Gene Expression Analysis and Genetic Studies in Multiple Sclerosis
Author Tajouri, Lotfi
Published 2005
Thesis Type Thesis (PhD Doctorate)
School School of Health Sciences
DOI https://doi.org/10.25904/1912/3873
Copyright Statement The author owns the copyright in this thesis, unless stated otherwise.
Downloaded from http://hdl.handle.net/10072/366467
Griffith Research Online https://research-repository.griffith.edu.au
GENE EXPRESSION ANALYSIS AND GENETIC STUDIES IN MULTIPLE
SCLEROSIS
By Lotfi Tajouri Bsc, Master of Cellular Physiology
A Thesis submitted as a fulfilment for the degree of Doctor of Philosophy in the School of Health Science, Griffith University, Gold Coast, Queensland. AUSTRALIA. August 2004
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ABSTRACT
Multiple Sclerosis (MS) is a neurodegenerative disease of the central nervous system
(CNS). As part of this disorder the myelin sheath undergoes degeneration, leading to alterations in the conductivity of axons, and impaired function. The onset of the disease occurs in young adults and clinical pathology is characterised by varying severity. These include i) Relapsing Remitting MS (RR-MS), ii) Secondary Progressive MS (SP-MS) and iii) Primary Progressive MS (PP-MS). MS is more prevalent in women and accounts for more than two thirds of all MS sufferers.
MS is considered to be a multifactorial disorder with both genetic and environmental components. The prevalence of MS is dependent on geographical localisation, with lower sunlight exposure linked to higher prevalence. Also, studies show an increased risk in close relatives, or in identical twins, indicating a significant genetic component to the disorder.
There are a number of genes that may plausibly be involved in MS pathophysiology. These include myelin-related genes, such as the myelin basic protein (MBP), immune-related genes, such FCγ receptor and osteopontin, and heat shock proteins such as αβ crystallin.
These candidate genes have been implicated in a variety of ways but usually through immunological and/or genetic studies. One of the most consistent findings in recent years has been the association of disease with alterations in the specific major histocompatibility complex (MHC) localised to chromosome 6p21.3, and includes MHC I, II, III.
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Genome wide screens have permitted the identification of loci in the genome, which are associated with MS susceptibility. The number of genes involved in MS is unknown and several case-control association studies have been undertaken to reveal the involvement of potential candidate genes. In general terms, current research is aimed at determining allelic variation of candidate genes. Such genes have been implicated in MS because they reside within susceptible regions of the chromosome associated with MS or they have a plausible potential pathophysiological role in MS.
Candidate loci investigated in this study, for association with MS susceptibility, include members of the nitric oxide synthase family of metabolic proteins (inducible NOS, iNOS/NOS2A and neuronal NOS, nNOS), methylenetetrahydrofolate reductase (MTHFR), catechol-O-methyl transferase (COMT), and vitamin D receptor (VDR). The MS population used in all studies consisted of over 100 MS cases and gender, age and ethnicity matched controls.
In our study of inducible and neuronal NOS genes, PCR based assays were developed to amplify a region of both promoters that contained known microsatellite variation.
Supporting phyisological data suggests that the neuroinflammatory aspects of MS are associated with aberrant NO production, which may be due to aberrant regulation of NOS activity. Specific amplified products were identified by fluorescent capillary electrophoresis and allele frequencies were statistically compared using chi-squared analysis. In the nNOS and iNOS study, no association was identified with allele frequency variation and MS susceptibility (nNOS: χ2=5.63, P=0.962; iNOS: χ2=3.4; P=0.082).
Similarly, no differences in allele frequencies were observed for gender or clinical course for both markers (Pvalue>0.05). In short, results from this study indicate that the NOS Tajouri Page 3 1/11/2006 promoter variations studied do not play a significant role in determining susceptibility to
MS in the tested population.
The COMT and MTHFR genes are localised at 22q12-13 and 1p36.3 respectively, regions of the genome that have been found to be positively associated with MS susceptibility. In
th our research, we set out to examine the G158A change in the 4 exon of the COMT gene.
This functional mutation leads to an amino acid change (valine to methionine) that is directly associated with changes in the activity of COMT. The MTHFR enzyme plays a role in folate metabolism, and can be implicated in the turnover of homocysteine. Previous investigations have shown that high levels of homocysteine are encountered in MS patients, where it is also linked to demyelination in the CNS. In our study the aim was to examine the C677T variation (alanine to valine amino acid change) in the exon 4 coding region of the
MTHFR gene and the G158A variation in the COMT gene. Restriction fragment length polymorphism (RFLP) analysis and gel electrophoresis was used to identify specific alleles for both COMT and MTHFR. However, as with the NOS study, no specific association was identified between MS susceptibility and variation for either of the tested COMT or
MTHFR (Pvalue>0.05) variants.
In a final genomic investigation of the MS population, three variations in the VDR gene were analysed for association with MS susceptibility and pathology. Using RFLP analysis, three VDR variants were investigated with genotypes detected using the Taq I, Apa I and
Fok I restriction enzymes. In contrast to previous genotypic analyses, this study did show a positive association, specifically between the functional variation in exon 9 of the VDR gene and MS (Taq I, χ2= 7.22, P= 0.0072). Interestingly, the Apa I variant of VDR was
Tajouri Page 4 1/11/2006 also found to be associated with MS (χ2=4.2, P=0.04). The Taq I and Apa I variants were also found to be in very strong and significant linkage disequilibrium (D’=0.96, Pvalue <
0.0001) and their associations were more prominent with the progressive forms of MS (SP–
MS and PP–MS).
In addition to genotypic analysis of a clinical population, additional research was undertaken to identify novel targets for MS susceptibility studies. Global gene expression analysis was undertaken using comparative subtractive fluorescent microarray technology to examine differences in gene activity (expression) in age and sex matched MS plaque tissue and anatomically matched normal white matter (NWM). MS plaques were obtained post mortem from MS sufferers with no drug history in the last two months before death and matched anatomically to healthy white matter from donors with no previous neurological disorders. Target arrays consisted of 5000 cDNAs and analysis was conducted using the Affymetrix 428 scanner. In this way, 139 genes were shown to be differentially regulated in MS plaque tissue compared to NWM. Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated
(Pvalue<0.0001, ρ=0.73); while 70 transcripts were uniquely differentially expressed (≥1.5- fold) in either acute or chronic active lesions.
To validate the gene expression profile results, quantitative real time reverse transcriptase
(RT) PCR (Q-PCR) analysis was performed. 12 genes were selected because they were shown to be differentially expressed by array analysis in this study, or because of their involvement in MS pathology. These included transferrin (TF), superoxide dismutase 1
(SOD1), glutathione peroxidase 1 (GPX1), glutathione S-transferase pi (GSTP1), crystallin,
Tajouri Page 5 1/11/2006 alpha-B (CRYAB), phosphomannomutase 1 (PMM1), tubulin beta-5 (TBB5), inositol 1,4,5- trisphosphate 3-kinase B (ITPKB), calpain 1 (CAPNS1), osteopontin (SPP1 or OPN), as well as the signal transducer and activator of transcription 1 (STAT1) and protein inhibitor of activated STAT1 (PIAS1). Both absolute (copy number) and comparative differences in the relative levels of expression in MS lesions and NWM were determined for each gene.
The results from this study revealed a significant correlation of real time PCR results with the microarray data, while a significant correlation was also found between comparative and absolute determinations of fold. As with the results of array analysis, a significant difference in gene expression patterning was identified between chronic active and acute plaque pathologies. For example, a >50-fold increase in SPP1 and ITPKB levels in acute plaques contrasted with the 5-fold or less increase in chronic active plaques (P<0.0.1, unpaired t-Test). Of particular note, gamma-amino butyric acid receptor γ2 (GABG2), integrin β5 (ITGB5), complement component 4B (C4B), parathyroid hormone receptor 1
(PTHR1) were found up-regulated in MS and glial derived neurotropic factor α2
(GDNFA2), insulin receptor (INSR), thyroid hormone receptor ZAKI4 (ZAKI4) were found down-regulated in MS. Data also revealed a decreased expression of the immune related genes STAT1 and PIAS1 in acute plaques.
In conclusion, this research used both genomic analysis and technologies in gene expression to investigate both known and novel markers of MS pathology and susceptibility. The study developed tools that may be used for further investigation of clinical pathology in MS and have provided interesting initial expression data to further investigate the genes that play a role in MS development and progression.
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STATEMENT OF ORIGINALITY
This work has not previously been submitted for a degree or diploma in any university. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made in the thesis itself.
______
Tajouri Lotfi
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TABLE OF CONTENTS
CHAPTER 1
INTRODUCTION 23
1.1 Theoretical and Methodological Background 24 1.2 Significance 28 1.3 Aims 29 1.3.1 Specific Aims 30 1.4 Research Plan 31
CHAPTER 2 CLINICAL BACKGROUND OF MULTIPLE
SCLEROSIS 33
2.1 Basic Description of Multiple Sclerosis 34 2.2 Clinical Types of Multiple Sclerosis 34 2.3 Types of MS Plaques 36 2.4 MS Clinical symptoms 37 2.5 Incidence and Possible Aetiology 38 2.6 Pathological Examination 39 2.7 Course of the Disease 40 2.8 Diagnosis and Prognosis of MS 41 2.9 Treatment 43
CHAPTER 3 GENETIC AND IMMUNOLOGICAL BACKGROUND
OF MULTIPLE SCLEROSIS 46
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3.1 Generalities 47 3.2 Genome Wide Screens in Multiple Sclerosis 47 3.3 Candidate Gene Studies in Multiple Sclerosis 48 3.3.1 Major Histocompatibility Complex (MHC) Locus on Chromosome 6p 48 3.3.2 Located at Non-MHC Chromosomal Loci 51 3.4 Immunological Mechanism Involved in MS 53 3.5 Expression Profiles in MS and EAE Mice 57 3.5.1 Expression Profiles in EAE mice 57 3.5.1.1 EAE mice Definition 57 3.5.1.2 Differential Displays and Microarray Experiments in EAE Mice 59 3.5.2 Expression Profiles in MS tissue 63 3.5.2.1 Differential Display and Microarray Experiments in MS 63
CHAPTER 4
METHODOLOGICAL APPROACH 65
4.0 Overview 66 4.1 Genetic Case-Control Association Studies 67 4.1.1 DNA Extraction 67 4.1.2 Polymerase Chain Reaction 68 4.1.3 Restriction Enzyme Polymorphism and Genescan Analysis 69 4.1.4 Analysis of Polymorphism Results 69 4.2 Gene Expression Studies 70 4.2.1 RNA Extraction 70 4.2.2 Microarray Experiments 72 4.2.3 Real Time PCR 76
CHAPTER 5 CASE-CONTROL ASSOCIATION STUDIES IN AN
MS AUSTRALIAN POPULATION 79
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5.0 Overview 80 5.1 Investigation of a Neuronal Nitric Oxide Synthase Gene (NOS1) Polymorphism in a Multiple Sclerosis Population. 80 5.1.1 Introduction 80 5.1.2 Materials and Methods 82 5.1.2.1 Subjects 82 5.1.2.2 Genotyping 82 5.1.2.3 Statistical Analyses 83 5.1.3 Results 84 5.1.4 Discussion 87 5.2 Investigation of an Inducible Nitric Oxide Synthase Gene (NOS2A) Polymorphism in a Multiple Sclerosis Population. 89 5.2.1 Introduction 89 5.2.2 Materials and Methods 91 5.2.2.1 Subjects 91 5.2.2.2 Genotyping 92 5.2.2.3 Statistical Analysis 93 5.2.3 Results 93 5.2.4 Discussion 96 5.3 Investigation of Methylenetetrahydrofolate Reductase (MTHFR) and Catechol-o-Methyl Transferase (COMT) in Multiple Sclerosis. 98 5.3.1 Introduction 98 5.3.2 Materials and Methods 101 5.3.2.1 Subjects 101 5.3.2.2 Genotyping 101 5.3.2.2.1 Genotyping of the MTHFR Gene Variant 101 5.3.2.2.2 Genotyping of the COMT Gene Variant 102 5.3.2.2.3 Statistical Analysis 105 5.3.3 Results 106 5.3.4 Discussion 109 5.4 Vitamin D Receptor Gene Variant (Taq) is a Risk Factor for Multiple Sclerosis in the Australian Population. 110 5.4.1 Introduction 110 Tajouri Page 10 1/11/2006
5.4.2 Materials and Methods 112 5.4.2.1 Subjects 112 5.4.2.2 Genotyping 113 5.4.2.3 Statistical Analysis 114 5.4.3 Results 114 5.4.4 Discussion 117
CHAPTER 6 MICROARRAY AND REAL TIME PCR EXPRESSION
STUDIES IN MULTIPLE SCLEROSIS 123
6.0 Overview 124 6.1 Quantitative and Qualitative Changes in Gene Expression Patterns Characterise the Activity of Plaques in Multiple Sclerosis. 125 6.1.1 Introduction 125 6.1.2 Material and Methods 127 6.1.2.1 Patients and Tissues 127 6.1.2.2 RNA Extraction and cDNA Synthesis 131 6.1.2.3 RNA Validation and Probe Preparation 131 6.1.2.4 Array Hybridisation 132 6.1.2.5 Q-PCR Analysis 133 6.1.2.6 Statistical Analysis 136 6.1.3 Results 136 6.1.3.1 Overview of MS Array Hybridisation and Q-PCR Validation 136 6.1.3.2 Genes Identified by Array Analysis as Differentially Regulated in both Chronic Active and Acute Plaques 142 6.1.3.2.1 Summary 144 6.1.3.2.2. Expression of Adhesion and Cytoskeletal Factors in both Chronic Active and Acute Plaques 145 6.1.3.2.3 Expression of Proliferation, Developmental and Metabolic Factors in both Chronic Active and Acute Plaques 145 Tajouri Page 11 1/11/2006
6.1.3.2.4 Expression of Immunological Factors in both Chronic Active and Acute Plaques. 146 6.1.3.2.5 Expression of Protein and Hormone Regulator Factors in both Chronic Active and Acute Plaques. 148 6.1.3.2.6 Other Transcripts Differentially Regulated in Both Chronic and Acute Plaques 148 6.1.3.3 Genes Uniquely Differentially Regulated in Chronic Active MS Plaques 149 6.1.3.4 Genes Uniquely Differentially Expressed in Acute Tissue 152 6.1.3.5 Q-PCR Validation of Array Analysis 154 6.1.4 Discussion 156 6.2 Real Time PCR: An Examination of Genes Identified as Differentially Regulated in Multiple Sclerosis Plaque Tissues, using Absolute and Comparative Real Time PCR Analysis. 164 6.2.1 Introduction 164 6.2.2 Materials and Methods 167 6.2.2.1 Tissues 167 6.2.2.2 Template Preparation for Absolute-PCR Purification and Dilution Series 167 6.2.2.3 Generation of MS Candidate Gene Standard Curves 168 6.2.2.4 Sybr Green I RealTime PCR 169 6.2.2.5 Data Analysis 170 6.2.3 Results 171 6.2.4 Conclusion and discussion 177
CHAPTER 7
GENERAL DISCUSSION 180
7.0 Overview 181
7.1 General Discussion on Genomics Case-Control Studies in MS 181
7.1.1 General discussion on Nitric Oxide Synthase 182
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7.1.2 General discussion on MTHFR gene 183
7.1.3 General Discussion on COMT 184 7.1.4 General Discussion on VDR gene 184
7.2 Discussion and Conclusion on Expression Studies in MS 187
7.2.1 Microarray Experiments Overview 187 7.2.2 Discussion on Microarray Experiments using MS Peripheral Blood Mononuclear Cells 188 7.2.3 Discussion on Microarray Experiments using MS Brain Tissues 195 7.3 Microarray Conclusions 207
7.4 General Conclusions 208
CHAPTER 8
REFERENCES 210
APPENDIX 244
Appendix I Genome Wide Screens in Multiple Sclerosis Thought to Harbour Susceptibility Chromosomal Loci 241
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LIST OF TABLES
3.5.1.1 Comparisons between Multiple Sclerosis and EAE, Clinical Pathology and Genetic 58
3.5.2.1 Summary Table of Differentially Displays and Microarray Experiments on Human MS
Brain Samples 64
5.1.3-A NOS1 Summary 85
5.1.3-B Allele Sizes and Frequencies of NOS1 Dinucleotide Polymorphism in MS Cases and Controls 86
5.2.3.A Genotype Frequencies of iNOS Insert in Australian Multiple Sclerosis Patients and Controls 94
5.2.3.B Allele Frequencies of iNOS Insert in Australian Multiple Sclerosis Patients and Controls 94
5.2.3.C Genotype Frequencies of iNOS Insert for Different Subtypes of MS in Australian Multiple
Sclerosis Patients and Controls 95
5.2.3.D Allele frequencies of iNOS Insert for Different Subtypes of MS in Australian Multiple
Sclerosis Patients and Controls 95
5.3.2.2.2.1 PCR Condition Summary for COMT Amplification 104
5.3.2.2.2.2 Master Mix for Restriction Enzyme Digest of COMT 104
5.3.3.1 Distribution of MTHFR C677T (Genotype and Allele) Frequencies in MS Case and
Control groups 108
5.3.3.2 Distribution of COMT H/L (Genotype and Allele) Frequencies in MS Case and Control groups 108
5.4.3.1 Distribution of VDR Taq I Variant (genotype and allele) Frequencies in MS
Case and Control groups 116
5.4.3.2 Distribution of VDR Apa I Variant (genotype and allele) Frequencies in MS
Case and Control Groups 116
5.4.3.3 Distribution of VDR Fok I Variant (genotype and allele) frequencies in MS
Case and Control Groups 117
6.1.1 Histopathology of MS Plaques 129
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6.1.2 Histopathology and Clinical Details of MS Tissue 130
6.1.3 Primer Sequences 135
6.1.4 Genes Identified in Both Acute and Chronic Active Plaques 142
6.1.5 Transcripts Uniquely Differentially Expressed in Chronic Active Plaques 149
6.1.6 Genes Uniquely Differentially Expressed in Acute Plaque 152
6.1.7 Comparison of the Results of Array Hybridisation and Q-PCR Analysis 154
6.1.8 Summary Gene Expression Patterns in Acute and Chronic Active Tissue 163
6.2.1 Susceptibility Loci Harbouring Candidate Genes in MS 166
6.2.2 Brief Histopathology of MS Plaques 167
6.2.3 Primer Sequences 168
6.2.4 Results of Linear Regression Analysis for Absolute Standard Curves 172
6.2.5 Q-PCR and Absolute Real Time Results. MS/Control Gene Expression Ratios
(MS 1-3: CA Plaques; MS 5,6: Acute Plaques) 175
7.2.3 Genes Altered in Expression from Different Gene Profiling Studies in MS 204-6
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LIST OF FIGURES
4.2.2 Microarray Illustration 75
5.3.3.1 COMT PCR Product in a 2% Agarose Electrophoresis Gel 106
5.3.3.2 COMT Genotyping after Nla III Digestion 106
5.4.3.A Odds Ratios for the Clinical Subtype Groups Compared to Controls; The T/t-t/t
Genotypes Combined versus T/T 117
5.4.3.B Restriction Polymorphism of VDR DNA sequence 118
6.1.3.1.α Plaque Histology 138
6.1.3.1.β Probe Preparation and Fluorescent Hybridisation Analysis 139
6.1.3.1.γ Osteopontin Real Time PCR Example 140
6.2.3.1 Picture of Comparative Analysis 173
6.2.3.2 Absolute Real Time PCR Standard Curve 174
6.2.3.3 Comparison of Comparative and Absolute Determination of Fold Difference in
Gene Expression between MS Plaque Tissue (Chronic Active/ Acute). 176
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Publications Arising from Work Described in this Thesis
-Lotfi Tajouri, Albert S. Mellick, Kevin J. Ashton, Anthony E.G. Tannenberg, Rashed M. Nagra, Wallace W. Tourtellotte, and Lyn R. Griffiths. Quantitative and qualitative changes in gene expression patterns characterise the activity of plaques in multiple sclerosis. Molecular Brain Research. 2003;119(2)170-183.
-Lotfi Tajouri, Linda Ferreira, Micky Ovcaric, Rob Curtain, Rod Lea, Peter Csurhes, Michael P. Pender and Lyn R. Griffiths. Investigation of a neuronal nitric oxide synthase gene (NOS1) polymorphism in a multiple sclerosis population. Journal of the Neurological Sciences. 2004;218(1-2):25-8.
-Lotfi Tajouri, Virginie Martin, Micky Ovcaric, Rob P. Curtain, Rod A. Lea, Peter Csurhes, Michael P. Pender and Lyn R. Griffiths. Investigation of an inducible nitric oxide synthase gene (NOS2A) polymorphism in a multiple sclerosis population. Brain Research Bulletin. 2004;64(1): 9-13.
- Lotfi Tajouri, Micky Ovcaric, Rob Curtain, Rod Lea, Mathew Johnson, Peter Csurhes, Michael P. Pender and Lyn R. Griffiths. Allelic variation in the vitamin D receptor gene is associated with multiple sclerosis in an Australian population. Neurogenetics. In press 2004.
- Lotfi Tajouri, Micky Ovcaric, Rob Curtain, Virginie Martin, Claudia Gasparini, Rod Lea, Larisa Haupt, Peter Csurhes, Michael P. Pender and Lyn R. Griffiths. Genetic investigation of Methylenetetrahydrofolate reductase (MTHFR) and Catechol-O-Methyl Transferase (COMT) in multiple sclerosis. Submitted to Brain Research Bulletin. October 2004.
-Lotfi Tajouri, Albert S. Mellick, Wallace W. Tourtellotte, Lyn R. Griffiths. An examination of genes identified as differentially regulated in MS plaque tissue, using absolute and comparative real time PCR analysis. Submitted to Brain Research Protocol. August 2004.
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Oral Presentations at Conferences
2002 Lotfi Tajouri and Lyn R. Griffiths. Microarray analyses in multiple sclerosis. Australian Health and Medical Research Congress. Melbourne Exhibition and Convention Centre, Melbourne, Victoria, AUSTRALIA. 2001 Lotfi Tajouri and Lyn R. Griffiths. Microarray in Multiple Sclerosis. Australian Society of Medical Research Conference, Gold Coast, AUSTRALIA (November). 2000 Lotfi Tajouri and Lyn R. Griffiths. Multiple sclerosis gene expression. Australian Society of Medical Research Conference, Melbourne, AUSTRALIA
Abstracts – Conference Poster Presentation
-Lyn R. Griffiths, Lotfi Tajouri, Albert S. Mellick. Microarray gene expression analyses of multiple sclerosis plaque tissue. American Journal of Human Genetics Abstract 73 (5): 1486 NOV 2003
-Lotfi Tajouri and Lyn R. Griffiths. Microarray in Multiple Sclerosis. Australian Society for Medical Research Conference, Gold Coast, AUSTRALIA (November 2001)
-Lotfi Tajouri, Tony Tannenberg, Lyn R Griffiths. Microarray in Multiple Sclerosis Lorne Conference, Melbourne, AUSTRALIA (February 2001)
-Lyn R. Griffiths, Lotfi Tajouri, Kevin J. Ashton. Microarray gene expression analysis in MS. Multiple Sclerosis Conference, Melbourne, November 2000
-Lotfi Tajouri, Tony Tannenberg and Lyn R. Griffiths. Microarray in Multiple Sclerosis. Multiple Sclerosis Conference. Melbourne, November 2000
-Lyn R. Griffiths, Lotfi Tajouri, Kevin J. Ashton. Multiple Sclerosis microarray. Australian Society for Medical Research Conference, Melbourne, AUSTRALIA (November 2000)
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-Lotfi Tajouri, Albert S. Mellick, Kevin J. Ashton, Graham Shepherd and Lyn R. Griffiths. An intron spanning system for competitive RT-PCR. Lorne Conference, Melbourne, AUSTRALIA (February 2000)
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ACKNOWLEDGMENTS
I would like to acknowledge the contribution of a number of people for their assistance in the preparation of this work. Firstly, my supervisor Prof Lyn Griffiths, Director of the
Genomics Research Centre for her patience and insight. I would like to thank Dr Albert
Mellick and Dr Kevin Ashton, for technical assistance and personal support. In addition I would like to thank members of the Genomics Research Centre, Ms Linda Ferreira, Ms
Virginie Martin, Ms Claudia Gasparini for their assistance in preparing samples for association studies. A special thank you must also be given to Dr Rod Lea, Mr Mathew
Johnson, Mr Micky Ovcaric and Mr Rob Curtain for assistance in PCR analysis and statistical analysis.
MS brain tissue used in this study was kindly donated by Professor Wallace Tourtellotte
(Director of the UCLA, USA Brain Bank) and Professor Michael Pender provided blood samples for the population studies. Special thanks must also be given to Professor Tony
Tannenberg for assistance in pathology.
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ABBREVIATIONS
A acute APCs antigen presenting cells BBB blood brain barrier B-MS benign MS Bp base pair CA chronic active CAPNS1 calpain gene cDNA complementary DNA CNP 2', 3'-cyclic nucleotide 3'-phosphodiesterase CNS central nervous system COMT cathecol-o-methyl transferase CS chronic silent CSF cerebro spinal fluid CT computed tomography DNA deoxyribonucleic acid EAE experimental allergic encephalomyelitis EDSS expanded disability status scale H20 water HLA human leucocyte antigen IgG immunoglobulin gamma IL interleukin Infβ interferon beta Infγ interferon gamma iNOS inducible nitric oxide synthase ITPKB inositol tri-phosphate kinase B LOV lovastatin MAG myelin associated glycoprotein MBP myelin basic protein
MgCl2 magnesium chloride MHC major histocompatibility complex MOG myelin oligodendrocyte glycoprotein Tajouri Page 21 1/11/2006
MRI magnetic resonance imaging MS multiple sclerosis MTHFR methyl-tetra-hydrofolate reductase NA noradrenaline NAWM normal apparent white matter nNOS neuronal nitric oxide synthase NWM normal white matter OD260 optical density at 260nm ON optic neuritis OPN osteopontin (SPP1) PBMCs peripheral blood mononuclear cells PCR polymerase chain reaction PIAS1 protein inhibitor of STAT1 PLP proteolipid protein PP-MS primary progressive MS Q-PCR quantitative polymerase chain reaction QTL quantitative trait loci RFLPs restriction fragment length polymorphisms RNA ribonucleic acid ROS reactive oxygen species RR-MS relapsing remitting MS RT-PCR real time-polymerase chain reaction SP-MS secondary progressive MS SPP1 osteopontin (OPN) STAT1 signal transducer and activator of transcription Th T heper (CD4+ T cells) VDR vitamin D receptor
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CHAPTER 1
Introduction
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1.1 Theoretical and Methodological Background
MS is a neurological debilitating disorder that affects particularly Caucasians in their second to fourth decades of their life (Weinshenker BG, 1998). MS was characterised for the first time, by Dr Jean Martin Charcot in 1868 from the hospital “Salpêtrière”, in Paris who reported the presence of multiple plaques in the central nervous system (CNS) of a deceased patient. Despite the progress of research in the last 150 years the aetiology of MS remains unknown.
The disorder is well documented for its neuroinflammatory course and symptoms. The disease has particular hallmarks. MS is more prevalent in women, and symptoms appear
(typically) between 20 and 40 years of age (Weinshenker BG, 1998). MS plaques appear as lesions in the normal white matter (NWM) and occasionally in the gray matter (Peterson et al., 2001). Lesions are restricted to the CNS and are not present in the peripheral nervous system (PNS). MS also has an autoimmune component, characterised by infiltration in the CNS of activated T cells that are autoreactive to myelin white matter proteins. MS is also more prevalent at higher latitudes of the globe (Hernan et al., 1999), suggesting a strong environmental influence; while disease susceptibility has a strong genetic link, as evidenced by numerous twin studies (Mumford et al., 1994).
Human and animal studies have undertaken to investigate the immunological component of
MS and revealed common inflammatory factors presenting altered expression. A summary of these findings is provided in Table 7.2.3 (page 203). To date, particular interest has been focused on the experimental allergic encephalomyelitis (EAE) mouse models. EAE mice Tajouri Page 24 1/11/2006 MS Thesis display an MS-like autoimmune pathology (Mendel et al., 1992) and are used to investigate gene functions and pathways (Espejo et al., 2002), as well as the role of particular factors in pathology and pharmacology (Paintlia et al., 2004). This research has historically been critical in identifying and confirming the function of MS susceptibility genes. However, the molecular basis of the human disease, particularly the non-immunological components, has yet to be fully explored.
In order to understand the underlying complexity of human disease, global screening approaches have been undertaken. The Human genome project, which is now complete and the identification of some 30,000 coding regions, has recently provided a strong basis for an array of studies associated with the investigation of gene activity within candidate loci for MS susceptibility (Collins et al., 2003). As many as 21 articles were published in
October 2003 in the Journal of Neuroimmunology, relating to the findings of genome wide screens in a diverse array of MS populations, including those within Europe and Australia.
These studies have contributed to the identification of chromosomal loci involved in MS susceptibility. A summary of these loci is provided in Appendix I (page 241) and such findings allow for further investigation of genes likely to play a role in MS. Of particular importance are those genome studies focused on the analysis of isolated populations (eg.
Icelandic population or the Sardinian cohort) (Jonasdottir et al., 2003; Corradu et al., 2001).
Other global screening methods have been used, such as high-throughput gene profiling technologies. These technologies have revolutionised our ability to investigate changes in gene expression and have provided clues about the presence of altered gene expression in the disease biology. Fluorescent hybridisation microarray technology has also provided
Tajouri Page 25 1/11/2006 MS Thesis large amounts of data in gene activity (Schena et al., 1998) associated with complex diseases and disease processes for which there is no simple (single) genetic cause. A clear example is in cancer research, where microarray technology has allowed the stratification of seemingly homogenous neoplasia, into a variety of pathological types which can be specifically targets for diagnosis and therapy (Alizadeh et al., 2001).
In contrast, very few genome wide studies have investigated the molecular basis of neurological disorders. This is in part because of the lack of material available, and in part, the practical limitations of existing technologies. A limited number of microarray studies are, however, now available for cross comparison in MS pathology (Table 3.5.2.1) (Becker et al., 1997; Whitney et al., 1999; Whitney et al., 2001; Lock et al., 2003, Chabas et al.,
2003; Tajouri et al., 2003; Lindberg et al., 2004). This has lead to the identification of genes that belong to chromosomal ‘hot’ spots (susceptibility loci in MS affected populations). In this way, microarray technology can be used as a complementary technical tool that allows further resolution of genetic information and variation. However, microarray experiments (or differential gene expression) studies result in large databases that make the analysis and cross-comparison problematic (Herrero et al., 2004). Further drawbacks in microarray technology can be the result of false positive findings. As a consequence, data arising from microarray should be carefully validated through the use of other means of gene expression analysis such as northern blot hybridisation or/and quantitative real time polymerase chain reaction (Q-PCR). Further confirmation of functional significance can also be obtained through localisation studies (in situ hybridisation) or through the use of animal models.
Tajouri Page 26 1/11/2006 MS Thesis One of the techniques used to validate array data is Q-PCR analysis. Q-PCR is a technique of very high sensitivity requiring the use of gene specific deoxynucleotide primers for target gene amplification. Normal PCR amplification of a gene DNA sequence is non- linear and therefore cannot be used to accurately quantitate levels of gene expression. Real time detection technology allows the researcher to examine the amount of PCR product
(proportional to fluorescence emission) in the linear phase of the PCR amplification.
Furthermore, due to the sensitivity of fluorescent dyes used in this technique and the ability to amplify a signal from very small amounts of target, Q-PCR analysis is particularly useful for: i) the analysis of genes that might be expressed below the level of detection for array analysis; or ii) to validate differential gene expression changes identified by microarray analysis (Hein et al., 2001). In MS studies, correlation of fold regulation from both microarray and real time PCR, has allowed researchers to characterise MS candidate genes
(eg. inducible Nitric oxide synthase, iNOS) (Iglesias et al., 2004). Once these candidate genes are found, further investigations can be undertaken such as case-control association studies that pinpoint eventual genetic variations (Barcellos et al., 2003). However, despite the high sensitivity of Q-PCR analysis only a small number of genes can be analysed by Q-
PCR and thus the researcher usually focusses on candidate genes that show altered expression via array analysis.
In this thesis, we have used analysis of specific genetic variations by association studies in an MS population, microarray analysis in plaque tissue, and Q-PCR analysis to identify and characterise candidate MS genes.
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1.2 Significance
MS is relatively common and very debilitating, and at present there is no suitable method of treatment to halt the disease, only ways to immunosuppress the condition (interferon therapy). To date, research on MS has been focussed on viral (Kriesel et al., 2004; Cirone et al., 2002), immunological (Kahl et al., 2002; Van Boxel-Dezaire et al., 2001) and familial genetic causes (Sadovnick et al., 2000). Genome screening studies provide the basis for further analysis of gene function and relevance to pathology, however, very few candidates show a strong association with MS disease and pathophysiology. In contrast, high throughput profiling techniques provide a relatively novel means of looking at the basic underlying problem associated with MS. MS sufferers show marked degeneration of the myelin sheath with normal apparent white matter (NAWM) surrounding the plaque. By comparing the gene expression differences in these tissues, the research presented in this thesis has, as a major aim, the identification of genes involved in the pathophysiology of the condition. The plan is to use methods in genetic analysis and association, as well as global (and specific) gene expression analysis to pinpoint genes implicated in both MS susceptibility and pathophysiology.
There are several theories as to the cause of MS in humans. These include environmental agents, viral infections, autoimmune reactions and genetic disturbances and predispositions
(Sarchielli et al., 1993). A number of studies have been performed on animal models but currently there is little published data on human tissue in situ models. Several studies with animal models targeted various classes of genes, including immunological components such as class I and class II HLA molecules, inflammatory cytokines released by different Tajouri Page 28 1/11/2006 MS Thesis populations of white blood cells and diverse compounds of the central nervous myelin white matter (Ligers et al., 2001). Other studies have focused on retroviral involvement such as Epstein Barr virus (Wandinger et al., 2000) or herpes simplex virus (Guttierez et al., 2002), proteins involved in tight junction formation (Kirk et al., 2003; Hubert et al
2001) and adhesion molecules (Elovaara et al., 2000) or dissolution and free radical effects on the myelin sheath such as reactive oxygen species (ROS) (Van der Goes et al., 1998).
The research presented in this thesis is in contrast focused on the identification and analysis of gene targets in human disease.
1.3 Aims
This research was aimed at identifying genes involved in MS susceptibility and pathology.
Candidate genes were investigated using cross-sectional association analysis and new candidates using identified using microarray screening and Q-PCR validation approaches.
The first part of the study involved the use of known genes and gene markers as well as a population of MS patient blood samples, as well as matched controls. The second part of the study involved the use of plaque tissue and NWM to examine global gene expression changes and to identify gene families, as well as metabolic pathways associated with MS pathology. The third part of the study developed methods in specific gene expression analysis (applied to plaque tissue) to investigate changes in gene activity (expression) that can be used to stratify number of patients according to underlying molecular profile.
Tajouri Page 29 1/11/2006 MS Thesis
1.3.1 Specific Aims
1. To identify iNOS/nNOS/MTHFR/COMT/VDR allelic variants in an Australian MS
population relative to an age, sex and ethnicity matched control population.
2. To develop methods for microarray cDNA analysis that can be applied to MS plaque
lesions and NWM; and to identify changes in gene expression in tissue pathology.
3. To develop methods in Q-PCR analysis for the validation of gene expression changes
identified by microarray analysis and to be used as clinical markers of MS pathology
(stratify patients according to underlying molecular biology).
The overall goal of this project was to investigate genes involved in MS. Blood samples were taken from MS sufferers that are still living, as well as control subjects, to investigate implicated susceptibility genes. Genetic case-control association studies were used to identify differences of allelic variants between an MS affected group and a non-affected control population, all Caucasian Australians. Post mortem brain material from MS sufferers, as well as non-sufferers was also used for gene expression analysis. Comparative substractive microarray hybridisation analysis was used to identify genes differentially regulated in MS. The results of this study were then validated through the use of Q-PCR analysis.
The hypotheses underlying this project are that specific gene variation and gene expression differences are involved in the aetiology and progression of MS and that an association and a microarray screening approach can be used to detect the genes implicated in this disorder.
Tajouri Page 30 1/11/2006 MS Thesis 1.4 Research Plan
1. Genotyping: Gene candidates from previously published studies were examined for
association with MS susceptibility.
2. Array analysis was used to identify novel genes associated with MS pathophysiology.
3. Novel gene targets (identified by array analysis and identified by previous studies) were
examined by Q-PCR analysis
Candidate genes associated with MS were investigated in case-control association studies using an MS Australian cohort of 104 individuals. Genomic DNA was also extracted from a control population that matches each MS individual for age, sex and ethnicity. All samples were collected in South-East Queensland, Australia. These association studies were undertaken in the laboratory using specific primers flanking functional regions within promoter regions or exons. iNOS/nNOS/MTHFR/COMT/VDR allelic variants were investigated in our Australian MS population.
In a second stage, the comparison of healthy and non-healthy tissue with a cDNA expression array system allowed the identification of genes whose altered expression may be involved in MS. Array chips that were used included 5000 genes and five MS tissues were screened for this analysis. The five MS tissues included three chronic active plaques and two acute lesions. Briefly, changes in gene expression can be measured by isolating mRNA from test samples (eg. MS individuals) and comparing expression with that of a control sample (eg. healthy individuals). This is achieved by differentially labelling each sample with fluorescent nucleotides and simultaneously hybridising resulting cDNAs to the microarray. By probing the microarray with cDNA samples from both MS and healthy Tajouri Page 31 1/11/2006 MS Thesis brains, we can develop a global picture of changes in gene expression. Gene expression profiles have been determined by microarray analysis in numerous types of cancer including stomach (Kim et al., 2003) prostate (Stamey et al., 2003) and bladder cancer
(Sanchez-Carbayo et al., 2003).
Candidate genes as identified by array, were further studied using Q-PCR analysis. In addition, potential candidates arising from the literature (suspected of involvement in MS susceptibility) were also investigated for differential gene regulation in the two plaque types. These included STAT1 and the early T cell activator gene, osteopontin.
Tajouri Page 32 1/11/2006 MS Thesis
CHAPTER 2
General Background of Multiple Sclerosis
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2.1 Basic Description of Multiple Sclerosis
MS is a serious neurological disorder affecting young Caucasian individuals, usually with age of onset at 18 to 40 years old. Females account for approximately 60% of MS cases
(Weinshenker BG et al., 1994). The CNS in MS sufferers is affected with patches of myelin degeneration resulting from multifocal inflammatory events. Myelin, which is composed of a lipid bilayer and proteins, forms the extended membrane of oligodendrocyte and insulates neurons to provide a rapid conduction of the action potential along the axons.
The cell bodies and nerve axons are generally injured in early lesions (Fergusson et al.,
1997; De Stefano et al., 2001). Progressed lesions also tend to show axon destruction, especially in the long tracts. Fibrous gliosis gives these tracts their sclerotic appearance
(and these appear as plaque lesions). Axonal loss and oligodendrocyte death lead to impaired neurological functions (Hickey et al., 1999; Trapp et al., 1999). Early and late lesions are often found simultaneously, with chemical changes in lipid and protein constituents of myelin demonstrated in the location of plaques (Holley et al., 2003). The gray matter can also be affected in MS, although this is uncommon (Kidd et al., 1999).
2.2 Clinical Types of Multiple Sclerosis
There are several forms of MS, characterised by the degree of symptomatic debilitation over time: Benign MS (B-MS), Relapsing Remitting MS (RR-MS), Secondary Progressive
(SP-MS), Progressive-Relapsing MS (PR-MS), Primary Progressive MS (PP-MS).
Tajouri Page 34 1/11/2006 MS Thesis B-MS is a condition in which individuals have an attack, but total recoveries, with no disability or further progression of the disorder.
