis software program (Image Pro Plus, version 6.2, Media Cybernetics,
Bethesda, USA). The regions of interest included the SN, putamen and pontine basis and these regions were delineated using a computer mouse. Using a motorised stage attached to the microscope (Nikon Eclipse 50i), random sites were sampled by the imaging software program within the delineated regions of interest and parkin-immunoreactive activated microglial structures quantified at x400 magnification. Intra- and inter-rater analysis using the Bland-Altman method revealed < 5% variance using this method of quantitation.
To assess the degree of protein colocalisation, double-labelled sections were viewed and photographed using Zeiss Axioskop MC80 DX or Olympus BX51 microscopes (Axiovision camera and software) and confocal images were taken using a Leica TCS4D confocal microscope with a 3-channel scan head and argon/krypton laser (University College London confocal imaging unit, London,
UK). The proportion of HLA-DR-immunopositive activated microglia colocalising parkin was determined in 10 random photographs of each section for each case taken at x200 magnification.
To determine differences in the severity of microglial activation between groups,
Mann Whitney U and Post Hoc tests were used (SPPS Inc., Illinois, USA).
Spearman’s rank tests (SPPS Inc., Illinois, USA) were performed to determine any relationships between the severity of activated microglia and pathological 214 and demographic variables. Stepwise logistic linear regression modelling (SPPS
Inc., Illinois, USA) was performed to determine whether changes in activated microglia related to clinical subtype.
7.3 RESULTS
7.3.1 Microglial activation in PD, PSP and MSA
HLA-DR immunoreactivity distinguished microglia that were activated and phagocytic as well as microglia that were activated but yet to become phagocytic (Deng and Sriram, 2005; Gehrmann et al., 1995). Activated non- phagocytic microglia were bushy in appearance with thickened processes (Deng and Sriram, 2005; Gehrmann et al., 1995) (Figure 7.1A). In contrast, activated phagocytic microglia had a general amoeboid shape, with some variance in their morphology (Figure 7.1B). Activated microglia were rarely observed in the putamen of controls. Non-phagocytic HLA-DR-immunoreactive microglia were observed in the pons of some control cases, with the greatest densities of activated microglia found in the SN of controls (Table 7.1), consistent with previously published distributions (Beach et al., 2007; Sugama et al., 2003).
Both phagocytic and non-phagocytic HLA-DR-immunoreactive microglia were observed in varying densities in PD, PSP and MSA.
The pattern of activation for both non-phagocytic and phagocytic microglia was similar (p>0.56) across all regions in PD, PSP and MSA except for the putamen where greater densities were observed in PSP (p=0.02) and MSA (p=0.005) compared to PD. In all diseases, the SN had limited non-phagocytic microglia 215 but prominent round amoeboid-like phagocytic microglia (ranging from none to severe in PD and mild to severe in PSP and MSA, Figure 7.2A, Table 7.1).
Increased densities of phagocytic microglia in this region correlated with decreased densities of non-phagocytic microglia (Rho<-0.9, p<0.001), supporting a continuum between these populations. The greatest densities of non-phagocytic but activated microglia were observed in the pons (Figure 7.2B), particularly in PSP and MSA, with few phagocytic microglia (average of mild in all disorders). In this region, greater densities of activated non-phagocytic microglia correlated with greater densities of phagocytic microglia (Rho>0.9, p<0.001), supporting less overall end-stage activation and destruction of this region. In both PD and PSP, there was limited activation of either non- phagocytic or phagocytic microglia in the putamen, however, more substantial microglial activation was observed in MSA (Figure 7.2C, Table 7.1). Non- parametric tests confirmed that MSA had significantly greater densities of activated non-phagocytic microglia in the putamen than the other groups
(p<0.01).
216 Figure 7.2 HLA-DR-immunoreactive phagocytic and non-phagocytic microglia
Representative brightfield photomicrographs of 5m thick, paraffin-embedded sections immunoperoxidase labelled with HLA-DR, taken at x400 magnification.
Scale in C is equivalent for all photomicrographs.
A Amoeboid-shaped phagocytic microglia surrounding dopaminergic
neurons in the substantia nigra of a PD case.
B Non-phagocytic activated microglia in the pons of a MSA case.
C Amoeboid-shaped phagocytic microglia in the putamen of a MSA case.