RR-MS is characterised by relapses over time; with new symptoms appearing spontaneously, while existing symptoms increase in severity. Older symptoms may reappear or worsen. Relapses are followed by periods of remission, during which the person partially or fully recovers from the relapse. This is referred to as the remitting phase. This period of silence can sometimes be for months or years. Relapses can last for days, weeks or months; with slow, gradual or almost instantaneous recovery. The vast majority of people presenting with MS are first diagnosed with RR-MS. RR-MS accounts for 85-90% of MS cases. Sudden unpredictable attack of the disease in these patients is accompanied often by depression (Mendes et al., 2003).
In the RR-MS phase the patient may experience a few relapses merging into disease progression. Around 40% of RR-MS enter the phase of SP-MS in the 10 years and 60% in the 25 years after onset (McDonnell et al., 2002). SP-MS is characterised by worsening symptoms and no remitting phase and sufferers may experience different symptoms from mild to severe.
PR-MS shows a progressive course from onset and is punctuated by relapses. There is significant recovery immediately following a relapse, however, between relapses there is a gradual worsening of the symptoms.
PP-MS is characterised by slow onset, followed by steadily, worsening global symptoms and almost no remissions (Lublin et al., 1996; Thompson, 2004). This type of MS differs Tajouri Page 35 1/11/2006 MS Thesis from RR-MS and SP-MS in that onset is typically in the late thirties or early forties
(Cottrell et al., 1999). PP-MS is the most severe form of the disease, and accounts for 15% of MS sufferers (McDonnell et al., 2002).
2.3 Types of MS Plaques
The histological hallmark of MS is the presence of widespread lesions (plaques) throughout the CNS. Lesions (which form in the white matter) may vary in diameter from less than one millimetre to several centimetres, and are most prominent in the periventricular white matter followed by the optic nerve and chiasm, pons, the cerebellar peduncles, medulla oblongata, the spinal cord (Lassman et al., 1995). Plaques also appear in the periphery of cerebral gyri (Lumsden et al., 1970). The optic nerve is also often a target of MS resulting in demyelination (optic neuritis, ON) and temporary unilateral blindness (Ebers, 1985).
Patients with ON condition can have silent plaques residing in the brain (Jacobs et al.,
1986) and ON is often important diagnostic marker to suspect that someone will suffer MS
(Hutchinson, 1976). Plaque formation, wherever it occurs is associated with degeneration of the myelin and impaired neuronal function (the conduction and transmission of action potentials).
Plaques are classified into three main types: acute (A), chronic active (CA) and chronic silent (CS) MS lesions. Acute MS lesions are not well-demarcated (oedematous) and are filled with macrophages commonly containing myelin debris. Additionally, these lesions contain hypertrophic astrocytes but no fibrous astrogliosis with an abundance of demyelinated axons. This plaque-type is characterised by the presence of perivascular lymphocytic infiltration and damaged of the blood brain barrier (BBB) (Gay et al., 1991). Tajouri Page 36 1/11/2006 MS Thesis Chronic active MS lesions, are the second type and do contain a well-demarcated margin.
In this case the centre of the plaque is lacking in lymphocyte activity. Instead macrophages reside in a margin which contains the debris of myelin degeneration. These macrophages are microglia in origin. The centre of a CA plaque is astrogliotic, with a generally absence of myelin. However, in this case the centre of CA lesions is characterised by signs of remyelination.
In contrast to both CA and A lesions, CS MS lesions have a highly demarcated margin with a fibrous centre with no inflammatory component. Remyelination can occur in the centre and within the margin. These plaques appear circular and differ from other forms of demyelination (eg. Balo’s syndrome). Balo’s syndrome, is characterised by alternate rings of degeneration and regeneration (or intact myelin)(Moore et al., 1985).
2.4 MS Clinical Symptoms
MS results in damage to white matter and leads to neurological impairments characterised by limb weakness, sensory losses, visual alterations and other complications (Walter G et al., 1996). Demyelination in the brain and spinal cord, leads to multiple and varied neurological symptoms and signs; usually accompanied by remissions and exacerbations
(Kanda, 2003). Central nervous dysfunction, with remissions and persistent exacerbations, characterise MS. Most disability appears 10 to 15 years after diagnosis (Weinshenker et al., 1998).
Visual disturbances include partial blindness and pain in one eye (retrobulbar ON), diplopia, dimness of vision, or scotoma. Other relevant acute signs include fleeting ocular Tajouri Page 37 1/11/2006 MS Thesis palsy, transient weakness of an extremity, slight stiffness or fatigability of a limb, minor gait disturbances, difficulties with bladder control, and vertigo (Bradley et al., 1978). In some patients heat may accentuate signs and symptoms. Fatigue in MS has recently been attributed to sympathetic vasomotor dysfunction (Flachenecker et al., 2003) and from 50 to
80% of MS patients complain of fatigue (Krupp et al., 1988).
Cognitive impairment is often seen in MS and is associated with loss of memory (Ling et al., 1998). Furthermore, recent studies show the correlation of plaque’s localisation in affected MS brains with the symptoms and type of disability of the patients studied (Charil et al., 2003). Such conclusions show that lesions localised in the grey-white junction of associative, limbic, and prefrontal cortex were correlating with cognitive dysfunction, whereas impairment in coordination movements were correlated with areas in inter- hemispheric and pyramidal white matter tracts (peri-ventricular), but also in the inferior and superior longitudinal fascicles. For example, spinal cord lesion at the pontine level might explain the bladder and urethral dysfunction in MS patients (Araki et al., 2003).
2.5 Incidence and Possible Aetiology
The aetiology of MS is unknown but evidence suggests a strong neuroinflammatory component within the CNS that is associated with peripheral leucocyte infiltration. It is actually hypothesised that MS is an autoimmune disease. That is one in which antigen presenting cells (APCs) present myelin proteins and antigens to specific immune cells to promote an aberrant autoimmune response. Such processes are probably also strongly linked with environmental factors; as well as a genetic component, which may predispose individuals for MS susceptibility (Kira, 2003). Tajouri Page 38 1/11/2006 MS Thesis
Familial aggregation studies show that recurrence rates of relatives are more susceptible to
MS with a recurrence risk ratio of 20-40 for siblings 7-13 for half siblings (Sadovnick et al., 1996). Non-Mendelian inheritance of MS susceptibility is strengthened with the incidence reported from twin studies (Bundey, 1991). The concordance rate among identical twins is greater than dizygotic twins with 25-30% to 1–5.5% respectively (Ebers et al., 1995). Women are more affected than men with a ratio to 2/3. Furthermore, the disease is more prevalent in temperate climates than in the tropics. Although geographic area seems to be related to the disease, socio-demographic variables have been shown to be limited predictors of health status in MS sufferers (Riazi et al., 2003).
2.6 Pathological Examination
For the physical examination of the disease, mental and motor involvements are considered important. Apathy, lack of judgment, and inattention may occur with emotional labiality being a common, widespread, mild sign. Several patients experience euphoria, and/or reactive depression. Sudden weeping or forced laughter is indicative of the involvement of the corticobulbar pathway used for the emotional control. Convulsive seizures may occur in some patients. Severe changes such as dementia and mania are also relatively uncommon, and tend to occur at the later stages of the disease (Compston et al., 2002)
MS patients do have some speech impairment (Fried et al., 1999) and scanning speech (the slow enunciation with a tendency to hesitate at the beginning of a word or syllable) is common in advanced stages of the disease. One or more ocular signs are generally seen with changes in visual fields; transient opthalmoplegia with diplopia (indicating brainstem, Tajouri Page 39 1/11/2006 MS Thesis and 3rd, 4th, and 6th cranial nerve implicated), and nystagmus are common findings (Barnes et al., 1992). Total blindness, as a direct result appears to be rare but ON (as mentioned above) is often the prelude to attacks. Deafness is also rare, although vertigo is not.
Unilateral facial numbness is sometimes observed, and shows same hallmarks as trigeminal neuralgia. Deep reflexes are generally increased (eg. knee and ankle jerks). Superficial reflexes, particularly upper and lower abdominals are diminished or absent. Tremors (from cerebellar lesions) are common, with continued purposeful effort accentuating the situation.
Ataxia is leading to shaky, irregular, tremulous, and ineffective motions. Static tremors are common in these patients and Charcot’s triad (nystagmus, intentional tremor, and scanning speech) is a common cerebellar manifestation in advanced forms of the disease.
2.7 Course of the Disease
The manifestation and course of the disease is highly variable from patient to patient. This unknown aetiology of the disease with development of plaques at varied CNS sites lead to variable expressions of physical signs. A defining characteristic of MS is episodes of remission. Months or years may separate remission episodes in acute cases. Episodes however, become more frequent with progression of the condition resulting in eventual permanent disability. Frequent attacks appear to correlate with rapid progression of the disease. Although MS progression in general is variable, sudden onset cases in middle age often end fatally within one year. The Expanded Kurtzke Disability Status Scale (EDSS)
(Kurtzke, 1983) defines progress points of the disorder and helps to classify patient disability. This scale ranges from 0-10, with 0 being normal neurological function upon examination, and 10 being death (Kurtzke, 1983).
Tajouri Page 40 1/11/2006 MS Thesis 2.8 Diagnosis and Prognosis of MS
To date, there is no specific test for MS but it is more the subject of a compiling set of information of different tests and clinical diagnostic means. Diagnosis remains general and is not possible after a first attack. Remissions and exacerbations and clinical evidence of disseminated CNS lesions in more than one CNS area are necessary to suggest MS pathology diagnosis. The real diagnosis of MS is possible if one can exclude other pathologies of similar symptomatology such as systemic lupus erythematosus, Lyme disease or B12 deficiency (Goodkin et al., 1991).
To identify the pathology of MS, past record information of the medical patient history is essential. This could reveal previous inflammation episodes such as ON, an inflammation of the eye that is often found monolateral. Also precise neurological examinations are required for MS that would show for example CNS neurological deficits with distinct clinical evidences (deficits affecting 2 different CNS areas within two different times).
Magnetic resonance (MR) images are powerful means to assess and visualise the presence and the size of CNS plaques (Offenbacher et al., 1993). MRI technology is capable of visualising plaques and images can be enhanced with contrast-enhanced CT scans.
Magnetic resonance imaging is a common and very useful as a method for confirming lesion distribution in MS (Nakashima et al., 2003). A special technique termed `double- dose delayed CT scan’ that uses a double dose iodine contrast material may also be employed to give better resolution MS specific scans (Weitze et al., 1998).
Nerve conduction assessments known as somatosensory evoked potential tests (EVTs) are also used to diagnose MS and such examinations include the auditory EVT or the visual Tajouri Page 41 1/11/2006 MS Thesis EVT. The evoked potential tests involve challenging an individual brain for the subject time capability in receiving, processing and responding to sensory information. A person with MS will usually have slow responses due to demyelination conduction delay. Further examinations could be required to ensure MS diagnostic such as lumbar puncture (LP) where specialists will withdraw CSF from the spinal cord central canal. Laboratory findings generally show abnormal CSF in >55% of MS cases. These abnormalities include the presence of high amounts of IgG as well as lymphocytes and protein content that may be slightly increased. Also, CSF concentration of MBP may be elevated during active demyelination in MS pathology. However, all these simple diagnostic tests do not conclude of someone having MS. For example, despite that OCB (indicating intra-blood brain barrier synthesis of IgG) may be found on agarose electrophoresis of the CSF of up to 90% of MS patients, absence of such band pattern does not rule out someone has MS.
Depending on diagnostic, patients are classified as definite, probable and possible MS
(Poser et al., 1983). This classification shows differences in MRI scans with abnormal
MRI in 90% with definite MS diagnosis, 70% of probable MS and 30 to 50% with possible
MS. A recently revised diagnostic criterion for MS has been published (Mitsiu et al., 2003).
This work reviews the diagnostic criteria for MS based on CSF findings, and defines CSF abnormality based on presence of oligoclonal bands (OCB) (presence of immunogloblin gamma), and/or the presence of an elevated IgG index. Observed clinical differences between grades of pleocytosis, protein content, and frequency of IgG abnormalities are discussed. Involvement of antibodies against myelin proteins, cytokines, and chemokines is evaluated. Recently, further precise imaging has been used such as the proton magnetic resonance spectroscopy (1H-MRS). H-MRS provides biochemical activity profiles for both disease and normal unaffected surrounding tissue (Watanabe et al., 2003). The Tajouri Page 42 1/11/2006 MS Thesis differentiation of different plaques (glioma/tumefactive) has been reported using this method (Butteriss et al., 2003). This has been an important advance since gliomas and acute MS plaques have indistinguishable chemical resonance spectra by traditional magnetic resonance techniques.
Prognosis is currently severe for PP-MS sufferers with individuals generally experiencing an acute onset of the disease and high degree of relapsing stage. Favourable prognosis usually follow the rules of low number of neurological affected regions, low neurological deficit scores and better recoveries status of the sufferer (Runmarker et al., 1993). MRI examinations show that plaque abnormalities do not correlate with the clinical course of
MS. For example, begnin MS type shows plaques of extensive abnormalities whereas the number of lesions is few in PP-MS (Thompson et al., 1990). Unfavourable prognosis is often linked with damage affecting the efferent nerves such as the motor neural tract, as opposed to the sensory tract with a better prognosis.
2.9 Treatment
The existence of spontaneous remissions makes treatment difficult to evaluate. Several accepted regimes exist with indication being dependent upon the stage of the disease. Acute stages are treatable with oral prednisone, or dexamethasone until manifestation remit.
Interferon β in high doses given every other day (subcutaneously) may reduce the frequency of neurological exacerbations in patients with RR-MS. The processes of demyelination and relapse are currently being treated with the drugs Avonex (interferon β-
1a), Betaferon (interferon beta-1β), Copaxone (Glatiramer acetate, Co-polymer-1 or COP-
1), Rebif (interferon β-1a), and Novantrone (chemotherapeutic agent) in the United States Tajouri Page 43 1/11/2006 MS Thesis and United Kingdom. Of particular interest is the drug Copaxone. This drug is an oligopeptide (L-glutamic acid, L-alanine, L-tyrosine and L-lysine) leading to a diminution of exacerbation rates in RR-MS (Multiple Sclerosis Study Group, 1998) inhibiting the migration of lymphocytes (Prat et al., 1999) and inhibition of T cell activation (Miller et al., 1998). Copaxone was shown as well to act on T cells by increasing their secretion of neurotrophic factors such as the brain derived neurotrophic factor (BDNF) (Chen et al.,
2003) with relevance to new research investigations for therapeutics (Ziemssen et al.,
2003).
Recent advances in the discovery of new treatments are encouraging. The classical immuno-modulator, β-interferon decreases the level of inflammation and has been shown to decrease the blood brain barrier monocyte infiltration within the CNS of MS animal models (Floris et al., 2002). However, patients on β-interferon therapy tend to produce neutralising antibodies against the drug, reducing overall beneficial effects of this type of therapy (Bertolotto et al., 2003). Furthermore, discontinuation of β-interferon treatment further increases antibody production and as a result leads to further reduction of interferon efficiency (Reske et al., 2004). Steroids are usually used in an attempt to reduce neutralising antibody production (Bagnato et al., 2003), however benefits of interferon therapy are now debatable following a recent study that showed no effect of interferon β in
PP-MS (Leary et al., 2003).
New therapeutic attempts are under investigation with the example of the use of pluripotent cells. Haematopoietic stem cell implantation in humans offers new hopes to patients with
MS (Burt et al., 2003) and studies using neural precursor cells in EAE rat models published
Tajouri Page 44 1/11/2006 MS Thesis promising results with a decrease of disease severity and reduced CNS inflammation (Ben-
Hur et al., 2003).
Additionally, some other studies have also been carried out with the use of statins (3- hydroxy-3-methylglutaryl conenzyme A reductase inhibitors). As an example, results of a recent study showed a 43 % decrease in the mean number of MRI lesions using Simvastatin
(Zocor drug) in 30 patients investigated with relapsing remitting MS (Vollmer et al., 2004).
Patients with RR-MS currently follow the ABC therapy (Avonex, Betaseron and
Copaxone) to minimise the neuroinflammation course of the disease but presently, there is no curative therapy for MS. New drug discoveries show preliminary promising data and researchers are attempting to find new strategies to cure MS. With new trials under way and increasing research undertaken in MS, sufferers may hope for a normal life with newly developed drugs.
.
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CHAPTER 3
Genetic and Immunological Background of Multiple Sclerosis
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3.1 Generalities
MS is a serious neurological disease. With the exception of trauma, MS remains the most frequent cause of neurological disability for young adults (Al-Omaishi et al., 1999). Little is known regarding the sequence of molecular and immunological events in this disease.
MS damage of white matter leads to neurological impairment with white matter lesions that may vary in diameter from less than one millimetre to several centimetres. Females account for 60% of MS cases (Weinshenker, 1994) and the incidence of MS in Northern Europe,
Canada, and the Northern United States is approximately 10 new cases each per year per
100,000 persons (between the age of 20 and 50 years). Twins studies show higher concordance rates of MS in monozygotic compared to dizygotic twins (Sadovnick et al.,
1993). Moreover familial susceptibility studies show that nearly 15% of MS patients have an affected relative. Familial risk for MS is thus very high compared to the lifetime prevalence in the general population of ~ 0.2% (Sadovnick et al., 1988). Logically research studies have thus focused on finding common genetic factors involved in MS pathology.
Some researchers have also focused on a viral aetiology (Mokhtarain et al., 1994) but these studies remain inconclusive. A common theory is that MS is an autoimmune disease, triggered in genetically susceptible individuals by an exogenous factor, possibly a viral infection during childhood.
3.2 Genome Wide Screens in Multiple Sclerosis
Genome wide screens for MS have provided potential data for finding specific chromosomal loci involved in MS susceptibility. A series of nine whole genome screens
Tajouri Page 47 1/11/2006 MS Thesis for linkage to MS have been undertaken. This included data from British (Sawcer et al.,
2002), American (Haines et al. 2002, Vitale et al., 2002), Australian (Ban et al., 2002),
Canadian (Dyment et al., 2003), Sardinian (Corradu et al., 2001), Italian (Broadley et al.,
2001), Finnish (Kuokkanen et al., 1997) and Scandinavian (Akesson et al., 2002) and
German (Goedde et al., 2002) populations. Recently, an enthusiastic collaborative effort, that gathered results from these research groups (the Trans-Atlantic Multiple Sclerosis
Genetics Cooperative and the Genetic Analysis of Multiple Sclerosis in Europeans:
GAMES) have published additional genome wide screen studies. Their results were published in 2003 through several scientific articles in the Journal of Neuroimmunology
(Eraksoy et al., 2003a; Goertshes et al., 2003; Coraddu et al., 2003; Santos et al., 2003;
Bielecki et al., 2003; Harbo et al., 2003; Liguori et al., 2003; Heggarty et al., 2003; Rajda et al., 2003; Weber et al., 2003; Alizadeh et al., 2003; Goris et al., 2003; Ban et al., 2003;
Yeo et al., 2003; Hensiek et al., 2003; Eraksoy et al. 2003b). Thousands of genetic markers were used to screen different populations around the world and the results summary and methodology were made publically available. All authors agreed that the
HLA locus at 6p21 is strongly linked to the disease. This marker confirmed data results of each study as it is usually considered as a positive control requirement. Of note, the appendix I shows a summary table of the recent genome wide screen findings. The most implicated genomic regions were 6p21, 7q, 19p, 19q, 5p, 5q and Xq.
3.3 Candidate Gene Studies in Multiple Sclerosis
3.3.1 Major Histocompatibility Complex (MHC) Locus on Chromosome 6p
Tajouri Page 48 1/11/2006 MS Thesis There are a number of genes that may plausibly be involved in the pathophysiology of MS.
These candidate genes have been implicated in a variety of approaches but usually involve immunological and/or genetic studies. One of the most consistent findings has been an association of specific major histocompatibility class II haplotypes with the disorder
(Kellar-Wood et al., 1995). However, the basis of this association has not yet been established (Trowsdale, 1993). The MHC region has been localised to 6p21.3, a locus of
4000kb which includes MHC II, III, I. There is much evidence supporting an autoimmune basis for MS and hence the MHC locus provides an ideal candidate for study since gene products are involved in antigen presentation. Class I and class II are involved in antigen presentation to CD8 and CD4 lymphocytes respectively. Class I has a region containing
HLA loci (HLA A, B, C, E, F, G). Association with molecules on the chromosome 6 p21 is often dependent on the population studied. For example, class II DR15 and DQ6 phenotypes are associated with northern European populations (Hillert, 1994) whereas the
Asian populations with MS are associated with DPB1 (Ito et al., 1998).
The MHC Class II locus is composed of genes coding for proteins LMP2 (proteasome subunit, beta type, 9) and LMP7 (proteasome subunit, beta type, 7), which are part of the proteasome. The conversion of viral protein or cellular proteins into small peptides is carried out in the proteasome from where peptides are translocated into the reticulum endoplasmic compartments (REC) to bind with nascent MHC class I molecules for presentation on the surface cell. The translocation into the REC is facilitated by the transporter 1, ATP-binding cassette (TAP) 1 and 2 which are coded by genes in the MHC
Class II region. It has been found that a polymorphism at the TAP1 and TAP2 locus shows no association with MS (Vandevyver et al., 1994) but the study showed a correlation with the eventual differential expression of these genes in affected and non-affected tissues. Tajouri Page 49 1/11/2006 MS Thesis
100kb telomeric to HLA F is the locus of the myelin oligodendrocyte glycoprotein (MOG), another potential candidate gene. This is a highly immunogenic component that plays an important role in the maintenance of the myelin sheath. Antisera raised against MOG activate a signalling pathway leading to degradation of microtubules and disruption of myelin basic protein (MBP) (Johns et al., 1999). This pathway is also triggered by antibodies of the galactolipid galactocerebroside (Dyer et al., 1992) (a unique marker of myelin-producing cells), shown in glioma cells (Joshi et al., 1992), and involves a possible second messenger (most likely Inositol Phosphate 3) activating a voltage Ca2+ channel
(Joshi et al., 1998). It results in an increase of intracellular calcium and microtubule disruption.
In the Class III MHC region are several genes which could be potential candidates for differential gene expression. These include a steroid enzyme 21-hydroxylase gene
(CYP21A2) and heat shock proteins (HSP): HSP70-1 and HSP70-2. Furthermore, MHC class III region contains the complement molecules of the immune system and tumour necrosis factor gene (TNFα and TNFβ). TNFα has been shown to be toxic to oligodendrocytes and myelin (Wingerchuk et al., 1997). In MS plaques, TNFβ is present and is at the origin of tissue repair (De Groot et al., 1999). Some studies have investigated
TNFα polymorphisms (Wingerchuk et al., 1997) but no association was found with MS except in HLA-DR2+ MS patients compared with HLA-DR2- ones (Oturai et al., 1999).
Studies on Caucasians from European descent show that class II HLA alleles are more strongly associated with the HLA-DR2 haplotype (Haines et al., 1998). However a
Spanish team (Fernadez-Arquero et al., 1999) has recently shown an association between
Tajouri Page 50 1/11/2006 MS Thesis TNFα-376 polymorphism and MS. Additionally, it has to be noticed that MS is dominated by class I MHC T8 lymphocytes with clonal expansion (Gay et al., 1997). In summary,
6p21.3 is a region which houses many genes with a possible role in the pathophysiology of
MS and which warrant further investigation. It is interesting to note that genome scan results consistently implicate the 6p21 region. In Caucasians, this region of MHC is estimated to account for 10-15 % of the genetic component in MS susceptibility (The
Multiple Sclerosis Genetics Group, 1998).
3.3.2 Located at Non-MHC Chromosomal Loci
Chromosome 17q22 is another genomic region showing MS involvement via linkage studies (Sawcer et al., 1996). Although this chromosome 17 region does not have a clear known candidate gene at present, there are a few potentials from what has currently been mapped. Within this region is an alternate splicing factor gene (SFRS1) that may potentially have a role in MS. Genes involved in myelin formation such as PLP (proteolipid protein), MBP, CNP (2', 3'-cyclic nucleotide 3'-phosphodiesterase) and MAG (myelin associated glycoprotein) exist in several isoforms due to an alternative splicing of their mRNA. The myelin basic protein and the proteolipid protein constitute 80% of the myelin proteins. Contradictory results have been previously obtained in studies of the MBP gene in terms of MS involvement but a defective splice gene could be involved (Tienari et al.,
1998; Wood et al., 1994). Additionally, 17q22 contains subunit 11 of cytochrome c oxidase (COX11), a protein known as being part of the mitochondrial respiration. Studies showed that oxidative damage to the mitochondria, by nitric oxide, decreases mitochondrial respiration, which is correlated with a decreased expression of MBP (Mackenzie-Graham et al., 1994). Finally 17q22 also contains myelin-associated enzyme: CNP, with high activity Tajouri Page 51 1/11/2006 MS Thesis in the CNS. Additional analyses were carried out on other potential candidate genes, such as the platelet endothelial cell adhesion molecule-1 gene (PECAM1), the regulatory subunit
RIα of cAMP-dependent protein kinase (PRKAR1A) and the myeloperoxidase (MPO) failed to reveal these genes as candidate genes (Nelissen et al., 2000).
Other data, from Finland, provide evidence for a predisposing locus for MS at 5p14-p12
(Kuokannen et al., 1996). This region is composed of many receptor genes which might be involved in the occurrence of the disease. These include Interleukin 7 receptor (IL7R) at
5p13, glial glutamate receptor (SLC1A3) at 5p13, prolactin receptor (PRLR) at 5p14-3, prostaglandin receptor (PTGER4), growth hormone receptor (GHR) at 5p13, leukemia inhibitory factor receptor (LIFR) at 5p13-12, and also transduction factor genes, such as the
FYN binding protein (FyB) at 5p13.1 and a zinc finger protein ZNF131 localised to 5p12-
11.
There are a number of other genes and chromosomal regions that also warrant gene investigation. Clearly genes involved in myelin production or associated with myelin protein are strong candidates. MAG is one such gene, it is capable of inducing demyelination in rats by initiating a T-cell immune response and installing an inflammatory process (Weerth et al., 1999). It has been mapped to chromosome 19q13, a region that has been shown to have a significant association with MS (Barcellos et al., 1997). Quantitation of MAG and CNP was done by radioimmunoassay in the human CNS of MS patients
(Johnson et al., 1986). Investigations were conducted inside plaques, in the periplaque regions and in normal appearing white matter regions. The quantitation results were compared amongst those three areas and human brain tissue from controls. It showed an overall reduced level of those proteins in all the three zones with a greater significant Tajouri Page 52 1/11/2006 MS Thesis decrease of MAG. The ‘normal appearing white matter’ (NAWM) of the periplaque region was also abnormal (Peters et al., 1995).
Transforming growth factorβ3 (TGFβ3) results have also been somewhat promising and deserve to be investigated further (Mertens et al., 1998), as have MOG studies (Seboun et al., 1999). Also recently a Japanese team showed an association of MS with the vitamin D receptor gene (VDR) polymorphism (Fukasawa et al., 1999) although a Canadian study showed no VDR role in MS (Steckley et al., 2000).
3.4 Immunological Mechanism Involved in MS
The immune system response is comprised of two immune systems: humoral and cellular.
In the case of MS, both systems apply resulting in CNS inflammation coupled with degeneration in myelin sheath. A plethora of cells may be involved in this disorder including microglial cells (macrophages of the CNS), B and T lymphocytes, natural killer cells and peripheral macrophages (Li et al., 1993). Their activities are coupled with the secretion of activating signals such as cytokines and interleukines that upon production affect surrounding cells. It has been reported that auto-reactive T-cells exist in the peripheral blood from both MS affected and healthy individuals (Lindert et al., 1999). In order to reach the CNS, the immune cells have to cross through the BBB but only activated
T-cells can penetrate this fence. However, it has been reported that in MS the BBB undergoes a breakdown resulting in facilitated passage of immune cells (McDonald et al.,
1992). The activation of T-cells is supposed to be due to a misguided immune response secondary to cross recognition of epitopes shared between a microbial pathogen and a putative antigen in the CNS (Wucherpfenning et al., 1995). These CNS-antigen specific T Tajouri Page 53 1/11/2006 MS Thesis cells transmigrate through the endothelial BBB by secreting and expressing adhesion molecules such as selectins and integrins (Monteyne et al., 1997). The T-cells occupy the
CNS in regions where further events take place. Furthermore, once they have occupied the
CNS, the T-cells stimulate the entry of further immune cells such as peripheral macrophages. Passage of macrophages in the CNS is facilitated by the T cell induced BBB disruption due to secretion of activated matrix metalloproteases (MMPs). In the cerebrospinal fluid of MS patients, a high gelatinase (MMP9) concentration has been found
(Rosenberg et al., 1996). Gelatinase B breaks down the BBB and its inhibition, by serine protease inhibitors, shows a protective effect on the MS animal model, EAE Lewis rats
(Brosnan et al., 1980). In the parenchymal of the CNS, T-cells are reactivated with the myelin antigen proximity and secrete a vast group of pro-inflammatory agents such as interferon gamma (INFγ), tumour necrosing factor alpha and beta (TNFα and TNFβ), interleukin 2 (IL-2) (Olson et al., 1995). IL-2 is an autocrine interleukin triggering a T-cell auto-activation loop process. On both astrocytes and microglial cells, those inflammatory mediators trigger an up-regulation of MHC class II molecules. The increase of MHC class
II molecules at the surface of these cells improves the amount of antigen presenting cells.
Moreover, microglia as well as T lymphocytes are developing a proliferating process in response of INFγ action (Martino et al., 1995; Grau et al., 1997).
Activated astrocytes trigger an up-regulation of adhesion molecules at the surface of the
BBB (Weiss et al., 1998). Chemo-attractants are produced such as the monocyte chemo- attractant protein 1 (MCP-1) (Van Der Voon et al., 1999) that chemically orientate peripheral phagocytes towards the BBB. The BBB endothelium is thus facilitated for further influx of inflammatory cells such as macrophages. Even macrophages disrupt the
Tajouri Page 54 1/11/2006 MS Thesis BBB with the secretion of neurotoxins (Brosnan et al., 1981). Secondly, activated astrocytes are able to excrete more pro-inflammatory molecules that turn the local CNS microglia (CNS resident macrophages) into ameboid microglia, a more active macrophage state. The activated astrocytes excrete factors such as GM-CSF (granulocyte monocyte- colony stimulating factor) whose role is to induce the proliferation of the ameboid cells.
The local microglia plays an important role in local antigen presentation in the CNS of
EAE animals (Bauer et al., 1994) allowing an immune response. The microglia is expressing B7 (Dangond et al., 1997) and vascular cell adhesion molecule (VCAM-1).
These two molecules bind CD28 and the very late antigen 4 (VLA4) respectively, on the surface of T-cells (Chabot et al., 1997) and these molecular interactions affect T-cell activation. Complement receptors (CR1 and CR2) are also found and are molecules that allow the binding of complement coated targets to be phagocytosed. Complement constitutes the major effector mechanism of humoral immunity. Contact with complement permits a better activation of the microglia but also the release of TNFα and interleukins
(IL-1 and IL-6) (Rajan et al., 1996). Microglia express receptors for Fc fragments of immunoglobulins (Ulvestad et al., 1994) and completes an association action with B- lymphocytes. Those B-lymphocytes, fewer in numbers, can pass the leaky BBB and produce antibodies against myelin proteins (Gerritse et al., 1994). The antibodies are observed, after a lumbo-puncture, in CSF from MS patients appearing as oligoclonal bands in agarose gel electrophoresis. T cell infiltration in the CNS not only induces microglial activation but also triggers the recruitment of high numbers of macrophages (Hulkower et al., 1993).
Tajouri Page 55 1/11/2006 MS Thesis Besides inflammation, demyelination is the second most characteristic feature of MS pathology. Both microglia and macrophages are capable of ingesting myelin in EAE animals (Rinner et al., 1995). However, oligodendrocytes do not express MHC calls II molecules so CD4+T cells cannot have a direct effect. Studies have shown that both complement and immunoglobulins are detected on oligodendrocytes and microglia in MS brain but none of the studies have ever shown the complement system alone (Fabry et al.,
1994). Oligodendrocytes are damaged via antibody cell mediated cytotoxicity (ADCC) triggered by microglia, macrophages with the help of T4+, B cells and complements molecules (Ozawa et al., 1994). The macrophages act as APCs via the major histocompatibility molecule class II. Their activities are indicators of ongoing demyelination activity (Li et al., 1993). Furthermore, the interaction of B cells with T4 cells (CD40-CD40L) turn the B-lymphocytes into APCs, which in consequence increase the myelinotoxic activity. Antibodies to CD 40 ligand (CD 40L) can prevent the MS like disease in EAE animals (Boon et al., 2001). MBP-specific CD8+ T cells are detected in MS plaques and have been shown to be cytotoxic in vitro on HLA-A2 not HLA-A3 transfected oligodendrocyte cell lines in the presence of MBP peptide 110-118 (Jurewicz et al., 1998).
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3.5 Expression Profiles in MS and EAE Mice
3.5.1 Expression Profiles in EAE Mice
3.5.1.1 EAE Mice Definition
Animal models for MS have been used to characterise and understand the pathological traits of MS (Table 3.5.1.1.A). The model most commonly used is the EAE mouse. It is generated by injecting normal mouse peptides related to the myelin sheath and producing an immune response with subsequent MS like symptoms. Such peptides may vary such as
MOG 35-55 (Mendel et al., 1992), MBP 87-99 (Brocke et al., 1996) and many others. The peptides used to induce EAE are diverse and can include fragments of the myelin basic protein, myelin oligodendrocyte glycoprotein or other proteins. Such immunisation is followed at around ten days later with central nervous system inflammation and clinical parameter appearance such as loss of weight and paresis/paralysis of the mice. Mice are carefully monitored, on a daily basis, for their disease progression but one must keep in mind that clinical signs vary according to species and strain. This model shares multiple pathological hallmarks with MS pathology (Table. 3.5.1.1A) and represents a suitable tool for the investigation of MS. The model can then be used for targeting studies of the different phases of inflammation, and for testing anti-inflammatory therapeutics and monitoring the outcome.
Tajouri Page 57 1/11/2006 MS Thesis Table 3.5.1.1 Comparisons between Multiple Sclerosis and EAE, Clinical Pathology and
Genetic
Multiple sclerosis EAE
CLINICAL PRESENTATION
Relapses and remissions Present Present
Paralysis Present Present
Ataxia Present Present
Visual impairment Present Present
GENETICS
MHC linked susceptibility Yes Yes
Females more susceptible Yes Yes
PATHOLOGY IN LESIONS
Clonal CD4+ T cells react to myelin Present Present
Clonal CD8+ T cells react to myelin Present Present
Perivascular cuffs Present Present
Antibodies to myelin Present Present
α4 integrin, complement Present Present
TNF-α, IFN-γ Present Present
Demyelination Present Present
Axonal dystrophy Present Present
Table from Steinman, 2001.
Tajouri Page 58 1/11/2006 MS Thesis 3.5.1.2 Differential Displays and Microarray Experiments in EAE Mice
Jeong et al., 1998 studied EAE mice induced by immunisation with MBP activated T lymphocytes. The investigator then undertook differential display gene expression studies comparing cDNA banks from encephalitogenic and non-encephalitogenic T cells. To minimise false positives, that could introduce errors in their data, the authors designed a reversed dot blot procedure following the differential display. Data showed 21 differentially expressed genes with an up-regulation of gene expression for the mouse urokinase-type plasminogen activator (uPA), the mouse gelsolin gene and interferon γ gene. Interestingly, an increase of IL-3 expression was observed in Non-encephalotigenic mice. IL-3 is a haematopoietic colony-stimulating factor and also plays a role as a neurotrophic factor
(Kamegai et al., 1990). Furthermore, IL 3 has been found to enhance presentation of superantigens to T cells in allergy and activating these T cells consequently (Celestin et al.,
2001). IL-3 is also shown decreased in expression in peripheral blood cells of MS individuals during relapsing episodes of the disease (Huberman et al., 1993).
Some years later, a second study was undertaken by Ibrahim (Ibrahim et al., 2001) in which the spinal cord of acute EAE mice were investigated and compared to normal mice. The
EAE development was monitored at two specific times of disease course: time of disease onset and time of peak of the disease (grade 3 with severe paraparesis). The authors found
213 differentially expressed genes with 100 being common to the two course stages.
Among these 213 genes, 166 were increased in gene expression and 47 showed a down regulation; a total of 51 genes mapped to known EAE-linked quantitative trait loci (QTL).
A number of these regions showed synteny to human chromosomal loci including EAE1
(MHC) and EAE7. Examples of genes differentially expressed and related to QTL regions Tajouri Page 59 1/11/2006 MS Thesis included: MHC class II region, C3 complement molecule, iNOS gene, normal T-cell expressed and secreted (RANTES or CCL5 or SCYA5), T cell receptor β (TCRβ), the leucocyte surface antigen CD53, IL 3R (the cyotkine γ receptor subunit) tumour necrosis factor 2 receptor (TNF2 R) and FCγR as well as chemokine (C-C motif) ligand 9 (CCL9 or
SCYA9 or MIP-1δ), a known chemoattractor factor and proinflammatory mediator (Mauer et al., 2004), all found up-regulated in expression. Down-regulated gene expression of genes mapping to known EAE-linked quantitative trait loci included platelet activating factor acetylhydrolase IB alpha subunit or lissencephaly 1 protein (PAFAH1B1), a protein critical for neuronal migration in which deficiency is responsible for brain malformation
(Mizugushi et al., 1995). Also decreased gene expression was observed for the phosphotyrosine-binding (PTB) protein amyloid β A4 precursor protein-binding, family A, member 2 (APBA2) and the sterol carrier protein X (SCPX or SCP2), a protein that facilitates the transport of cholesterol to mitochondria. TNFα, IL2, IL1, IL4, IL10 and IL12 did not show any differential expression, although their involvement in MS has been implicated in other studies. The comment, published on Science, by Steinman (Steinman et al., 2001) may explain the reason why such alteration of gene expression occurred.
Steinman noticed that the Ibrahim et al., 2001 study used EAE mice that were induced by immunisation with MOG specific T cells in complete Freund’s adjuvant plus the addition of Bordetella pertussis toxin and that all these immunisation factors might indeed alter the gene profile in these EAE mice.
In 2001 Whitney (Whitney et al., 2001) performed microarray gene profiling experiments using brains of SJL/J and C57BL/6 EAE mice compared to normal mice. In parallel, they established microarray experiments using human brains and provided a list of selected differentially expressed genes common to both human MS disease and the encephalotigenic Tajouri Page 60 1/11/2006 MS Thesis mice. The SJL/J mice were immunised with MBP specific T cells, whereas C57BL/6 were injected with MOG specific T cells. Further explanations are provided in the discussion section (Chapter 7; Section 7.2.3)
In 2002, the researcher Carmody et al (Carmody et al., 2002) also used gene microarray technology to identify significant altered gene expression from EAE during the acute phase and the recovery phase. C57BL/6 mice EAE were induced by MOG 38-50 peptides and total RNA was extracted from spinal cords and lymphoid tissues. Gene expression analysis of EAE mice was compared to naive mice and several selected groups of genes were validated by Nothern blot and semi-quantitative PCR techniques. Microarray data revealed different patterns of expression specific to either the acute phase or the recovery phase.
Briefly, immunological genes such as STAT1, granulocyte colony stimulating factor 1
(GCSF1) receptor, interferon inducible protein (IP-10 or CXCL10), interferon regulated gene 1 (IRF1) were increased during the acute phase of the EAE disease. Nervous responsive genes included an up regulation of expression of the glial fibrillary acidic protein (GFAP) as well as a down expression of the glial cell derived neurotrophic factor family receptor 1 (GDNFA2) during the acute phase of EAE. Of note, several genes involved in synaptic function were repressed in the acute phase of the EAE pathology including vesicle-associated membrane protein (VAMP) 1 and 2. In contrast, the EAE recovery phase showed an increased of gene expression for the insulin like growth actor 1
(IGF-1), lipoprotein lipase, apolipoprotein CI (APOC1), the B cell linker protein (BLNK) and a great number of myelin associated genes.
Recent additional arrays have enlarged the scope of gene expression profiles in EAE mice.
Paintlia (Paintlia et al., 2004) performed microarray experiments using the lumbar region of Tajouri Page 61 1/11/2006 MS Thesis EAE female Lewis rat spinal cords. These rats were injected with an equal volume of complete Freund's adjuvant and myelin basic protein. The subtlety of this experiment was to compare the gene expression profiling of such EAE rats to EAE rats treated with
Lovastatin (LOV), a known drug mediator that decreases severity of the EAE course
(Stanislaus et al., 1999). Results demonstrated an overall down-expression of 140 genes and only 18 over-expressed genes in EAE Lovastatin treated rats. The 18 over represented gene transcripts consisted of anti-inflammatory genes such as IL10, IL4, peroxisome proliferator activated receptor (PPAR)-γ and (PPAR)-δ as well as TGF-β1 and the tissue inhibitor of metalloproteinase 1 (TIMP1). In previous studies, PPARγ depletion in heterozygous mice resulted in an increase of exacerbations (Bright et al., 2003) and the use of PPARγ agonists inhibited the pro-inflammatory IL12 (Spiegelman, 1998). The list of genes down-expressed with Lovastatin included IFNγ, IFNγ receptor, STAT1, RANTES,
CXCL10 (or IP10), osteopontin (OPN or SPP1), CD44 (receptor of OPN), the chemokine receptor CCR5, T cell receptor genes, MHC class I and class II, adhesion molecules such as the intercellular adhesion molecule 1 (ICAM-1), L selectin and β-integrin, matrix metalloproteases such as MMP9, and genes involved in the production of nitric oxide such as iNOS.
Some other microarray studies relating to MS research included the investigation of EAE course using transgenic mice expressing the T cell receptor TCR specific for MBP-Ac1-11 peptide (Matejul et al., 2003). Recently, a gene expression profiling investigation was carried out using EAE mice after the administration of 1,25-dihydroxyvitamin D3 (ligand of vitamin D receptor) (Spach et al., 2004) and results showed an effect of vitamin D as an inducer of pro-apoptotic gene expression leading to decrease severity of EAE course. In summary, the gene expression that is carried out is EAE mice can be correlated to the Tajouri Page 62 1/11/2006 MS Thesis studies held in human MS tissues. However, these mice were immunised to induce EAE and as a consequence differential gene expression arsing from such investigation are more likely to reflect ongoing immunological reactions and so would fail to identify responsible factors that trigger MS pathology.
3.5.2 Expression Profiles in MS tissue
3.5.2.1 Differential Display and Microarray Experiments in MS
To date, a series of six high throughput gene profiling experiments using microarray has been undertaken (Table 3.5.2.1) in human brain tissues. Additionally, investigations of MS cDNA libraries have been undertaken in two studies and provided interesting datasets
(Table 3.5.2.1). Due to the high number of genes found altered in expression in these different studies and their relevance to the array studies performed in this thesis, I have introduced these studies and discussed their findings in the Discussion section of this thesis
(Chapter 7; Section 7.2.3). Chapter 7 (Section 7.2.3) thus includes a discussion that takes into account array findings investigated in EAE mice, MS peripheral blood mononuclear cells (PBMC), MS human brain tissues as well as the effects of MS therapeutic drugs on gene MS profiling and relates this to findings in this present study.
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Table 3.5.2.1 Summary Table of Differential Displays and Microarray Experiments on
Human MS Brain Samples.
Gene Type of Array Candidate gene expression MS patients Control or validation in MS cDNA libraries technique Becker et al., PP-MS:3 CA with 2 control Normalised None 1997 NAWM libraries cDNA library Whitney et 1 PP-MS: 2 A 1 RCA(33PdCTP) IHC al., 1999 NAWM© ~ 5000 genes 33 Whitney et 1 PP-MS:16 CS 3 NWMΘ RCA ( PdCTP) EAE (SJL/J via MBP87- 99 and C57Bl/6 MOG 35- al., 2001 1RR-MS:1 A +1 CA 2798 genes 55) + IHC CP-MS: 1A + 1CA 2: NWM OFA EAE (C57BL/6 via Lock et al., SP-MS:1CA + 1CS + WB ~5000 genes MOG 35-55) 2002 SP-MS:1CA + 1CS CP-MS4:1CS Mycko et al., 4 SP-MS: 2CA + 2CS © RCA (32PdATP) Real time PCR 2003 and 588 genes 2004 3 MS 1 control Non normalised EAE (SJL/J via PLP Chabas et al., library cDNA libraries 139-151; 129/C57Bl/6 via MOG 35-55 ) 2003 ~ 4000 clones/library Tajouri et al., 5 MS 5 NWM ~5000 genes Real time PCR 2003 Lindberg et 6 SP-MS (acute 12 12633 genes Real time PCR al., 2004 lesions and NAWM) controls Θ
© Tissue obtained from the same MS sufferer; CP-MS: Chronic progressive MS; EAE: Experimental allergic encephalomyelitis; IHC: Immunohistochemistry; NAWM: Normal apparent white matter; NWM: Normal white matter (None MS patient); OFA: Oligonucleotide fluorescence based arrays; RCA: Radioactive cDNA based arrays; WB: Whole brain; Θ Pooled tissues
Tajouri Page 64 1/11/2006 MS Thesis
CHAPTER 4
METHODOLOGICAL APPROACH
Tajouri Page 65 1/11/2006 MS Thesis
4.0 Overview
This study used three basic methodological approaches to investigate genes that may play a role in MS. The first was a case-control association approach to investigate specific potential candidate genes. Polymorphisms in the iNOS, nNOS, COMT, MTHFR and VDR genes were genotyped in an MS case and a matched control population to determine whether specific alleles occurred more often in the affected population. This would occur if the tested gene was associated with MS. In addition a microarray approach was used to investigate global gene expression difference in MS tissue. For this study, samples from
MS plaque tissue were compared to anatomically, age and sex matched normal brain tissue to identify any genes showing significant under or over-expression in the 5000 genes investigated. Finally, a real time-quantitative RT-PCR (Q-PCR) approach was used to further investigate genes showing differential expression in the array studies. Transferrin
(TF), superoxide dismutase 1 (SOD1), glutathione peroxidase 1 (GPX1), glutathione S- transferase, PI (GSTP1), crystallin, αβ (CRYAB), phosphomannomutase 1 (PMM1), tubulin beta-5 (TBB5), inositol 1,4,5-triphosphate kinase B (ITPKB), osteopontin (SSP1 or
OPN), calpain subunit 1 (CAPNS1), protein inhibitor of activated signal transducer and activator of transcription (PIAS1) and signal transducer and activator of transcription
(STAT1) genes were chosen for these studies and investigated using a real time PCR approach.
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4.1 Genetic Case-Control Association Studies
Genotyping studies have been employed for a variety of disorders to determine whether clinical symptoms are associated with particular inherited genetic variations or gene regions. In some cases, such as the HLA-DR studies, gene variation, clinical course and susceptibility to MS have been shown to be consistently associated. In many cases, functional variations, which are associated with a particular phenotype, are not necessarily a causative (or even the most significant) contributor to disease pathology. Genomic analysis involves the detection and analysis of mutations and polymorphic variants in specific genes. Genomic analysis can be used to detect causal mutations directly or genetic variations that may be associated with disease risk. Genotyping of case-control populations is generally undertaken to detect gene variants associated with disease risk, whilst DNA sequencing is generally undertaken to detect causal mutations or polymorphic variants useful for genotyping studies.
4.1.1 DNA Extraction
104 MS patients and 104 controls (age, sex and ethnicity matched) were used in the case control studies to investigate polymorphic alleles within particular candidate genes. DNA was obtained using a QIA amp DNA blood Maxi Kit following manufacturer’s recommendations. Briefly, lymphocytes were isolated and pelleted in Phosphate buffer saline (PBS). Lymphocyte membranes were lysed using protease and lysis buffer (AL buffer, Qiagen). 100% pure Ethanol was added to the mixture and the solution was applied
Tajouri Page 67 1/11/2006 MS Thesis to a QIAamp maxi column and centrifuged at 3000 rpm for 3 min. A second buffer (AW1,
Qiagen) was applied to the column to allow a strong fixation of genomic DNA to the column and centrifuged at 5000 rpm for 1 min. This step was followed by the addition of buffer AW2 (Qiagen) and a centrifugation at 5000 rpm for a 15 min to ensure that no ethanol was remaining within the matrix of the column. The column was transferred to a new collector tube and AE buffer (elution buffer, Qiagen) was applied to the top of the column and left to incubate for 5 min. Genomic DNA was eluted following a 5 min centrifugation at 5000 rpm. Genomic DNA was quantified at 260nm and diluted accordingly to obtain a PCR working template of 20 ng/μl.
4.1.2 Polymerase Chain Reaction
PCR was introduced in 1985 (Saiki et al., 1992). The process is simple and consists of using oligonucleotide primers (of about 20 bp length) that will complement the 5’ and 3’ ends of a DNA sequence. If the primers were designed specifically to their target, this would result in an amplification of the sequence spanned by this set of the primers. For the amplification to occur, the primers are to anneal at low temperatures (45 to 65°C) and with the help of a Taq polymerase and free nucleotides, the template DNA is copied and is extended at a set extension temperature. This set of extension temperature is approximately at 72°C. Once this extension is done, a denaturing temperature (usually around 94 °C) denatures all the templates and the copied DNA. A second cycle can begin with the common annealing, extension and denaturation steps that lead to additional copies. Cycles can be automated using thermal cyclers and results in the production of several millions of copies of a genomic segment after 20 to 45 cycles.
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4.1.3 Restriction Enzyme Polymorphism and Genescan Analysis
Association analysis is possible though the study of restriction fragment length polymorphisms (RFLPs) that are widespread throughout the genome. Particular sequences of the genome could possess RFLPs that could be functional. Using a restriction enzyme, one could identify these sequences possessing a specific RFLP from the ones without. If the
RFLP consists of several bp then a simple visualisation of the restricted DNA can be visualised through agarose gel electrophoresis. If the RFLP marker is only of a few nucleotides in length, it is limited to use an agarose gel. To visualise and appreciate such detailed genotyping a GeneScan analysis is preferred. For the investigation of particular gene markers using a GeneScan technology, PCR products, using one fluorescently labelled oligonucletotide, are produced and checked by electrophoresis in Ethidium-bromide-stained
2% agarose gels prior to pouring in a ABI 310 Genetic Analyser. A capillary electrophoresis is performed in the Genetic Analyser where a laser beam excites the fluorophor. The labelled PCR fragments are compared to labelled size standards to accurately determine the size of the PCR fragments investigated. Results can then be analysed using a GENOTYPER® software (version 2.1; PE Biosystems) to determine individual genotypes for each case and control sample investigated.
4.1.4 Analysis of Polymorphism Results
Genotypes were determined for both case and control populations and the frequencies of alleles and genotypes then compared. Chi-square analysis is usually used to compare allele
Tajouri Page 69 1/11/2006 MS Thesis and genotype frequencies to see if there are any significant differences in the case and control populations.
4.2 Gene Expression Studies
4.2.1 RNA Extraction
Total RNA extraction was performed using Trizol from Life Technologies. Basically, a range of 0.1 to 1.5 g of human brain tissue is added to 1 ml of Trizol (Life technologies).
The tissue is disrupted using either a syringe with series of needles: 19G, 23G, 25G either using a Rotor stator homogeniser. The homogenate is left on bench at room temperature for few minutes. 0.2 ml of chloroform is added (incubation at room temperature for 3 min) and a centrifugation at high speed (11000 rpm) with a Heraeus Sepatech lab top centrifuge separate the different phases of the lysate. The aqueous solution is transferred in a fresh tube and mixed with 0.5 ml of cold isopropanol. After 10 minutes incubation, the sample is centrifuged at high speed. The RNA pellet is washed with 75% DEPC ethanol (1 ml) twice and is resuspended in DEPC treated water (0.1 ml). The total RNA is quantified and its purity identified by the 260nm/280nm ratio provided by the RNA/DNA Calculator
(QuantaGene). The total RNA is then treated with DNAse 1 to avoid any genomic DNA contamination. A mix of DEPC water (40 μl), RQ1 buffer (20 μl), DTT (20 μl of 0.1M
DTT) and DNAse 1 (20 μl of 2U/μl) is poured onto the RNA and left incubated at 37°C for
15 minutes.
Tajouri Page 70 1/11/2006 MS Thesis In a second step, the total RNA is purified using Qiagen columns (mini RNA Qiagen kit) to obtain a higher purified product. Briefly, total RNA is mixed with 500 μl of 100% ethanol and poured on the top of the Qiagen column. The following steps are given by Qiagen protocol: RW1 buffer step, RPE buffer washing step and finally RNA elution step with
DEPC-treated water.
RNA quantitation was performed for all the RNA extractions with 5 μl of Total RNA using a Quantagene RNA/DNA calculator spectrophotometer machine (The Australian
Chromatography Company). The integrity of the RNA can be seen via a 1.2%
Formaldehyde Agarose (FA) Gel Electrophoresis: 0.6g agarose powder, 10× FA gel buffer
(200 mM MOPS, 50 mM sodium acetate, 10 mM EDTA, PH to 7 with NAOH.) overlay till
50 ml of DEPC water. All trays and tanks were washed first in 70% ethanol (with DEPC water), rinsed with DEPC water, washed with RNaseZAP (Sigma) and let to dry off in a free dust environment (Contamination control System PCR work station, Gelaire). The
RNA is mixed with a 5× RNA loading dye (saturated bromophenol blue solution, 500 mM
EDTA (pH8.0), 37% formaldehyde), 100% glycerol, formamide, 10× FA gel buffer. This
RNA mix samples were loaded following 3 min incubation at 65°C and pour within the FA gel yells for a run at 85 Volts for 30 min. The gel is then visualised under ultra violet illumination after ethidium bromide staining and photographed with a digital camera
(Kodak DC 120 Zoom DC).
Such RNA extraction could be contaminated with genomic DNA and measures are necessary to eliminate this problem. Briefly, a DNA contamination check is possible via the analysis of any gene by reverse transcription (RT-PCR). RT-PCR is performed with a
Tajouri Page 71 1/11/2006 MS Thesis final volume of 25 μl containing: 200 μM dNTPs (Promega), 5X RT-PCR buffer [300 mM
Tris-HCL, pH 8.3: 2.5 mM DTT; 250 mM KCl; 0.5% Triton X-100 (Evergreen Scientific);
30 μM EDTA; 7.5 mM MgCl2], 0.4 μM each primer (β-actin), 1 U Taq polymerase (Perkin
Elmer ABI), 1.2 units AMV reverse transcriptase (Promega) or superscript II RNAse H- reverse transcriptase (Invitrogen, life technologies). Thermal cycling is performed as follows: 30 min at 50°C (reverse transcription), then 5 min 94°C, followed by 5 cycles of
45 s at 94°C, 60 s at 57°C, 2 min at 72°C added to 30 cycles of 30 s at 94°C, 30 s at 57°C,
45 s at 72°C (with 3 s extension) and ended by a final incubation of 4 min at 72°C. Three
Controls for each RT-PCR are carried out: one without AMV, one without RNA, one without AMV nor RNA but only genomic DNA and Taq polymerase. PCR products were resolved using 2% agarose gel electrophoresis. The visualisation under ultra violet illumination after ethidium bromide staining is photographed with a digital camera (Kodak
DC 120 Zoom DC).
4.2.2 Microarray Experiments
Microarray technology is one of several developing approaches to comparatively analyze genome-wide patterns of mRNA expression. The technology for cDNA based microarray analysis is based on an approach where cDNA clone inserts are robotically printed onto a glass slide and subsequently hybridised to two differentially fluorescently labelled probes.
The probes are pools of cDNAs which are generated after isolating mRNA from the cells or tissues that one wishes to compare. Resulting fluorescent intensities are produced and compared using a laser confocal fluorescent scanner with ratio information obtained following image processing.
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Basically, RNA is extracted as shown above and adjusted to a volume corresponding to 30-
70 μg. A control RNA (Normal brain) and a test RNA (MS RNA) are prepared for the microarray experiment. The RNA is concentrated with a Microcon YM-30 concentrator
(Selby-Biolab). The concentrated RNA is adjusted to a precise 19 μl volume with DEPC water and the addition of 1μl of Rnasin Ribonuclease inhibitor (Promega). The RNA is left at 70°C for 10 min with the addition of 7 μg of PolydT (20-mer; GeneWorks). A reverse transcription reaction converts that RNA into complementary DNA using, Superscript II
Reverse Transcriptase TM (Invitrogen, Life Tech), a mixture buffer [5× first strand Buffer
(life Tech), 8 μl; 0.1M DTT 4 μl; 20× ‘low’ concentration dNTPs (final concentration 12.5 mM for dATP, dGTP, dTTP and a final concentration of 2.5 mM dCTP)].
Two μl of 1 mM of CY3-dCTP (Amersham) and Cy5-dCTP (Amersham) are poured in the two sets of RNA population. The dye Cy3 is commonly used to label the test RNA whereas the Cy5 dye is used for the reference RNA. The reversed transcription is set at 42°C for one hour after the addition of 1μl of superscrypt II reverse transcriptase. It is followed by an extra 90 min after adding 1.5 μl of more superscript II. cDNA is then put free of remaining RNA via RNA hydrolysation using 2.0 M NaOH and 0.5 M EDTA at 65°C. This process is neutralised after 20 min and followed by a clean up step that uses a QIAquick
PCR purification kit (Qiagen, Sydney, Australia). Briefly, both samples: Cy3 sample and
Cy5 sample are mixed together and purified following the instructions of the company’s kit. 20 μg of Poly dA (APBiotech) and 10 μg of Human Cot-1 DNA are added to the eluted purified solution. The entire solution is set to dry in a speed Vac and resuspended in 40 μl of Sigma ArrayHyb TM low temperature Hybridisation Buffer (Sigma). The solution is left
Tajouri Page 73 1/11/2006 MS Thesis to sit at 45°C for at least 30 minutes and gently and carefully spread on a array chip covered up by a clean cover slip.
Sets of microarrays chip slides, containing 5000 human cDNAs each, were obtained and prepared as customised arrays from the Queensland Institute Medical Research (QIMR,
Australia). The chip, in contact with the cocktail Hybridisation solution, is then placed in a
TeleChem/Arraylt hybridisation cassette and immersed in a 45°C water-bath for an overnight incubation. Following the hybridisation incubation (from 15 to 18 hours), the cDNA chip is removed and washed. The array is then ready for scanning using the 428 TM array scanner from Affymetrix that provides hybridisation signals. Signal intensities are processed and quantified via the software package ImageneTM software (Millenium
Sciences, Sydney, Australia).
Hybridisations were repeated using the reverse fluorescein dye label that follow the same protocol described above. 5 sets of signal intensities (Cy3 or Cy5, left panel or right panel) were then obtained from duplicate spots. These were transformed to log-ratios averaged to obtain a value for fold regulation. All clone sequences were obtained through the Entrez nucleotide database of the National Institutes of Health (www.ncbi.nlm.nih.gov/entrez) and gene designations confirmed through the use of local alignment search tools.
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Figure 4.2.2 Microarray Illustration. Example where two total RNA extracts (30-60 μg) of normal white matter (control brain tissue) and MS plaque (test brain tissue) undergo a reverse transcription and a labelling process simultaneously (labels Cy3 and Cy5). The two sets of labelled cDNA are mixed and cohybridised with an array containing thousands of genes. The array is scanned and results are represented by the ratio between the two dyes.
A red dot will express the up-regulation of a known gene in the test tissue compared to the control.
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4.2.3 Real Time PCR
Q-PCR analysis, like array analysis, is a recently developed method for investigating the level of gene expression (or activity) (Klein, 2002). While Q-PCR can be broadly used to describe a number of PCR (amplification) based quantitative molecular biology tools, it is commonly used to describe, real time detection of PCR product. In work related to MS such analysis is comparative because normal tissue, or serum gene expression levels are compared with that of the disease tissue. Q-PCR approaches have the advantage of sensitivity, but require specific gene optimisation and so depend upon the selection of a select number of candidate genes. Q-PCR is relatively cheap and once the primer sets are optimised allows for the high throughput examination of many patient samples.
Representative amplification of individual mRNA molecules can be achieved by reverse transcriptase-polymerase chain reaction (RT-PCR) analysis.
Conventional RT-PCR is however, not suitable for quantitation due to the non-linear
(exponential) nature of PCR product amplification (Kainz, 2000). Several methods have been developed to overcome this deficiency. These include competition-based assays and real time-fluorescent detection of PCR product (Lekanne Deprez et al., 2002). Q-PCR has the advantage of being able to allow researchers to conveniently determine the PCR cycle at which specific product is amplified, in a linear way (Ginzinger et al., 2002). This value is referred to as the cycle threshold (CT) number, where a single CT difference represents a two-fold difference in the amount of specific target. Modern real time PCR detection systems allow for the examination of many different gene products over a broad range of
Tajouri Page 76 1/11/2006 MS Thesis target expression. This type of data can then be used to produce standard curves, derived from known amounts of specific PCR-product, which have the same primer binding sites as that of the specific cDNA target (Bustin, 2000). Standard curve analysis then allows investigators to determine the amount of specific target in an unknown sample (copy number). The values derived can then be used to determine the relative abundance of a particular transcript with respect to others within the same tissue. This methodology is referred to as absolute Q-PCR analysis. Briefly, a successful Q-PCR requires primers that are designed as intron spanning primers. In our laboratory, primers are designed using
Primer express version 2.0 (Applied Sciences). Gene sequences, with exon and intron boundaries, can be found in Ensembl (http://www.ensembl.org/).
PCR was performed using a laboratory made cocktail of SYBR Green mix [1ΧPCR buffer
(50 mM KCl & 10 mM Tris HCl pH 8.3); 200 mM dNTP mix (equimolar dGTP, dCTP, dTTP, dATP) (Amersham–Pharmacia Biotech); 3 mM MgCl2 final concentration, 1Χ
Bovine Serum Albumin (BSA) (New England Biolabs); 15 nM Fluorescein Dye (Bio-Rad);
0.6 x SYBR Green I (Sigma)]. 4 μl of diluted cDNA, Taq DNA polymerase (0.07U/μl)
(Amersham–Pharmacia Biotech) as well as forward and reverse primers (0.5 μM each.)
(Geneworks, Australia) were added to this mix with a final volume of 25 μl. Detection of
PCR product in real time was performed using the Corbett Research Rotor-Gene 3000.
PCR volumes were placed in individual Corbett 0.1 ml strip tubes on –20°C pre-cool metal tube carriers with this order: cDNA, PCR mix. Tubes were closed off and manually handle to allow the whole PCR solution to be at the bottom of the tube. All PCR tubes were placed in the 72 well Rotor within the real time PCR machine. The following cycling conditions were used and entered in the Rotor Gene (Corbett research, Australia) as follows: Cycle 1,
Tajouri Page 77 1/11/2006 MS Thesis 94oC 4 min (x1), Cycle 2, 94oC 30 s, 58-59oC 30-60 s, 72oC 30-45 s (x45). A post-PCR amplification protocol was preset before the run to obtain melt curve representations
(ramping from 50 to 99°C with 1°C ramping every 5 seconds).
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CHAPTER 5
Case Control Association Studies in an MS Australian Population
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5.0 Overview
A Test population comprised of 104 MS genomic DNA samples was used in case control association studies. Variants of two NOS genes, iNOS and nNOS, were investigated with primers designed to flank their functional promoter region. In addition, two nucleotide substitution variations were also investigated and consisted of the C677T MTFR variant and the G158A COMT variant. Finally, three markers within the VDR gene were studied with one marker specifically designed for the 5’ region and two markers for the 3’ region of the VDR gene. Data showed no association of nNOS, iNOS, MTHFR and COMT variants with MS susceptibility. On the other hand, specific association was identified between MS susceptibility and variation of the VDR gene.
5.1 Investigation of a Neuronal Nitric Oxide Synthase Gene (NOS1) Polymorphism in a Multiple Sclerosis Population.
5.1.1 Introduction
MS is a chronic disease affecting the central nervous system (CNS). The disorder is characterised by demyelination associated with an infiltration of mononuclear white blood cells within the CNS. The demyelination leads to an impairment of the action potential conduction along neurons. MS results in neurological impairment characterised by limb weakness, sensory loss, visual alterations, bladder dysfunction and many other complications (Bradley et al., 1978).
Tajouri Page 80 1/11/2006 MS Thesis The aetiology of MS remains unknown, but is thought to be due to polygenetic and environmental factors (The Transatlantic Multiple Sclerosis Genetics Cooperative, 2001).
A significant genetic component is supported by disease concordance of monozygotic twins and dizygotic twins, which shows an incidence of 25% and 4%, respectively, compared to a
0.1% incidence in the overall population (Sadovnick et al., 1993). A recent full genome scan has implicated several chromosomal regions, with the strongest evidence for a susceptibility region at the major histocompatibility (MHC) locus on chromosome 6p21
(Haines et al., 1998). Linkage studies also indicate the presence of an MS locus on chromosome 12q24.2 (The Multiple Sclerosis Genetics Group, 1996). This genomic region is known to harbour the neuronal nitric oxide synthase gene (nNOS) (Redford et al., 1997).
Nitric oxide (NO) production arising from nNOS has been involved in the pathophysiology of several disorders of the brain (Xing et al., 2002; Heales et al., 1999; Iadecola et al.,
1997). NO has been shown to be toxic to oligodendrocytes and to induce axonal degeneration (Mitovic et al., 1994), (Kapoor et al., 1999). Also, nNOS can be induced in response to nerve injury (Ikeda et al., 1999). An increased concentration of NO degradation product, nitrate, is found in cerebrospinal fluid (CSF) of MS patients
(Giovannoni et al., 1998). Also, within active MS lesions intense nitrotyrosine residues are found as indicated by the presence of the oxidised agent, peroxynitrite (Liu et al., 2001).
Furthermore, in an MS-like disease model, Experimental Allergic Encephalomyelitis
(EAE) mice, NO scavengers have been shown to decrease the severity of the EAE condition (Giovannoni et al., 1998). Nitric oxide is also known to be a modulator of neuronal function affecting the release of neurotransmitters and playing a role in long-term potentiation, as well as long-term depression (Prast et al., 2001). Interestingly, a 5'- flanking region immediately upstream of the starting region of nNOS gene has been found Tajouri Page 81 1/11/2006 MS Thesis to be associated with Parkinson’s disease (Lo et al., 2002). Although the nNOS gene has not been found to be associated with MS in multiplex Swedish families (Modin et al., 2001 and Xu et al., 1998), we present a study investigating whether an nNOS gene polymorphism is associated with MS in an Australian population.
5.1.2 Materials and Methods
5.1.2.1 Subjects
The study protocol was approved by Griffith University’s ethics committee for experimentation on humans. The association population consisted of 104 MS-affected individuals and 104 controls, matched for ethnicity (Caucasian), sex and age (+/- 5 years).
The MS population was obtained from patients from the Multiple Sclerosis Clinic at the
Royal Brisbane Hospital, all from the South East Queensland region. The MS population consisted of 75% females and 25% males and were subdivided into 3 clinical courses:
Relapsing-Remitting MS (RR-MS), Secondary Progressive MS (SP-MS), Primary
Progressive MS (PP-MS) with frequencies of 40%, 36%, 24% respectively. The control group was also obtained from the South East Queensland region through the Genomics
Research Centre, Southport, with each control age (+/- 5 years), sex, and ethnicity matched to the affected population. All individuals gave informed consent before participating in the research. Genomic DNA was extracted from peripheral blood using a standard salting- out protocol (Miller et al., 1988).
5.1.2.2 Genotyping
Tajouri Page 82 1/11/2006 MS Thesis Primers and PCR conditions for the dinucleotide repeat of nNOS have been described by
Xu et al., 1998. Primers were 5’-CCT GCG TGG CTA CTA CTA TC-3’ and 5’-AGA
CGT CGC AAC CCT CAT TA-3’. Primers were purchased from GeneWorks. Optimal
PCR conditions consisted of 95°C for 1 min, 55°C for 40 s and 72°C for 1 min with 30 cycles using a PCR thermocycler machine (Gene Amp PCR System 9700; Applied
Biosystems). The fragment containing the dinucleotide repeat was amplified and run on an ethidium bromide stained 2% agarose gel. Capillary electrophoresis was performed on an
ABI 310 Genetic Analyser. Results were analysed using GENOTYPER® software (version
2.1; PE Biosystems). The accuracy and reproducibility of automated sizing of the fragments were confirmed by randomly chosen repeated analyses of identical samples.
5.1.2.3 Statistical Analyses
The CLUMP program was used to derive a chi-square (χ2) value and P-values simulated using the Monte Carlo approach. From this analysis it is possible to determine whether there is a significant difference between allele frequencies in cases and controls. Monte-
Carlo simulation, as opposed to the standard chi-squared distribution, was used to estimate significance as the number of alleles is large and the corresponding contingency table sparse (many cells <5 expected). The CLUMP program generates two statistics of importance, the normal chi-squared (T1) which is derived using the raw 2-by-m table or the chi-squared for the “clumped” 2x2 table (T4) in which columns of the original table are clumped to maximise the chi-squared value. The CLUMP program was run over 5,000 simulations to estimate a P value for this analysis.
Tajouri Page 83 1/11/2006 MS Thesis Additionally, an analysis using the Wilcoxon Mann Whitney test was performed. This method uses a ranking approach to determine whether the allele distributions of the groups are statistically different. Significance for this test was also estimated using the Monte
Carlo simulations as the standard assumptions for performing a Wilcoxon Mann Whitney test were also violated due to the large numbers of alleles. For both analyses, an α = 0.05 significance level was used. Power estimates suggested that if an allele of frequency 0.15 were to confer a modest two-fold increase in relative risk of multiple sclerosis, and assuming near complete linkage disequilibrium between this allele and the direct MS- influencing allele, the case and control groups used in this study were of sufficient size to have ≥ 80% power to detect an association at the 0.05 level (Schork et al., 2002).
5.1.3 Results
To determine whether a dinucleotide polymorphism of nNOS (Table 5.1.3-A) was associated with susceptibility to MS, allelic data from 104 MS cases and 104 controls was analysed. In this Australian population, thirteen alleles of this polymorphism were identified with sizes ranging from 182 – 210 bp. Controls displayed a heterozygosity value of 0.86, which is consistent with previously published heterozygosity values for this polymorphism. The allele distribution (Table 5.1.3-B) showed that allele 10 was the most prevalent allele in both groups (~33%). We compared the NOS1 variant data of our MS control group with the control group of a similar MS case control study in Sweden (Modin et al., 2001). This comparison indicated that the allele frequency distributions were very similar despite the different ethnic backgrounds of the samples (χ2 = 10.2, P = 0.54).
Tajouri Page 84 1/11/2006 MS Thesis Allele frequency distributions of MS cases and controls were compared using the χ2 test to determine whether an association exists between the polymorphism and the disease. This analysis, using Monte Carlo simulations implemented in the CLUMP program, produced a
T1 χ2 value of 5.628 with a simulated P value of 0.962 and a T4 χ2 of 2.573 with a simulated P value of 0.9402. The T4 statistic was achieved by clumping alleles 1, 2, 3, 8 and 13 together and comparing this to the clumped remaining alleles. This analysis indicates that the nNOS variant does not confer an altered effect on MS (OR(max) = 1.41,
95% CI: 0.926 – 2.15). Rank analysis also indicated that allelic distributions were not significantly different between test groups (Z = -0.868, P = 0.377). Stratified analyses testing for a gender-specific relationship between MS and nNOS and comparisons of a specific clinical course group were also negative for association (P > 0.05).
Table 5.1.3-A. NOS1 Summary
Polymorphism Protein Gene Locus Region Heterozygosity (n =)# Type nNOS NOS1 12q24 5’flanking region 0.86 [(GT)nA(TG)m] 13
# of alleles
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Table 5.1.3-B. Allele Sizes and Frequencies of NOS1 Dinucleotide Polymorphism in MS
Cases and Controls
Size MS Cases Control
Allele (bp) Count Frequency Count Frequency
1 182 46 0.25 36 0.196
2 184 9 0.049 8 0.043
3 190 1 0.005 0 0
4 192 32 0.174 35 0.19
5 194 2 0.011 5 0.027
6 196 1 0.005 2 0.011
7 198 2 0.011 3 0.016
8 200 21 0.114 19 0.103
9 202 7 0.038 11 0.06
10 204 59 0.321 62 0.337
11 206 1 0.005 1 0.005
12 208 1 0.005 1 0.005
13 210 2 0.011 1 0.005
χ2 analysis revealed no significant difference between MS cases and the control group.
(CLUMP T1 χ2 = 5.628, P = 0.962, T4 χ2 = 2.573, P = 0.9402)
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5.1.4 Discussion
MS aetiology remains unknown but evidence from several studies suggests a genetic component may be influencing disease susceptibility (Bell et al., 1996), (Ebers et al.,
1996). NOS isoenzymes are encoded by three genes: NOS1 (neuronal NOS) on chromosome 12 (12q 24.2), NOS2 (macrophage inducible NOS) on 17 cen-q12 and NOS 3
(endothelial NOS) on 7 q35-36. NOS1 and NOS 3 are constitutive enzymes and calcium dependent whereas NOS2 is an inducible protein and calcium independent. NO is produced by neurons and by infiltrating macrophages within MS lesions. In the present work, we studied a dinucleotide repeat polymorphism in the nNOS gene, in patients with different subgroups of MS and compared it with the genotypes of healthy controls that had no history of MS.
This study indicated no association of the tested nNOS polymorphism in an Australian MS population. Our findings support those obtained for an ethnically-different Swedish population (Modin et al., 2001, Xu et al., 1998). Despite these findings, it is still possible that NOS is implicated in MS susceptibility. The gene nNOS has been shown being induced in response to nerve injury and in the case of MS, multiple studies show axonal damage in this pathology (Ferguson et al., 1997, Ozawa et al., 1994, Trapp et al., 1998). It has been shown that NO production within MS plaques is capable of producing neoantigens on proteins due to direct S-nitrosylation of cysteine residues. The emergence of new epitopes can lead to the presence of antibodies, which have been found in patients with different clinical forms of MS (Boullerne et al., 1995). Hence, although our study does not
Tajouri Page 87 1/11/2006 MS Thesis support a role for the tested neuronal NOS genetic variant in this disorder, NO may play a role in MS pathology.
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5.2 Investigation of an Inducible Nitric Oxide Synthase Gene (NOS2A) Polymorphism in a Multiple Sclerosis Population.
5.2.1 Introduction
MS is a serious disabling neurological disorder affecting young Caucasian individuals, with an age of onset typically ranging from 18 to 40 years. A high prevalence accounts for with a ratio of 2 to 3 MS cases (Wienshenker et al., 1994]. With the exception of trauma accidents, MS remains the most frequent cause of neurological disability in young adulthood. The central nervous system (CNS) in MS is affected with plaque areas of myelin degeneration as a result of inflammatory events. The disease has three clinical course namely relapsing-remitting MS (RR-MS), secondary-progressive MS (SP-MS), and primary-progressive MS (PP-MS) (Storch et al., 1997). Studies indicate that MS has a genetic component with 25% of monozygotic twins developing the disease compared to only 4% in dizygotic twins (Sadovnick et al., 1993). The HLA gene complex has been shown to be associated with MS (Fogdell-Hahn et al., 2000), but the HLA contribution does not appear to explain all the susceptibility. Other genes have been found to be related with disease severity including the interleukin-1 receptor antagonist (IL-1ra) gene (Crusius et al., 1995), and Fc-receptor (FcγR) genes (Myhr et al., 1999).
Nitric oxide (NO) is a free radical agent with wide biological functions. It is produced by a group of enzymes called nitric oxide synthase (NOS). NOS catalyses the production of NO and L-citrulline from L-arginine, O2 and NADPH. There are three isoforms of NOS: neuronal NOS (nNOS), endothelial NOS (eNOS) and inducible NOS (iNOS). The last Tajouri Page 89 1/11/2006 MS Thesis isoform is a calcium independent enzyme responsible for producing high output and long- lasting release of NO, exceeding the NO production level of nNOS and eNOS isoforms.
Expression of iNOS is under the regulation of several cytokines such as interferon Gamma
(IFN-γ), Tumour necrosis factor (TNF-α) and Interleukin 1 beta (IL-1β) (Fostermann et al.,
1995) and its function is part of the macrophage-mediated response to infectious agents.
Activated macrophages residing within MS brain lesions have been demonstrated
(Bashalov et al., 1999). Within the cerebrospinal fluid (CSF), NO products have been found at a higher concentration in MS patients compared to healthy control subjects
(Nazliel et al., 2002). Furthermore, increased iNOS activity has been detected in the CSF of MS patients with high NO concentration levels correlating with disease activity
(Calabrese et al., 2002; Danilov et al., 2003). In animals with experimental allergic encephalomyelitis (EAE), a model of MS, increased CNS mRNA levels of iNOS have been demonstrated along with high levels of cytokines, particularly involved in iNOS activation
(Okuda et al., 1995). Interestingly, this up-regulation of iNOS in EAE is concomitant with a decrease in Ca2+-dependent NOS activity of eNOS and nNOS (Teixeira et al., 2001). In a human MS study, iNOS mRNA and iNOS enzymatic activity have been detected in MS plaque lesions (Liu et al., 2000). Inducible NOS activity resides in activated and differentiated monocytes in MS patients suggesting a role for monocyte iNOS in the autoimmune response underlying disease pathogenesis (López-Moratalla et al., 1996). The activity of iNOS has detrimental effects on oligodendrocytes, cells responsible for the myelination of neurons in the CNS (Merryl et al., 1993).
Nitric oxide might play a critical role in the pathogenesis of MS, and alterations of the iNOS gene could possibly have an impact on the disease. The human iNOS (NOS2A) gene has been localised to chromosome 17q11-2-q12, a locus close to a region linked with MS Tajouri Page 90 1/11/2006 MS Thesis on chromosome 17q21-q22 (GAMES and the Transatlantic Multiple Sclerosis Genetics
Cooperative, 2003). The gene consists of 27 exons and is about 40 kb in length (Xu et al.,
1996). To determine the possible involvement of polymorphisms of iNOS in the pathogenesis of MS, a bi-allelic tetranucleotide polymorphism in the promoter region of the human iNOS gene has been examined by employing an association study approach in a group of MS patients and age/sex-matched controls.
5.2.2 Materials and Methods
5.2.2.1 Subjects
The study protocol was approved by Griffith University’s Ethics Committee for experimentation on humans. The case-control sample consisted of 101 MS patients and 101 healthy controls, matched for ethnicity (Caucasian), sex and age (+/- 5 years). The MS patients were recruited from the Multiple Sclerosis Clinic at the Royal Brisbane and
Women’s Hospital, all from the South East Queensland region. The MS group consisted of
74% females and 26% males and was subdivided into 3 clinical subtypes: RR-MS, SP-MS and PP-MS with frequencies of 41%, 35%, 24% respectively. The control group was also obtained from the South East Queensland region through the Genomics Research Centre,
Southport, with each control age (+/- 5 years), sex, and ethnicity matched to the affected population. All individuals gave informed consent before participating in the research.
Genomic DNA was extracted from peripheral blood using a standard salting-out protocol
(Miller et al., 1988).
Tajouri Page 91 1/11/2006 MS Thesis 5.2.2.2 Genotyping
DNA was extracted from frozen whole blood by a standard salting out procedure and used as a template to generate polymerase chain reaction (PCR) products for genotyping. Within the 5’ –flanking DNA of the iNOS gene there is a AAAT/AAAAAT repeat sequence extending from –756 bp to –716 bp 5’ to the main TATA-directed transcription initiation site (Nunokawa et al., 1994). Primers specific for this bi-allelic tetranucleotide repeat polymorphism located between –891 to –575 bp of the iNOS gene were used to perform
PCR (5’-TGG TGC ATG CCT GTA GTC C-3’ for the forward primer and 5-GAG GCC
TCT GAG ATG TTG GTC-3’ for the reverse primer) (Bellamy and Hill, 1997). They were purchased from GeneWorks. The forward primer was fluorescently labelled with 5- carboxyfluorescein (FAM) dye. The PCR was performed with a PCR thermocycler machine (Gene Amp PCR System 9700; Applied Biosystems) with the following singleplex reaction: 1 unit of Taq polymerase, 0.2 µM of each primers, 7.5 µL of Buffer
(MasterAmpTM 2X PCR PreMix K), 25 ng of genomic DNA made to a final volume of 15
µl with sterile distilled water. The cycle parameters were as follows: 1 cycle at 94°C for 4 min, followed by 40 cycles for 1 min at 94°C and 1 min at 60°C, and 1 cycle for final extension for 2 min at 72°C.