217 A
B
C
20μm Table 7.1 Regional severity gradings for nigral cell loss, pathological inclusion formation, and increased HLA-DR-immunoreactive microglial activation
Mean severity grade (range) Control PD PSP MSA
Substantia nigra
Cell loss 0 3 (2 – 3) 3 (2 – 3) 3 (2 – 3)
Inclusion formation 0 2 (0 – 3) 2 (0 – 3) 1 (0 – 3)
HLA-DR non-phagocytic 0 (0 – 1) 0 (0 – 2) 1 (0 – 3) 1 (0 – 2)
HLA-DR phagocytic 0 (0 – 1) 2 (0 – 3) 2 (1 – 3) 2 (1 – 3)
Putamen
Inclusion formation 0 0 (0 – 1) 0 (0 -1) 2 (1 – 3)
HLA-DR non-phagocytic 0 (0) 0 (0) 1 (0 – 1) 1 (0 – 3)
HLA-DR phagocytic 0 (0) 1 (0 – 1) 1 (0 – 1) 1 (0 – 3)
Pons
Inclusion formation 0 1 (0 – 1) 1 (0 – 3) 1 (0 – 3)
HLA-DR non-phagocytic 1 (0 – 2) 1 (0 – 2) 2 (0 – 3) 2 (0 – 3)
HLA-DR phagocytic 0 (0) 1 (0 – 3) 1 (0 – 2) 1 (0 – 2)
PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy, HLA-DR= human leukocyte antigen-DR1, 0= none, 1= mild, 2= moderate, 3= severe.
Correlation analyses revealed that the severity of microglial activation related to the core pathologies in these parkinsonian disorders. In PD, increasing densities of pontine LB correlated with increasing activation of non-phagocytic microglia in the pons (Rho=1.00, p<0.001), while cell loss influenced these variables in the
SN. Increasing activation of non-phagocytic microglia in the SN correlated with
218 fewer PD LB (Rho=-0.82, p=0.02) and increasing densities of phagocytic microglia in the SN negatively correlated with the Braak LB stage (Rho=-0.76, p<0.05) and the volume of the globus pallidus (Rho=-0.88, p=0.009). In PSP, increasing densities of pontine NFT correlated with increasing activation of non- phagocytic microglia in the pons (Rho=1.00, p<0.001), while increasing activation of non-phagocytic microglia in the SN correlated with fewer PSP NFT in the SN (Rho=-0.82, p=0.02), confirming the impact of cell loss in this region.
Similarly in MSA, increasing densities of putaminal GCI correlated with increasing activation of phagocytic microglia in the SN (Rho=0.61, p<0.05) and decreases in non-phagocytic microglia in the SN (Rho=-0.91, p<0.001), increasing densities of pontine GCI correlated with increasing activation of non- phagocytic microglia in the putamen (Rho=0.76, p<0.01), and increasing activation of non-phagocytic microglia in the putamen correlated with increasing pathological stage (Rho=0.38, p=0.03). These data suggest that the deposition of a variety of proteins in abnormal neuronal and glial inclusions activates microglia, directly stimulating non-phagocytic rather than phagocytic morphologies. In PD and PSP, no other correlations between non-phagocytic activated microglia and any pathological parameters were observed.
In MSA, non-phagocytic microglia activation also correlated with the overall degree of neurodegeneration. Increasing activation of non-phagocytic putaminal microglia correlated with decreasing putaminal volume (Rho=-0.57, p<0.01) and increasing putaminal GFAP-immunoreactive astrocytes (Rho=0.70, p<0.01),
219 while increasing activation of microglia in the SN correlated with decreasing midbrain volume (Rho=-0.87, p=0.01).
In both PD and MSA, the density of phagocytic microglia directly correlated with the densities of PACRG-immunoreactive astrocytes in the putamen (Rho>0.75, p<0.05). In PSP, the severity of phagocytic microglia was related across regions, with increasing phagocytic microglia in the pons correlating with less phagocytic microglia in the SN (Rho=-0.77, p=0.02) and putamen (Rho=-0.61, p=0.002) and more non-phagocytic microglia in the SN (Rho=0.62, p<0.05), putamen (Rho=0.62, p<0.05) and pons (Rho=0.88, p<0.001).
There were no correlations between the degree of HLA-DR-immunoreactive
(both non-phagocytic and phagocytic) microglia and clinical indices and disease duration (all p values > 0.05). However, greater densities of non-phagocytic and phagocytic HLA-DR-immunoreactive microglia in the pons both related to the cerebellar/RS clinical phenotype (p<0.05) across disorders using logistic regression analysis.
7.3.2 Microglial parkin in PD, PSP and MSA
The glial expression of parkin has been previously reported without the identification of the cell types involved (Zarate-Lagunes et al., 2001). As previously described, parkin immunoreactivity was observed in a proportion of reactive astrocytes in PSP (refer to chapter 5) and GCI in MSA (refer to chapter
6). In the present study, double-labelling experiments were performed to 220 determine whether parkin immunoreactivity was localised in microglial cells.
These experiments revealed that parkin immunoreactivity was commonly observed in HLA-DR-immunoreactive microglia across disease groups and in controls. In all controls, the morphology of the parkin-immunoreactive microglia was confined to the non-phagocytic activated microglia (Figure 7.3A). However in all disease groups, in addition to a predominant non-phagocytic morphology, parkin-immunoreactive microglia was also observed in some phagocytic microglia (Figure 7.3B). Across all regions and cases, approximately 70% of activated microglia also contained parkin immunoreactivity, with the majority having a non-phagocytic morphology (Figure 7.3C-E).