All PCR products were then electrophoresed in Ethidium-bromide-stained 2% agarose gels.
Capillary electrophoresis was performed on an ABI 310 Genetic Analyser. Results were analysed using GENOTYPER® software (version 2.1; PE Biosystems). The accuracy and reproducibility of automated sizing of the fragments were confirmed by randomly chosen repeated analyses of identical samples.
Tajouri Page 92 1/11/2006 MS Thesis 5.2.2.3 Statistical Analysis
Allele and genotype frequencies were compared using standard chi-square (independence) analysis and the Fisher’s exact test, implemented in the SPSS program. Power estimates indicated that if the iNOS tetranucleotide polymorphism were to directly confer a two-fold increase in relative risk of MS, the case and control groups used in this study were of sufficient size to have > 80% power to detect a significant association at the 0.05 level.
5.2.3 Results
The sizes of the DNA fragments amplified for the iNOS variants were 313 bp and 317 bp corresponding to the two alleles: no insertion (n) and insertion (i). Results for genotype and allele frequencies are provided in Tables 5.2.3.A-D. Genotype frequencies for the control and the MS groups conformed to Hardy-Weinberg equilibrium expectations reducing the risk of error during genotyping. The proportion of the alleles for the control population was similar to others found in independent studies (Lea et al., 2001) and Modin et al., 2001).
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Table 5.2.3.A Genotype Frequencies of iNOS Insert in Australian Multiple Sclerosis
Patients and Controls
Genotype Control (n=101) % MS (n=101) % P-Value*
n/n 84 83.2 75 74.3
n/i 17 16.8 24 23.8 0.15
i/i 0 0 2 2
Allele n = no AAAT insert; i= presence of the AAAT insert;
* Fisher’s exact test
Table 5.2.3.B Allele Frequencies of iNOS Insert in Australian Multiple Sclerosis Patients and Controls
Allele Control (n=202) % MS (n=202) % Statistic
n 185 91.6 174 86.1 χ2=3.03
i 17 8.4 28 13.9 P=0.0819
Allele n = no AAAT insert; i= presence of the AAAT insert;
Results for the Fisher’s exact test and the chi squared analysis indicate that there is no significant difference between MS patients and the control population, either for genotype frequencies (P = 0.15) or for allele frequencies (χ2 = 3.03, P = 0.0819) (Tables 5.2.3.A and
5.2.3.B).
Tajouri Page 94 1/11/2006 MS Thesis Table 5.2.3.C Genotype Frequencies of iNOS Insert for Different Subtypes of MS in
Australian Multiple Sclerosis Patients and Controls
Genotype Control RR-MS1 Control SP-MS2 Control PP-MS3
(n=42) (n=42) (n=35) (n=35) (n=24) (n=24)
n/n 34 30 29 27 21 18
n/i 8 11 6 7 3 6
i/i 0 1 0 1 0 0
Fisher’s exact test P 1 = 0.44, P 2 = 0.77, P 3 = 0.46
Allele n = no AAAT insert; i= presence of the AAAT insert;
Table 5.2.3.D Allele Frequencies of iNOS Insert for Different Subtypes of MS in
Australian Multiple Sclerosis Patients and Controls
Allele Control RR-MS1 Control SP-MS2 Control PP-MS3
(n=84) (n=84) (n=70) (n=70) (n=48) (n=48)
n 76 71 64 61 45 42
i 8 13 6 9 3 6
Fisher’s exact test P 1 = 0.35, P 2 = 0.59, P 3 = 0.49
Allele n = no AAAT insert; i= presence of the AAAT insert;
Results for the Fisher’s exact test showed no significant differences between the subtypes of MS and the control population for both genotype frequencies or for allele frequencies
(Tables 5.2.3.C and 5.2.3.D).
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5.2.4 Discussion
MS is a complex neurological disease, with genetic factors believed to play a significant role in susceptibility. Several genes have been found to be associated with the disease including the Human Leucocyte Antigen (HLA) haplotypes, HLA DRB1*1501,
DQA1*0102, DQB1 0602 (Fogdell-Hahn et al., 2000), the Cytotoxic T lymphocyte- associated antigen-4 (CTLA-4) gene (Ligers et al., 1999) and the osteopontin (OPN) gene
(Niino et al., 2003). Infiltrating macrophages within MS plaque lesions produce NO products generated by iNOS gene activity. In the present study, we investigated a tetranucleotide repeat polymorphism in the iNOS gene promoter in patients with different subgroups of MS and compared it with the genotypes of healthy controls with no history of
MS. This study indicated no association of the tested iNOS polymorphism in an Australian
MS population. Our findings support those obtained in studies on an ethnically-different
Swedish population (Modin et al., 2001) and Spanish population (Blanco et al., 2003), which showed no linkage or association of the same iNOS promoter marker polymorphism with MS. Despite these findings, it is still possible that NOS is implicated in MS susceptibility. NO is a potent mediator of inflammatory responses and can lead to the formation of new epitopes by S-nitrosylation of cysteine residues of myelin proteins in MS plaques. Antibodies for such epitopes were found in different clinical forms of MS
(Boullerne et al., 1995). Furthermore, IFN-β, a drug used for MS therapy, is thought to be a selective inhibitor of human glial iNOS (Hua et al., 1998). Although the iNOS tetranucleotide promoter polymorphism did not show association with MS in the present study, it is possible that an alteration of iNOS gene activity through mutation or polymorphism may still contribute to MS susceptibility. Interestingly, very recent single Tajouri Page 96 1/11/2006 MS Thesis nucleotide polymorphism studies in MS using pedigree disequilibrium test data have provided some evidence for NOS2A (iNOS) involvement, and linkage between a different
NOS2A promoter polymorphism marker (CCTTT)n and MS DR2 positive families was also demonstrated (Barcellos et al., 2003).
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5.3 Investigation of Methylenetetrahydrofolate Reductase (MTHFR) and Catechol-o-
Methyl Transferase (COMT) in Multiple Sclerosis.
5.3.1 Introduction
The chronic CNS inflammatory disease MS is typically affecting young Caucasian individuals. MS pathology is characterised both by patches of white matter degeneration and infiltration of inflammatory cells across the blood-brain barrier (Hemmer et al., 2002).
Several genetic studies have shown potential linkage of several chromosomal loci for MS susceptibility, in particular implicating the major histocompatibility complex (MHC) locus at 6p21 (Multiple Sclerosis group, 1996). Genome screen studies using markers specific to chromosome 22q12-13 have also demonstrated an association of this locus with MS in several different populations (Jonasdottir et al., 2003; Goertsches et al., 2003; Akesson et al., 2002).
A post-synaptic neuronal enzyme, catechol-O-methyl transferase (COMT), is genetically localised to chromosome 22q11.2. COMT is a key enzyme in the catabolic pathway of noradrenaline, a widely used neurotransmitter of the CNS. Previously, a COMT gene haplotype has been shown to be highly associated with schizophrenia (Shifman et al.,
2002). Exon 4 of the COMT gene contains a G to A base pair substitution resulting in a valine-methionine amino acid change at codon 158 of the expressed membrane bound protein. This substitution is responsible for a 3 to 4 fold-decreased activity of the COMT enzyme (Lachman et al., 1996) leading to a reduction of noradrenaline catabolism within synapses. Interestingly, the noradrenaline is postulated to decrease the inflammation Tajouri Page 98 1/11/2006 MS Thesis occurring in neuroinflammatory diseases. Studies on mouse and rodent astrocytes show that noradrenaline induces reduced expression of MHC class II molecules (Frohman et al.,
1988; Frohman et al., 1998). By attenuating the role of APCs such as astrocytes, noradrenaline may confer a natural immunosuppressive protection within normal healthy brain environments, as brains from healthy individuals demonstrate a lower threshold of inflammation compared to other organs (Lassmann et al., 1991). A decreased amount of noradrenaline, which could result from an increase of activity of the COMT enzyme, could thus lead to CNS inflammation in MS patients. Interestingly, a case-control study involving
108 MS patients found that two bi-allelic polymorphisms within the promoter of phenylethanolamine N-methyltransferase (PNMT), a final enzyme involved in the biosynthesis of noradrenaline, were associated with MS (Mann et al., 2002).
The human methylenetetrahydrofolate reductase (MTHFR) gene, composed of 11 exons
(Frosst et al., 1995), has been mapped to the 1p36.3 chromosomal locus, a region found to be positively associated to an Icelandic MS population in a genome wide scan (Jonasdottir et al., 2003). The MTHFR enzyme plays a role in folate metabolism where it catalyses the reduction of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate (Goyette et al.,
1994). Folate is a cofactor in the remethylation of homocysteine, without which, homocysteine levels in the plasma increase. Patients with a deficiency in MTHFR present an elevation of blood and urinary levels of homocysteine. Interestingly, high levels of homocysteine are encountered in MS patients (Besler et al., 2003) and hypercystinuric patients show neuronal loss associated with diffuse demyelination (Rosenblatt et al., 1995).
An elevated concentration of homocysteine in the blood may trigger oxidation of low- density lipoproteins (LDL) extending to lipid peroxidation and atherosclerosis stages
(Hirano et al., 1994). Furthermore, elevated concentration of homocysteine in the blood Tajouri Page 99 1/11/2006 MS Thesis may be also responsible for the sensitisation of neurons to oxidative stress (Kruman et al.,
2000). Oxidative stress is a hallmark of MS (Toshniwal et al., 1992) and anti-oxidant therapy leads to a decrease of severity of MS-like disease in animal models of experimental allergic encephalomyelitis (EAE) (Mohamed et al., 2003). The MTHFR C677T genotype has also been shown to enhance atherosclerosis in Parkinson disease (PND), and other neurodegenerative diseases (Nakaso et al., 2003). The MTHFR C677T is a common mutation of the MTHFR gene with a C to T transition, located at nucleotide 677. This mutation results in the alanine to valine amino acid change leading to reduced activity of the enzyme (mean activity is 65% in the Ala/Val heterozygote and 30% in the Val/Val homozygous state, respectively compared to the mean activity in the Ala/Ala homozygote).
As a result, this MTHFR gene functional mutation may play a possible role in MS susceptibility.
The regulators of homocysteine formation as well as the regulators for noradrenaline formation could have a detrimental effect on the blood-brain barrier and neuroinflammation in MS patients. One could predict that mutations in COMT could result in the alteration of noradrenaline levels thus developing a potential increase of inflammation in the CNS of
MS patients. In addition, this detrimental effect of increased neuroinflammation could be accentuated by a decreased functionality of the MTHFR gene resulting in myelin sheath instability as seen in MTHFR knock-out animals. Neuroinflammation and myelin instability are the two major hallmarks encountered in MS pathology. The aim of this study was thus to investigate whether functional variants of the MTHFR and COMT genes show association with MS in an Australian cohort.
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5.3.2 Materials and Methods
5.3.2.1 Subjects
All participants of the study were unrelated and of UK-Caucasian origin. The study protocol was approved by Griffith University’s Ethics Committee for experimentation on humans. The association population consisted of 104 MS-affected individuals and 104 controls, matched for ethnicity (Caucasian), sex and age (+/- 5 years). The MS population was obtained from patients of the Multiple Sclerosis Clinic at the Royal Brisbane and
Women’s Hospital, all from the South East Queensland region. The MS population consisted of 75% females and 25% males and was subdivided into 3 clinical courses:
Relapsing-Remitting MS (RR-MS), Secondary Progressive MS (SP-MS) and Primary
Progressive MS (PP-MS) with frequencies of 40%, 36% and 24% respectively. The control group was also obtained from the South East Queensland region through the Genomics
Research Centre, Southport, with each control age (+/- 5 years), sex, and ethnicity matched to the affected population. All individuals gave informed consent before participating in the research. Genomic DNA was extracted from peripheral blood using a standard salting- out protocol (Miller et al., 1988).
5.3.2.2 Genotyping
5.3.2.2.1 Genotyping of the MTHFR Gene Variant
Tajouri Page 101 1/11/2006 MS Thesis Genomic DNA (40 ng) was amplified by the polymerase chain reaction, in a DNA Thermal
Cycler (Perkin-Elmer, Norwalk, CT, USA) using the MTHFR primers designed by Frosst et al. [12] (5'-TGA AGG AGA AGG TGT CTG CGG GA-3' for the sense oligonucleotide primer and 5'-AGG ACG GTG CGG TGA GAG TG-3' for the antisense primer, both synthesised by Geneworks) in the following singleplex reaction: 1.75 mM of MgCl2, 1X standard PCR buffer, 0.2 mM of dNTPs, 0.2 μM each of forward and reverse primers, 0.16 g/L of BSA, 1 unit of Taq polymerase (Perkin-Elmer), 40 ng of genomic DNA, made to a final volume of 25 μL with sterile distilled water. The cycle parameters were as follows: 1 cycle at 95°C for 3 min for an initial denaturation, followed by 35 cycles of denaturation for 1 min at 94°C, primer annealing for 1 min at 65°C, primer extension for 2 min at 72°C and a final extension for 10 min at 72°C. This amplification reaction resulted in the synthesis of a 198 bp fragment. The MTHFR gene contains a C to T substitution at nucleotide 677; the alteration created a HinfI site that was used to screen the 104 patients.
For the restriction digestion, 7 units of HinfI, 2 μl of NE buffer II and 2.3 μl of sterile water were added to each extension mix at a final volume of 20 μl and samples digested overnight at 37°C. HinfI did not digest the fragment derived from the C allele, whereas
HinfI digested the fragment of the same length from the T allele into 175- and 23-bp fragments. These fragments were then electrophoresed using a 5% ultra-high-resolution agarose gel, stained with ethidium bromide and visualised under UV light.
5.3.2.2.2 Genotyping of the COMT Gene Variant
Genomic DNA (40 ng) was amplified by the polymerase chain reaction, in a DNA Thermal
Cycler (Perkin-Elmer, Norwalk, CT, USA) using the COMT primers 5’ TAC TGT GGC
Tajouri Page 102 1/11/2006 MS Thesis TAC TCA GCT GT 3’ for the sense oligonucleotide primer and 5’ TGA ACG TGG TGT
GAA CAC CT 3’ for the antisense primer (primers synthesised by GeneWorks). In the following singleplex reaction: 2 mM of MgCl2, 1X standard PCR buffer, 0.2 mM of dNTPs,
0.3 μM each of forward and reverse primers, 1 unit of Taq polymerase (Perkin-Elmer), 40 ng of genomic DNA, made to a final volume of 20 μL with sterile distilled water (Table
5.3.2.2.2.2). The cycle parameters were as follow: 1 cycle at 95°C for 5 min for an initial denaturation, followed by 35 cycles of denaturation for 30s at 94°C, primer annealing for 1 min at 57°C, primer extension for 1 min at 72°C and a final extension for 7 min at 72°C.
This amplification reaction resulted in the synthesis of a 237-bp fragment (Figure 5.3.3.1).
In exon 4 of the COMT gene, a G to A base pair substitution results in a valine-methionine amino acid change at codon 158 of the expressed protein. This Val/Met polymorphism is detectable with a restriction enzyme, Nla III enzyme (R0125S, New England BioLabs), which was used to screen the 104 patients (Table 5.3.2.2.2.2). For the restriction digestion,
2 units of Nla III, 1.5 μl of 10x NEB buffer 4, 0.2 μl of 100x BSA (10mg/ml) and 3.1 μl of sterile water were added to each extension mix at a final volume of 15 μl and samples digested overnight at 37°C. COMT mutation transforms nucleotide G to A, leading to a low (L) activity of the enzyme (containing mutated amino acid methionine). High (H) activity of COMT enzyme (containing wild type valine) in the HH genotype could be a risk factor for MS. The COMT-HH genotype was represented by a single fragment at 114 bp,
COMT-LL genotype by a single fragment at 96 bp and COMT-HL by two fragments at 114 bp and 96 bp (Figure 5.3.3.2). These fragments were then electrophoresed by using a 4% ultra-high-resolution agarose gel, stained with ethidium bromide and visualised under UV light.
Tajouri Page 103 1/11/2006 MS Thesis Table 5.3.2.2.2.1 PCR Condition Summary for COMT Amplification
Reagents Volume 1 reaction (μL) Concentration 1x
10x PCR Buffer 2.0 1x
25mM MgCl2 1.6 2mM
5mM dNTPs 0.8 0.2mM
5μM COMT Forward 1.2 0.3μM
5μM COMT Reverse 1.2 0.3μM
Taq Polymerase (1U/Rxn) 0.2 0.2μM
Water 11.0 Up to 20.0μL
DNA 2.0 40.0ng
Total 20.0
Table 5.3.2.2.2.2 Master Mix for Restriction Enzyme Digest of COMT
Reagents Volume 1 reaction (μL) Concentration 1x 10x NEBuffer 4 1.5 3x 100x BSA 0.2 4x Nla III enzyme* 0.2 2U/rxn Water 3.1 Up to 5.0μL PCR product 10.0 200.0ng
Total 15.0
5’…...CATG▼….3’
*The NlaIII enzyme with recognition site 3’…▲GTAC…....5’ cleaves both COMT alleles producing different sized fragments.
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5.3.2.2.3 Statistical Analysis
The MTHFR C677T and COMT variant genotype and allele frequencies were calculated from observed genotype counts. Genotype and allele frequencies for the MTHFR and
COMT gene variants were initially assessed for association with MS using standard contingency table analysis incorporating the chi-squared test of independence. This analysis produces a χ2 statistic with 1 or 2 degrees of freedom and corresponding P-values for allele and genotype distributions, respectively. Conditional multivariate logistic regression analysis for matched case control groups was performed to estimate the adjusted independent and interactive effects of the MTHFR and COMT genotypes on MS susceptibility. Risk magnitudes were estimated by calculating odds ratios with 95% confidence intervals. The conventional α-level of 0.05 was specified as the significance threshold. All the statistical analyses were performed using SPSS (v10) software.
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5.3.3 Results
1 2 3 4 5 6 7 8 9 10
Figure 5.3.3.1 COMT PCR Product in a 2% Agarose Electrophoresis Gel
Figure demonstrates the expected agarose gel after PCR amplification of a region of the COMT gene containing the G→A single nucleotide polymorphism (SNP). Lane 1 contains a 100-bp DNA marker (FBI Fermentas) to allow determination of band size in lanes 2-9, in which control genomic samples were run. The amplified product was 237 bp. Lane 10 was a negative control. No DNA should be present in this lane; therefore presence of a band in the DNA free lane is indicative of contamination, rendering result invalid.
1 2 3 4 5 6 7 8 9 10 11
Figure 5.3.3.2 COMT Genotyping after NlaIII Digestion. Subsequent digestion of COMT PCR products with 2U of NlaIII enzyme produced a distinct banding pattern for each genotype as shown in Figure 2. The COMT-HH genotype was represented by a single fragment at 114 bp seen in lanes 7 and 8, the COMT-LL genotype by a 96 bp fragment in lanes 3 and 5 and COMT-HL by two fragments at 114 bp and 96 bp seen in lanes 4, 6, and 9-11. A 100-bp marker (MBI Fermentas) was used as a size standard for each gel lane for genotyping of the population. In addition uncut PCR product was run in lane 2 to check for completeness of digestion.
Tajouri Page 106 1/11/2006 MS Thesis Genotypes for the Val/Met COMT polymorphism were determined for 205 unrelated MS sufferers and matched unaffected controls.
Contingency table analysis of the MTHFR C677T frequency data (Table 5.3.3.1) indicated that the T allele was not over-represented in the MS group compared to the control group
(31% versus 33%). Comparison of the genotype distributions showed that the homozygous mutant genotype (T/T) was slightly over-represented in the MS group (16% vs 11%), but this trend did not reach statistical significance (P = 0.15).
For the COMT H/L polymorphism, the allele frequency distributions were not significantly different between any case group and controls (P > 0.05) (Table 5.3.3.2). Comparison of the genotype distributions for this variant also showed that the homozygous high-activity genotype (H/H) was slightly over-represented in the MS group (24% vs 19%), but this trend was also not statistically significant (P = 0.32).
To test for a possible MTHFR*COMT genotypic interaction, conditional multiple logistic regression analysis was performed incorporating data for both the MTHFR C677T and
COMT H/L variants. The risk factor genotype groups were set as “T/T” and “H/H” for the
MTHFR and COMT variants, respectively. The results of these multivariate analyses did not reveal any statistically significant independent or interaction effects (results not shown).
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Table 5.3.3.1 Distribution of MTHFR C677T (Genotype and Allele) Frequencies in MS
Case and Control Groups
Genotypes* Alleles
N Group C/C C/T T/T C T (genotypes)
MS (total) 139 54 (54%) 31 (31%) 16 (16%) 101 63 (31%) (69%)
Control 46 (46%) 44 (44%) 11 (11%) 101 136 66 (33%)
(67%)
*genotype distribution comparison (χ2 = 3.82, 2df, P = 0.15)
Table 5.3.3.2 Distribution of COMT H/L (Genotype and Allele) Frequencies in MS Case
and Control Groups
Genotypes* Alleles
N Group H/H H/L L/L H L (genotypes)
MS 25(24%) 53(51%) 26(25%) 104 102(49%) 106(51%) (total)
Control 19(19%) 62(61%) 20(20%) 101 100(50%) 102(50%)
*genotype distribution comparison (χ2 = 2.26, 2df, P = 0.32)
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5.3.4 Discussion
The aim of this study was to investigate the potential role of functional variants of MTHFR and COMT genes in MS susceptibility within an Australian population. Low activity or deficiency of MTHFR functionality may lead to high levels of homocysteine in the blood.
Interestingly, hyperhomocysteinemia is encountered in MS patients and can result in diffuse demyelination, a hallmark of MS pathology. Demyelination could result from
MTHFR deficiency as observed in MTHFR knock-out animals in which proteolipid protein expression (a myelin stabiliser protein) and osteopontin expression (a early T cell activator protein involved in MS) are down-regulated and up-regulated, respectively. In the present study, the MTHFR C677T mutation was studied in an MS population and although the results showed a slight increase in the number of individuals with the low activity mutant genotype, these results failed to reach statistical significance (P = 0.15).
The second gene investigated was COMT, a gene involved in the catabolism of noradrenaline. Alterations in the CNS levels of noradrenaline, which exerts an immunosupressive effect, may play a role in MS. Supporting this possibility, recent findings have shown that phenylethanolamine N-methyltransferase (PNMT), a gene involved in noradrenaline biosynthesis, was found to be associated with MS in a non-
Hispanic Caucasian American population (Mann et al., 2002). In the present study we investigated a functional variant of COMT in an MS Australian population. Although the
COMT homozygous high-activity genotype (H/H) was slightly over-represented in the MS group, these results also failed to reach statistical significance (P = 0.32). Hence, although both of these genes could be considered potential candidates for involvement in MS Tajouri Page 109 1/11/2006 MS Thesis susceptibility and pathology, the results of our study do not support a significant role for either of the tested functional variants in the disorder.
5.4 Vitamin D Receptor Gene Variant (Taq) is a Risk Factor for Multiple Sclerosis in the Australian Population.
5.4.1 Introduction
Young adult Caucasians are likely to be affected with MS pathology, a chronic CNS inflammatory demyelinating disease. Interestingly, the prevalence of MS is dependent on geographical localisation where very low sunlight exposure is directly linked to higher prevalence (Kurland et al., 1952). MS patients have low serum levels of vitamin D (Nieves et al., 1994) and this condition is reflected by higher rates of bone fractures occurring in
MS patients as opposed to healthy individuals (Cosman et al., 1998). The vitamin D receptor (VDR) is a nuclear receptor that, once bound to 1,25-Dihydroxyvitamin D3 [1,25-
(OH)2D3], leads to transcriptional suppression or activation of genes. Experiments on an
MS animal model, experimental allergic encephalomyelitis (EAE), have shown a complete inhibition of disease course after the injection of the biologically active form 1,25-
(OH)2D3 (Cantorna et al., 1996). This inhibition of disease course was accompanied by enhanced activation of transforming growth factor beta (TGFβ), a known protective factor in EAE mouse models (Cauatin et al., 2001 and Cantorna et al., 1998). To induce EAE, animals are immunised with CNS myelin antigens. If such immunisation is preceded by
1,25-(OH)2D3 intake, this hinders EAE induction (Cantorna et al., 1996). Additionally, in
Swiss Jim Lambert (SJL) mice, the vitamin D analogue, TX527 was shown to decrease
EAE disease severity and to postpone disease onset (Van Etten et al., 1998). Furthermore, Tajouri Page 110 1/11/2006 MS Thesis studies of VDR null mice show that VDR presence is necessary for suppressing EAE activity (Meehan et al., 2002). Considering these data, VDR and its ligand show relative immunosuppressive and anti-inflammatory potential. VDR is expressed in peripheral leucocytes including activated T lymphocytes, which may explain the immunological role of VDR in suppressing EAE. Vitamin D decreases antigen expression by antigen- presenting cells (Tsoukas et al., 1984), inhibits the proliferation of activated T cells (Nataf et al., 1996) and the production of proinflammatory cytokines such as interferon gamma
(IFN-γ) (Muller et al., 1992 and Muller et al., 1996). IFN-γ, a type II interferon, is found in high amounts in sera, plasma and lesions of patients with MS (Shrijver et al., 2004). This interferon activates a transduction cascade involving STAT1 factor and is detrimental in
MS. STAT1 interaction with VDR antagonises vitamin D action (Vidal et al., 2002).
The VDR gene is located on chromosome 12q12-14 and interestingly, a Sardinian genome- wide association study has shown a significant association (P-value, at the 5% level), for the D12S1643 marker (marker for 12q12 position) in MS (Coraddu et al., 2003). In addition, a second genome screen on a Spanish population has also shown association with a P-value for the same marker, D12S1643, of P = 0.000001 (Goertsches et al., 2003). The
VDR gene contains multiple allelic variants some of which may lead to alterations in VDR function. Such variants may contribute to pathologies such as rickets or susceptibility to autoimmune diseases such as primary biliary cirrhosis (PBC) (Peter et al., 1997) and autoimmune hepatitis (AH) (Arndt et al., 2002). Specifically, the VDR gene contains 11 exons, with 3 exons (1a, 1b and 1c) found in the 5` non-coding sequence and 8 exons (2 –
9) encoding the structural portion of the protein (Miyamoto et al., 1997). The gene contains
3 restriction fragment length polymorphisms defined as Taq I, Apa I and Fok I (Graph
5.4.3.b) polymorphism (an ACG to ATG transition) introduces an initiation codon leading Tajouri Page 111 1/11/2006 MS Thesis to the addition of three amino acids to the VDR protein. The Apa I and Taq I polymorphisms are located towards the 3’ end of the VDR gene more precisely within an intron flanked by exons 8 and 9 for Apa I and within exon 9 for Taq I. These VDR polymorphisms have been found to be associated with an increased risk of several autoimmune diseases including systemic lupus erythematosus (Huang et al., 2002) and diabetes type 1 (Skrabic et al., 2003). Interestingly, a Japanese study reported an association of the vitamin D receptor gene b (Bsm I) (Fukasawa et al., 1999) and gene a
(Apa I) alleles with MS (Nino et al., 2000). Prompted by these genetic findings, and the potential significance of the VDR in MS, we decided to investigate three VDR sequence polymorphisms, one from the 5’ region (Fok I) and two from the 3’ region (Apa I and Taq
I), for their potential involvement in MS susceptibility in the Australian population.
5.4.2 Materials and Methods
5.4.2.1 Subject Group
All participants of the study were unrelated and of Caucasian origin. The study protocol was approved by Griffith University’s ethics committee for experimentation on humans.
The association population consisted of 104 MS-affected individuals and 104 controls, matched for ethnicity (Caucasian), sex and age (+/- 5 years). The MS population was obtained from patients from the Multiple Sclerosis Clinic at the Royal Brisbane Hospital, all from the South East Queensland region. The MS population consisted of 75% females and 25% males and was subdivided into 3 clinical courses: RR-MS, SP-MS and PP-MS with frequencies of 40%, 36%, 24% respectively. The control group was also obtained from the South East Queensland region through the Genomics Research Centre, Southport, with Tajouri Page 112 1/11/2006 MS Thesis each control age (+/- 5 years), sex, and ethnicity matched to the affected population. All individuals gave informed consent before participating in the research. Genomic DNA was extracted from peripheral blood using a standard salting-out protocol (Miller et al., 1988)
5.4.2.2 Genotyping
Three RFLPs were genotyped; the Fok I polymorphism in the initiation codon at the 5’ end and 2 polymorphisms (Apa I and Taq I) in the 3’ region of VDR (Graph 5.4.3.B). These polymorphic regions were amplified by standard, unlabelled oligonucleotides followed by restriction enzyme digestion corresponding to each RFLP. Oligonucleotide primers used were for Apa I and Taq I RFLP: forward primer 5’ CAG AGC ATG GAC AGG GAG CAA
G 3’; reverse 5’ GCA ACT CCT CAT GGG CTG AGG TCT CA 3’ and finally for Fok I
RFLP: forward 5’ GAT GCC AGC TGG CCC TGG CAC TG 3’ and reverse 5’ ATG GAA
ACA CCT TGC TTC TTC TCC CTC 3’. For detection of the initiation codon polymorphism, 50–100 ng genomic DNA was amplified with 1 Χ polymerase chain reaction (PCR) buffer, 3 mM MgCl2, 0.2 mM each dNTP, 0.25 µM each primer and Taq polymerase in a 20-µL final volume on a Corbett (Sydney, Australia) PC-960 thermocycler.
Cycles consisted of a 4-min denaturation at 94°C followed by 30 cycles of 94°C for 1 min and 60°C for 1 min then a final extension at 60°C for 7 min. PCR products were digested with Fok I (1 U at 37°C) and electrophoresed on 2% ethidium bromide stained agarose gels. Genotypes were denoted as FF (272 bp), Ff (272, 198, 74 bp) or ff (198, 74 bp). For detection of the Apa I and Taq I RFLPs, amplification required 50–100 ng genomic DNA with PCR Premix Optimisation Buffer E (Epicentre Technologies, Madison, WI), 0.2 µM of each primer and Taq polymerase in a 25-µL reaction volume. Amplification was then performed on a Perkin Elmer (Foster City, CA) thermocycler with a 94°C initial Tajouri Page 113 1/11/2006 MS Thesis denaturation for 4 min followed by 5 cycles of 94°C for 45 s, 64°C for 60 s and 72°C for 2 min; and a further 25 cycles of 94°C for 30 s, 64°C for 30 s and 72°C for 45 s. Following amplification, PCR products were digested with Apa I (2 U at 37°C) or Taq I (2 U at 65°C) and electrophoresed on 2% agarose gels stained with ethidium bromide. Genotypes were determined as AA (740 bp), Aa (740, 515, 225 bp) or aa (515, 225 bp) for Apa I polymorphism and TT (490, 245 bp), Tt (490, 290, 245, 205 bp) or tt (290, 245, 205 bp) for
Taq I polymorphism (dominant alleles denoting absence of restriction site).
5.4.2.3 Statistical Analysis
Genotype and allele frequencies for the VDR variants were calculated from observed genotype counts. As a statistical control for systematic genotyping error and population stratification, the expected genotype proportions according to the Hardy-Weinberg law were calculated and compared to observed genotypes. Genotype and allele frequencies were initially assessed for association with MS using conventional contingency table analyses incorporating the standard chi-squared test for independence. This analysis produces a χ2 statistic with one or two degrees of freedom and corresponding P-values for allele and genotype distributions, respectively. Genetic risk magnitudes (effect size) were estimated by calculating ORs with 95% confidence intervals. Estimated haplotype frequencies between the three VDR variants were determined using EH (Xie et al., 1993) and the measure and strength of linkage disequilibrium (haplotype) was evaluated using a two-locus linkage disequilibrium calculator program (Zhao et al., 2004).
5.4.3 Results
Tajouri Page 114 1/11/2006 MS Thesis The genotype and allele frequencies for all three variants are shown in Tables 5.4.3.1-3. All the three genotypes for the case-control association studies conform to Hardy-Weinberg equilibrium (HWE) expectations (P > 0.05) in both case and control groups. Both genotype and allele frequency comparison for the Taq I variant were significantly different (P =
0.0016 and P = 0.0072, respectively). A significant difference was also observed for the allelic distribution of the Apa I variant (P = 0.04) although the genotype distribution was not significantly different (P = 0.1). Neither the genotype nor the allele frequency distribution was significantly different for the Fok I variant (P > 0.2).
The Taq I and Apa I variants were found to be in very strong and significant linkage disequilibrium (D’ = 0.96, P < 0.0001). Neither of these two variants was in LD with the
Fok variant. The disease associated haplotype A-t was shown to be present in 28% of cases compared to 16% of controls. We decided to focus our subsequent genotypic analyses on the Taq variant only since a) there is near complete LD between Taq and Apa and b) the
Taq I variant is exonic and c) this variant yielded the strongest independent association with the MS. For the entire case control group, comparison of the T/t-t/t genotypes combined against the T/T genotype yielded an OR of 2.35 (95% CI: 1.29 – 4.27, P = 0.0048).
Analysis of this genotype composition in the clinical subtypes separately (Graph 5.4.3.A) indicated that the association of the Taq I variant is with the SP and PP subtypes specifically (OR >3, P < 0.05).
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Table 5.4.3.1 Distribution of VDR Taq I Variant (genotype and allele) Frequencies in MS
Case and Control Groups
Genotypes* Alleles#
N Group T/T T/t t/t T t (genotypes)
Total MSa 27 (26%) 57 (55%) 20 (19%) 104 111 (53%) 97 (47%)
Controlb 42 (45%) 40 (43%) 11 (12%) 93 124 (67%) 62 (33%)
*Genotype distribution comparison for total MS (χ2 = 8.27, P = 0.016), #allele distribution comparison for total MS (χ2 = 7.22, P = 0.0072) a Hardy-weinberg equilibrium P = 0.302 b Hardy-weinberg equilibrium P = 0.756
Table 5.4.3.2 Distribution of VDR Apa I Variant (Genotype and Allele) Frequencies in MS
Case and Control Groups
Genotypes Alleles
N Group A/A A/a a/a A a (genotypes)
Total MSa 35 (34%) 55 (53%) 14 (13%) 104 125 (60%) 83 (40%)
Controlb 23 (23%) 54 (54%) 23 (23%) 100 100 (50%) 100 (50%)
*Genotype distribution comparison for total MS (χ2 = 4.604, P = 0.1), #allele distribution comparison for total MS (χ2 = 4.2, P = 0.04) a Hardy-weinberg equilibrium P = 0.295 b Hardy-weinberg equilibrium P = 0.424
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Table 5.4.3.3 Distribution of VDR Fok I Variant (genotype and allele) Frequencies in MS
Case and Control Groups
Genotypes Alleles
N Group F/F F/f f/f F f (genotypes)
Total MSa 47 (48%) 40 (41%) 11 (11%) 98 134 (68%) 62 (32%)
Controlb 34 (37%) 48 (51%) 11 (12%) 93 116 (62%) 70 (38%)
*Genotype distribution comparison for total MS (χ2 = 2.69, P = 0.26), #allele distribution comparison for total MS (χ2 = 1.52, P = 0.218) a Hardy-weinberg equilibrium P = 0.577 b Hardy-weinberg equilibrium P = 0.337
Graph 5.4.3.A Odds Ratios for the Clinical Subtype Groups Compared to Controls. The T/t-t/t Genotypes Combined versus T/T.
12 11 10 9 8 7 6
Odds Ratio Odds 5 4 3 2 1 0 RR SP PP MS Clinical Subtype
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Graph 5.4.3.B Restriction Polymorphism of VDR DNA Sequence
Fok I Bsm I -Apa I Taq I
5’ 3’
1a 1b 1c 2 3 4 5 6 7 8 9
Exons of VDR gene DNA sequence are represented by squares.
5.4.4 Discussion
The aim of this study was to investigate three sequence polymorphisms in the VDR gene, one from the 5’ region and two from the 3’ region, for their involvement in MS susceptibility within an Australian cohort. The 3 polymorphisms investigated were distinguishable by Fok I, Apa I and Taq I restriction enzymes and genotyped in 104 MS patients and 104 matched controls. Taq I is localised in exon 9 of the VDR gene with a T/C nucleotide substitution (ATT to ATC) although this doesn’t result in amino acid sequence change from codon 352 (isoleucine). However, the presence or absence of Taq I restriction sites has been found to be associated with variable mRNA stability of VDR (Morrison et al., 1994).
In this present study, we report a strong positive association of the Taq I VDR marker in
MS susceptibility. Both genotype and allele frequency distributions for the Taq I variant were significantly different between the MS and control populations. The allelic association
Tajouri Page 118 1/11/2006 MS Thesis was observed to be more significant than the genotypic association. These findings demonstrate that the rarer allele (t) is more predominant in MS cases than in controls.
Moreover, these results suggest that those who carry the t allele are at least 2 times more likely to have MS than those who do not carry this allele. Further analysis of the clinical subtypes of MS indicates that the association with the Taq variant is derived primarily from the progressive clinical subtypes (SP–MS and PP–MS) and that the risk of progressive MS is increased 3 fold for t allele carriers.
The second VDR marker investigated, Apa I, was also found to be associated with MS.
Apa I allele frequency distribution comparison was significant at the 0.05 level with a predominant susceptibility for the A allele in MS. Interestingly, allele A was found associated with the progressive subtypes of MS (SP–MS and PP–MS). Both positive marker Taq I and Apa I variants were found to be associated with MS with a stronger susceptibility role for the functionally associated variant Taq I. The Taq I and Apa I variants were found to be in strong and very significant linkage disequilibrium (D’ = 0.96,
P < 0.0001). This strong LD has been observed in several other studies (Curran et al.,
1999). Therefore we suggest that the Taq I variant, representing a tag single nucleotide polymorphism for this haplotype, should be the only variant requiring genotyping in future disease- association studies of this region of the VDR gene. Neither of these 3’ variants was in LD with the Fok I variant. Thus, the LD breakdown among the VDR variants has dissociated the susceptibility haplotype (A-t) of the 3’ region from the 5’ Fok I variant region.
A similar MS case-control study, examining the Apa I marker, was previously undertaken by a Japanese team (Nino et al., 2000 as ref 23). The authors used 77 Japanese MS Tajouri Page 119 1/11/2006 MS Thesis patients and 95 controls and found a significant association for Apa I allele distribution (P =
0.032) (Bell et al., 2001). Additionally they studied Bsm I VDR gene variants in MS. This other 3’ untranslated region (UTR) marker of the VDR gene was also found to be associated with MS, both for the allele frequency distribution (P = 0.014) and for the genotype frequency distribution (P = 0.049). Further data analysis showed that both the
Bsm I and Taq I markers are also in strong LD (P < 0.0001) (Wilkinson et al., 2000).
Consequently these three markers are all in LD and clustered possibly as a common susceptibility haplotype (BAt) for MS. A Canadian team has also investigated VDR markers in MS, specifically Apa I and Taq I markers for the VDR gene. However, they reported no preferential transmission of any alleles to affected offspring using a family- based association cohort (Taq I and Apa I; P > 0.05) (Syeckley et al., 2000). The genetic heterozygosity (Hu) of the markers based on the genotypes of the parents was very low (Hu
Taq I = 0.488 and Hu Apa I = 0.447). Reliant upon high heterozygosity values, the use of bi- allelic markers for family-based association analyses (e.g. TDT) will diminish the power to identify susceptibility allele transmission.
MS pathology is associated with the invasion of peripheral mononuclear blood cells into the CNS. These cells induce local inflammation in the CNS with increased synthesis of proinflammatory cytokines, major histocompatibility complex molecules, and oxidative molecules leading to CNS demyelination. Vitamin D inhibits T cell proliferation and IFN-
γ cytokine expression (Bhalla et al., 1986). Vitamin D activation of VDR leads to the transcription of responsive elements of several genes. Certain VDR haplotypes could lead to the reduced expression of VDR protein and alter VDR-induced transcription in the CNS.
Vitamin D is an efficient antioxidant and plays a critical role in control of free radical induced tissue damage, another hallmark of MS pathology. VDR also has important roles Tajouri Page 120 1/11/2006 MS Thesis affecting insulin secretion (Wilson et al., 1992), hormone production (Haschek et al., 1978) including the parathyroid hormone (Manolagas et al., 1987) and also on estrogen biosynthesis with a direct action on the aromatase gene (Kinuta et al., 2000). Of special interest, we have recently undertaken cDNA array-based differential display analysis of MS brain tissues versus healthy control brain tissue (Tajouri et al., 2003). Although our arrays did not contain a VDR cDNA for analysis, results showed a common pattern of activated expression of immunological genes in MS, and interestingly a reduced expression of the insulin receptor gene and insulin-related genes. Of interest, Vitamin D has been shown to prevent reversibly mouse models of type I diabetes (Mathieu et al., 1992). Additional studies show that impaired VDR functionality in mice leads to impaired insulin secretion
(Zeitz et al., 2003). An up regulation of parathyroid hormone receptor gene was also found in MS from these microarray data. VDR-responsive elements are also found in the osteopontin gene, an early T cell activator gene found strongly expressed in MS brains
(Chabas et al., 2001). Taken together, lower amounts of Vitamin D concentrations by inadequate Vitamin D intake or ultraviolet radiation (UVR) exposure could contribute to the pathogenesis of MS, and additionally, presence of specific haplotypes for the VDR gene could increase susceptibility to MS, particularly the progressive forms of MS.
Different geographical latitudes of the Japanese, Canadian and Australian populations could be a factor influencing the differences in Apa I and Taq I data obtained from each study. Low UVR exposure and reduced Vitamin D synthesis correlate with MS geographical prevalence. The MS Canadian population was pooled around the whole country and Canada is situated at latitudes of around 70° to 50°N. The MS Japanese population studied was from the northernmost island of Japan, Okaido, and is located between 42° and 43°N whereas South-East Queensland for the MS Australian population is Tajouri Page 121 1/11/2006 MS Thesis localised at around 25 to 29°S. It would be interesting to further investigate case-control studies of the Taq I VDR marker in extended Japanese populations, in the Canadian population and also in a Tasmanian Australian population (latitude of 43°S for Hobart,
Tasmania).
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CHAPTER 6
Microarray and Real Time PCR Expression Studies in Multiple Sclerosis
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6.0 Overview
Microarray experiments were undertaken using 3 MS chronic active plaques and 2 MS acute plaques. These samples were obtained from SP-MS sufferers and were matched anatomically with sex, age and ethnicity matched white matter controls. The methodology used consisted in a direct cDNA labelling with two different fluorescent dyes (Cy3 and
Cy5) and hybridised to 5000 cDNA chips. All experiments were scanned using an
Affymetrix 428 scanner to provide Tiff file images. Image processing was undertaken and results of fluorescence intensities were represented by the ratio between the two dyes.
Clustering analysis revealed expression differences in MS affected tissue. Some variations were unique to the type of plaque (A and CA). These experiments were preliminary studies and further investigations are required to validate such differential patterns.
Further studies of seven differentially regulated genes were undertaken using Q-PCR analysis. Results of real time PCR showed a significant correlation with results obtained by array analysis. Other candidates (OPN, CAPNS1, PIAS1, STAT1 and ITPKB) were also investigated by Q-PCR analysis and the generation of standard curves for each gene provided accurate fold level expression determinations.
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6.1 Quantitative and Qualitative Changes in Gene Expression Patterns Characterise the Activity of Plaques in Multiple Sclerosis.
6.1.1. Introduction
MS disorder is an autoimmune disease of the CNS, characterised by zones of demyelination and inflammatory plaques (Lucchinetti et al., 2000). Symptoms include limb weakness, sensory loss, visual alterations and bladder dysfunction. MS is one of a number of inflammatory-demyelinating diseases (IDDs), which are characterised by the appearance of lesions that are disseminated in time and space (either restricted or diffuse) (Weinshenker,
1995). Prototypic MS is characterised by an initial disease onset that is often followed by a secondary progressive course. In general terms, acute lesions show an infiltration of lymphocytes, as well as oligodendroglial hyperplasia (Francis et al., 1991). Chronic active plaques, in contrast, possess a rich oligodendrocyte population, and are characterised by a patchwork of inflammatory and ‘silent’ zones, or regions showing some remyelination.
Chronic ‘silent’ plaques show extensive remyelination, and unlike acute and chronic active lesions lack an obvious inflammatory component (Prineas et al., 1993; Raine et al., 1993).
While complex environmental factors play an important role in disease, the inheritance of genetic alterations, particularly those within the Major Histo-Compatibility loci (eg. human leucocyte antigens: HLA-DR-1, HLA-DR-2, and HLA-DR-4), also contribute significantly to the specific characteristics displayed by each plaque type (Raine et al., 1981; Kantarci et al., 2002; Wienshenker et al., 1998). Genetic studies have also revealed the potentially important contribution of non-MHC loci to disease progression. Significant associations Tajouri Page 125 1/11/2006 MS Thesis between MS clinical course, susceptibility and inherited mutations have been identified for the following loci: Immunoglobulin (Ig) G (Myhr et al., 1999), Interleukin (IL) –1ra
(Feakes et al., 2000), transforming growth factor (TGF)-β (Green et al., 2001), and apolipoprotein (APO) E (Chapman et al., 2001), and selected glutathione S transferase
(GST) isoforms (Mann et al., 2000).
Recent advances in array hybridisation analysis have allowed the investigation of many thousands of candidate markers of disease simultaneously. This approach has already been used successfully in the identification of the Jagged-Notch-Hes (putative oligodendrocyte differentiation pathway) as a contributor to MS development (Oksenberg et al., 2001, John et al., 2002). However, arrays by themselves have limitations that restrict analysis to particular transcripts based on relative abundance and representation on the array.
Furthermore, while the experimental allergic encephalomyelitis (EAE) models of disease have been used successfully to characterise the role of T- and B-cell markers in MS, such models, by their nature, advance the importance of particular gene pathways, and do not take into consideration the wide variation in clinical symptoms displayed by sufferers of
MS. In contrast, Q-PCR is a robust and sensitive method, which is frequently employed to investigate gene expression differences independent of the absolute level of gene expression (Rose’meyer et al., 2002). However, the need to optimise each assay for particular targets does mean that its usefulness is limited to the investigation of known markers. Putative MS candidate genes, whose altered expression has been specifically investigated by Q-PCR analysis, have included T-cell specific antigens (Muraro et al.,
2003), cytokines (Kahl et al., 2002), and viral RNA (Trottier et al., 2002).
Tajouri Page 126 1/11/2006 MS Thesis In this study, we have employed array hybridisation and Q-PCR analysis to examine quantitative, as well as gross qualitative changes in gene expression that may differentiate inflammatory forms of MS plaques. RNA from plaque tissue was isolated from patients who died with MS and compared with patient-matched normal white matter. The data collected in this way was then used to examine patterns of gene expression that differentiate genes and gene clusters, grouped by designated biological function. The results of this study show a significant correlation in gene expression pattern (P<0.01, ρ=0.73, by
Spearman’s bivariate correlation) for the 69 genes identified as differentially expressed in both acute and chronic active lesions as compared to normal tissue (or 49.6 % of all the
139 genes identified as differentially expressed in MS). However, for these genes the mean
‘fold’ level of gene expression difference was found to be significantly higher in acute plaques, suggesting that symptomatic variation in inflammatory lesions in MS may be the result of overall quantitative, rather than specific gross qualitative differences in gene activity. In this study, SYBR Green I, real time Q-PCR was used to validate the differential expression of array selected clones; and to examine the expression of transcripts that may be present below the level of sensitivity for array analysis. The determinations of ‘fold regulation’, obtained by Q-PCR analysis of 7 array-selected genes, were found to correlate significantly with determinations of fold obtained following fluorescent array analysis, of chronic active and acute plaque tissue.
6.1.2 Materials and Methods
6.1.2.1 Patients and Tissues
Tajouri Page 127 1/11/2006 MS Thesis MS plaques, or aberrant tissue, were obtained post mortem (16.6 ± 7.7 hr) (Table 6.1.1 and
Table 6.1.2). Tissue was classified based on published criteria (Sanders et al., 1993, Bo et al., 1994). Tissue was collected and 7 mm sections were imaged and snape frozen (-
150oC), prior to storage at –80°C. Computerised serial full coronal digital images from each case were used as a guide for dissection of frozen slices; facilitated by high-speed dental equipment. The bottom half of each section was kept for histological classification: necessary for determining demyelinating activity. The mean age at death±SD for MS subjects (S) 1-5 was 53.6 ± 4.5 yr (4 female and 1 male) (Table 6.1.1). Control tissue
(Normal/Non-MS) was obtained and matched to MS plaque tissue by sex, age ±8 yr, ethnicity and anatomical brain localisation. The distribution was as follows: 2-acute lesions and 3-chronic active lesions. All patients were diagnosed with secondary progressive MS
(Table 6.1.2). Out of these samples only one human brain section (HSB) 3131 showed signs of recent hypoxia (Table 6.1.1). All control tissues were obtained from patients that had no past history of neurological disorder and experimental procedures were conducted following ethical guidelines of the National Health Medical Research Council, Australia.
Samples were obtained with ethical consent from the NHMRC Brain Bank, University of
Queensland, Australia and the Human Brain and Spinal Resource Centre, Los Angeles,
USA. All tissue was immediately placed in liquid nitrogen upon dissection, and stored at -
80oC until used. The demyelinating activity of specimens was made available to authors at the completion of array analysis, and all five samples were used in Q-PCR and array hybridisation analysis.
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Table 6.1.1 Histopathology of MS Plaques
Plaque Subject Tissue Timeα Quantity Locationβ Sex Ageγ Type
1 HSB3163 20 h 0.9 g Subcortical WM F CA 57 yr
2 HSB3161 20 h 0.4 g Periventricular WM F CA 51 yr
3 HSB3131 24 h 0.3 g Subcortical WM F CA 53 yr
4 HSB2589 4 h 0.5 g Medial Subcortical WM F A 48 yr
5 HSB2946 15 h 1.1 g Medial Subcortical WM M A 59 yr
α after death; βfrom which control and matched plaque tissue was obtained; and γ of death. WM: White Matter; CA: Chronic Active; A: Acute
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Table 6.1.2 Histopathology and Clinical Details of MS Tissue
Tissue Duration (MS Type) Cause χ Lesion Pathology of illnessy
70-80% axonal loss, mild associated gliosis and
HSB3163 macrophage activity. Also, perivascular lymphocytic 1 Found dead 14 (SP) infiltration associated with the plaque and the
adjacent white matter.
80-90 % axonal loss. Slight increase in cellularity at
Respiratory the plaque border. Mild associated gliosis and HSB3161 2 insufficiency 19 macrophage activity. Perivascular lymphocytic (SP) cuffings are present. Complete demyelination in
myelin stain sections.
Near complete loss of myelin. Macrophage
HSB3131 associated intracytoplasmic myelin debris. Reactive 3 Found dead 24 (SP) macrophages along focal regions of the plaque
edges.
Marked demyelination, CD68 MHC Class 2 HSB2589 Respiratory 4 30 activated macrophages, deposited evenly throughout (SP) insufficiency the plaque.
HSB2946 Respiratory Marked demyelination and axonal loss and sparse, 5 16 (SP) insufficiency focal chronic perivascular inflammation.
χcause of death yyears
Tajouri Page 130 1/11/2006 MS Thesis 6.1.2.2 RNA Extraction and cDNA Synthesis
The protocol used for the purification of total RNA from plaque and non-plaque tissue (0.3-
1.1 g) was adapted from existing protocols. To maximise the quality of RNA used as probe in array hybridisation each sample was first extracted in phenol-containing Trizol™
(Invitrogen/Life Technologies, CA). The aqueous phase was removed and subjected to a further round of purification, following the protocol outlined in the RNeasy™ Mini Kit
Manual (Qiagen, CA). 1-5 μg of total RNA not used in probe preparation, was also converted to cDNA using 5 U/μL Superscript II reverse transcriptase (RT) (Invitrogen), RT buffer (50 mM Tris-HCl pH 8.3, 75 mM KCl, 3 mM MgCl2), 100 μM dNTP mix
(equimolar dG/C/A/TTP) (Amersham Pharmacia Biotech), 10 μM dithiothreitol (DTT) and
25 ng/μL anchored oligo-dT primer mix [equimolar: 5’-T19(A/C/G)-3’]. Each cDNA pool
(matched control and plaque) was stored at -20oC, until used for Q-PCR analysis.
6.1.2.3 RNA Validation and Probe Preparation
The quality of RNA extracted post mortem from brain tissue can be problematic unless certain precautions are taken (Schramm et al., 1999, Harrison et al., 1997). In our study, one step RT-PCR was performed using published methods to investigate the integrity of extracted post-mortem RNA (Selvey et al., 2001). The following cycling conditions were used: Cycle 1 (x 1): 50oC 30 min; Cycle 2 (x 45): 95oC 30s, 57oC 1min, 72oC 30s; Cycle
3(x 1): 72oC, 4 min. All products were resolved by agarose (2 %) gel electrophoresis. The
6000 Nano Lab Chip™ kit (Agilent Technologies, Ca) in conjunction with the 2100
Bioanalyzer™ (Agilent Technologies) was also used to investigate the integrity of RNA
Tajouri Page 131 1/11/2006 MS Thesis used in probe preparation (Gottwald et al., 2001). Probe was prepared for hybridisation analysis from 10-20 µg of total RNA (plaque and matched control brain tissue) using either
[Cy3]-dCTP or [Cy5]-dCTP fluorescein dyes (Amersham Pharmacia Biotech), following standard methods and using mixed anchored primers (5’-T12VN-3’) (Amersham Pharmacia) and Superscript II RT enzyme.
6.1.2.4 Array Hybridisation
The protocol used for microarray hybridisation follows previously published methods
(Schena et al., 1995). Custom made glass arrays, containing 5000 random genes/cDNAs each (Queensland Institute of Medical Research, Australia), were used. All clones were double spotted to assess hybridisation specificity, and were obtained with gene reference identifiers for independent verification of sequence, using the National Centre for
Biotechnology Database (http://www.ncbi.nlm.nih.gov/entrez). A complete gene list is available at http://www.genomicsresearchcentre.org/ms.html. Following hybridisation (12 h, 45oC), each slide was scanned (428 Array scanner™, Affymetrix), and signal intensity ratios for Cy3/Cy5 used to determine a fold value for the difference in expression between aberrant and control tissue. Over 100 control (house keeping and 3x SSC) spots on each array were used to normalise the fold expression, and to determine the degree of non- specific hybridisation. Each experiment was also repeated with the alternate dye label, and the mean fold determined following statistical validation. Signal intensity ratios for duplicate spots that differed (>2-fold), were excluded from analysis. In order to examine small differences that might be associated with particular gene groups or pathways, all transcripts, were provided with a functional designation based on relationship to disease,
Tajouri Page 132 1/11/2006 MS Thesis from information available through the Online Mendelian Index in Man (OMIM)
(http://www.ncbi.nlm.nih.gov/entrez). With the use of Imagene, Cy5 and Cy3 fluorescent intensities on each array slide were subjected to spot filtering and normalization. After filtering, spots that were flagged using the ImaGene software were excluded from further analysis. Flagging refers to the marking of spots on the array that are removed and this is processed within Imagene 4.2 version. In addition, local background intensity normalization was undertaken for each slide. Both Cy5/Cy3 normalized ratios were used to determine the relative gene expression levels in the experimental samples. Measurements from replicate samples were then averaged after normalization.
6.1.2.5 Q-PCR Analysis
Primer design, and optimisation of MS array-selected genes, followed protocols previously developed within this laboratory (Rose’meyer et al., 2002). Where possible primers for each selected gene were designed to be intron spanning, so that genomic DNA could be used as a positive control template (Table 6.1.3). All Q-PCRs were performed in 96 well
Bio-Rad iCycler iQ plates (Bio-Rad, Sydney, Australia), and contained 15 nM Fluorescein
Dye (Bio-Rad), 1 x PCR buffer II [50 mM KCl & 10 mM Tris HCl (pH 8.3)], MgCl2 (see
Table 6.1.3), 200 μM dNTPs (equimolar dG/C/T/ATP), 1 x Bovine Serum Albumin (BSA)
(NEB, Beverly, MA); 0.5 x SYBR Green I (Sigma); Taq DNA Polymerase (0.05 U/μL)
(Amersham Pharmacia); as well as forward and reverse primers (0.5 μM each.)
(Geneworks, Australia). The following cycling conditions were used: Cycle 1, 95oC 5min
(x1), Cycle 2, 95oC 30s, 55oC 1 min, 72oC 30 s (x45), Cycle 3, 72 oC, 4 min. Detection of
PCR product in real time was performed using the Bio-Rad iCycler iQ system. All products were resolved at end point using melt curve, and 10 % polyacrylamide gel Tajouri Page 133 1/11/2006 MS Thesis electrophoresis (PAGE). Each determination of fold was conducted from three repeat determinations of cycle threshold (CT) at linearity, which were corrected using 18S rRNA as a loading and house keeping gene control (ΔCT) (Thellin et al., 1999). Comparative differences in gene expression levels were then obtained from the difference between ΔCT
ΔΔCT for control (ΔCTc) and test (plaque) tissue (ΔCTt), or 2- (Livak et al., 2001).
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Table 6.1.3 Primer Sequences
Forward (5'-3') a b c Gene Gene Reference cDNA gDNA MgCl2 Reverse (5'-3')
ATG TGG CCT TTG TCA AGC ACT (EX 6) TF Ref|NM_001063.2| 74 bp 567 bp 3.50 GCT CAT CAT ACT GGT CCC TGT CA (EX 7)
GCT TCC CGT GCA ACC AGT TT (EX 1) GPX1 Ref|NM_000581.1| 70 bp 349 bp 3.50 CTT GAG GGA ATT CAG AAT CTC T (EX 2)
CAG GGA GGC AAG ACC TTC AT (EX 6) GSTP1 Ref|NM_000852.2| 60 bp 237 bp 3.50 GCA GGT TGT AGT CAG CGA A (EX 7)
CAC CCA GCT GGT TTG ACA CT (EX 1) CRYAB Ref|NM_001885.1| 65 bp 1139 bp 3.50 TGA CAG AGA ACC TGT CCT TCT (EX 2)
GGT CCT CAC TTT AAT CCT CTA T (EX 3) SOD1 Ref|NM_000454.1| 99 bp 838 bp 3.50 CAT CTT TGT CAG CAG TCA CAT T (EX 4)
CAG CTT CGA CAC CAT CCA CTT (EX 7) PMM1 Ref|NM_002676.1| 74 bp 441 bp 3.75 TCG GCA AAG ATC TCA AAG TCG T (EX 8)
GGA TCA ACG TGT ACT ACA ACG A (EX 2) TBB5 Ref|NM_006087.2| 102 bp 219 bp 3.75 CAG AAC GGA CAG AGT CCA TGG T (EX 3)
CTT AGA GGG ACA AGT GGC 18S rRNA Gb|U13369.1| 110 bp 110 bp 3.50 ACG CTG AGC CAG TCA GT
a cDNA refers to the length of amplicon. b gDNA refers to the length of the corresponding genomic DNA. c MgCl2 concentration (mM) optimised for Sybr Green I Q-PCR analysis. Ex: exon
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6.1.2.6 Statistical Analysis
SPSS Version 10.1 (PC) was used to collate and analyze all data collected. Standard independent t-test analysis was used to determine whether determinations of fold based array analysis data were statistically significant (P<0.05). Spearman's ρ analysis was used to determine whether the observed correlation in gene expression patterning between pathologies was significant (P<0.05). To investigate whether observed differences in gene expression patterns for genes assigned to different gene groups were significant, Mann-
Whitney, U tests, were used (P <0.05).
Following Q-PCR analysis, the corrected differences in CT (for control and test cDNA:
ΔCTc and ΔCTt) were examined by independent t-test analysis to determine whether the observed difference between them (ΔΔCT) was statistically significant (P<0.05). Pearson's bivariate correlation analysis was also used to determine whether the observed similarities between array and Q-PCR values were significant (P<0.05). In this study, the coefficient of variation (CV) of the values is used to indicate patient variance.
6.1.3 Results
6.1.3.1 Overview of MS Array Hybridisation and Q-PCR Validation
MS plaque (Figure 6.1.3.1.α) and unaffected patient matched brain tissue was isolated.
Total RNA, extracted from both, was then compared using fluorescent microarray hybridisation analysis (Figure 6.1.3.1.β). The mean fluorescence ratio was then used to Tajouri Page 136 1/11/2006 MS Thesis determine the degree of expression compared to normal matched tissue and expressed as the mean fold for each plaque type (chronic active, or acute). In this way, 139 genes were identified as differentially regulated in the 5 inflammatory MS plaques examined in this study (mean ≥1.5-fold). Forty six of the total number of differentially regulated transcripts
(or 33.1 %), represent products that are preferentially regulated in the brain, or that have previously been linked to neurological disease, such as Ninjurin 1 (NINJ1), which promotes axonal growth (Araki et al., 1996), or the brain specific creatine kinase, brain
Creatine Kinase (CKB) (Benger et al., 1991). This suggests that despite the labile nature of
RNA and the variable preservation of the body post mortem (Miller et al., 2003), an adequate representation of neuronal markers, and those potentially significant to disease pathology, were identified following the microarray protocol outlined above.
Sixty-nine of the 139 genes identified as differentially regulated in MS plaques were commonly regulated in either chronic active or acute plaques (Table 6.1.4), and showed a significant correlation (P<0.0001) in the pattern of expression, by Spearman’s ρ correlation
(Figure 6.1.3.1.γ). These 69 were then divided into groups based on function and these functional clusters were investigated to determine specific differences in gene expression between acute and chronic active lesions (Table 6.1.4).
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Figure 6.1.3.1.α Plaque Histology (A) Computerised full colour image of brain section HSB3163, showing regions of MS affect tissue. 1) Plaque, 2) Normal apparent white matter, 3) Non-apparent grey matter, 4) Plaque, 5) Normal apparent white matter, 6) normal apparent grey matter. (B) Microscopic analysis of demyelinating activity Haematoxylin and eosin staining of MS-affected white matter, from typical chronic active plaque (HSB3163). Shown infiltration of stromal cells (eg. leucocytes) from vasculature into the area of the plaque (arrow) (magnification 20x, scale bar 100 μM).
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Figure 6.1.3.1.β Probe Preparation and Fluorescent Hybridisation analysis. (A) Representative agarose (2%) gel electrophoresis of total RNA, isolated from MS plaque tissue and normal tissue post-mortem (prior to DNase I treatment). Lane 1, HSB2589 (20 μg), Lane 2, Normal tissue (20 μg). 28S rRNA (α) and 18S rRNA (β) bands can be identified following denaturing extracted from normal and MS plaque tissue. (B) One step RT-PCR analysis of total RNA from MS plaque RNA, following DNase I treatment. Shown agarose (2%) gel electrophoresis of PCR product. Lane 1, DNaseI treated genomic DNA control; Lane 2, HSB3163 RNA post DNaseI treatment; and Lane 3, normal brain RNA post RNA treatment. Primers used, human β- actin, forward: 5’-ACC CAC ACT GTG CCC ATC TA-3’, reverse: 5’-CGG AAC CGC TCA TTG CC-3’. (C) Representative Agilent™ trace (left) and chromatographic separation (right) of DNaseI treated total RNA from MS brain tissue (HSB3163), and prior to probe labelling: α, 18S rRNA (40 sec); β, 28S rRNA (45 sec). (D) Scatter Plot: Log of relative difference in fluorescence units (ΔRFU), following 5000 gene HSB2589/array analysis. Those cDNAs with a ratio of 1 (line) are not regulated significantly, and are not included in analysis of fold. (E) Result of fluorescent array analysis (HSB2589), following hybridisation with fluorescently labelled probe. Cy3 (green), Cy5 (red). Each clone spotted twice on the array aids in differentiating specific and non-specific hybridisation events. Results of array analysis: χ. MBP, 63.1-fold up- regulated in acute tissue; and δ. ITGAE, 145.9-fold down-regulated in acute tissue.
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Figure 6.1.3.1.γ Osteopontin Real Time PCR. (A) Representative real time Q-PCR trace (iQ iCycler System) of PMM1 cDNA (HSB3163) showing product amplification. Shown: CT at linearity (arrow); Trace 1, 18S rRNA control tissue (CT, 15.9); Trace 2, 18S rRNA MS tissue (CT, 15.6); Trace 3, PMM1 control
(CT, 19.5); and Trace 4, PMM1 plaque (CT, 21.2). ΔCTPMM1 control = 4, ΔCT PMM1 plaque = 5.6, ΔΔCTPMM1 = 1.6, Putative fold determination (21.2) = 2.3-fold up. (B) Representative trace following melt curve analysis of PMM1 product at end point: 18S rRNA (85oC), and PMM1 (94oC). (C) 10 % PAGE, PMM1 PCR product at end point: Lanes 1 & 3 cDNA control; and Lanes 2 & 4, cDNA MS plaque; Lanes 5 & 6, no template control (H2O); Lane 7, genomic DNA, positive template control. α. PMM1 genomic PCR product (441 bp); β, PMM1 PCR product; and χ, 18S rRNA cDNA product (74 bp).
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Seventy (54.0 %) of the 139 genes identified as differentially regulated in MS were uniquely regulated in either chronic active or acute plaques (Table 6.1.5 and Table 6.1.6).
Seven genes, identified as differentially regulated in MS inflammatory plaques (chronic and active) following array analysis, were then selected for real time Q-PCR analysis (Table
6.1.3). Primers were designed for these array-selected genes and were optimised for the use of SYBR green I detection. Comparative Q-PCR analysis was then performed to examine differential gene expression in MS plaque and non-plaque tissue for acute and chronic active lesions. Following normalisation with 18S rRNA as a ‘house keeping gene’ control, the CT value was used to determine the degree of fold regulation. When the results of Q-PCR analysis were compared with array determinations of fold, a significant (P<0.01) correlation was identified (Table 6.1.7). A comparison of array and Q-PCR determinations of fold is provided in Table 6.1.7.
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6.1.3.2 Genes Identified by Array Analysis as Differentially Regulated in both Chronic Active and Acute Plaques
Table 6.1.4 Genes Identified in both Acute and Chronic Active Plaques GENE OMIM CAα A LOCUS FDβ INTEGRIN, -α-E (ITGAE) 604682 1000.0↓ 145.9↓ 17p13 ADH CALPONIN 2 (CNN2) 602373 81.1↓ 333.3↓ 21q11.1 ADH VILLIN 2 (VIL2) 123900 1.7↑ 3.5↑ 6q25.2-q26 ADH CAP PROTEIN, ACTIN, α-1 (CAPPA1) 601580 333.3↓ 28.6↓ 1 CYT DYNACTIN 2 (DCTN2)# 607376 125.0↓ 28.5↓ 12q13.2- CYT MICROTUBULE-ASSOCIATED PROTEIN, RP/EB FAMILY, MEMBER 3 605788 9.4↓ 55.6↓ 2p23.3-p23.1 CYT (MAPRE3)# TUBULIN, β-5 (TBB5)# 602662 2.1↑ 16.3↑ 19p13.3 CYT FLIGHTLESS I, DROSOPHILA, HOMOLOG OF (FLII)# 600362 107.9↓ 6.3↓ 17p11.2 DEV TRANSFERRIN (TF) 190000 2.9↑ 32.7↑ 3q21 DEV PROTEIN-TYROSINE PHOSPHATASE, RECEPTOR-TYPE, J (PTPRJ) 600925 12.8↓ 15.4↓ 11p11.2 DEV AlkB, E. COLI, HOMOLOG OF 605345 55.6↓ 57.2↓ 14q24 DRP X-RAY REPAIR, COMPLEMENTING DEFECTIVE, IN CHINESE 602956 20.2↓ 500↓ 9p13 DRP HAMSTER, 9 (XRCC9) EXCISION-REPAIR, COMPLEMENTING DEFECTIVE, IN CHINESE 133530 23.2↓ 55.1↓ 13q22 DRP HAMSTER, 5 (ERCC5)#$ COLLAGEN, TYPE III, α-1 (COL3A1) 120180 14.7↓ 36.1↓ 5p15.2 ECM TEB4 Similar to S. cerevisiae (SSM4) NA 9.1↓ 2.4↓ NA EST Homo sapiens cDNA FLJ32847 fis, clone TESTI2003376 NA 6.2↓ 3.5↓ 17q21 EST SUPEROXIDE DISMUTASE 1 (SOD1)$# 147450 2.0↑ 14.0↑ 21q22.1 FRM GLUTATHIONE PEROXIDASE (GPX1)# 138320 1.4↑ 20↑ 3p21.3 FRM ESTs, Highly similar to A33507 hypothetical protein DUC-1 NA 3.2↑ 5.2↑ NA HYP KIAA1046 protein NA 6.1↓ 5↓ 4q31.21 HYP GAMMA-AMINOBUTYRIC ACID RECEPTOR, γ-2 (GABRG2) #$ 137164 5.0↑ 11.2↑ 5q31.1-q33.1 ICH INTERFERON REGULATORY FACTOR 1 (IRF1) 147575 17.2↓ 46.3↓ 5q31.1 IMM CHEMOKINE, CXC MOTIF, LIGAND 10 (CXCL10)# 147310 2.5↑ 16.1↑ 4q21 IMM INTERLEUKIN 10 RECEPTOR, β (IL10RB) 123889 2.4↑ 5.5↑ 21q221- IMM ANKYRIN 2, neuronal (ANK2) 106410 6.3↓ 16.1↓ 4q25-q27 IMM MHC, CLASS I, A (HLA-A) 142800 NSD 40.1↑ 6p21.3 IMM ISOLEUCYL-tRNA SYNTHETASE (IARS) 600709 7.9↓ 181.0↓ 9q21 IMM GUANINE NUCLEOTIDE-BINDING PROTEIN, α-INHIBITING 139360 1.7↑ 8.5↑ 3p21 IMM ACTIVITY 2 (GNAI2) T-LYMPHOCYTE MATURATION-ASSOCIATED PROTEIN (MAL) 188860 NSD 20.8↑ 2cen-q13 IMM MYELIN BASIC PROTEIN (MBP)$# 159430 3.4↑ 63.1↑ 18q23 IMM ARYLACETAMIDE DEACETYLASE (AADAC) 600338 22.5↓ 9.3↓ 3q21.3-q25.2 MET PALMITOYL-PROTEIN THIOESTERASE 1 (PPT1)# $ 600722 71.4↓ 48.9↓ 1p32 MET ENOLASE 2 (ENO2)$ 131360 1.7↓ 16.7↑ 12p13 MET COMPLEMENT COMPONENT 1, q SUBCOMPONENT, β 120570 8.0↑ 18.1↑ 1p36.3-p34.1 MET SOLUTE CARRIER FAMILY 10, MEMBER 1 (SLC10A1) 182396 2.7↑ 27.7↑ 14q24.1 MET PHOSPHOMANNOMUTASE 1 (PMM1)$ 601786 1.7↑ 15.1↑ 22q13.2 MET GLYCOGEN PHOSPHORYLASE, BRAIN TYPE (PYGB)$ 138550 1.6↑ 18.2↑ 20p11.2- MET DOLICHYL-PHOSPHATE MANNOSYLTRANSFERASE 1, CATALYTIC 603503 9.3↑ 47.6↓ 20q13.13 MET SUBUNIT (DPM1)# BETAINE-HOMOCYSTEINE METHYLTRANSFERASE (BHMT) 602888 2.3↑ 17.6↑ 5q13.1-q15 MET
Tajouri Page 142 1/11/2006 MS Thesis
INOSITOL 1,4,5-TRISPHOSPHATE 3-KINASE B (ITPKB)$ 147522 2.6↑ 19.8↑ 1q41-q43 MET SOLUTE CARRIER FAMILY 25 (MITOCHONDRIAL CARRIER), Xp22.32 and 300151 2.1↑ 14.1↑ MET MEMBER A6 (SLC25A6) Yp BETA-GALACTOSIDASE PROTECTIVE PROTEIN, (PPGB)# 256540 1.9↑ 19.0↑ 20q13.1 MET ALDOLASE A, FRUCTOSE-BISPHOSPHATE (ALDOA)$ 103850 2.0↑ 8.0↑ 16q22-q24 MET CYTOCHROME C1 (CYC1) 123980 9.1↓ 9↓ 8q24.3 MIT ATP SYNTHASE, H+ TRANSPORTING, MITO F1 Complex, β (ATP5B) 102910 2.6↑ 15.7↑ 12p13q-ter MIT RIBONUCLEASE A FAMILY, 1 (RNASE1) 180440 2.5↑ 20.7↑ 14q11.2 NUC CHROMOSOME 21 OPEN READING FRAME 33 (C21ORF33)$ 601659 9.4↓ 19.3↓ 21q22.3 ORF UBIQUITIN-ACTIVATING ENZYME 1 (UBE1) 314370 2.2↑ 48.7↑ Xp1123 PRA UBIQUITIN A-52-RESIDUE RIBOSOMAL PROTEIN FUSION 191321 2.1↑ 17.8↑ 19p13.1-p12 PRA PRODUCT (UBA52) SMALL NUCLEAR RIBONUCLEOPROTEIN POLYPEPTIDE N (SNRPN) 182279 2.0↑ 52.4↑ 15q12 PRA
CYSTATIN C (CST3) 604312 1.9↑ 23.7↑ 20p11.21 PRA
PHOSPHATIDYLINOSITOL 3-KINASE, REGULATORY, 4 (PIK3R4) 602610 125.0↓ 16.1↓ 3q22.1 PRA
INSULIN-LIKE GROWTH FACTOR II RECEPTOR (IGF2R) 147280 31.9↓ 66.7↓ 6q26 PRA PROTEIN C RECEPTOR (PROCR) 600646 23.3↓ 25.6↓ 20q11.2 PRA CALPAIN, SMALL SUBUNIT 1 (CAPNS1) 114170 2.7↑ 15.7↑ 19q13.13 PRA ATP SYNTHASE, H+ TRANSPORTING, MITO F1 COMPLEX, O 21q22.1- 600828 2.6↑ 4.9↑ PRA SUBUNIT (ATP5O) q22.2 RIBOSOMAL PROTEIN S4, X-LINKED (RPS4X)# 312760 2.4↑ 25.0↑ Xq13.1 PRA INSULIN-LIKE GROWTH FACTOR-BINDING PROTEIN 6 (IGFBP6) 146735 56.6↓ 18.4↓ 12q13 PRO CULLIN 5 (CUL5) 601741 50.8↓ 22.7↓ 11q22-q23 PRO BRCA1-ASSOCIATED RING DOMAIN 1 (BARD1) 601593 12.4↓ 27.9↓ 2q34-q35 PRO CYCLIN-DEPENDENT KINASE INHIBITOR 3 (CDKN3) 123832 8.1↓ 24.4↓ 14q22 PRO CYCLIN B1 (CCNB1) 123836 7.9↓ 6.5↓ 5q12 PRO ABELSON MURINE LEUKEMIA VIRAL ONCOGENE Homolog (ABL1) 189980 2.3↑ 5.3↑ 9q34.1 PRO
THYROID HORMONE-RESPONSIVE GENE ZAKI4 (ZAKI4) $ 604876 32.3↓ 11.2↓ NA RHA INSULIN RECEPTOR (INSR) 147670 11.4↓ 5.8↓ 19p13-p13.2 RHA CYTOCHROME B-5 (CYB5) #$ 250790 8.0↓ 111.1↓ 18q23 RHA CYTOCHROME P450, 51 (CYP51) 601637 7.9↓ 98.2↓ 7q21.2-q21.3 RHA HUMAN IMMUNODEFICIENCY VIRUS TYPE 1 ENHANCER-BINDING NA 194540 16.9↓ 52.2↓ TRE PROTEIN 1 (HIVEP1) 6p24-p22.3 FORKHEAD, DROSOPHILA, HOMOLOG-LIKE 5 (FKHL5) 601089 2.3↑ 10.4↑ 16q24 TRE
$, preferential nervous system expression; #, gene dysfunction associated with nervous system disease; ↑, up-regulated compared with normal tissue; ↓, down-regulated when compared with normal tissue; NA, non available. αchronic active; βFunctional Designation: ADH, adhesion; AXT, axonal transport; CYT, cytoskeletal; DRP, DEV, developmental; DNA repair and protection; ECM, extracellular matrix component; EST, expressed sequence tag; FRM, free radical metabolism; HMB, heavy metal binding; HYP, hypothetical; ICH, ion channel; IMM, immunological; LYM, lysosomal Marker; MET, metabolic; MIT, mitochondrial; NUC, nuclease; ORF, open reading frame; PRA, protein regulatory activity; PRO, cell cycle regulation; RHA, regulation of hormone activity; RPA, apoptosis regulation; TRE, transcription factor or enhancer; and χ. Data not available
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6.1.3.2.1 Summary
Sixty-nine of the 139 genes identified as differentially regulated in MS plaques were commonly regulated in either chronic active or acute plaques (Table 6.1.4), and showed a significant correlation (Pvalue<0.0001) in the pattern of expression, by Spearman’s ρ correlation. These 69 were then divided into groups based on function and these functional clusters were investigated to determine specific differences in gene expression between acute and chronic active lesions. Seventy (54.0%) of the 139 genes identified as differentially regulated in MS were uniquely regulated in either chronic active or acute plaques. Of the 69 genes differentially regulated in both inflammatory MS plaque types
(see above): 34 (49.3 %) showed a higher degree of expression, compared with normal white matter, or were up-regulated in both chronic active and acute plaques; 33 (47.8 %) showed a lower level of expression, compared with normal white matter; or were down- regulated in both chronic active and acute plaques. Neuronal gamma Enolase 2 (ENO2)
(Oliva et al., 1991) and dolichyl-phosphate mannosyltransferase polypeptide 1, catalytic subunit (DPM1) which is associated with severe mental psychomotor retardation (Kim et al., 2000) were the only transcripts to be down-regulated in one plaque type, and up- regulated in the other. This strong correlation in expression pattern was confirmed by
Spearman's ρ correlation analysis (ρ=0.73, P<0.0001, n=69). However, in general it should be noted that the mean level of up-regulation was higher in acute (mean 19.9-fold, CV 70
%, median 17.6-fold) compared with chronic active (mean 2.4-fold, CV 56 %, median 2.3- fold) tissue. In contrast, no significant difference was identified in the mean level of genes down-regulated in both acute (mean 60.4-fold, CV 99.8 %, median 25.6-fold) and chronic active (median 67.1-fold, CV 173.5 %, median 16.9-fold) tissues (Table 6.1.7). Tajouri Page 144 1/11/2006 MS Thesis
6.1.3.2.2 Expression of Adhesion and Cytoskeletal Factors in both Chronic Active and
Acute Plaques.