221 Figure 7.3 Parkin-immunoreactive activated microglia
Representative photomicrographs of 8m thick, paraffin-embedded sections of the putamen in MSA and PSP cases.
A A brightfield photomicrograph of non-phagocytic activated microglia
immunoperoxidase labelled with parkin in a MSA case. Scale in B is
equivalent for A.
B A brightfield photomicrograph of both non-phagocytic and phagocytic
(arrows) microglia immunoperoxidase labelled with parkin in a MSA case.
C-E Immunofluorescent photomicrographs of a non-phagocytic activated
microglia labelled with parkin (Alexa 568, red, C) and colocalising with
HLA-DR (Alexa 488, green, D) as shown in the merge image (E) in a PSP
case. Scale in E is equivalent for C and D.
222 A B
20μm C DE
15μm Quantitation of the density of parkin-immunoreactive microglia in each region of interest confirmed these findings revealing significant differences between controls, PD, PSP and MSA cases in the SN (p=0.01), putamen (p<0.01) and pons (p<0.001) (Table 7.2). In controls, the SN contained 143 95/mm2 parkin- immunoreactive microglia, 31 36/mm2 in the putamen and none in the pons
(Table 7.2). This is consistent with previous studies showing that the SN has the highest densities of activated microglia in the normal ageing brain (Beach et al.,
2007; Sugama et al., 2003). As may have been expected from the HLA-DR results above and the identification of parkin immunoreactivity mainly in non- phagocytic microglia, the pattern of parkin expression differed between disease groups. The greatest increase in microglial parkin expression was observed in the pons with a >20-fold increase in expression compared with controls (Table
7.2). This increase in expression was more marked in MSA (>100-fold increase) compared with PD and PSP (p=0.01, Table 7.2), as observed for the non- phagocytic HLA-DR-immunoreactive microglia (see above). A 10-fold increase in the expression of parkin in microglia was observed in the putamen in all groups compared with controls (Table 7.2), while in the SN, there was only a two-fold increase in the microglial expression of parkin in PD and PSP but not in
MSA (p<0.01, Table 7.2). This result in the SN is consistent with the predominant phagocytic microglia found in this region in all disease groups
(Table 7.1). Overall, this data confirms the type of microglia containing parkin immunoreactivity (mainly non-phagocytic) and their distribution (mainly in the pons) as demonstrated using HLA-DR immunostaining (see above).
223 Table 7.2 Mean and standard deviations of parkin-immunoreactive structures
(per mm2) in controls, PD, PSP and MSA
Regions Controls PD PSP MSA
SN 143 95 245 59* 327 193* 198 103
Putamen 31 36 300 192* 300 192* 285 167*
Pons 0 0 19 13* 42 78* 106 98*
* significantly different from controls (p<0.05)
PD= Parkinson’s disease, PSP= progressive supranuclear palsy, MSA= multiple system atrophy, SN= substantia nigra.
As expected from the analyses above, the severity of parkin-immunoreactive microglia did not correlate with disease duration. However, logistic regression analyses suggested a trend associating increasing densities of parkin- immunoreactive microglia in the pons with a cerebellar clinical phenotype
(p=0.09), similar to the association observed with HLA-DR-immunoreactive microglia.
7.4 DISCUSSION
The present study confirms that microglial activation is robust within the SN and regions of severe pathology in all parkinsonian disorders (Gerhard et al., 2003;
Ishizawa et al., 2004; Mosley et al., 2006; Ouchi et al., 2005; Stefanova et al.,
2007). To determine the relationship between this activation and the degenerative changes observed, the morphological phenotype of the microglia
224 was assessed (phagocytic versus non-phagocytic). This is the first study to assess the type of microglia activation in association with clinical, cellular and pathological parameters across these parkinsonian disorders. Novel data is presented showing that parkin is one of the proteins expressed following microglia activation, although it is rarely present in phagocytic microglia, supportive of a role for this protein in neuroprotection by microglia.
Resting microglia has a ramified morphology that changes within hours of activation by an extracellular stimulus (Kreutzberg, 1996; Raivich et al., 1999).
The activation of microglia occurs in a morphologically stereotypic and graded fashion that can be differentiated into several stages (Gehrmann et al., 1995).
The first step of activation involves swelling of the cell body and retraction of ramified processes that appear shorter and stouter (Graeber et al., 1988; Streit and Kreutzberg, 1987). These activated microglia express a number of receptors, including HLA-DR (Graeber et al., 1988; Streit et al., 1989a; Streit et al., 1989b). This stage is considered a state of alertness with appropriate reactivity to cope with a change in tissue homeostasis. If the activating stimulus does not disappear, two important signalling principals organise further microglial responses (Hanisch and Kettenmann, 2007). The sudden appearance of factors, (such as neuronal distress or protein aggregation) are sensed by specific receptors and trigger a response (“on” signals). However, there are also constitutive signalling mechanisms with calming influences on microglia (“off” signals). These stimuli compete for the dominating influence over microglial
225 actions that can be neurotoxic (phagocytic) or neuroprotective (non-phagocytic)
(Biber et al., 2007).