Seven (9.8 %) of the genes differentially regulated in both chronic and acute tissues serve cytoskeletal, motility, and adhesion functions. Of these, 5 (71 %) were down-regulated in chronic active (mean 309.7-fold, CV 130.0 %, median 404.2-fold) and acute (mean 118.4- fold, CV 109.0 %, median 129.5-fold) tissue. These included: the lymphocyte antigen,
Integrin, alpha E (ITGAE) (Cerf-Bensussan et al., 1987); the actin-growth regulator, capping protein alpha 1 CAPPA1 (Baron-Casella et al., 1995); the axonal transport regulator, Dynactin 2 (DCTN2) (LaMonte et al., 2002); and the neuronal growth regulator, microtubule-associated protein, RP/EB family member 3 (MAPRE3) (Nakagawa et al.,
2000). Both Villin 2 (VIL2 or called Ezrin), which is a marker of T-cell activation
(Roumier et al., 2001), and the neuronal embryonic factor, Tubulin beta-5 chain (TBB5)
(Dennis et al., 2002), were both up-regulated in MS tissue. Notably, no significant difference (NSD) (P>0.05) was observed in the expression patterning of these cytoskeletal factors between chronic active or acute tissue (Table 6.1.4).
6.1.3.2.3 Expression of Proliferation, Developmental and Metabolic Factors in Both
Chronic Active and Acute Plaques.
Twenty-three (32.9 %) genes differentially regulated in plaque tissue have roles in development, proliferation, as well as broad metabolic functions. Nine (39.1 %) of these genes were down-regulated in both chronic active (mean 35.8-fold, CV 97.0 %, median
17.7-fold) and acute (mean 20.4-fold, CV 62.0 %, median 20.6-fold) tissue. These include: Tajouri Page 145 1/11/2006 MS Thesis FLII, which is associated with Smith-Magenis syndrome (Chen et al., 1995); the small glycoprotein, Palmitoyl-protein Thiolesterase 1 (PPT1) (Gupta et al., 2001); the autocrine growth regulator, Insulin growth factor binding protein 6 (IGFBP6) (Shimsaki et al., 1991); and factors implicated in regulation of cell cycle progression, such as cyclin-dependent kinase inhibitor 3 (CDKN3) (Gyuris et al., 1993). 13 (56.5 %) were up-regulated in both chronic active (mean 2.6-fold, CV 65.4 %, median 2.1-fold) and acute (mean 17.7-fold, CV
40.6 %, median 18.1-fold) tissue. These included: v-abl Abelson murine leukemia viral oncogene homolog 1 (ABL1) (Chissoe et al., 1995); glutathione peroxidase (GPX1) 1, which has diverse roles in free radical metabolism (De Haan et al., 1998); and factors associated with glyco/lipoprotein synthesis such as the phosphorylase, glycogen phosphorylase, brain-type PYGB (Glaser et al., 1989), and Betaine-homocysteine methyltransferase (BHMT) (Garrow et al., 1996). Notably, a significant difference was observed in the expression pattern of developmental, proliferation and metabolic factors,
(P<0.001), between chronic or acute plaques (Table 6.1.4).
6.1.3.2.4 Expression of Immunological Factors in Both Chronic Active and Acute
Plaques.
Nine (12.9 %) of the genes differentially regulated in MS chronic active and acute lesions have immunological functions. Of these 6 (66.7 %) were up-regulated in chronic active
(mean 1.7-fold, CV 84.0 %, median 2.1-fold) and acute (mean 25.7-fold, CV 85.8 %, median 18.5-fold) tissue, while 3 were down-regulated in chronic active (mean 10.5-fold,
CV 56 %, median 7.9-fold) and acute (mean 81.1-fold, CV 108 %, median 46.3-fold) tissue. The list includes: the nuclear factor, interferon regulatory factor 1 (IRF1), required for B-cell differentiation (Yamada et al., 1991); and the immunoreactive ankyrin, brain Tajouri Page 146 1/11/2006 MS Thesis isoform (ANK2) (Tse et al., 1991). Several interferon inducible genes were up-regulated in both tissues including: CXCL10, which has functions in adhesion and motility (Angiolillo et al., 1995), and the inflammatory cytokine receptor, IL10RB (Spencer et al., 1998).
Interestingly, while major histocompatibility complex, class 1, A (HLA-A) (Shukla et al.,
1991) was up-regulated in acute tissue (40.1-fold), NSD was identified in the chronic active tissue. Several T-, and B-cell markers were also up-regulated, including Myelin and lymphocyte protein (T-lymphocyte maturation-associated protein) (MAL) (Milan et al.,
1997), and Myelin Basic Protein (MBP) (Marty et al., 2002). While there was NSD in the pattern of down regulation, a significant difference (P<0.01) was observed in the expression pattern of immunological factors up-regulated, in acute and chronic active tissue.
6.1.3.2.5 Expression of Protein and Hormone Regulator Factors in both Chronic
Active and Acute Plaques.
Fourteen (20 %) genes regulated in both acute and chronic active tissue have functions in the regulation of protein function and hormone activity. Seven (50 %) are up-regulated in chronic active (mean 2.3-fold, CV 133.8 %, median 2.2-fold) and acute (mean 26.9-fold,
CV 65.0 %, median 23.7-fold) tissue. These include: members of the ubiquitin pathway, such as the X-linked Ubiquitin activating enzyme (UBE) 1 (Brown et al., 1989), and
Ubiquitin A-52 residue ribosomal protein fusion product 1 UBA52 (Webb et al., 1994); the coagulation factor, Protein C receptor (PROCR) (Hayashi et al., 1999); the cysteine proteinase, calpain, small subunit 1 (CAPNS1) (Ohno et al., 1986), and cysteine protein inhibitor, cystatin C (CST3), which is linked to hereditary brain damage (Palsdottir et al.,
1988). Interestingly the X-linked, Ribosomal protein S4 (RPS4X), which is linked to the Tajouri Page 147 1/11/2006 MS Thesis neurocognitive disorder, Turner Syndrome, was also up-regulated in both tissues
(Lafreniere et al., 1993). Seven (50.0 %) of genes were down-regulated in both chronic active (mean 34.3-fold, CV 120.8 %, median 23.2-fold) and acute (mean 47.8-fold, CV
91.6 %, median 25.6-fold) plaque cDNAs. Interestingly, the regulators of hormone activity were all down-regulated: including, Insulin receptor (INSR) (Seino et al., 1989), and the neuronal thyroid responsive factor, ZAKI4 (Miyazaki et al., 1996). While there was NSD in the pattern of gene down regulation, a significant difference (P<0.01) was identified in the pattern of gene up regulation.
6.1.3.2.6 Other Transcripts Differentially Regulated in Both Chronic Active and
Acute Plaques.
The remaining genes differentially regulated in chronic active and acute tissue, included:
DNA repair and protection factors, X-ray repair
XRCC9 (Liu et al., 1997) and the excision repair ERCC5 (Hori et al., 1983); the extracellular matrix component, Collagen, type III, alpha 1 (COL3A1) (Solomon et al.,
1985); transcriptional regulators, Human immunodeficiency virus type I enhancer binding protein 1 (HIVEP1) (Gaynor et al., 1991), and Fork head gene (FKHL5) (Pierrou et al.,
1994); the antiviral nuclease, ribonuclease A family, 1 (pancreatic) (RNAse I) (Hassel et al., 1993); mitochondrial factors, Cytochrome c-1 CYC1 (Fukuyama et al., 1991); the gamma-aminobutyric acid (GABA) receptor subunit, GABRE (Davies et al., 1997); an
ORF chromosome 21 open reading frame 33 (C21ORF33), linked with autoimmunity
(Nagamine et al., 1996), two ESTs (SSM4 and TEST12003376), and two transcripts that may encode (hypothetical) protein products.
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6.1.3.3 Genes Uniquely Differentially Regulated in Chronic Active MS Plaques
Table 6.1.5 Transcripts Uniquely Differentially Expressed in Chronic Active Plaques
Genes OMIM Fold Locus FDα
MICROTUBULE-ASSOCIATED PROTEIN 4 (MAP4)$ 157132 1.7↑ 3p21 CYT Dynein, cytoplasmic, light intermediate polypeptide 2 (DNCLI2) NA 8.0↑ 16q22.1 CYT SARCOGLYCAN, ALPHA (SGCA) 600119 40.0↓ 17q12-q21.33 CYT GLIAL FIBRILLARY ACIDIC PROTEIN (GFAP)$# 137780 1.6↓ 17q21 CYT PROFILIN 2 (PFN2) 176590 4.1↑ 3q25.1-q25.2 CYT DERMATOPONTIN (DPT) 125597 42.0↓ 1q12-q23 ADH INTEGRIN, BETA-5 (ITGB5) 147561 5.1↑ 3q21.2 ADH DERMATAN SULFATE PROTEOGLYCAN 3 (DSPG3) 601657 5.8↓ 12q21 ADH MITOGEN-ACTIVATED PROTEIN KINASE 9 (MAPK9) 602896 56.8↓ 5q35 PRO PROTEIN PHOSPHATASE 2, REGULATORY SUBUNIT B (B56), BETA 11q12-q13 PRO (PPP2R5B)$ 601644 11.3↓ GDNF FAMILY RECEPTOR ALPHA-2 (GFRA2)$ 601956 4.5↓ 8p21 PRO PERIPHERAL MYELIN PROTEIN 22 (PMP22)$# 601097 2.9↑ 17p12-p11.2 PRO MOESIN (MSN) 309845 2.9↑ Xq11.2-q12 PRO TYROSINE 3-MONOOXYGENASE/TRYPTOPHAN 5-MONOOXYGENASE 22q12.3 PRO ACTIVATION PROTEIN, ETA ISOFORM (YWHAH) $# 113508 5.3↑ INHIBITOR OF DNA BINDING 2 (ID2) 600386 1.6↓ 2p25 PRO EXOSTOSIN-LIKE 1 (EXTL1) 601738 9.0↑ 1p36.1 PRO GRANULIN (GRN)$ 138945 2.9↑ 17q21.32 PRO CYCLIN-DEPENDENT KINASE INHIBITOR 2A (CDKN2A) 600160 1.9↑ 9p21 PRO RNA-BINDING MOTIF PROTEIN, X CHROMOSOME (RBMX) 300199 5.3↓ Xq26 DEV ENDOMETRIAL BLEEDING-ASSOCIATED FACTOR (EBAF) 601877 2.5↓ 1q42.1 DEV HEAT-SHOCK 70-KD PROTEIN 1A (HSPA1A)# 140550 19.6↑ 6p21.3 IMM PEROXIREDOXIN 1 (PRDX1) 176763 2.4↑ 1p34.1 IMM BETA-2-MICROGLOBULIN (B2M)# 109700 1.8↑ 15q21-q22.2 IMM BRADYKININ RECEPTOR B2 (BDKRB2) 113503 3.1↑ 14q32.1- IMM COMPLEMENT COMPONENT 4B (C4B) 120820 1.5↑ 6p21.332 2 IMM ALDO-KETO REDUCTASE FAMILY 1, MEMBER C3 (AKR1C3) 603966 4.3↓ 10p15-p14 MET CREATINE KINASE, BRAIN TYPE (CKB) $# 123280 3.5↑ 14q32 MET PHOSPHATIDYLINOSITOL 4-KINASE, CATALYTIC, BETA (PIK4CB) 602758 15.9↓ 1q21 MET GLUTATHIONE S-TRANSFERASE, PI (GSTP1) 134660 2.8↑ 11q13 FRM ATPase, Ca(2+)-TRANSPORTING, SLOW-TWITCH (ATP2A2)# 108740 2.4↑ 12q23-q24.1 ICH GAMMA-AMINOBUTYRIC ACID RECEPTOR, EPSILON (GABRE)$ 300093 24.3↓ Xq28 ICH RIBOSOMAL PROTEIN S13 (RPS13) 180476 1.6↑ 11p15 PRA INOSITOL POLYPHOSPHATE PHOSPHATASE-LIKE 1 (INPPL1) 600829 61.2↓ 11q23 RHA PARATHYROID HORMONE RECEPTOR 1 (PTHR1) 168468 2.7↑ 3p22-p21.1 RHA PARATHYMOSIN (PTMS)$ 168440 1.5↑ 12p13 RHA URACIL DNA GLYCOSYLASE (UNG) 191525 71.4↓ 12q23-q24.1 DRP ATR-X GENE (ATRX) 300032 13.9↓ Xq13.1-q21.1 DRP Ribonuclease 6 precursor (RNASE6PL) NA 47.6↓ 6q27 NUC E74-like factor 4 (ets domain transcription factor) (ELF4) NA 17.5↑ Xq26 TRE αFunctional Designation; $, preferential nervous system expression; #, gene dysfunction associated with
nervous system disease;
Tajouri Page 149 1/11/2006 MS Thesis A list of genes 39 (32.1 %) regulated specifically in chronic active plaque tissue (and not also expressed in acute plaques) is listed in Table 6.1.5. Eight (20.5%) have cytoskeletal and adhesion functions. Of these, four (50.0 %) were up-regulated in MS chronic active tissue, including: the neuronal microtubule associated protein (MAP4) (Chapin et al.,
1991); while 4 (40 %) were down-regulated, such as the astroglial intermediate filament protein, Glial fibrillary acidic protein (GFAP) that is related to Alexander disease (Brenner et al., 2001).
Fifteen (38.5 %) genes identified in chronic active tissue have roles in development, proliferation and metabolism. 7 (46.7 %) are up-regulated, including: the myelin protein,
Peripheral myelin protein 22 (PMP22), linked to hereditary neuropathy (Aarskog et al.,
2000); Moesin (MSN), associated with T-cell activation (Delon et al., 2001); Tyrosine 3- monooxygenase/tryptophan 5-monooxygenase activation protein, eta polypeptide
(YWHAH), implicated in mediating neuronal responses to narcotics (Muratake et al.,
1996); Granulin (GRN), expressed by glial tumours (Liau et al., 2000); and the brain-type, creatine kinase, CKB (Brubacher et al., 1989). Eight (53.3 %) were down-regulated, including: MAPK9, which is required for T-cell differentiation (Dong et al., 2000); the neuronal survival factor, Glial cell derived neurotrophic factor (GDNF); and the X-linked homolog of the Male spermatogenic factor, RNA-binding motif protein, Y chromosome
(RBMY), RNA binding motif protein, X-linked (RBMX) (Delbrige et al., 1999).
Five (12.8 %) of the genes preferentially regulated in chronic active tissue have immunological roles, all of which are up-regulated, including: Heat shock 70kDa protein
1A (HSPA1A) (Cummings et al., 2001), Beta-2-microglobulin (B2M), required for HLA expression (Robinson et al., 1981); and the inflammatory mediator, Bradykinin receptor B2 Tajouri Page 150 1/11/2006 MS Thesis (BDKRB2) (Hess et al., 1992). Five (10 %) genes have functions in the regulation of protein and hormone activity, 4 (80.0 %) of which were up-regulated: such as Parathyroid hormone receptor 1 (PTHR1) (Juppner, 1994). Other genes identified in chronic tissue, include: ATPase, Ca2+ transporting (ATP2A2), which is linked with hypertension (Ohno et al., 1996); the GABA receptor subunit E, GABRE (Wilke et al., 1997); and factors with various DNA repair and protection functions: such Uracil-DNA glycosylase (UNG)
(Dinner et al., 2001), and the X-linked helicase, ATRX (Stayton et al., 1994).
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6.1.3.4 Genes Uniquely Differentially Expressed in Acute Tissue
Table 6.1.6 Genes Uniquely Differentially Expressed in Acute Plaque
Genes OMIM Fold locus FDα.
GTPase-ACTIVATING PROTEIN, RHO, 1 (ARHGAP1) 602732 9.6↑ 11p12-q12 CYT YES-ASSOCIATED PROTEIN 1, 65-KD (YAP1) 606608 1.7↓ 11q13 CYT MYOSIN VIIA (MYO7A)# 276903 250↓ 11q13.5 CYT TUBULIN, ALPHA, BRAIN-SPECIFIC$ (TUBA3) 602529 27.6↑ 12q12- CYT ZONA PELLUCIDA GLYCOPROTEIN 3 (ZP3) 182889 4.6↓ 7q11.23 ADH NERVE INJURY-INDUCED PROTEIN 1 (NINJ1)$# 602062 9.7↓ 9q22 ADH INTERFERON-INDUCED TRANSMEMBRANE PROTEIN 3 (IFITM3) 605579 58.1↓ 11p15.5 IMM PREGNANCY-SPECIFIC BETA-1-GLYCOPROTEIN 3 (PSG3) 176392 41.9↑ 19q13.2 IMM TRANSMEMBRANE PROTEIN 1 (TMEM1)$ 602103 16.7↓ 21q22.3 IMM CRYSTALLIN, ALPHA-B (CRYAB)$ 123590 19.3↑ 11q22.3- IMM EPHRIN RECEPTOR EphB6 (EPHB6)$ 602757 63.9↑ 7q33-q35 DEV PYRUVATE KINASE, LIVER AND RED BLOOD CELL (PKLR) 266200 12.0↑ 1q21 DEV RIBOSOMAL PROTEIN L21 (RPL21) 603636 6.9↑ 13q12.2 PRA RAS-ASSOCIATED PROTEIN RAB2 (RAB2) 179509 5.3↑ 8q12.1 PRA RELATED TO THE N TERMINUS OF TRE (RNTRE) 605405 1000. 10p13 PRA CALCIUM-DEPENDENT ACTIVATOR PROTEIN FOR SECRETION 604667 166.7 3p21.1 PRA PROTEIN INHIBITOR OF ACTIVATED STAT1 (PIAS1) 603566 26.3↓ 15q22 PRA ALKALINE PHOSPHATASE, LIVER (ALPL)# 171760 12.2↑ 1p36.1-p34 MET FARNESYL DIPHOSPHATE SYNTHASE (FDPS) 134629 8.1↑ 1q22 MET SOLUTE CARRIER FAMILY 6, 8 (SLC6A8)$ 300036 31.5↑ Xq28 MET CYTOCHROME P450, SUBFAMILY IIB, POLYPEPTIDE 6 (CYP2B6) 605059 11.8↓ 19q13.2 MET AMYLOID BETA A4 PRECURSOR PROTEIN-BINDING, FAMILY A, 1 602414 7.1↓ 9q13-q21.1 MET PCTAIRE PROTEIN KINASE 3 (PCTK3) 169190 20.4↑ 1q31-q32 PRO REQUIEM, APOPTOSIS RESPONSE ZINC FINGER GENE (REQ) 601671 17.5↓ 11q13 PRO PRKR INHIBITOR, REPRESSOR OF (PRKRIR) 607374 10.0↓ 11q13.5 PRO ADRENOMEDULLIN (ADM) 103275 7.4↑ 11p15.4 RHA ADENYLATE CYCLASE-ACTIVATING POLYPEPTIDE 1 (ADCYAP1) $# 102980 7.2↓ 18p11 RHA METALLOTHIONEIN 1L (MT1L) 156358 30.4↑ 16q13 HMB ESTs, Moderately similar to T00390 KIAA0614 protein NA 8.1↑ 12 EST ZINC FINGER PROTEIN 38 (ZNF38) 601261 47.6↓ 7q22.1 TRE 8-@Oxogunanine DNA Glycosylase (OGG1) 601982 19.2↓ 3p26.2 DRP αFunctional Designation; $, preferential nervous system expression; #, gene dysfunction associated with nervous system disease;
A list of genes 31 (22.3 %) regulated specifically in acute tissue is listed in Table 6.1.6. Six
(19.4 %) have cytoskeletal and adhesion functions. Both the Rho GTPase activating protein 1 (ARHGAP1) (Lancaster et al., 1994), and the brain specific, Tubulin alpha (Todd et al., 1991), are up-regulated in MS acute tissue. The rest of the genes in this category are
Tajouri Page 152 1/11/2006 MS Thesis down-regulated, and include: Myosin VIIA (MYO7A) (Ernest et al., 2000), and the oocyte receptor, Zona pellucida glycoprotein 3 (ZP3) (Van Duin et al., 1992). Eleven (35.5 %) have roles in development, proliferation and metabolism. Of these, 7 (63.6 %) are up- regulated, including: the ‘malignancy suppressor’ and important for neural development,
Ephrin type-B receptor (EPHB6) (Tang et al., 2000), and the serine/threonine kinase,
PCTAIRE protein kinase 3 (PCTK3) (Okuda et al., 1992). Four (36.6 %) are down- regulated: including cytochrome P450, family 2, subfamily B, polypeptide 6 (CYP2B6)
(Miles et al., 1988), the candidate Alzheimer marker, amyloid beta (A4) precursor protein- binding, family A, member 1 (X11) APBA1 (Blanco et al., 1998), and the interferon inducible kinase, Protein-kinase, interferon-inducible double stranded RNA dependent inhibitor (PRKRIR) (Gale et al., 1998).
Eight (25.8 %) genes have functions related to the regulation of protein and hormone activity. Those up-regulated include, the GTP binding, member RAS oncogene family
(RAB2) (Tisdale et al., 1996), and the hypoxia inducible factor, Adrenomedullin (ADM)
(Udono et al., 2001). The myeloid factor, RNTRE (Lanzetti et al., 2000), and the protein inhibitor of activated STAT1 (PIAS1) (Weiskirchen et al., 2001), were down-regulated.
The remaining genes identified as differentially expressed in acute plaque tissue include:
Pregnancy specific beta-1-glycoprotein 3 (PSG3), which is part of the immunoglobulin super family (Leslie et al., 1990); the interferon inducible, Interferon induced transmembrane protein 3 (IFITM3) (Lewin et al., 1991); Transmembrane protein 1
(TMEM1), linked to epilepsy (Yamakawa et al., 1995); Metallothionein 1 MT1 (Karin et al., 1984); and 8-oxoguanine DNA glycosylase (OGG1), implicated in the repair of DNA following oxidative damage (Arai et al., 1997).
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6.1.3.5 Q-PCR Validation of Array Analysis
Table 6.1.7 Comparison of the Results of Array Hybridisation and Q-PCR Analysis
Q-PCR Array CA a(n=3) Acute (n=2) CA a(n=3) Acute (n=2) TF 2.3↑ b(47.8 %) c 11.2↑ (2.6 %) 2.9↑ 32.8↑ GPX1 2.2↑ (13.6 %) 18.9↑ (11.6 %) 1.4↑ 20.0↑ GSTP1 2.3↑ (4.3 %) 5.5↑ (18.2 %) 3.2↑ NAd SOD eNSD (137.5 %) 16.4↑ (4.3 %) 2.0↑ 14.0↑ CRYAB 1.4↑ (78.6 %) 8.1↑ (4.9 %) NA 19.3↑ PMM1 NSD (125.6 %) 18.4 ↑ (107.3 %) 1.7↑ 15.1↑ TBB5 NSD (130.2 %) 13.5 ↑ (112.8 %) 2.1↑ 16.3 ↑
↑, up-regulated compared with normal tissue; ↓, down-regulated when compared with normal tissue. aCA, chronic active; bMean; cCoefficient of variation; ddata not available; eNSD, no significant difference (P <0.05, by t-test analysis); NA, not available. Pearsons Bivariate correlation analysis showed a significant association between the results of Q-PCR and array hybridisation analysis across the 7 genes and two different cDNA groups tested (n = 14, r =0.75, P <0.01).
In this study, comparative Q-PCR analysis has been used to validate the results of array analysis (Figure 6.1.3.1.γ), and to investigate the expression of genes that may be expressed below the level of sensitivity for array hybridisation. Each of the genes chosen for Q-PCR examination demonstrated a mean degree of regulation of at least 1.5-fold in MS plaques by array analysis. The genes chosen for Q-PCR investigation included, TF (Beutler et al.,
2000), GPX1 (De Haan et al., 1998), GSTP1 (Golbe et al., 1998), SOD1 (Wang et al.,
1998), which have important functions in regulating free radical metabolism, as well as the Tajouri Page 154 1/11/2006 MS Thesis MS associated autoantigen, CRYAB (Steinman et al., 1995), the brain specific glycosylation factor, PMM1 (Heykants et al., 2001), and TBB5 (Denis et al., 2002). Q-
PCR results for these genes as compared to array results are outlined in Table 6.1.7. TF was identified following array analysis and was positively regulated by 2.9 and 32.8-fold in chronic active and acute plaque tissue, respectively and was shown to be similarly expressed by Q-PCR with 2.3 and 11.2 fold in chronic active and active respectively.
GPX1 (chronic active, 1.4-fold and acute, 20.0-fold) and SOD1 (chronic active, NSD and acute, 20.0-fold) showed a similar pattern of expression via Q-PCR, CRYAB was not identified as differentially regulated in chronic active tissue by array but was 19.3-fold up- regulated in acute tissue, whilst GSTP1 was up-regulated (3.2-fold) in chronic active tissue by array but not identified as differentially regulated in acute tissue. PMM1 and TBB5 also showed on the whole, a greater degree of array up-regulation in acute tissue, when compared with chronic active tissue. While PMM1 and TBB5 were regulated at 1.7 and
2.1-fold respectively, in chronic active tissue, this response was significantly greater at
15.1-fold (PMM1) and 16.3-fold (TBB5) respectively, in acute tissue. The results of Q-
PCR analysis, as well as comparison with the array determination of fold for all seven genes are outlined in Table 6.1.7.
Following Q-PCR analysis the mean quantitative degree of fold regulation for all genes tested was found to be significantly (P<0.0001) higher in acute (mean 13.1-fold up, CV
39.2 %, median 13.5-fold up), compared with chronic active (mean 1.2-fold up, CV 97.2 %, median 1.4-fold up) plaque tissue. This correlated well with the results of array analysis for the same group of 7 genes investigated in acute (mean 19.6-fold up, CV 35.2 %, median
16.3-fold up) and chronic active (mean 2.2-fold up, CV 31.4 %, median 2-fold up) tissues.
Notably, while array analysis of SOD1, PMM1 and TBB5 expression demonstrated Tajouri Page 155 1/11/2006 MS Thesis differential gene expression in chronic active tissue, Q-PCR analysis showed that any difference was not significant. In only two instances, CRYAB and TF analysis of acute tissue, did Q-PCR and array determinations of fold differ by greater than 10-fold.
During analysis, the average variation between repeat determinations of CT (for the same matched control and test cDNA) on the same plate was less than 1 %, although patient variation (CV) was much larger (Table 6.1.7). The average difference between array and
Q-PCR analysis, in chronic active cDNA, across the 7 array-selected genes was 1.1-fold
(CV 103.8 %). This represents less than a cycle difference, and is well within the error of real time detection of PCR product. By contrast, acute tissue showed a much larger difference between array and Q-PCR determination of fold (difference in the mean fold 5.2- fold, CV 185.1 %). In this case the result is strongly influenced by two key outliers: TF and CRYAB (Table 6.1.7). For these two transcripts, the relative error can be attributed to the relative abundance of the target, and (to a lesser degree) the quality of cDNA. Both factors would negatively influence hybridisation kinetics for array analysis, and comparative Q-PCR, determination of fold (Thellin et al., 1999). Despite these outliers
Pearson correlation analysis showed a significant correlation between the results of array analysis and Q-PCR (r=0.75, P<0.01, n=14) (Table 6.1.7).
In conclusion, SYBR green I detection was found to provide a sensitive and reproducible means of PCR product detection in real time over a wide dynamic range. As such it represents a convenient and cost effective tool for examining the results of array hybridisation analysis.
6.1.4 Discussion
Tajouri Page 156 1/11/2006 MS Thesis Gene expression studies seek to capture the complexity of disease processes, through the identification of genetic changes that are common to the disease: and those that define a particular clinical diagnosis. It was the intention of our study to use currently available methods in global microarray hybridisation, and specific gene expression analysis to characterise the changes between MS plaque tissue and patient-matched normal brain tissue, and to expand upon the number of known clinical markers for MS. Multiple sclerosis plaque gene expression patterns are primarily a function of host response to disease and are, therefore, a significant driver of disease severity and clinical course (Lock et al., 2002). The application of global and specific gene expression analyses allows the examination of genes and gene pathways that may be commonly regulated, and specifically regulated in different subtypes of disease. The results may provide novel targets of therapeutic research.
MS tissue from 5 patients who had died with acute and secondary progressive (chronic) forms of MS was obtained by dissection. The RNA was purified and labelled with fluorescent markers (Cy5/Cy3), to be used as probe in comparative hybridisation analysis with unaffected matched brain tissue. Total message (not used in array analysis) was then subjected to further study by real time comparative Q-PCR to validate the results of the array analysis, and to examine the regulation of genes in MS plaque whose expression may be below the level of sensitivity for hybridisation analysis (Whitney et al., 2001). Unlike immunohistochemistry, the Q-PCR validation of array results is quantitative. Q-PCR also allows validation of biologically important transcripts, which may not be translated as protein products. In this study, we have also developed an approach for extracting total
RNA from brain tissue, a convenient method of validating the quality and integrity of nervous system RNAs prior to probe preparation, and used non-parametric methods of Tajouri Page 157 1/11/2006 MS Thesis analysis, to measure gene expression patterns between functional gene groups. These methods do not assume that expression is normally distributed and allows the examination of biological significant data, independent of the quantitative mean of the fold values involved in regulation.
MS lesions, with their regions of cell death, and ‘silent’ zones, which show evidence of tissue remodelling, provide a special challenge for microarray analysis. Several studies have sought to investigate gene expression in MS using methods in global gene expression analysis. Putative MS target genes, confirmed by subsequent work as differentially expressed in MS, include the colony-stimulating factor 3 (CSF3), Interleukin 6 (IL-6),
Myelin Basic Protein (MBP) (Lock et al., 2002), and a component of the pro-inflammatory leucotrienes, 5-lipoxygenase (5-LO) (Whitney et al., 2001). However, array based approaches have often provided contradictory results, or at least results that do not directly correlate with each other. This is, at least in part, a function of the nature of the target arrays used, the number of samples examined, as well as the nature of the target and control tissues. In these same studies, mouse models of experimental encephalomyelitis (EAE) have proven useful in providing a format by which array selected genes can be examined more closely for a putative role in MS pathology. However, it seems that such approaches favour an immunological model of MS, or one that might be selective for some genes and gene pathways over others (Mix et al., 2002). The results of such studies may not truly reflect human specific gene expression, or the wide symptomatic and clinical variation observed in human MS patients. In the study by Lock et al., (Lock et al., 2002) emphasis was placed on those genes that defined inflammatory MS lesions (chronic active/acute) from those that show lesser or little inflammation, and some remyelination, or ‘silent’ chronic plaques. Genes thus identified as being particularly important in inflammatory Tajouri Page 158 1/11/2006 MS Thesis lesions, include immunological factors and T- and B-cell markers, such as gap junction markers, factors associated with neurogenesis and remyelination, such as connexin, cytokines and growth factors such as insulin-like growth factor (IGF-1), as well as various endocrine factors, and regulators of hormone activity, such as the sulphur transferases.
In our study, we wished to examine the different specific inflammatory responses associated with acute and chronic active lesions. All transcripts that were significantly regulated, by least 1.5-fold (either up or down), with respect to normal tissue were classified according functions and by pattern of regulation: whether they were differentially regulated in both inflammatory plaque types, or uniquely differentially regulated in either chronic active or acute plaques. In this way 139 genes were identified. Seven genes were then selected for independent Q-PCR validation of array results. This number was sufficient to obtain a statistically significant validation of the array data (see above). Of the
69 genes identified as differentially regulated in both tissues, a strong correlation was identified in the pattern of gene expression. Although preliminary, this result does suggest that the correlation between the plaque types is indicative of a common underlying biological response to lesion formation. It is true that 70 transcripts were uniquely identified in either one of the two plaques; however, this difference may be due to absolute qualitative differences in abundance. Genes expressed below the level of sensitivity for array analysis in a sample would be identified as uniquely differentially regulated in this study.
It is widely accepted that the pathology of MS is primarily characterised by an immune
(autoimmune) response to components of the myelin sheath, such as the encephalitogenic,
MBP (Warren et al., 1995). In our study, MBP was up-regulated in both chronic active and Tajouri Page 159 1/11/2006 MS Thesis acute tissues, by 3.4 and 63- fold, respectively. Interestingly, the pattern of gene expression for MBP closely followed that of the related HLA-A (Dressed et al., 1997). Although no significant increase in HLA-A mRNA was identified in chronic active tissue, a significant increase in expression was identified in acute tissue, 40.1-fold. Another MS associated antigen identified as differentially regulated in this study was alpha-beta crystallin,
CRYAB. CRYAB is a highly immunogenic, heat-shock protein that is expressed by oligodendrocytes and astrocytes, and is not usually found in unaffected myelin (Van Noort et al., 1995). In this study, CRYAB was differentially regulated in both plaque types, but was only identified following Q-PCR analysis in chronic active tissue, suggesting a low basal level of expression in this tissue type. This difference in relative abundance may also be reflected in the array and Q-PCR determination of fold (Table 6.1.7). Interestingly, the myelin protein, Peripheral myelin protein 22 (PMP22) was also identified by array analysis as only expressed in the acute plaques; however, no Q-PCR was conducted for this transcript. PMP22 has been linked to some forms of neuropathy, however, what if any role this gene may play in autoimmunity is unclear (Ionasescu et al., 1997).
The inflammatory response in MS is mediated by T-, and B-lymphocytes; so it is not surprising that many markers of T-cell maturity were identified in MS plaque tissue.
Interestingly, one such marker Myelin-lymphocyte associated protein (MAL) (Alonso et al., 1987) was up-regulated in acute tissue (20.8-fold), but not in chronic active tissue.
Factors, which enhance antigen presentation such as Villin 2 (VIL2) (or Ezrin), were also up-regulated in MS plaque tissue: 1.7 and 3.5-fold in chronic active and acute tissues respectively. Lymphocyte proliferation factors and chemotactic cytokines may also play an important role in pathogenesis. In this study, the interferon inducible factor, chemokine (C-
X-C motif) ligand 10 (CXCL10) was up-regulated in MS plaque tissues: 2.5 and 16.1-fold, Tajouri Page 160 1/11/2006 MS Thesis in acute and chronic active tissues respectively. CXCL10 is found in the cerebrospinal fluid of MS patients as acts as a ligand for the T-cell receptor, chemokine (C-X-C motif) receptor 3 (CXCR3) (Sinder et al., 2002). In contrast, other interferon inducible factors were down-regulated in this study. These include the membrane bound interferon induced transmembrane protein 3 (IFITM3), (Lewin et al., 1991) (58.1-fold down-regulated in the acute plaques), and the interferon-inducible kinase, PRKRIR (Gale et al., 1998) (10.0-fold down-regulated in acute plaques). This result coincides with the observation that IRF1
(Miyamoto et al., 1998) was also down-regulated in MS plaque tissue (17.2-fold and 46.3- fold in chronic active and acute tissues respectively). Recent studies suggests that the overall down regulation of interferon inducible factors in MS may be due to a decrease in the amount of activated signal transducer and activator of transcription 1 (STAT1) (Feng et al., 2002). In this study, we observed a decrease in the expression of regulators of STAT1 activity, including PIAS1 (Weiskirchen et al., 2001), which was down-regulated by an average of 26.3-fold in acute tissues.
Tissue remodelling and turnover is also an important aspect of MS pathology. The co- regulation of the cysteine protease, CAPNS1 (up-regulated 2.7 and 15.7 fold in chronic active and acute plaques, respectively), and the cysteine proteinase inhibitor, cystatin C
(CST3) (up-regulated 1.9 and 23.7 fold in chronic active and acute plaques, respectively)
(Barrett et al., 1984), suggests significant tissue turnover in the plaque regions.
Interestingly, mutations in CST3 have also been linked to Alzheimer's disease (Maruyama et al., 2001). The co regulation of TF, SOD1, GPX1, and GSTP1, (verified by Q-PCR analysis, see previously) all point to significant tissue remodeling, as well as the induction of responses to free radical metabolism. TF, which can provides protection from iron may be expressed as a response to iron accumulation in MS plaques (Mehindate et al., 2001). Tajouri Page 161 1/11/2006 MS Thesis TF has also been linked to amyotrophic lateral sclerosis (ALS), and Parkinson’s disease.
SOD1 has also been linked to amyotrophic lateral sclerosis, ALS (Okado-Matsumoto et al.,
2002), while GPX1, which may act to mediate some of the effects of SOD1, was also up- regulated in both tissues (Table 6.1.7). There is some evidence to suggest that serum GPX1 levels are higher in MS patients (Sakai et al., 2000). Mutations in GSTP1 have also been associated with MS (Kantarci et al., 2002), and its link with Parkinson’s disease (Menegon et al., 1998) suggest a role in maintaining neuronal homeostasis.
Novel pathways identified in this study include factors that have various DNA repair and protective functions. These include XRCC9 which is linked to Fanconi Anemia (Auerbach et al., 2003), and ERCC5 (Hori et al., 1983) which is linked to the ability of cells to rejoin
DNA double-strand breaks, and is associated with their radiosensitivity (Chan et al., 2001).
Both of these genes are significantly down-regulated (>20-fold) in both acute and chronic active plaques. Another interesting observation has been the identification of a number of
X-linked genes including RPS4X (Lafreniere et al., 1993) which is up-regulated by 2.4 and
25 fold in chronic active and acute plaques respectively; while RBMX (Delbridge et al.,
1999), the helicase, and ATRX (Stayton et al., 1994) are both down-regulated in chronic active plaque tissue, by 5.3-fold and 13.9-fold respectively.
Despite the strong correlations in gene expression patterns that were identified across the
69 genes differentially expressed in both chronic active and acute plaques, a significant difference was found between chronic active and acute plaque gene expression patterns within certain gene groups (Table 6.1.8). For instance, the significant difference between different metabolic and proliferation factors might provide a clue as to the relative metabolic activity displayed by acute and chronic plaques. The differences in the Tajouri Page 162 1/11/2006 MS Thesis expression patterns of immunological factors up-regulated in this study suggest that each clinical phenotype may be driven by a fundamentally different inflammatory response. The potential clinical significance of the differences in the regulation of hormones and protein activity is unknown, although this might relate to the metabolic activity and aggressiveness.
Table 6.1.8 Summary Gene Expression Patterns in Acute and Chronic Active Tissue
GENE CATEGORIES ACUTE CHRONIC ACTIVE
n Mean CV Median Mean CV Median
CYT/ADH ↑ 2 9.9-fold 91.5 % 9.9-fold 1.9-fold 14.9 % 1.9-fold
↓ 5 118.4-fold 109.0 % 129.5-fold 309.7-fold 130.0 % 404.2-fold
PRO/MET/DEV ↑ 13 17.7-fold 40.6 % 18.1-fold* 2.6-fold 65.4 % 2.1-fold*
↓ 9 20.4-fold 62.0 % 20.6-fold* 35.8-fold 97.0 % 17.7-fold*
IMM ↑ 6 25.7-fold 85.8 % 18.5-fold* 1.7-fold 84.0 % 2.1-fold*
↓ 3 81.1-fold 108.0 % 46.3-fold 10.5-fold 56.0 % 7.9-fold
PRA/HR ↑ 7 26.9-fold 65.0 % 23.7-fold* 2.3-fold 133.8 % 2.2-fold*
↓ 7 47.8-fold 91.6 % 25.6-fold 34.3-fold 120.8 % 23.2-fold n, number of genes; ↑, up-regulated compared to normal tissue; ↓, down-regulated when compared with normal tissue; * Significantly different (P<0.05 by Mann Whitney, U) between acute and chronic tissues.
Overall, the results of this study suggest that individual response to inflammation is a result of quantitative changes in gene expression, determined by the nature of the initiating agent, and mediated by environment and inherited genetic variations that improperly mediate gene activity.
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6.2 Real Time PCR: An Examination of Genes Identified as Differentially Regulated in MS Plaque Tissue, using Absolute and Comparative Real Time PCR Analysis.
6.2.1 Introduction
MS is mostly a Caucasian disease leading to serious neurological abnormalities following demyelination in the CNS. Histological hallmarks of MS are the presence of widespread plaque lesions throughout the CNS. These plaque lesions are classified into three main types: acute (A), chronic active (CA) and chronic Silent (CS) MS lesions. Common drug therapies in MS are usually immuno-modulatory drugs that include Avonex (interferon β-
1a), Betaferon (interferon β-1b), Copaxone (Glatiramer acetate, Co-polymer-1 or COP-1),
Rebif (interferon β-1a), and Novantrone (chemotherapeutic agent). Beta-interferon therapy decreases the level of inflammation occurring in MS disease however, along time course the patient produce neutralising antibodies to the drug reducing therapy effect (Bertolotto et al., 2003).
Using real time PCR analysis, characterising the relative abundance and the absolute amount of cDNA copies of several candidate genes is possible. Analysis of candidate genes via real time PCR is a potent tool to estimate accurately the level of expression in MS tissue and non-MS tissue. Genes for this study were selected upon their potential involvement in MS and their level of expression investigated in chronic active and acute
MS plaques from post-mortem MS brains. These genes comprised ITPKB, SSP1 or OPN
(Table 7.2.2), CAPNS1 and interferon related genes, PIAS1 and STAT1 (Table 7.2.2).
These particular genes were investigated because of their chromosomal localisation with Tajouri Page 164 1/11/2006 MS Thesis ITPKB, SSP1 and CAPNS1 being localised at 1q41.43, 4q21-q25 and 19q13 respectively.
These chromosomal loci are potentially associated with MS susceptibility as they have been implicated in genome scan studies (Table 6.2.1). PIAS1 gene and STAT1 are located at
15q22 and 2q32 respectively and are regions that were also reported in MS genome screens
(Table 6.2.1).
In our array analysis CAPNS1 and ITPKB were found to be over-expressed in both plaque types (CA and A). Interestingly, CAPNS1 was previously found to be up-regulation in expression in EAE animal models (Shields et al., 1999b) and this calcium-activated proteinase gene has also been shown to take part of the EAE onset (Schaecher et al., 2002).
Additionally, calpain activity is also involved in ON (Shields et al., 1998a; Shields et al.,
1998b), the eye inflammation condition that precedes some MS attacks. In addition, calpain activity leads to the destruction of several targets within the CNS including the autoimmune MBP protein (Banik et al., 1985) and myelin components in general
(Deshpande et al., 1995). The putative demyelination mechanism undertaken by calpain in
MS (Shields et al., 1999a) makes this gene a very important candidate for MS pathology.
In contrast, ITPKB was less documented and this protein catalyses the adenosine triphosphate (ATP) dependent phosphorylation of inositol 1,4,5-triphosphate (IP3) to inositol 1,3,4,5-tetraphosphate (IP4) and plays an important role in the regulation of intracellular calcium concentration. ITPKB belongs to the phosphatidyl inositol pathway that plays a role in the activation of T cells (Jayaraman et al., 1995). Acute plaques containing a large amount of T cells (Francis et al., 1991) may be linked to the high level of
ITPKB transcripts seen in our array experiments.
Tajouri Page 165 1/11/2006 MS Thesis The three other genes of this study were chosen for their potential involvement in MS, as previously reported in the scientific literature. MS plaques are the result of immune system activation in which several immunological genes are involved including OPN, previously found up-regulated in MS tissue (Chabas et al., 2003). Interestingly, OPN plasma concentrations are elevated in RR-MS sufferers but not elevated in SP-MS and PP-MS in comparison to control plasma donors (Vogt et al., 2003). In this report, we aim at finding the levels of expression of OPN in SP-MS brain lesions. Additional immunological events taking place in MS involves Interferon γ. INFγ regulates immunity and causes exacerbations in MS (Zhang et al., 2000). In the present study we aimed to accurately monitor the level of expression of the downstream factor of interferon γ cascade STAT1
(Lui et al., 1998), and a protein that inhibits the DNA binding activity of STAT1, the
PIAS1 gene.
Table 6.2.1 Susceptibility Loci Harbouring Candidate Genes in MS
Population studied Susceptibility locus Reference Australia 1q42 Ban et al., 2002 Iceland 2q32 Jonasdottir et al., 2003 Iceland 4q22 Jonasdottir et al., 2003 Portugal 4q25 Martin Silva et al., 2003 Iceland 15q22 Jonasdottir et al., 2003 Turkey 19q13.1 Eraksoy et al., 2003b Australia 19q13.1 Ban et al., 2003 North/Ireland 19q13.1 Heggarty et al., 2003
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6.2.2 Materials and Methods
6.2.2.1 Tissues
MS plaques, or aberrant tissue, were obtained post mortem (16.6 ± 7.7 hr) from SP-MS
Patients and normal white matters were obtained by post mortem non-disease brains. These tissues are described in Table 6.1.2, a breif table is also presented for the types of plaques used in this study (Table 6.2.2). All the MS patients did not receive interferon based therapy drugs in the last two months before their death.
Table 6.2.2 Brief Histopathology of MS Plaques
Subject Tissue Timeα Locationβ Sex Type Ageγ MS 1 HSB3163 20 h Subcortical WM F CA 57 yr MS 2 HSB3161 20 h Periventricular WM F CA 51 yr MS 3 HSB3131 24 h Subcortical WM F CA 53 yr MS 4 HSB2589 4 h Medial Subcortical WM F A 48 yr MS 5 HSB2946 15 h Medial Subcortical WM M A 59 yr α post mortem delay; β from which control and matched plaque tissue were obtained; and γ of death. WM: White Matter; CA: Chronic Active; A: Acute.
6.2.2.2 Template Preparation for Absolute-PCR Purification and Dilution Series
Genomic DNA was first used to optimise specific amplification conditions prior to SYBR
Green I real time analysis of gene expression from total cDNA (data not shown). MS cDNA was used as a template to generate a PCR product using the specific gene primers
Tajouri Page 167 1/11/2006 MS Thesis studied (Table 6.2.3) and without SYBR Green dye. PCR conditions followed the similar cycle used for Q-PCR experiments. Each gene amplicon was purified using a PCR DNA purification kit (Qiagen, CA) with a prerequisite of adding for each PCR sample 8 μl of 3M
Na-acetate (PH5). Amplicon size and purity were checked on 2% agarose gel electrophoresis by pouring 3 μl of purified PCR.
Table 6.2.3 Primer Sequences
Genomic Genes Forward (5’-3’) Reverse (5’-3’) cDNA# DNA# CAPNS1 AAACAGTTCGACACTGACCGAT AGTAGCGTCGGATGATCATGTT 114 bp 261 bp
ITPKB TGTGACCAAGCCACGGTACAT CCCTCGTTTTGGTCT TCTTGAA 131 bp 2.4 kbp
STAT1 GGCAAAGAGTGATCAGAAACAA GTTCAGTGACATTCAGCAACTCT 118 bp 327 bp
PIAS1 ACAACAAGTGCAGCAAATCAGT GTCACATTTGGTCCCAGAAA 57 bp 316 bp
SPP1 GTGATAGTGTGGTTTATGGACT GCACCATTCAACTCCTCGCT 123 bp 691 bp
18s CTTAGAGGGACAAGTGGCG GGACGTCTAAAGGGCATCACA 110 bp 110 bp
# PCR product
6.2.2.3 Generation of MS Candidate Gene Standard Curves
Purified PCR amplicons were quantified by spectrophotometry and set at different 10-fold dilution series. Templates for the elaboration of standard curve formation were chosen by starting at 103 and follow up till 108 dilution.
Copies/ml = 6.023 х 1023 х [C] х OD260 Molecular Weight
Tajouri Page 168 1/11/2006 MS Thesis The y-intercept (C) and slope (M) for each dilution series was calculated using the formula
Y=mx+C. This was then used to calculate the relative abundance of each gene examined
(see data analysis below). Methods for real time PCR analysis are outlined below.
6.2.2.4 Sybr Green I Real Time PCR
Primers were designed as intron spanning primers using Primer express version 2.0
(Applied Sciences). Gene sequences, with exon and intron boundaries, were found in
Ensembl (http://www.ensembl.org/). PCR were performed using a laboratory made cocktail of Sybr Green mix [1ΧPCR buffer (50 mM KCl & 10 mM Tris HCl pH 8.3); 200 mM dNTP mix (equimolar dGTP, dCTP, dTTP, dATP) (Amersham–Pharmacia Biotech); 3
mM MgCl2 final concentration, 1Χ BSA (New England Biolabs); 15 nM Fluorescein Dye
(Bio-Rad); 0.6 x SYBR Green I (Sigma)]. 4 μl of diluted cDNA, Taq DNA polymerase
(0.07U/μl) (Amersham–Pharmacia Biotech) as well as forward and reverse primers (0.5 μM each.) (Geneworks, Australia) were added to this mix with a final volume of 25 μl.
Detection of PCR product in real time was performed using the Corbett Research Rotor-
Gene 3000. PCR volumes were placed in individual Corbett 0.1 ml strip tubes on –20°C pre-cool metal tube carriers with this order: cDNA, PCR mix. Tubes were closed off and manually handle to allow the whole PCR solution to be at the bottom of the tube. All PCR tubes were placed in the 72 well Rotor within the real time PCR machine. The following cycling conditions were used and entered in the Rotor Gene software (Version: Cycle 1,
94oC 4 min (x1), Cycle 2, 94oC 30 s, 59oC 1 min, 72oC 30 s (x45). A post-PCR amplification protocol was preset before the run to obtain melt curve representations
(ramping from 50 to 99°C with 1°C ramping every 5 seconds).
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6.2.2.5 Data Analysis
Following Q-PCR analysis, CT values from triplicates were collected at linearity and used to calculate the 18S rRNA corrected CT (or ΔCT) for each gene. Brains from MS individuals were classified as either chronic active plaques (ΔCTCA) or acute plaques
(ΔCTA). Triplicate repeat ΔCT were assigned with ± SE determinations and were then used to calculate the mean corrected difference in CT for normal white matter of non-MS brains (or ΔΔCT ± SE). The extent of the response is determined by 2 mean (ΔΔCT), while a negative value suggests repression of receptor expression, so the relative degree of response is calculated by 2 -mean (ΔΔCT).
The same CT values obtained from real time analysis were also used to identify the relative abundance of each transcript in both MS plaques and non-pathological white matter. For each gene, a set amount of amplified amplicons was obtained using the formula mentioned in Section 6.2.2.3.
Serial dilutions were performed and a standard curve was obtained for each gene.
The relative abundance of each transcript was calculated using the following formula:
Copy Number = (CT-C)/M*
* Where CT is the cycle threshold at linearity of gene in unknown sample, M the slope and
C the y- intercept determined for each gene specific standard curve. In this case the copy
Tajouri Page 170 1/11/2006 MS Thesis number difference represents the absolute change in gene expression between MS and normal white matter.
6.2.3 Results
Each gene expression level was monitored by real time PCR for MS plaques and normal white matter. An example of comparative fold regulation is illustrated in Figure 6.2.3.1
Figure 6.2.3.1 shows a real time PCR of osteopontin gene and 18S internal control gene (A) and the resulting melt curve analysis (B). Total results of Q-PCR analysis are tabulated in
Table 6.2.3.2 with values for comparative fold regulation (2 -mean (ΔΔCT)) and absolute copy number ratio (gene copies in MS / gene copies in non-MS). A graphical representation of
Q-PCR and absolute folds is provided in Figure 6.2.3.3. Analysis and results of linear regression analysis for the findings of gene copy numbers are tabulated in Table 6.2.3.1.
Figure 6.2.3.2 shows examples of results obtained from the osteopontin gene with real time
PCR dilution series (A), graphic representation of regression analysis for osteopontin (C) and polyacrylamide gel electrophoresis of osteopontin serial dilutions used for the determination of absolute copy number (B).
The expression level of osteopontin was investigated in our experiments with data revealing an up regulation of osteopontin in all the sets of MS cDNA analysed compared to normal white matter. However a marked difference of expression levels was seen depending on plaque type. Acute plaques showed dramatic increased levels of osteopontin expression when compared to chronic active plaques. The ITPKB gene showed a similar trend with up-regulation of the gene in MS compared to non-MS tissue. A dramatic up regulation of expression was observed within acute plaques when compared to levels of expression in Tajouri Page 171 1/11/2006 MS Thesis chronic plaques. However, for the interferon-related genes PIAS 1 and STAT1, a strong down regulation of expression level was noticed in acute plaques. The Calpain gene showed expression levels that are difficult to interpret with decrease and increase expression within each type of plaque.
Table 6.2.3.1 Results of Linear Regression Analysis for Absolute Standard Curves
Gene MWt* Efficiency (E)# Slope (M) R2§ CT(C) CAPNS1 67.4kDa 0.93 3.5 0.9988 24.6 ITPKB 86.2kDa 1.51 2.5 0.9776 20.7 SPP1 80.9kDa 1.15 3.0 0.9953 20.0 PIAS1 37.5kDa 0.75 4.1 0.9994 24.3 STAT1 77.6kDa 0.83 3.8 0.9996 25.9 18srRNA 72.3kDa 1.21 2.9 0.9950 20.0
*Molecular weight (MWt)=number base pair х 6.58х102; #E= (10 1/M)-1; §results of linear regression.
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A 1 2 3 4 5
RFU
0.2
Threshold 0 10 20 30 Cycles
B 5 4 3 2 1
RFU 0.4
0.2
0 Threshold 80 85 90 Temp ( o C)
Figure 6.2.3.1 Picture of Comparative Analysis. A. Example of real time log scale quantitation analysis traces of Osteopontin gene with the internal control 18S rRNA (1-2: 18s control-MS; 3-4 OPN control-MS; 5: primer dimers from H2o control). B. Example of Melt curve traces of Osteopontin gene with the internal control 18S rRNA on chronic active MS case 2. For figure 1A and figure 1B: Traces 1 and 2 are the 18s PCR from MS cDNA and Non-MS cDNA respectively; Traces 3 and 4 are the Osteopontin gene PCR from MS cDNA and Non-MS cDNA respectively; Trace 5 is the water no template control used with MS cDNA and Non-MS cDNA and denotes for late primer dimer apparition. Each trace pointed corresponds to a triplicate of Sybr green fluorescence PCR amplifications.
Tajouri Page 173 1/11/2006 MS Thesis
A
0.4
RFU 0.2 14562 332
0 ThresholdThre shold 0 10 20 30 B Cycles 18
14 CT 10
6
2
1.7x104 1.7x105 1.7x106 1.7x107 1.7x108 1.7x109 Copies C 1 2 34567 200bp
100bp
Figure 6.2.3.2 Absolute Real Time PCR Standard Curve. A. Example of standard curve derived from OPN PCR product at 10Χ-dilution series (in triplicate). Dilutions from 103 (1) to 108 (6) are represented (1- 6). B. Excel graphical determination of the absolute real time PCR standard curve (representation of Ct values versus osteopontin mRNA copy number). C. 10% SDS Polyacrylamide gel picture of osteopontin serial concentration obtained in the absolute real time PCR standard curve (7: H2O control).
Tajouri Page 174 1/11/2006 MS Thesis Table 6.2.3.2 Q-PCR and Absolute Real Time Results. MS/Control Gene Expression Ratios (MS 1-3: CA Plaques; MS 5,6: Acute Plaques). Comparative Absolute MS1 avΔCT avΔCT Av Copyn (C1) Av Copyn (MS1) Fold Fold (C1) (MS1) SPP1 9.9±0.029 7.0±0.023 7.5↑** 3.1×103±246 2.8×104±90 9.0↑** ITPKB 15.4±0.069 14.2±0.191 2.3↑** 3±0 1±0 2.5↑** PIAS1 15.5±0.052 16.5±0.092 1.9↓* 2.4×103±8.2 1.3×103±7.3 2.0↓* STAT1 16.4±0.058 15.9±0.006 1.5↑** 303±1 411±0 1.4↑** CAL 10.9±0.088 10.5±0.075 0.8↓ 3.8×103±27 2.9×103±24 1.3↓ MS2 avΔCT avΔCT Av Copyn (C2) Av Copyn Fold Fold (C2) (MS2) (MS2) SPP1 13.4±0.048 11.8±0.071 3.0↑** 5.6×103±20 3.5×104±208 6.2↑** ITPKB 16.8±0.084 14.7±0.199 4.3↑** 3±0 19±0 7.4↑** PIAS1 NA NA NA NA NA NA STAT1 NA NA NA NA NA NA CAL 15.5±0.101 14.5±0.047 2.0↑* 4.0×103±26 7.6×103±25 1.9↑* MS3 avΔCT avΔCT Av Copyn (C3) Av Copyn Fold Fold (C3) (MS3) (MS3) SPP1 12.2±0.069 11.8±0.071 1.3↑ 3.2×104±183 4.6×104±277 1.4↑ ITPKB 17.9±0.107 16.7±0.046 2.3↑* 32±0 114±0 3.6↑* PIAS1 16.7±0.075 16.7±0.069 1.0 2.1×104±96 2.2×104 ±92 1.0 STAT1 13.5±0.024 12.8±0.037 1.6↑** 8.6×103±15 1.3×103±36 1.5↑** CAL 13.6±0.060 13.0±0.090 1.5 1.7×104±75 3.0×104±206 1.7↑ MS4 avΔCT avΔCT Av Copyn Av Copyn (MS4) Fold Fold (C4) (MS4) (C4) SPP1 11.5±0.046 6.4±0.032 34.3↑** 3.1×104±126 1.8×106±9.1×103 57.6↑** ITPKB 19.4±0.014 15.1±0.179 19.7↑** 11.3±0 192±2 16.9↑** PIAS1 16.7±0.009 20.0±0.032 9.9↓** 1.0×104±6 2.2×104±26 2.0↓** STAT1 14.1±0.067 16.8±0.020 6.5↓** 1.4×104±68 5.3×103±6 2.5↓** CAL 12.8±0.017 14.5±0.098 3.4↓** 1.3×104±17 8.0×103±54 1.7↓** MS5 avΔCT avΔCT Av Copyn Av Copyn (MS5) Fold Fold (C5) (MS5) (C5) SPP1 13.0±0.092 7.2±0.072 55.7↑** 7.4×103±53 7.1×105±7.1×103 95.8↑** ITPKB 20.8±0.006 14.9±0.000 59.7↑** 3±0 208±0 74.5↑** PIAS1 17.9±0.038 20.6±0.052 6.5↓** 7.6×103±16 1.1×104±28 1.4↓** STAT1 15.0±0.033 17.6±0.087 6.0↓** 5.1×103±10 2.1×103±10 2.5↓** CAL 13.9±0.050 12.4±0.064 2.8↑** 4.8×103±17 2.5×104±129 5.1↑** AvΔCT, average difference in cycle treshold (CT); Av Copyn , average copy number/μg; ↑up-regulated in MS plaque tissue compared with NWM; ↓down-regulated in MS plaque tissue compared with NWM; *Significant by Students t-test (P<0.05); ** Significant by Students t-test (P<0.01); ±Standard error; NA, gene expression below the level of sensitivity for analysis. Tajouri Page 175 1/11/2006 MS Thesis
Figure 6.2.3.3 Comparison of Comparative and Absolute Determination of Fold Difference in Gene Expression between MS Plaque Tissue (Chronic Active/ Acute). A. SPP1; B. ITPKB; C. PIAS1; D. STAT1; E. CAPNS1. Δ Difference in fold determination between absolute and comparative analysis of fold.
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6.2.4 Conclusion and Discussion
In the present study, SYBR Green I Q-PCR and absolute quantitation were performed in post mortem human brains. The tissue specimen consisted of 5 MS brains and 5 sex, age, anatomical localisation and ethnicity matched healthy brain tissue. MS is an inflammatory demyelinating disease of the CNS, characterised by lesions or zones of inflammation
(plaques). Such plaques are characterised by chronic and acute morphological and physiological changes in MS disease development. In our study, we investigated acute and chronic active plaques for gene expression. We assessed quantitative changes in gene expression using Real time PCR analysis using post-mortem MS brain plaques compared to healthy human brain white matter. Levels of expression as well as relative abundance were investigated for several genes including CAPNS1, ITPKB, SSP1, PIAS1 and STAT1. We have demonstrated that differential expression of key genes brings more understanding to the underlying pathology of different MS plaques. To lead to a means for examining candidate markers, RNA extraction was carried out through a double purification series with intermediate step of DNAse treatment. Plaques used in our experiments ranged from only 0.3 to 1.1 g and cDNA, following reverse transcription, was retrieved from post- mortem brain tissue. Double strand DNA binding dye SYBR Green I was used and provided a convenient and sensitive means of examining specific PCR amplification product in real time, and allowed the generation of standard curves from which relative gene activity (mRNA abundance) could be determined.
One of the genes investigated, the proteinase CAPNS1, an enzyme involved in the onset of
EAE models (Schaecher et al., 2002), showed a different degree of expression levels in
Tajouri Page 177 1/11/2006 MS Thesis both acute and chronic active plaques. Due to the limited plaque sample studied, no real conclusion could be held for this gene. The highest fold regulation obtained in chronic active plaques was 2 and 2.8 in acute plaques. However, in the second acute plaque, we noticed a particular sharp down regulation of CAPNS1 expression and this contradiction of level of expression was unique for this gene. This difference might reveal a particular evolution of the acute plaque pathology in which calpain could be partly responsible. Such a possibility requires further research with the use of a greater number of MS tissues. It would be interesting to know if such a critical proteinase gene could follow the biological evolution course of each plaque.
In contrast, the second gene investigated ITPKB showed consistency in expression for both plaques. Over expression of ITPKB was observed in both plaque types and was expressed at a higher extent in acute lesions. These Q-PCR data correlate with the array data presented in this thesis. The implication of ITPKB in MS pathology is difficult to interpret since this gene has not been thoroughly investigated in MS. However, its implication in T cell activation and its high level of expression in acute plaques might indicate that ITPKB is playing a significant role in MS pathology.
Additional genes were studied and analysis of Q-PCR and absolute relative ratios confirmed levels of expression of known genes to be involved in MS that included a high transcribed amount of OPN mRNA. A dramatic increase in gene expression for OPN occurred in acute lesions and to a lesser extent in chronic active plaques of SP-MS patients.
This pattern of expression could reflect the high capacity of antigen presentation of APCs in acute plaques. In fact, stimulation of APCs by OPN has been shown to trigger secretion
Tajouri Page 178 1/11/2006 MS Thesis of the proinflammatory cytokine IL12 and also to reduce the anti-inflammatory IL10 secretion (Ashkar et al., 2000).
Our results also revealed a dramatic down-regulation of the two interferon-related genes in both plaques. A strong down-regulation of STAT1 and PIAS1 was observed in acute plaques of SP-MS patients with non previous interferon based therapy (last two months of their life). Inflammatory activity within acute lesions must be dependent on different immunological signals other than STAT 1/PIAS1 molecules. Interestingly, a recent study using TCR transgenic mice against MBP has shown that in STAT1 depleted mice, the frequency and intensity of developing EAE was dramatically increased (Nishibori et al.,
2004).
In conclusion, real time PCR is a very rapid way to assess a number of genes and can provide new insights into MS pathology. Despite the relative low number of plaques we had available to investigate, we could still draw specific conclusions regarding trends of gene expression within different MS plaques. Both comparative and absolute-copy number changes in ITPKB, SPP1, CAPNS1, STAT1 and PIAS1 genes show differences of expression levels between pathological and non-pathological tissues and also between types of plaques. The experiments undertaken in this thesis are preliminary data and need further investigation. Interestingly, an examination of aberrant gene expression levels (mRNA levels) for STAT1 and PIAS1 were found in MS plaque tissue and normal brain white matter (NBWM). These two interferon related genes were strongly down-regulated in acute plaques whereas pro-inflammatory osteopontin, an early T cell activator, and ITPKB, involved in T cell activation, were found dramatically up-regulated in MS acute plaques.
Tajouri Page 179 1/11/2006 MS Thesis
CHAPTER 7
General Discussion
Tajouri Page 180 1/11/2006 MS Thesis 7.0 Overview
In this first part of the current thesis, case control association studies were undertaken using a population of 104 MS affected individuals that were matched with healthy controls. A total of 5 genes were investigated and included nNOS, iNOS, MTHFR, COMT and VDR.
With the exception of VDR markers, all variants from of the genes used showed no positive association results. VDR though showed a strong allelic and genotypic association with the
Taq variant being associated with the most severe cases of MS pathology.
The second part of this thesis consisted in setting up five microarray experiments using 3 chronic active and 2 acute plaques against normal white matter brain controls (age; sex and anatomically matched). Fluorescence intensities from 5000 genes were computed and gene expression ratios were calculated. Clustering analysis showed differentially regulated genes involved in immunological response, myelin formation, metabolic pathways and autoimmunity with several genes uniquely differentially expressed within each plaque type.
Q-PCR analysis was performed on 7 random genes differentially expressed on the array and data showed a significant correlation with array analysis data.
A third part of the current research was the investigation of additional candidate genes potentially involved in MS pathology or found differentially expressed in our array experiments. STAT1, PIAS1, CAPNS1, OPN and ITPKB were studied using Sybr green Q-
PCR analysis with absolute quantitation. Data showed a high level of expression of ITPKB and OPN in MS and this over-expression was more pronounced within acute plaques.
Additionally, the genes STAT1 and PIAS1 were found to be down-regulated in MS acute plaques. Tajouri Page 181 1/11/2006 MS Thesis
7.1 General Discussion on Genomics Case-Control Studies in MS
7.1.1 General Discussion on Nitric Oxide Synthase Genes
The MS disorder, affecting most commonly the CNS of Caucasian populations, has a significant genetic component although the gene(s) involved have not yet been defined.
Nitric oxide synthases are a family of enzymes that control the production of nitric oxide.
It is possible that neuronal NOS could be involved in MS pathophysiology and hence the nNOS gene is a potential candidate for involvement in disease susceptibility. An investigation of allelic frequencies for nNOS was then undertaken using an MS Australian population cohort. DNA samples obtained from a Caucasian Australian population affected with MS and an unaffected control population, matched for gender, age and ethnicity, were genotyped for a microsatellite polymorphism in the promoter region of the nNOS gene.
The allelic marker used consists in a dinucleotide repeat found within the 5'-flanking region, a region upstream to the starting region of nNOS gene. Allele frequencies were compared using chi-squared based statistical analyses with significance tested by Monte
Carlo simulation. Chi-squared allelic analysis of MS cases and controls as well as a Mann-
Whitney U allele distribution analysis gave non-significant differences in allele frequencies for gender or clinical course subtype (P > 0.05). Statistical analysis indicated that there is no association of this nNOS variant and MS and hence the gene does not appear to play a genetically significant role in disease susceptibility. However, nitric oxide is a biological signalling and effector molecule for different physiological processes and is especially important during inflammation. Consequently a second case control-study was undertaken for iNOS. This gene is one of the three enzymes responsible for generating NO. Tajouri Page 182 1/11/2006 MS Thesis Macrophages are found in high level amounts in MS lesions and are responsible for the phagocytic activity of myelin in the CNS. These phagocytic cells induce iNOS gene expression that results in high levels of reactive oxygen species (ROS) molecules. High levels of nitrite and nitrate concentrations were found in cerebrospinal fluid of MS sufferers but also relative high amounts of iNOS mRNA in MS plaques. This study investigated the role of a bi-allelic tetranucleotide polymorphism located in the promoter region of the human iNOS (NOS2A) gene in MS susceptibility. A group of MS patients (n=101) were genotyped and compared to an age- and sex-matched group of healthy controls (n=101).
The MS group was subdivided into three subtypes of MS, namely relapsing-remitting MS
(RR-MS), secondary progressive MS (SP-MS) and primary progressive MS (PP-MS).
Results of a chi-squared analysis and a Fisher’s exact test revealed that allele and genotype distributions between cases and controls were also not significantly different for the total population and for each subtype of MS (P > 0.05). This suggests that there is no direct association of this iNOS gene variant with MS susceptibility. Our findings support those obtained in studies on an ethnically-different Swedish population (Modin et al., 2001) and
Spanish population (Blanco et al., 2003). However even though NOS genes do not appear to be involved in MS susceptibility, the involvement of reactive oxygen species is evident in MS pathology and as demonstrated by the plethora of antioxidant activity proteins that are expressed in MS lesions as a defence mechanism. In our array-based experiments, increased gene expressions of GPX1, SOD1 and GSTP1 may be indicative of the presence of an ongoing oxidative attack in MS lesions. Nitric oxide formation has been well documented in MS and the action of inducible NO synthase account for the presence of nitrotyrosine residues in MS plaques, reflecting peroxnitrite formations (Oleszak et al.,
1998). The gene iNOS is highly expressed in acute inflammatory phases of MS but not expressed or reduced in chronic active MS plaques (Hill et al., 2004). This early stage of Tajouri Page 183 1/11/2006 MS Thesis oxidative attack in acute phases of MS is correlated by the high levels of gene expressions encountered by the antioxidant enzymes cited above. In our study, GPX1, SOD1 and
GSTP1 genes are more expressed in acute plaques than chronic active plaques. Such oxidative effect/attack is more detrimental on oligodendrocytes since these latter show low capacities of antioxidant capacities against oxidative stress and lipid peroxidation compared to astrocyte defence capacities. The presence of oligodendrocyte precursors is an important component for remyelination in MS pathology and such cells are found in margins of chronic MS lesions and could be the last barrier against the ongoing demyelination
(Keirstead et al., 1999).
7.1.2 General discussion on MTHFR gene
A third case-control study investigated the potential role of the methylenetetrahydrofolate reductase gene in MS. The C677T substitution variant in the MTHFR gene has been associated with increased levels of circulating homocysteine and is a mild risk factor for vascular disease. Higher blood levels of homocysteine have also been reported in MS.
Thus, the C677T mutation of the MTHFR gene may influence MS susceptibility. DNA from an MS Caucasian and an unaffected control population, matched for gender, age and ethnicity, were genotyped for the MTHFR C677T mutation. Genotype distributions showed that the homozygous mutant MTHFR genotype (T/T) was slightly over-represented in the
MS group (16% versus 11%), but this variation failed to reach statistical significance (P =
0.15). Although MTHFR may play a role in MS pathology, our results do not support a significant role for MTHFR in susceptibility to MS. The MTHFR mutation investigated in this study showed no significant difference in frequency in MS versus normal individuals
Tajouri Page 184 1/11/2006 MS Thesis and hence, results from this study do not support a role for MTHFR functional gene mutation in MS susceptibility.
7.1.3 General Discussion on COMT
Noradrenaline, a neurotransmitter believed to play an immunosupressive role in neuroinflammatory disorders, is catabolised by catechol-O-methyl transferase (COMT).
The COMT G158A substitution results in a 3-4 fold decreased activity of the COMT enzyme, which may influence CNS synaptic catecholamine breakdown and could play a role in MS inflammation. COMT G158A mutation was genotyped in an MS Australian population and results showed that although the COMT wild type (H/H) genotype was slightly over-represented in the MS group (24% versus 19%) results were not statistically significant (P = 0.32). Hence, results from the present study do not support a role for
COMT functional gene mutation in MS susceptibility.
7.1.4 General Discussion on VDR gene
In our study, different VDR markers were investigated using three types of MS pathology:
RR-MS, SP-MS and the most severe type PP-MS. The MS disorder is prevalent at high earth latitudes with more cases increasing away of the equator line. Previous studies showed that MS was associated with an intronic marker of Vitamin D receptor (VDR),
Bsm1, in MS Japanese individuals. However, no positive associations with VDR were found in a Canadian family cohort study. In this study, we investigated the VDR polymorphism variants using three restriction polymorphism markers (Apa I, Taq I and Fok
I) using an Australian case-control sample. Genotypes were designated as AA, Aa, aa for Tajouri Page 185 1/11/2006 MS Thesis Apa I polymorphism, FF, Ff, ff for Fok I and TT, Tt, tt for Taq I polymorphism. Our results showed a strong significant difference in genotype and allele distribution frequency for the functional exon 9 VDR marker Taq I in MS versus normal tested individuals (P =
0.0072 allele frequency variation). The Apa I marker was also found to be associated with
MS (P = 0.04 allele frequency variation). Additionally, the Taq and Apa variants were shown to be in very strong and significant linkage disequilibrium (D’ = 0.96, P < 0.0001) and their associations were more prominently associated with the severe subtype of MS,
PP-MS. Neither of these two positive variants located in the 3’ end of the gene VDR was shown to be in LD with the Fok I variant, a located at the 5’ end of the VDR gene which did not show association with MS in the tested population.
In conclusion, our VDR results provide strong support for involvement of VDR in MS risk.
The VDR Taq I variant increased the risk of developing multiple sclerosis and this risk factor is in strong linkage disequilibrium with two intronic factors Apa I and Bsm I that also show association with MS.
In light of these VDR results it would be important to look at potential effects of VDR in
MS. Hence in our laboratory, we also wanted to investigate the level of expression of VDR within MS plaques. However there were two major drawbacks. Firstly, this gene was represented in our array chip but no array data could be provided for it since only 2 arrays showed expression of the gene. Secondly, the case-control study for VDR was undertaken towards the end of this thesis and despite some preliminary attempts to amplify VDR no amplification of the gene was observed in our brain tissues, although it was detected in other tissues such as skin (data not shown). VDR is expressed in the brain (Issa et al.,
2001) and such a lack of amplification could be due to the quality of stock cDNA we stored Tajouri Page 186 1/11/2006 MS Thesis or due to the primer DNA sequence design. We noticed for example that some cDNAs were losing their integrity with time. In addition, PCR amplification of a gene can fail if the primers do not flank the 3’ region of cDNAs, a region less susceptible to be degraded as opposed to the 5’ region of the gene. Within the cytoplasm, mRNA molecules are protected by the 5’ capping guanine residue and the long adenine tail in their 3’ region. With time, though, this protection does not last and the 5’ region can start to suffer of exonuclease degradation while the 3’ region would still be protected by an A tail. In our post mortem samples, the mRNA were degraded by local nucleases due to the post mortem delay (time in between death occurred and time of brain removal and storage at appropriate temperatures). The primers specific for VDR that were previously used in our laboratory with success were designed for the 5’ region of the gene. At the moment, new primers are being designed for the 3’ region of the VDR gene other researchers are now planning to perform Q-PCR analysis using our MS samples and NWM. An honours student of our laboratory will undertake this work.
7.2 Discussion and Conclusion on Expression Studies in MS
7.2.1 Microarray Experiments Overview
Many gene expression studies have been undertaken to look at the specific patterns of gene transcript levels in MS. Human tissues and experimental mice were used in these gene- profiling studies. A very valuable and interesting set of data, listing hundreds of genes, was found from these various expression studies. In general, the cluster of such gene candidates includes mainly immunological and inflammatory genes, stress and antioxidant genes, metabolic and central nervous system markers. Of particular interest are a number of Tajouri Page 187 1/11/2006 MS Thesis specific genes genetically localised at susceptible loci found to be in linkage with MS
(largely reported in genome wide screen studies). However due to clinical complexity of the disease, the heterogeneity of the tissues used as well as the DNA chips/membranes used for the gene profiling, one is faced with a phenomenal load of differentially expressed genes. Although this information is essential for the understanding of the pathogenesis of
MS, one must now depict and comprehend the gene pathways involved in the MS disorder.
Experiments in gene expression profiling in MS have been numerous and lists of candidates are now available for analysis. Researchers have investigated gene expression in peripheral mononuclear white blood cells (PBMCs), in MS animal models (EAE) and post mortem
MS brain tissues.
7.2.2 Discussion on Microarray Experiments using MS Peripheral Blood Mononuclear
Cells
Peripheral blood cells from MS individuals were used to extract mRNA and gene expression levels were investigated by microarray experiments. Bomprezzi et al., 2003 used a set of PBMC from fresh blood obtained from 14 MS patients and 7 controls but also frozen blood from 3 MS patients and 2 controls. A second set of cells was investigated and obtained from frozen blood of 10 MS patients and 10 controls. All of these patients were chosen under the condition of non-previous therapy. The differential gene expression from this study revealed 303 differentially expressed candidate genes. Among these, the platelet activating factor acetyl hydrolase (PAFAH1B1), a gene involved in brain development and chemoattraction during inflammation and allergy, was found with an increased transcript expression in MS peripheral blood cells when compared to controls. Tumour necrosis factor receptor (TNFR or CD27) is found also highly regulated in these MS cells. This gene Tajouri Page 188 1/11/2006 MS Thesis is a costimulator for T cell activation and is crucial for immune response development. The
T cell receptor (TCR) gene was also found increased in expression (Table 7.2.2) as well as the zeta chain associated protein kinase (ZAP70). TCR is essential for T cell mediated immune response and has been implicated in MS susceptibility (Beall et al., 1993). ZAP70 is directly implicated in TCR induced T cell activation (Chan et al., 1992). Other candidates such as zinc protein 128 (ZNF128) and transcription factor 7 (TCF7) play a role in T cells and both were found at higher expression levels in MS blood cells. Cytokines are numerous and act on cytokine receptors during inflammation. The interleukin 7 receptor (IL7 R) is up-regulated in Bomprezzi et al., 2003 as well as the myelin and lymphocyte protein (MAL) (Table 7.2.2). This receptor plays roles in B cells and T cells activation and particularly is involved in γδ T cells. γδ T cells are present in MS lesions
(Hvas et al., 1993) and their inhibition decrease the severity of EAE mice and induced the reduction proinflammatory cytokines and iNOS expression (Rajan et al., 1998). The main down-regulated genes under-expressed were tissue inhibitor of metalloproteinase 1
(TIMP1), plasminogen activator inhibitor 1 (SERPINE 1), the histone coding genes, and the heat shock protein 70 (HSP70), an autoantigen implicated in the ubiquitin proteasome pathway for the degradation of cytokines.
A second study by Ramanathan et al., 2001 investigated RR-MS patients within their clinical remission to investigate around 15 thousand genes. The results have shown common differential gene expression implicated in TCR activation such as the cAMP responsive element modulator and lymphocyte specific protein tyrosine kinase (LCK), both found at a high level of expression. Interleukin receptor gene was also found up-regulated in MS blood compared to controls. Detoxification genes were increased in expression such as haemoglobin scavenger receptor (M130 or CD 163 antigen), as well as high expression Tajouri Page 189 1/11/2006 MS Thesis levels of autoantigens such as autoantigen (PM-SCL). Interestingly, a high level of gene transcripts was found for the melanocyte specific transporter protein gene (P protein) a gene involved in the oculocutaneous albinism disorder (Lee et al., 1994).
Other studies on PBMCs were undertaken but differential expression studies have focussed on MS patients treated with particular therapeutics and comparison of their response was made against non treated controls. Interferon β therapy (Betaferon and Avonex drugs) in
MS is effective due to its immunosuppression activity and was investigated in a few studies. The action of interferon beta is thought to play a role in decreasing the MHC class
II molecules on the surface of glial cells (thus diminishing their capacity as antigen presenting cells) (satoh et al., 1995). Also, interferon β is thought to decrease the disruption of the blood brain barrier (Young et al., 1998) and to shift a proinflammatory Th1 mediated immunity to Th2 immunity (Karp et al., 2000). Koike et al., 2003 performed microarray experiments on T cells using 13 MS patients, before and after interferon β therapy. Data showed 21 differentially expressed genes after treatment with beta interferon and nine of these genes possess interferon responsive elements. Of particular interest, this study upon interferon beta treatment showed the down regulation of gene expression of tumour necrosis factor alpha induced protein 6 (TNFAIP6 or TSG-6). TSG-6 is a gene previously found implicated with murine experimental arthritis, another form of autoimmune disease
(Bardos et al., 2001). An interesting conclusion held by the author is the exclusion of the hypothesis that interferon β treatment in MS actually shifts immunity from a Th1 to Th2 shift. This is in concordance with the work of Wandinger et al., 2001 and Sturzebecker et al., 2003. Sturzebecher et al investigated the gene expression profile of PBMCs ex vivo and in vitro from 10 RR-MS patients with interferon therapy. The authors noted altered gene expression for interferon related genes such as an up-regulation of STAT1. Tajouri Page 190 1/11/2006 MS Thesis Interestingly, they found the down regulation of IL 8 gene, a known chemoattractant for neutrophils, but as well a down-regulation of a fair number of proliferative effectors. This antiproliferative effect was evident especially via the down regulation of gene expression of
FBJ murine osteosarcoma viral [v-fos] oncogene homolog (cFos), protooncogene cJun (c-
Jun) and FMS-related tyrosine kinase 3 (Flt-3). The gut-enriched Kruppel-like zinc finger protein (GKLF4) was found prominently decreased in expression with interferon β therapy.
This gene is thought to play a role in pregnancy specific glycoproteins (PSG) gene expression control since both GKLF4 and PSG molecules are co-expressed in the late stage of placenta formation (Blanchon et al., 2001).