The further transformation of activated microglia into phagocytes can occur through either an increase in on signalling or a loss of “off” signalling (Hanisch and Kettenmann, 2007). Morphologically phagocytic microglia transform into a tissue macrophage phenotype with a rod- or amoeboid-like appearance lacking ramified-type processes (Brierley and Brown, 1982; Streit and Kreutzberg,
1988). These phagocytic microglia increase the range of receptor expression further and can stimulate adaptive immune mechanisms (Graeber et al., 1990;
Kreutzberg, 1996; Sasaki et al., 2008; Streit et al., 1989a; Thomas et al., 1994).
In all disorders, the SN was dominated by phagocytic microglia. Such phagocytic microglia in the SN have been previously well documented in all parkinsonian disorders (see chapter 7 Introduction). In PD, phagocytic microglia have been shown to target dopaminergic neurons (Imamura et al., 2003;
McGeer et al., 1988; Mirza et al., 2000), and in the present study decreasing densities of phagocytes in the SN related to an increase in the Braak stage of
PD. This supports a direct role for phagocytic microglia in the slowly progressive dopaminergic cell loss observed in PD (Cho et al., 2006; Cho et al., 2003; Choi et al., 2003; Croisier et al., 2005; Su et al., 2007). The density of SN phagocytes in PD also correlated with the numbers of PACRG-immunoreactive protoplasmic astrocytes in the putamen, cells that abnormally contain non-fibrillar -synuclein
226 (refer to chapter 5). This suggests a direct association between ongoing SN cell loss and the loss of putaminal protoplasmic astrocytes over time in PD. L-dopa responsiveness was shown to correlate with the densities of this type of astrocyte in the putamen in PD (refer to chapter 5), suggesting a relationship between nigral cell loss and these factors over time. Previous toxin-induced animal studies of PD have shown a close association between striatal astrocyte activation and dopaminergic cell loss (Kato et al., 2004; Kurosaki et al., 2002;
Muramatsu et al., 2003; Watanabe et al., 2008), also consistent with such an association. Although speculative, the non-fibrillar -synuclein that abnormally accumulates in these astrocytes in PD could contribute to their demise, as cell culture studies show that higher levels of astrocytic -synuclein increases their susceptibility to oxidative stress and induces apoptosis (Stefanova et al., 2002;
Stefanova et al., 2001; Stefanova et al., 2003). This is consistent with a slow toxic astrocytic cell death in the PD putamen, not driven by phagocytic microglia in this region.
In MSA, the density of phagocytes in the SN correlated with the density of putaminal GCI, the two sites previously identified as most vulnerable in this disease (Ozawa et al., 2004). Cell loss in MSA is known to be greatest in the SN compared with other brain regions, and does not correlate with the generally milder numbers of GCI found in the SN (Ozawa et al., 2004). Previous detailed studies have suggested that neuronal loss in the SN is rapid and independent of
GCI in MSA (Ishizawa et al., 2008; Ozawa et al., 2004), consistent with the
227 greater numbers of phagocytic microglia observed in this region in MSA. Similar to PD, the density of SN phagocytes in MSA also correlated with the numbers of
PACRG-immunoreactive protoplasmic astrocytes in the putamen. However, in
MSA no -synuclein immunoreactivity was observed in these astrocytes (refer to chapter 5) but rather -synuclein abnormally accumulates in nearby oligodendroglia. MBP is necessary for the assembly of myelin, whereby a reduction in MBP, as seen in MSA (refer to chapter 6), leads to changes in plasma membrane lipids and an increase in lipid-raft endocytosis reducing myelination (Simons and Trotter, 2007). -Synuclein avidly binds to negatively charged membranes and lipid rafts (Lucke et al., 2006; Madine et al., 2006) and could enter oligodendroglia through this mechanism. Protoplasmic astrocytes are functionally coupled to oligodendroglia by specific gap junctions formed by the astrocytic connexins (26 or 30) and the oligodendroglial connexin-32
(Altevogt and Paul, 2004) that facilitate direct cytoplasmic communication and allow the transfer of small molecules involved in cell signalling and metabolism
(Kielian, 2008). -Synuclein directly interacts with connexin-32 to reduce gap junction signalling (Sung et al., 2007), whereas reduced astrocytic -synuclein increases gap junctions by docosahexaenoic acid incorporation (Golovko et al.,
2007) and reducing fatty acids and phospholipids (Castagnet et al., 2005) in the plasma membrane. An active reduction in astrocytic -synuclein may occur in
MSA as compared with PD, in order to metabolically assist oligodendroglia with reduced MBP.
228 In PSP, increases in phagocytic microglia were more coordinated across regions. Cases with high densities of phagocytic microglia in the SN also had high densities in the putamen but low densities in the pons. In addition to the similar association with SN dopaminergic cell loss to that observed for PD and
MSA, there is a separate association between more marked astrogliosis in the
SN and putamen in PSP (refer to chapter 5), a finding that could be related to more phagocytic microglia observed in these regions. There was a robust clinical association with increased phagocytes in the pons in both PSP and MSA and a cerebellar/RS phenotype, consistent with previous findings (Yokoyama et al., 2007).
The commonality of phagocytic cell loss in the SN across PD, MSA and PSP suggests potentially similar underlying mechanisms that precipitate different glial responses in associated regions depending on other factors. Similar selective phagocytic activation of microglia in the SN occurs following toxin-administration in monkey and other animal studies that cause SN degeneration without inclusion formation (Barcia et al., 2004; McGeer et al., 2003). As most toxin- induced models of SN degeneration occur via mitochondrial poisoning (Cochiolo et al., 2000; Mandavilli et al., 2000; Przedborski and Jackson-Lewis, 1998;
Storch et al., 2004), environmental factors or mitochondrial susceptibility may be important in all these parkinsonian disorders, as indicated in PD (Schapira,
2006; Sherer et al., 2002; Yamashita and Matsumoto, 2007). Varying genetic susceptibilities may then influence the propagation of other cellular pathologies
(eg. tau polymorphisms in PSP, (Albers and Augood, 2001)). 229
Unexpectedly, protein inclusion formation in all disease groups related to an increase in non-phagocytic microglia, particularly in areas with limited neuronal loss, but also in areas with measured tissue loss in MSA. This suggests a prominent non-phagocytic microglial activation in response to abnormal protein inclusions, rather than the transformation into tissue phagocytes. Experimentally induced -synuclein-mediated microglial activation is thought to contribute to the disease pathogenesis (Croisier et al., 2005; Stefanova et al., 2003; Su et al.,
2007), as is experimentally induced tau-mediated microglial activation (Sasaki et al., 2008). In the present study, not only were the morphology of microglial associated with protein deposition not phagocytic, but they also expressed parkin protein. This study is the first report of parkin expression in microglial cells. The presence of parkin in activated microglia may be due to their need to upregulate cytoskeletal proteins such as tubulin, as cytoskeletal proteins are key proteins involved in their morphological change (Abd-El-Basset et al., 2004). As discussed in chapter 5, parkin can bind and interact with tubulin (Ikeda, 2008), with parkin mutants unable to ubiquitinate or degrade tubulin (Ren et al., 2003).
This suggests that cellular signals leading to this more ramified type of non- phagocytic microglial activation may rely on increased tubulin that, in turn, elicits parkin upregulation in effort to stabilise their more elaborate cytoskeleton.
In addition to its potential role in stabilising tubulin, increased parkin would enhance the ubiquitination and degradation of misfolded proteins (Feany and
230 Pallanck, 2003; Ren et al., 2003; Wang et al., 2005) and in this way may contribute to neuroprotection. In particular, a loss of parkin function relates directly to substantial neuronal vulnerability (Feany and Pallanck, 2003; Kitao et al., 2007; Paterna et al., 2007; Wang et al., 2005) and parkin knock-out models show an increase in microglial activation (Serrano et al., 2005; Solano et al.,
2008). Several recent studies suggest that protein aggregates are cleared by microglia (Bellucci et al., 2004; Lee et al., 2008; Yoshiyama et al., 2007) and that in models overexpressing either -synuclein (Junn and Mouradian, 2002;
Orth et al., 2004; Tabrizi et al., 2000) or tau (Klein et al., 2006; Klein et al.,
2005), the suppression of parkin expression enhances nigrostriatal cell death.
The present study would suggest that a loss of the ability of microglia to upregulate parkin may contribute to such increased susceptibility to degeneration.
7.4.1 Conclusions
This study is the first to comparatively assess HLA-DR-activated non-phagocytic and phagocytic microglia in PD, MSA and PSP and determine their relationships to different pathological indices. In all parkinsonian disorders, phagocytic microglia concentrated in the SN where their numbers related to the degree of neuronal degeneration. The densities of non-phagocytic microglia related to the degree of abnormal protein inclusion formation, and were most prominent in cases with a cerebellar/RS phenotype. These non-phagocytic microglia contained parkin immunoreactivity, a protein not previously associated with
231 microglial activation. The expression of parkin in these activated, but not ramified, microglia could relate to an increase in tubulin stability associated with this morphological phenotype, as well as to an increase in protein clearance through the proteasomal system of these cells. Overall, this study confirms the microglial targeting of SN neurons across these disorders, and suggests that parkin may play a significant role in neuroprotection through microglial protein clearance.
232
Chapter 8: Discussion
The main aim of this thesis was to identify overlapping and differentiating regional glial changes in patients with typical PD and the atypical parkinsonian syndromes PSP and MSA. Despite clear differences in the inclusion pathologies observed between these disorders, there is substantial overlap in clinical features (refer to chapter 1) that may be due to early glial changes occurring in overlapping regions/pathways in these disorders. To address this, correlations between the severity of glial changes and clinical features were performed. The data confirm there is substantive glial pathology in PD, PSP and MSA with a number of these changes clearly associated with core clinical and pathological features. Perhaps surprisingly, the assessment of proteins associated with genetic forms of PD were found to concentrate in glia and were upregulated in different types of glia in the different disorders investigated. This data in particular, suggest that glia play a significant role in the propagation of PD, PSP and MSA.
Initially, to assess the relationships between glial changes and the severity of pathology in PD, MSA and PSP, all cases were pathologically staged (refer to chapters 3 and 4). As described in chapters 1 and 3, pathological staging schemes have previously been established to grade the progression of
233 pathology in PD (Braak et al., 2003; Braak et al., 2004) and MSA (Jellinger et al., 2005), however, currently there is no overall staging scheme to grade the severity of pathology in PSP. Previous assessment of tau deposition have been used to differentiate clinical subtypes (Ahmed et al., 2008; Williams et al.,
2007a), however, the progression of the more common degenerative changes used to pathologically diagnose PSP has not been previously assessed. As described in chapter 3, a novel pathological staging scheme for PSP was devised by implementing various dominant pathological features in core and ancillary regions involved in PSP.
The clinicopathological characterisation of PD, PSP and MSA cases revealed overlapping and distinct clinical and pathological features in these disorders. A recent study has compared the onset of clinical features, between PSP and
MSA, and also compared between PSP-P versus PSP-RS and MSA without early autonomic failure versus MSA with early autonomic failure (O'Sullivan et al., 2008). This previous study differed to the current study (refer to chapter 4), focusing on the onset of dominant clinical features. The classification of MSA subtypes also differed, as cases were not divided into a parkinsonian or cerebellar phenotype, and typical PD cases were not included as a comparative cohort. As described in chapter 4, the current study also comparatively assessed the pathological indices across typical and atypical parkinsonian disorders for the first time, in particular correlating these pathologies with each other and clinical features and phenotypes. Despite differences in core inclusion pathologies, degeneration of the SN was a consistently observed feature of PD, 234 PSP and MSA, regardless of clinical subtype. As discussed previously, this may be due to more common factors, as the same phagocytic microglial reaction is found in this region in all these disorders. As expected, patients with all parkinsonian phenotypes had L-dopa responsiveness. This was associated with a preservation of pallidal volume, a region targeted for degeneration in the cerebellar phenotypes. In contrast, cases with cerebellar/RS phenotypes had greater midbrain atrophy compared with parkinsonian phenotypes, confirming the targeting of additional non-dopaminergic cell populations in and around the midbrain in such cohorts (Minnerop et al., 2007; Murphy et al., 2008; Oyanagi et al., 2001). Pathologically, the severity of -synuclein inclusion formation in both
PD and MSA was related between different regions, as may have been expected, based on the pathological staging of these disorders (Braak et al.,
2003; Braak et al., 2004; Jellinger et al., 2005). The neuronal deposition of - synuclein in LB appeared more benign compared with its deposition in GCI, as on average PD cases had a significantly prolonged disease course compared with MSA cases. The glial deposition of tau appeared similar in toxicity to the glial deposition of -synuclein, with PSP cases having a similar time course to that observed for MSA.
The studies performed in this thesis revealed that distinct glial reactions are related to particular disorders. These reactions can be considered as related to neurodegeneration and tissue destruction, or associated with a reactive change that is not destructive. In PD, the glial changes observed were either directly
235 related to the primary loss of neurons in the SN (increased SN phagocytes and decreased putaminal protoplasmic astrocytes) or a reaction to abnormal neuronal inclusion formation (abnormal -synuclein immunoreactivity in protoplasmic astrocytes and an increase in non-phagocytic microglia).
Substantive tissue destruction was largely limited to the SN in PD, despite more widespread neuronal -synuclein deposition, supporting previous descriptions of an unusual and targeted glial response in this disease (Mirza et al., 2000). This is also consistent with in vivo imaging studies demonstrating that SN (and not striatal or thalamic) microglial activation directly relates to the progressive degeneration of PD (Ouchi et al., 2005). The more widespread microglial activation in the pons, basal ganglia, and neocortices is relatively static over time in PD (Gerhard et al., 2006), consistent with the non-destructive and non- progressive microglial reaction observed in the present study. The current findings show relationships between abnormal neuronal inclusion formation and the astrocytic accumulation of -synuclein. Interestingly, L-dopa responsiveness was found to correlate with greater densities of putaminal protoplasmic astrocytes. Previous experiments show that astrocytes serve as temporary storage for L-dopa through the active uptake through L-type amino acid transporters, regulated by intracellular calcium or 3’-5’-cyclic adenosine monophosphate (cAMP) (increases cellular accumulation) and cyclic guanosine monophosphate (cGMP) (decreases cellular accumulation) (Sampaio-Maia et al., 2001). In addition, astrocytes also synthesise dopamine (Tsai and Lee,
1996). Losing further capacity to endogenously produce dopamine in the
236 putamen through a loss of these protoplasmic astrocytes is likely to impact on L- dopa responsiveness in PD. Overall, these data indicate that early therapeutic targeting of phagocytic SN microglia, and the reduction of putaminal protoplasmic astrocytes during the symptomatic phase, may minimise the clinical severity and neurodegeneration observed in PD.
In MSA, the glial changes observed were either directly related to the primary loss of neurons in the SN (increased SN phagocytes and decreased putaminal
GCI and oligodendroglia, and protoplasmic astrocytes) or a reaction to GCI
(reactive fibrous astrocytes, non-phagocytic microglial activation, and a slow degeneration of small-fiber myelinating oligodendroglia due to myelin abnormalities). MSA differed significantly from the other parkinsonian disorders in the targeted destruction of oligodendroglia, as previously shown (Dickson et al., 1999b; Higuchi et al., 2005; Shults et al., 2005; Yazawa et al., 2005).
However, MSA did not differ from PD and PSP in the targeting of SN degeneration. This early selective targeting of the SN through a different process has been previously highlighted in MSA (Ozawa et al., 2004), although few studies have provided further information on this process. This thesis shows that similar regional glial cell types are involved early in both PD and MSA, however there were significant differences in the glial reactions observed. In
MSA there is a lack of astrocytic -synuclein accumulation, and this different astrocytic reaction is associated with an accumulation of -synuclein in GCI.
The targeting of the SN and putaminal glia, early in MSA has not been
237 previously assessed, but now warrants further study. Surprisingly, a slower destructive process appears to emanate from these into connected regions, possibly dispersed through the glial syncytium (protoplasmic astrocytes and related oligodendroglial changes) and involving the early degradation of myelin prior to GCI formation. This may provoke the reactivity of fibrous astrocytes that support myelinating oligodendroglia, and the activation of non-phagocytic microglia. An association between microglial activation and -synuclein- immunoreactive GCI has been previously identified (Gerhard et al., 2003;
Ishizawa et al., 2004). Although the present thesis shows that this microglial activation is not phagocytic in nature as has been assumed. Overall these data indicate that therapeutic targeting of phagocytic SN microglia, putaminal oligodendroglia and protoplasmic astrocytes early, and the reduction of small- fiber myelinating oligodendroglia during the symptomatic phase, may limit the clinical severity and neurodegeneration observed in MSA.
The use of oligodendroglial pathologies in differentiating clinical subtypes in PSP
(Williams et al., 2007a) and MSA (Jellinger et al., 2005), and the overlap in region assessment, suggested some common underlying oligodendroglial changes in these disorders. Therefore, it was hypothesised that oligodendroglial dysfunction occurs early in MSA and/or in the parkinsonian phenotypes of MSA and PSP. However, no relationships were observed between the severity of oligodendroglial pathologies and clinical subtype. The GCI of MSA contained many of the constituent oligodendroglial and myelin proteins, including p25,
238 degraded MBP and ApoD, and abnormally accumulated PACRG and parkin immunoreactivity in addition to -synuclein. This is the first study to identify
PACRG and parkin in GCI of MSA.
In PSP, the glial changes observed were either directly related to the primary loss of neurons in the SN (increased SN and putaminal phagocytes, increased
SN and putaminal astrogliosis) or a reaction to abnormal neuronal inclusion formation (non-phagocytic microglial activation and CB in oligodendroglia). In contrast to PD and MSA, whereby phagocytes are relatively restricted to the SN and there is a decrease in putaminal astrocytes, the reactive glial changes observed in the SN and putamen in PSP are more similar to those observed in toxin models of PD (Kato et al., 2004; Kurosaki et al., 2002; Muramatsu et al.,
2003; Watanabe et al., 2008). Toxin models have an early increase in striatal and nigral astrogliosis associated with nigral loss (Kato et al., 2004; McGeer and
McGeer, 2008; Muramatsu et al., 2003) as well as a widespread reactive astrogliosis that includes the cortex and hippocampus (Chen et al., 2005;
Luellen et al., 2003). In fact rotenone-treatment triggers a cerebral tauopathy in rats, reflecting PSP-like pathology with increased tau-immunoreactive astrogliosis (Hoglinger et al., 2005). These similarities may suggest the involvement of toxins in the etiology of PSP. Environmental toxins, such as acetogenins, rotenone and neurotropic viruses, cause similar parkinsonian tau depositing conditions in humans (Caparros-Lefebvre and Lees, 2005; Lees,
2003), with toxic metabolites recently shown to significantly increase
239 cytoskeletal gene expression (Vahidnia et al., 2007). The findings of this thesis show that PSP was unique in the type of reactive astrogliosis in that the disease process induced parkin expression. In addition to the H1 haplotype of the tau gene predisposing to PSP, the V380L polymorphism of the parkin gene has a similar independent increased risk for PSP (Ros et al., 2008). This polymorphism is predicted to modify the binding of parkin to tubulin and alter the stability of the microtubule system (Ros et al., 2008). As previously discussed, parkin aids in proteasomal protein degradation and stabilising of misfolded proteins on microtubules (Yang et al., 2005) and parkin mutants are unable to ubiquitinate or degrade tubulin (Ren et al., 2003). Therefore, the reactive glial changes observed in PSP could be explained by a combination of parkin polymorphisms that affect microtubule stability and an insult (potentially a toxin) that requires a robust glial reaction with stable microtubules. This theory could explain many of the pathological features of PSP, including the abnormal microtubules in oligodendroglial CB (Arima et al., 1992). PSP is primarily related to microtubule instability in many cell types, as indicated by the correlations between many of the pathologies in this disease (tau-immunoreactive CB related to increasing NFT and PACRG-immunoreactive astrocytes and astrogliosis, in turn associated with increasing phagocytic microglia). Overall, these data suggest that the therapeutic targeting of parkin in PSP may provide substantial benefits to what appears to be a more global vulnerability to stress- related processes that require the stability of microtubules.
240 One hypothesis tested was that astrogliosis occurs early in PSP and/or in the cerebellar/RS phenotypes of PSP and MSA. This was based on previous findings associating the deposition of tau-immunoreactive TA with the degenerative changes of PSP (Togo and Dickson, 2002). The colocalisation studies performed in this thesis (refer to chapter 5) could not identify activated
GFAP-immunoreactive astrocytes as those with tufted morphologies, but instead identified PACRG as a novel protoplasmic astrocytic protein. A proportion of these PACRG/GFAP-immunoreactive protoplasmic astrocytes also contained tau immunoreactivity, whereas TA were found to be tau-immunoreactive but
GFAP/PACRG-negative. While the reactive astrogliosis was very prominent in
PSP, it was not associated with considerable astrocytic tau accumulation. As described above, these upregulated PACRG/GFAP-immunoreactive protoplasmic astrocytes also expressed parkin. This is the first study to identify these changes. There was no association between the severity of these changes and a cerebellar clinical phenotype, although these astrocytic changes did correlate with the severity of tau pathology in PSP. Such a robust reactive astrogliosis to the surrounding tau deposition suggests that astrocytic parkin expression is a reactive neuroprotective response to PSP.
Overall, the studies in this thesis have identified novel and distinct glial abnormalities across these clinically overlapping disorders. Parkin expression was commonly associated with neuroprotective responses in both astrocytes in
PSP and in microglia in PD, PSP and MSA. Parkin is thought to confer protection to neurons against a wide range of cellular insults (Darios et al., 2003; 241 Jiang et al., 2004) including -synuclein toxicity (Petrucelli et al., 2002) and tau accumulation (Klein et al., 2006; Menendez et al., 2006). The role of parkin in non-neuronal cells has not been emphasised previously. In the current studies
(refer to chapters 5 and 7), parkin expression occurred in reactive glial cells requiring cytoskeletal stability (non-phagocytic activated microglia in all disorders and astrocytes in PSP) was a consistent observation. The greatest variability between parkinsonian disorders was the striking astrocytic responses
– a fibrous astrogliosis and limited protoplasmic astrocytic response due to astrocytic degeneration in MSA, the astrocytic accumulation of -synuclein in protoplasmic astrocytes in PD, and the reactive expression of parkin in protoplasmic astrocytes in PSP. Developing a better understanding of the reasons for such varied astrocytic responses is likely to be highly informative for these disorders.
In summary, the investigation of glial abnormalities across PD, PSP and MSA has revealed diverse glial responses related to specific disease processes. As described in chapter 5, this study identified PACRG as a novel constituent protein found in protoplasmic astrocytes. The upregulation of PACRG and expression of parkin in these protoplasmic astrocytes were identified in response to PSP. This astrocytic change was only observed in PSP and correlated with PSP-associated clinical symptoms. As shown in chapter 6, the study of pathological changes in oligodendroglia revealed a novel, early and specific oligodendroglial abnormality in MSA. The relocalisation of p25 from the
242 myelin to expanding oligodendroglial cell bodies in conjunction with the degradation of MBP was observed, prior to the development of -synuclein- immunoreactive GCI. In contrast to the pathological changes in astrocytes and oligodendroglia, widespread microglial activation was common across all disorders, as previously described (Gerhard et al., 2003), although no previous studies have assessed changes related to non-phagocytic versus phagocytic microglia in PD, PSP or MSA. As described in chapter 7, the SN was a region with prominent phagocytic microglia across all disorders, whereas activated but non-phagocytic microglia were associated with the severity of the dominant protein inclusions in each disorder, being most severe in cerebellar/RS phenotypes. In addition, this study revealed for the first time that non-phagocytic microglia express parkin immunoreactivity possibly to assist with cellular stability for a neuroprotective function. The studies in this thesis show that the glial changes observed in these parkinsonian disorders either exacerbate or protect against the neurodegenerative processes, and that they are initiated at the very earliest disease stages. Further studies to understand the types of interactions between affected glia and neurons are now warranted.
243
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