Of interest, studies on the Pregnancy in Multiple Sclerosis (PRIMS) show that the third trimester of pregnancy is the subject of a marked reduction in relapse rate (Vukusic et al.,
2004). Surprisingly, Sturzebecker reports an up-regulation of pro-inflammatory chemokines such as interferon-gamma-inducible protein 10 (IP-10 or CXCL10), monocyte chemoattractant protein 1 (MCP1 or SCYA2 or CCL2) and karyopherin beta-2 (Mip1).
Previous gene profiling studies by the same research team by Wandinger et al., 2001, has shown that proinflammatory factors such as interleukin 12 receptor β2 (IL12Rβ2) chain as well as chemokine, CC motif, receptor 5 (CCR5) were also up-regulated in expression in
MS peripheral blood cells after interferon β treatment. IL12 Rβ2 is also found by Hong et al. 2004, to be significantly over-expressed with interferon β. Although, the inhibition of
IL12R has been reported to be mediated by interleukin β induced interleukin 10 dependant activation pathway (Wang et al., 2000), such various findings show the eventual reason why some MS patients do fail to respond to interferon β treatment. The cytokine gene profiling results from Wandinger et al. also rules out partially the hypothesis that interferon
β therapy induces a Th1-Th2 shift in PBMC of MS patients. Such an idea is further Tajouri Page 191 1/11/2006 MS Thesis supported by additional findings showing increased expression, after interferon β therapy, of other Th1 mediators such as Chemokine (C-C) receptor 5 (CCR5). CCR5 being the chemokine receptor for normal T-cell expressed and secreted (RANTES) and the two isoforms of the chemoattractor macrophage inflammatory protein 1 cited above (MIP1α and MIP1β). The gene CCR5 has already been found at high level of expression in acute phase of EAE animals and low in expression during the recovery phase of these animals
(Carmody et al., 2002). Interestingly, CCR5 is significantly down-expressed in MS with
Glatiramer acetate drug treatment (Hong et al., 2004) and such a treatment could compensate for the interferon β inability to decrease CCR5. Of note, CCR5 is also down- regulated in expression with Lovastatin drug treatment in EAE mice (Paintlia et al., 2004) and seems to be a key factor in remission in EAE mice (Carmody et al., 2002).
Also, the up-regulation of some proinflammatory markers after interferon β therapy has been noted. An interesting study by Der et al (Der et al., 1998) performed an oligonucleotide array experiments with untreated HT1080 cells and cells treated with interferon α-β or γ. The results attempted to identify levels of gene expression of interferon regulated and non-regulated genes. The interferon regulated genes such as interferon- induced protein P78 (MxA) (MxA is homolog to Myxovirus influenza resistance 1: MX1) and the interferon-inducible protein p78, second locus (MxB, homolog MX2) showed an up-regulation of gene expression following interferon β treatment but were not differentially expressed with interferon γ. Consequently, MxA and MxB over-expression with interferon β are in favour and support the findings of Wandinger et al. Significant increased of expression of MxA was also found in MS peripheral blood cells after interferon β therapy (Weinstock-Guttman et al., 2003 and Hong et al., 2004). However, in
Wandinger et al., large multifunctional protease 2 (LMP2), with a role in antigen Tajouri Page 192 1/11/2006 MS Thesis presentation and IL-15R α chain were found with high levels of transcripts after interferon
β therapy. Additional microarray experiments examining interferon β-responsive transcripts in PBMC of MS patients, have shown that in Avonex-treated MS patients (interferon β treatment), the gene LMP2 is inversely modulated compared to Avonex non treated MS patients (Iglesias et al., 2004). Such high levels of LMP2 in both studies may not be due to the interferon β therapy by itself but simply due to the increase of interferon γ concentration along with interferon β therapy. Der’s (Der et al., 1998) research has also shown that over representation of transcripts from LMP2 is dependent on interferon γ exclusively but not dependent on interferon β treatment. Interestingly, Wandinger et al., 2001 report that IFN-
γ gene expression is actually increasing transiently after two months of interferon β therapy during the course of MS pathology.
Hong et al., 2004, established PBMC preparations from 18 MS patients treated with interferon β-1a and a group of 12 MS patients treated with Glatiramer acetate. Interferon related genes were differentially expressed with interferonβ but also Th1 type molecules were increased in expression. Additionally, Glatiramer acetate treatment shows that some of these proinflammatory molecules were indeed down-expressed with this drug.
Iglesisas et al., 2004 undertook a study investigating the Avonex treatment. The methodology consisted in comparing peripheral blood cells from 5 RR-MS, treated with the drug, to 5 RR-MS without Avonex free. A second comparison was made against healthy blood donors. A set of 6800 genes was screened in this microarray experiment and data were focused mainly on the E2F pathway, a pathway of high interest in autoimmunity
(Murga et al., 2001). This pathway is triggered by interleukin 2, a potent interleukin involved in maturation and activation of T cells. Briefly, IL2 acts on IL2 receptor leading to Tajouri Page 193 1/11/2006 MS Thesis a phosphatidyl 3-kinase dependant intracellular cascade inducing subtypes of E2F proteins
(E2F 1-3 are downstream activators; E2f 4-5 are repressors). E2F transcription factors bind to DNA and induce immune cell proliferation and S phase entry in the cell cycle. The listing of genes resulting from the microarray experiments in Iglesias et al., 2004 showed a common up-regulation of expression of histone genes in MS. Interestingly, the histone genes and Fas1, that are normally increased in MS pathology, and decreased in expression in the presence of the Avonex drug. Additionally, the gene GM-CSF receptor β chain
(CSF2RB), E2F3 and histone H4/D (HIST1H4A), were increased in MS but were inversely modulated in PBMCs from Avonex-treated patients when compared to untreated MS patients. Of interest, the H4/D gene is localised at 6p21, a strong MS linked chromosomal locus. On the other hand the gene E2F2, found up-regulated in PBMC of MS patients, was not inversely modulated by the action of Avonex. Avonex appears to be inhibiting the E2F3 pathway and has a strong negative effect on the monocyte activation factor GM-CSF but no effect on the differentiation of thymocytes from precursor cells [absence of inverse modulation found for the gene thymopoeitin (TMPO)]. The author also found the down- regulation of expression in MS PBMC of the gene O-6-methylguanine-DNA methyltransferase (MGMT), a gene involved in DNA repair. DNA repair mechanism may interact directly with the E2F pathway (Ren et al., 2002). Of note, data from our array experiments showed two differentially genes expressed that relate to DNA repair mechanism, the base excision repair gene (UNG) and BRCA1-associated RING domain protein 1 (BARD1). These two genes are involved in the E2F pathway (Ren et al., 2002) and both were down-regulated with the UNG gene being down-regulated only in chronic active plaques and the BARD1 gene being down-expressed in both chronic active and acute plaques. Of note, BARD1 showed lower down expression in chronic active plaques than withinaacutebplaques. Tajouri Page 194 1/11/2006 MS Thesis 7.2.3 Discussion on Microarray Experiments of MS Brain Tissues
MS is a complex autoimmune disorder of the CNS with both genetic and environmental contributing factors. Clinical symptoms are broadly characterised by initial onset, and progressive debilitating neurological impairment. The microarray experiments performed in this thesis (Tajouri et al., 2003) used RNA from MS chronic active and MS acute lesions.
RNA was extracted, and compared with patient matched normal white matter by fluorescent cDNA microarray hybridisation analysis. This resulted in the identification of
139 genes that were differentially regulated in MS plaque tissue compared to normal tissue.
Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated; while 70 transcripts were uniquely differentially expressed
(≥1.5-fold) in either acute or chronic active tissues. These results included known markers of MS such as the myelin basic protein (MBP) and glutathione S-transferase (GST) M1, nerve growth factors, such as nerve injury-induced protein 1 (NINJ1), X-ray and excision
DNA repair factors (XRCC9 & ERCC5) and X-linked genes such as the ribosomal protein,
RPS4X. In parallel to the microarrays experiments, primers were designed for seven array- selected genes, including TF, SOD1, GPX1, GSTP1, CRYAB, PMM1 and TBB5, and real time quantitative (Q)-PCR analysis was performed. The results of comparative Q-PCR analysis correlated significantly with those obtained by array. Both chronic active and acute plaques shared the majority of factors identified suggesting that quantitative, rather than gross qualitative differences in gene expression pattern may define the progression from acute to chronic active plaques in MS. Several genes were involved in inflammation including a number of leucocyte markers that are present in MS plaques. As an example, the gene granulin has been found to be slightly up-regulated compared to normal controls.
Granulin is a novel class of growth regulators expressed by leucocytes (Bateman et al., Tajouri Page 195 1/11/2006 MS Thesis 1990). This gene is normally not expressed in normal brains but in brain glial tumour cells
(Liau et al., 2000) and located at 17q21.32, a region of suggestive linkage in MS pathology
(GAMES, 2003). In addition complement molecules or acute phase proteins such as
Complement component 1, q subcomponent, beta polypeptide (C1QB) were found to be up-regulated in expression in the most inflammatory forms of plaque types, the acute plaques. The expression of C1QB may originally come from blood vessel endothelial cells and could act detrimentally on the CNS with this complement inflammatory molecule
(Klegeris et al., 2000). Interestingly, this inflammatory gene is involved in sporadic amyotrophic lateral sclerosis neurodegeneration in which high levels of gene expression are found in post mortem tissues (Grewal et al., 1999). In parallel, anti-inflammatory proteins such as Endothelial protein C receptor (PROCR) were found, in our study, to be dramatically down-expressed in acute inflammatory plaques but this effect was less pronounced in chronic active plaques.
Whitney et al., 1999 described the analysis of MS acute lesions from a single female MS patient with PP-MS. Such plaques were compared with the white matter of the same patient and results showed 62 differentially expressed genes. The genes with increased expression in acute plaques included leucotriene A-4 hydroxylase, TNFα receptor, the autoantigen annexin XI, interferon regulatory factor 2 (IRF-2), activin Type II receptor
(ACVR2), protein Kinase C type β-1 (PRKCB1), myelin transcription factor-1 (MYT1)
(Table 7.2.2) and many others. In 2001, the same team (Whitney et al., 2001) undertook microarray experiments using 2 patients. The first patient had a total of 16 chronic inactive
(silent) plaques and the second had an acute and a chronic active plaque. The authors compared the expression of the genes coming from these plaques to a pool of normal white matter gathered from controls. The authors found a set of differentially expressed genes in Tajouri Page 196 1/11/2006 MS Thesis their MS tissues and confirmed their results using EAE mouse differential expression studies. Different candidates were found up-regulated in expression within EAE mice and human tissue. One of these genes consisted of the thrombin receptor gene or proteinase activated receptor 3 (PAR3). This gene was previously found up-regulated in macrophages previously stimulated with granulocyte-macrophage colony-stimulating factor (GM-CSF)
(Colognato et al., 2003). The putative ligand for the IL-1 receptor-related molecule
(T1/ST2) and Jun-D were also over-expressed in comparison to control mice. An interesting candidate, the arachidonate 5-lipoxygenase (5-LO), was found up-regulated in expression in MS. This gene codes for a key enzyme in the leucotriene formation and is responsible for the passage of arachidonic acid to leucotriene A4 (LTA4). Interestingly the same team in their previous microarray study undertaken in human MS brain tissue
(Whitney et al., 1999), found an over-expression of a second gene, the leucotriene A4 hydrolase (LTA4H). LTA4H is actually responsible for the passage of LTA4 to LTB4.
LTBA4, acting on leucotriene B4 receptor 1 (BLTR), is a potent chemotaxic factor for neutrophils and induce leucocyte adhesion to endothelial cells (Yokomizo et al., 1997).
These findings show the potential importance of the leucotrienes in MS pathology. To validate this hypothesis involving the chemoattraction pathway and the genes involved in the formation of the LTB4 chemoattractor molecule, one could focus their attention on the
LTB4 omega hydroxylase or Cytochrome P450 family 4 subfamily F polypeptide 3
(LTBAH or CYP4F3). LTBA4H is a gene encoding two possible isoforms, CYP4F3A and
CYP4F3B that aim at catabolising the effect of LTB4 action (Shak et al., 1984).
Becker et al., 1997 investigated a normalised cDNA library from CNS lesions of a PP-MS sufferer. The most important finding was a set of 16 genes all involved in autoimmunity.
Three of these genes coded for proteins previously implicated in MS and include MBP, Tajouri Page 197 1/11/2006 MS Thesis PLP and α-β crystallin (Table 7.2.2). Of note, seven of these 16 genes are autoantigens associated with systemic lupus erythematosus (SLE) and two are associated with insulin dependent diabetes mellitis (IDDM).
In 2001, a study (Chabas et al., 2001) was performed involving a high throughput sequencing of expressed sequence tags. The authors used non-normalised cDNA brain libraries from MS brain lesions and normal control brains. They identified 330 gene transcripts common for all libraries with several of these involved in inflammatory response. Genes that were found highly expressed included Prostaglandin D synthase
(PTGDS), prostatic binding protein (PBP), ribosomal protein L17 (RPL17), osteopontin
(SPP1), heat shock protein 70 (HSP70), myelin basic protein (MBP) and glial fibrillary acidic protein (GFAP) (Table 7.2.2). In our research, we found as well an over expression of HSP 70 within chronic active plaques. The inducible form of HSP 70 has been shown to promote myelin autoantigen presentation in APCs (Mycko et al., 2004). Of note, HSP 70 was found to be down-regulated in other studies (Bomprezzi et al., 2003 and Lock et al.,
2002). The over expression of prostaglandin D synthase interrogates once again about the important role that may play arachidonic acid related metabolites in MS neuroinflammation. Whitney et al., 1999 and 2001 showed the enzymatic involvement of the 5-lipoxygenase and leucotriene A4 hydrolase gene in the production of leucotriene proinflammatory molecules in MS disorder. In addition, Chabas et al. showed that the second enzymatic pathway that metabolises acid arachidonic might also be playing a significant role in MS pathology. The cyclooxygenase pathway, with prostaglandin- endoperoxide synthase 1 and 2 (COX 1 and COX2), transforms arachidonic acid (AA) into prostaglandins (PGG2 series and PGH2 series). PGH2 is turned into PPD2 by prostaglandin D synthase, the enzyme that Chabas et al. found in high amounts in MS Tajouri Page 198 1/11/2006 MS Thesis cDNA libraries (Chabas et al., 2003). The prostaglandins and leucotrienes are both proinflammatory molecules and might play a significant role in MS pathology. Of interest,
PGJ2 a molecule derived from PGD2, is a natural ligand of the peroxisome proliferator activated receptor (PPARγ). PPARγ acts as an anti-inflammatory element and inhibit the pro-inflammatory IL12 cytokine. PPARγ was found with higher gene expression levels in
EAE mice treated with Lovastatin drugs (Paintlia et al., 2004). Further implicating the cycloxygenase enzymatic pathway can be found in Paintlia et al study in which Lovastatin treated EAE mice showed reduced expression of the COX2 enzyme. Taken together, this implicates that the transformation of PGD2 into PGJ2 might play a potential role in MS.
Enzymatically, PGD2 can be either transformed into PGJ2 or PGF2. Of note, the product of prostaglandin F synthase (PFS), PGF2, was reported to be involved in acute demyelination of peripheral nerves (Hu et al., 2003). Additionally, in Chabas et al., 2001 decreased transcription levels were observed for synaptobrevin (VAMP3) (Table 7.2.2), amyloid beta precursor protein-binding (Table 7.2.2), family B, member 1 (APBB1), LDL- receptor related protein (LRP1), glycogen synthase kinase 3 alpha (GSK3A), brain specific sodium-dependent inorganic phosphate cotransporter or solute carrier family 17
(SLC17A7). Chabas’s team placed their attention on the increase of osteopontin transcripts in MS. A closer analysis of this candidate was performed on EAE mice. Interestingly, a knock out mouse for osteopontin showed in their study a decrease in EAE severity when compared to control mice (Chabas et al., 2001). However, Blom et al., 2003 published a comment on Chabas’s work after their studies using a knockout mouse for the osteopontin gene (OPN-/- 129/C57/BL10 with q haplotype: B10.Q usually susceptible to EAE). The gene OPN was solely and completely inactivated with the use of fully backcrossed mice.
EAE mice were induced by injections of recombinant rat MOG myelin proteins emulsified in complete Freund adjuvant. The results from Blom et al. showed no decrease in severity Tajouri Page 199 1/11/2006 MS Thesis of these EAE OPN-/- mice and such data were in direct contradiction with Chabas’s findings. Blom concluded: “The lack of effect in the OPN-deleted mouse is most likely explained by the influence of other genes that may replace the role of OPN. Identifying the
OPN-linked polymorphic genes that exert a strong influence on arthritis and encephalomyelitis therefore represents a challenging and important task”. The genes closely linked to OPN that have potential inflammatory functions were cited and accounted for 14 genes. This would include the IFN-gamma-inducible protein 10 (IP-10 or CXCL10) a chemoattractant factor localised on chromosome 4q21. CXCL10 is a chemokine that preferentially attracts Th1 lymphocytes through its receptor CXCR3, expressed at high levels on these cells (Loetscher et al., 1996). IP-10 is induced in a variety of cells in response to the Th1 cytokine IFN-gamma (Luster et al., 1985). IP-10 expression is most often associated with Th1-type inflammatory diseases, where it is thought to play an important role in the recruitment of Th1 lymphocytes into tissues. Of note, our array findings in this current thesis showed that CXCL10 was over-expressed in chronic active plaques by a fold increase of 2.5 whereas this increase was more prominent in acute plaques in secondary progressive MS brains (16.1 fold increased compared to control).
Relapses in MS often are preceded by increased TH1 cytokine levels and decreased levels of TH2 cytokines. Remissions, on the other hand, exhibit a rise in the anti-inflammatory
TH2 cytokines (Wingerchuk et al., 2001 and Yong et al., 1998). CXCL10 levels are related to clinical relapses in EAE (Fife et al., 2001, Carmody et al., 2002) and the source of production of CXCL10 is from astrocytes in EAE mice (Tani et al., 1996).
Immunoreactivity to CXCL10 was shown in demyelinating plaques (Huang et al., 2000).
Also, this protein is found in higher levels within the CSF of MS patients compared to healthy controls (Franciotta et al., 2001) and such levels of expression correlate with the count of leucocytes in the CSF (Sorensen et al., 1999). Anti- CXCL10 reduces disease Tajouri Page 200 1/11/2006 MS Thesis activity in common EAE (Fife et al., 2001). In viral model of MS (chronic demyelinating phase of mouse hepatitis virus infection of the CNS), mice showed a decrease severity of their pathology (Liu et al., 2001). CXCL10 acts on a receptor, the CXC-chemokines
Receptor 3 (CXCR3) that is localised genetically on chromosome X (Xq13). The gene for
CXCR3 was localised on human chromosome Xq13 which is in clear contrast to all other chemokine receptor genes, suggesting unique function(s) for this receptor and its ligands that may lie beyond their established role in T cell-dependent immunity (Loetscher et al.,
1998). CXCR3 is found over-expressed in macrophages, T cells and reactive astrocytes in
MS plaques (Simpson et al., 2000). Perivascular cuffs in post mortem MS lesions showed
CXCR3+ cells presence correlating with an increase of interferon gamma production
(Balashov et al., 1999). In 2002, Sorensen et al showed a continuous accumulation of
CXCR3 +cells in lesion formation of MS patients (Sorensen et al., 2002). Targeting the
CXCR3 receptor via antagonists could alter T-cell diapedesis through the CNS in MS
(Ransohoff et al., 2000). Hong et al., 2004 demonstrated that treatment with Glatiramer acetate was significantly reducing the expression of CXCR3.
More recently, Lock et al., 2003, investigated the differences in gene expression between acute and chronic silent plaques from 4 MS individuals and found 1080 genes with a fold change of >2 in at least 2 out of 4 MS samples. Genes expressed in 4/4 MS samples were classified according to the type of lesion studied. Over-expressed genes included T- B and macrophage cell related genes, growth and endocrine factors, granulocyte and mast cell related genes as well as neurogenic and remyelinating factors. As an example, interleukin
17 (IL-17), transforming growth factor 3 (TGF-β3), adrenocorticotropic hormone receptor
(ACTHR), tryptase-III and immunoglobulin E receptor β chain (Igεβ) and matrix metalloproteinase 19 (MMP-19) were up-regulated in expression only in chronic silent Tajouri Page 201 1/11/2006 MS Thesis plaques. In acute plaques, melanocortin-4 receptor (MC4R), signal transducer and activator of transcription 5B (STAT5B), insulin like growth factor 1 or somatomedin C (IGF1), granulocyte colony stimulating hormone (G-CSF) and interferon, alpha-inducible protein
(G1P2) transcripts were over represented. Of note, G-CSF was also found over-expressed in the acute phase of EAE animals (Carmody et al., 2002). Of interest as well, some pregnancy related genes were differentially expressed such as an increased of expression of pregnancy-specific β1 glycoprotein (PSG3) in acute plaques, a decreased expression for
PSG11 in chronic silent (Table 7.2.2). In our microarray experiments, we also found a dramatic increase of PSG3 within acute plaques (Table 7.2.2) and interestingly this gene is genetically localised on 19q13.2, a promising MS linked susceptibility locus (Pericak-
Vance et al., 2004).
Mycko et al., (2003) established arrays to compare MS chronic active plaques and chronic inactive plaques. They investigated as well the differential gene expression in between the centre and the margin of such plaques. This resulted in the identification of very interesting features such as an increased level of expression of adenosine A1 receptor
(ADORA1) in the marginal zone of the chronic active plaques. Studies on EAE animals depleted of the ADORA1 gene showed an increased severity of the disease course (Tsutsui et al., 2004). Consequently, ADORA1 may be involved in reducing the ongoing worsening effect of inflammation in MS lesions. The purine nucleoside adenosine inhibits IL-12 and this effect results in the increase of the Th2 type IL 10 mediator (Hasko et al., 2000). We are currently investigating some case control association and expression studies of several adenosine receptors (Data not published) to further investigate the potential role of these genes in MS. Additionally in Mycko et al., an up regulation of expression was observed for the myelin transcription factor (MyT1) (Table 7.2.2) in the margins of chronic active Tajouri Page 202 1/11/2006 MS Thesis lesions. Such MyT1 factor, preluding of ongoing attempts of remyelination in MS plaques, was previously identified as over-expressed in acute plaques in Whitney et al., 1999 (Table
7.2.2). DNA repair related genes such as the X-ray repair complementing defective repair in Chinese hamster cells 9 (XRCC9) were also found up-regulated in the margins of chronic active and silent plaques (Table 7.2.2). In our array data of this current thesis,
XRCC9 gene was down regulated in MS acute and chronic active plaques (Table 7.2.2).
Lindberg et al., 2004), used oligonucleotide DNA chips that included a total of 12 633 probes. He investigated the gene expression of MS lesions and NAWM (surrounding these lesions) that were extracted from SP-MS brain patients. Common immune responsive and neural homeostatic related genes were altered in expression. As an example, the neural development factor Ephrin receptor (EPBR), the cytoskeletal genes tubulin A and B and the pro-inflammatory interleukin 6 receptor were all increased in expression. The gene lysosome–associated membrane protein 2 (LAMP2), a neuro-lysosomal protector was down-expressed as well as synaptojanin 2b (SYNJ2), a gene involved in vesicle recycling.
Tajouri Page 203 1/11/2006 MS Thesis Table 7.2.3 Genes Altered in Expression from Different Gene Profiling Studies in MS
Differential display of gene GENE ID Category expression data ↑ Tajouri et al., 2003 a,b ↑ Chabas et al., 2003L ↑ Becker et al., 1997L MBP (myelin basic protein) Myelin related gene ↓ Whitney et al., 2001 ↑ Iglesias et al., 2004ρ ↑ Carmody et al., 2002∑R ↑ Tajouri et al., 2003b PMP22 (Peripheral myelin proetin 22) Myelin related gene ↓ Lindberg et al., 2004 ↑ Iglesias et al., 2004ρ MOBP (myelin-associated ↓ Lock et al., 2002 Myelin related gene oligodendrocyte basic protein) ↑ Carmody et al., 2002∑A ↑ Chabas et al., 2003L ↑ Becker et al., 1997L PLP1 (Proteolipid protein 1) Myelin related gene ↓ Lock et al., 2002 ↑ Carmody et al., 2002∑A ↑ Whitney et al., 1999 MYT1 (myelin transcription factor 1) Myelin related gene ↑ Mycko et al., 2003bd ↑ Tajouri et al., 2003b Myelin related gene MAL (Myelin and lymphocyte protein) ↑ Bomprezzi et al., 2003ρ and T cell related ↑ Tajouri et al., 2003$a,b SPP1 (Osteopontin) ↑ Chabas et al., 2003L Immune related gene ↓ Lindberg et al., 2004 ↑ Iglesias et al., 2004ρ ↑ Lock et al., 2002c TCR (T cell receptor) Immune related gene ↑ Bomprezzi et al., 2003 ↑ Carmody et al., 2002∑A ↑ Becker et al., 1997L IL-1R (Interleukin 1 receptor) ↑ Lock et al., 2002 Immune related gene ↑ Carmody et al., 2002∑A ↑ Whitney et al., 1999 ↑ Ramanathan et al., 2001ρ IL-7R (Interleukin 7 receptor) ↑ Bomprezzi et al., 2003ρ Immune related gene ↑ Xu et al., 2002 ↑ Carmody et al., 2002∑A ↑ Wandinger et al., 2001ρβ Immune related gene IL-12R (Interleukin 12 receptor) ↑ Hong et al., 2004ρβ (Th1 type) ↑ Iglesias et al., 2004ρ ↓ Tajouri et al., 2003$a ↑ Tajouri et al., 2003$b STAT1 (signal transducer and activator Immune related gene of transcription 1) ↓ Paintlia et al., 2004∑δ ↑ Carmody et al., 2002∑A ↑ Sturzebecker et al., 2003ρ
Tajouri Page 204 1/11/2006 MS Thesis Differential display of gene GENE ID Category expression data ↑ Iglesias et al., 2004ρ ↑ Ibrahim et al., 2001∑ ↑ Becker et al., 1997L FcγR (Fc fragment of IgG receptor) Immune related gene ↑ Lock et al., 2003c ↓ Paintlia et al., 2004∑δ ↑ Carmody et al., 2002∑A ↑ Tajouri et al., 2003a HLA class I (Human leukocyte ↑ Iglesias et al., 2004ρ Immune related gene antigen class I) ↑ Lock et al., 2002 ↓ Tajouri et al., 2003b ↑ Chabas et al., 2003L GFAP (glial fibrillary acidic protein) ↓ Lindberg et al., 2004 Gliosis ↑ Lock et al., 2002 ↑ Carmody et al., 2002∑A ↓ Chabas et al., 2003L VAMP3 (synaptobrevin) ↓ Lindberg et al., 2004 Synaptic transport ↓ Lock et al., 2002a ∑A VAMP 1 and 2 ↓ Carmody et al., 2002 Synaptic transport ↑ Tajouri et al., 2003a CRAYB (alpha-beta crystallin) ↑ Chabas et al., 2003 Autoimmunity ↔ Becker et al., 1997L ↑ Tajouri et al., 2003ab Tubulin β ↑ Lindberg et al., 2004e Cytoskeletal ↓ Lock et al., 2002a PSG3 (pregnancy specific ↑ Tajouri et al., 2003a Pregnancy related glycoprotein 3) ↑ Lock et al., 2002a gene c PSG11 (pregnancy specific ↑ Lock et al., 2002 Pregnancy related glycoprotein) ↑ Iglesias et al., 2004ρ gene XRCC9 (-ray repair complementing ↓ Tajouri et al., 2003ab defective repair in Chinese hamster cells ↑ Mycko et al., 2003bd,cd DNA repair 9) UNG (uracil-DNA glycosylase) ↓ Tajouri et al., 2003b DNA repair ab BARD1 (BRCA1-associated RING ↓ Tajouri et al., 2003 DNA repair domain protein 1) ERCC5 (excision repair cross- ↓ Tajouri et al., 2003ab complementing rodent repair deficiency, DNA repair complementation group5) a OGG1 (8-Hydroxyguanine DNA ↓ Tajouri et al., 2003 DNA repair glycosylase) ↓ Tajouri et al., 2003b Transcription ID2 (inhibitor of DNA binding 2) ↓ Sturzebecker et al., 2003ρ regulatory protein ↑ Lock et al., 2002a MAPKK1 or MKK or MEK1 bd (Mitogen-activated protein kinase ↑ Mycko et al., 2003 Signalling kinase)
Tajouri Page 205 1/11/2006 MS Thesis Differential display of gene GENE ID Category expression data ↑ Iglesias et al., 2004ρ ↓Iglesias et al., 2004ρβ P38MAPK Signalling ↓ Wandinger et al., 2001β ↑ Lock et al., 2003 ab PI3KR4 (phosphatidyl inositol 3 ↓ Tajouri et al., 2003 ρ Signalling kinase, regulatory sub-unit 4) ↓ Bomprezzi et al., 2003 ↑ Carmody et al., 2002∑R IGF1 (insulin like growth factor-1) ↑ Lock et al., 2002 Signalling ↑ Tajouri et al., 2003a Enolase 2 (Neuron specific gamma ↓ Tajouri et al., 2003b Signalling- enolase) ↑ Whitney et al., 1999a Glycolysis ↓ Tajouri et al., 2003b GDNFA2 (GDNF family receptor Neural growth factor alpha 2) ↓ Carmody et al., 2002∑A ↑ Tajouri et al., 2003ab EPHRB6 (Ephrin receptor) Neural growth factor ↑ Lindberg et al., 2004 ↑ Ibrahim et al., 2001∑ ↑ Iglesias et al., 2004ρ iNOS (inducible Nitric oxide synthase) Oxidant related gene ↑ Hong et al., 2004ρβ ↓ Paintlia et al., 2004∑δ ↑ Tajouri et al., 2003b ↓ Lock et al., 2003 HSP70 (heat shock protein 70) Heat shock protein ↑ Chabas et al., 2003L ↓ Bomprezzi et al., 2003ρ ρβ MMP9 (matrix metalloproteinase 9 or ↓ Hong et al., 2004 Metalloproteinase gelatinase B) ↓ Wandinger et al., 2001ρβ related gene ↑ Ramanathan et al., 2001ρ Metalloproteinase MMP19 (matrix metalloproteinase 9) ↑ Lock et al., 2003c related gene ρ TIMP1 (metalloproteinase tissue ↓ Bomprezzi et al., 2003 Metalloproteinase inhibitor 1) ↓ Becker et al., 1997L related gene ↑ Lock et al., 2003 P selectin ↓ Wandinger et al., 2001ρβ Adhesion ↓ Hong et al., 2004ργ a APBA1 (amyloid beta (A4) precursor ↓ Tajouri et al., 2003 Amyloid related protein-binding, family A, member 1) L APBB(Amyloid β precursor binding ↓ Chabas et al., 2003 Amyloid related protein, family B) ∑ APBA2 (amyloid beta (A4) precursor ↑ Ibrahim et al., 2001 Amyloid related protein-binding, family A, member 2) ∑A SAA2 and SAA3 (Serum Amyloid) ↑ Carmody et al., 2002 Amyloid related ↑ over-expressed transcripts; ↓ down-expressed transcripts; $ Validated by real time PCR Human MS plaque examined: a A plaques; b CA plaques; c CS plaques; Tissue examined: d margin of the plaque; e NAWM; ρ human MS PBMC; L human MS cDNA libraries; ∑ EAE animals; Expression due to drug therapy: β regulated with interferon β therapy; γ regulated with Glatiramer acetate therapy; δ regulated with Lovatstatin therapy; Pathological phase: R recovery phase of the EAE mice; A acute phase of the EAE mice
Tajouri Page 206 1/11/2006 MS Thesis
7.3 Microarray Conclusions
Microarray experiments for gene expression in MS have revealed several hundreds of significantly altered expressed candidate genes. Some of these genes have been further investigated and have provided a new understanding of the complex pathological mechanism of MS. Many more genes need further analysis and represent an interesting and exciting future in MS research. All this analysis then needs to be included into a biological and physiological context to define the gene pathways involved in this disorder. Clustering analysis should aid in providing a means to classify candidates into global functional groups.
Inherent variabilities are encountered in microarray experiments but consistent findings are obtained through replications or dye swap experiments. Additionally, there is a fair difference of data between studies. Such differences are the result of several parameters: the type of platform used (oligonucleotide, or simple cDNA platforms), commercial or non- commercial custom-made arrays (better correlation across multiple data acquisition with commercial platforms) and the source and type of tissue used for experiments. With recent statistical tools, data analysis can be performed with the prerequisite of multiple corrections and validation strategies (normalization, dye swap validations, multi data pooling) that result in the acquisition of reliable data. Despite these efforts to narrow down differences between studies, one cannot control the heterogeneity of the tissue tested in microarray experiments. With studies of particular diseases, selection of pathological tissues can be critical for the outcome of data acquisition and analysis. MS pathology is very complex and the etiology unknown with tissue classifications of plaques reflecting the diverse course of pathological physiology. The comparison of array data is then very difficult to assess and Tajouri Page 207 1/11/2006 MS Thesis the task is even more difficult with the high number of genes studied. To obtain less complexity and reliable data sets from array experiments, future studies should emphasize the use of similar experimental criteria to enable reproducibility and data comparison.
Uniform microarray protocols and platforms, similar sources of tissue, the same positive and negative controls, as well as the same key reagents should be used by the general research community using microarray technology. This approach, even if fastidious, could benefit to breakthroughs (new susceptible candidate genes) and offer a stringent clarity for future research directions.
The large amount of data arising from all these microarray studies is daunting and includes several gene profiling studies of MS brain tissue, of MS PBMC and animal models of MS.
To solve this puzzle, pharmacological studies in MS have been undertaken in human and animals in order to pinpoint responsive genes known to have positive effects in MS. Both approaches should aid in unravelling factors responsible for triggering MS pathology and could allow means to find new therapeutics. Gene profiling analysis has indicated that some proinflammatory molecules are drug resistant to interferon β therapy and seem to be indeed be repressed by Lovastatin drug. Intensive investigation of each candidate gene and pathways is the next step in MS research and will require further research at the proteomic level and the use of new pharmaceutic trials.
7.4 General Conclusions
The etiology of MS is still unknown. Three hypotheses are drawn in an attempt to understand this neurological disorder i) a genetic predisposition with a strong link with the
HLA locus (at 6p21) ii) an environment factor that could trigger the disease in a so called
North-South MS gradient iii) an autoimmune disease with the action of autoreactive T cells Tajouri Page 208 1/11/2006 MS Thesis against myelin epitopes. Each of these hypotheses can be the source or the trigger of the disease and may even act in combination. The involvement of the immune system is a hallmark in MS. Passage of peripheral white blood cells within the CNS lead to repetitive attacks against the myelin sheath resulting in plaque formation. Studies showed that inhibiting the passage of such cells within the CNS is beneficial for MS. What factors are controlling the migration of such unwanted cells? Why cells are targeting specifically the central myelin and not the peripheral myelin? And also why women account for a higher prevalence? Immune genes are commonly expressed in MS pathology but their expression is often the result of ongoing inflammation within the CNS. The shift of Helper lymphocytes Th1 to lymphocyte Th2 cytokines demonstrate how complex the immune system is regulated in MS. However, other neurological pathologies such as Parkinson disease have and develop similar immunological hallmarks with particular immune gene expressions. Cross comparison of different neurological disorders will aid at defining the real causative agents of MS. This approach would discriminate the population of genes that are altered in level of expression in MS. Researchers could then find the real causative genes implicated in the mechanism of MS disease from the genes that are simply a consequence of the disease.
Tajouri Page 209 1/11/2006 MS Thesis CHAPTER 8
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Tajouri Page 243 1/11/2006 MS Thesis APPENDIX
Appendix I Genome Wide Screens in Multiple Sclerosis Thought to Harbour Susceptibility
Chromosomal Loci
Country Susceptible locus References Iceland 1p12 Jonasdottir et al., 2003 Spain 1p13.2 Goertschees et al., 2003 Finland 1p21.2 Laaksonen et al., 2003 Finland 1p21.3 Laaksonen et al., 2003 Iceland 1p22 Jonasdottir et al., 2003 Iceland 1p22 Jonasdottir et al., 2003 Iceland 1p22 Jonasdottir et al., 2003 Portugal 1p22;1p13 Martin Silva et al.,2003 Portugal 1p31 Martin Silva et al.,2003 Hungry 1p31 Rajda et al., 2003 Spain 1p31.1 Goertschees et al., 2003 Scandinavia 1p33 Harbo et al., 2003 Turkey 1p34 Eraksoy et al., 2003a Iceland 1p36 Jonasdottir et al., 2003 Iceland 1p36 Jonasdottir et al., 2003 Iceland 1p43 Jonasdottir et al., 2003 Portugal 1q15.4 Martin Silva et al.,2003 Finland 1q21.1 Laaksonen et al., 2003 Spain 1q23.2 Goertschees et al., 2003 Portugal 1q23-24 Martin Silva et al.,2003 Portugal 1q24 Martin Silva et al.,2003 Portugal 1q25 Martin Silva et al.,2003 Spain 1q31.3 Goertschees et al., 2003 Iceland 1q32 Jonasdottir et al., 2003 Iceland 2p12 Jonasdottir et al., 2003 N/Ireland 2p14 Heggarty et al., 2003 Iceland 2p15 Jonasdottir et al., 2003 Portugal 2p16 Martin Silva et al.,2003 Poland 2p16 Bielecki et al., 2003 Italia 2p22-p21 ligori et al., 2003 Turkey 2p23-25 Eraksoy et al., 2003a Sardinia 2p23-2p16 Corradu et al., 2003 Germany 2p24 Weber et al., 2003 N/Ireland 2p25 Heggarty et al., 2003 Belgium 2q11.1 Goris et al., 2003 Iceland 2q12 Jonasdottir et al., 2003 N/Ireland 2q14 Heggarty et al., 2003 Finland 2q23.2 Laaksonen et al., 2003 Iceland 2q32 Jonasdottir et al., 2003 Iceland 2q33 Jonasdottir et al., 2003 Iceland 2q33 Jonasdottir et al., 2003 Germany 2q33.2 Weber et al., 2003 Sardinia 2q36 Corradu et al., 2003
Tajouri Page 244 1/11/2006 MS Thesis
Spain 2q36.3 Goertschees et al., 2003 Iceland 2q37 Jonasdottir et al., 2003 Hungry 2q37 Rajda et al., 2003 Iceland 3p12 Jonasdottir et al., 2003 Spain 3p12.2 Goertschees et al., 2003 Poland 3p13 Bielecki et al., 2003 Iceland 3p14 Jonasdottir et al., 2003 Iceland 3p14 Jonasdottir et al., 2003 Iceland 3p14-p21 Jonasdottir et al., 2003 Hungry 3p21 Rajda et al., 2003 Finland 3p22.1 Laaksonen et al., 2003 Hungry 3p23 Rajda et al., 2003 N/Ireland 3p24 Heggarty et al., 2003 Spain 3p25.2 Goertschees et al., 2003 Spain 3p26.3 Goertschees et al., 2003 Portugal 3q12 Martin Silva et al.,2003 Turkey 3q13 Eraksoy et al., 2003a Scandinavia 3q13 Harbo et al., 2003 Iceland 3q13.1 Jonasdottir et al., 2003 Spain 3q13.13 Goertschees et al., 2003 Iceland 3q22 Jonasdottir et al., 2003 Iceland 3q24-25 Jonasdottir et al., 2003 Iceland 3q25 Jonasdottir et al., 2003 Iceland 3q25 Jonasdottir et al., 2003 Spain 4p15.2 Goertschees et al., 2003 Belgium 4p15.2 Goris et al., 2003 Sardinia 4p15.3 Corradu et al., 2003 N/Ireland 4p16 Heggarty et al., 2003 Portugal 4q11 Martin Silva et al.,2003 Iceland 4q13 Jonasdottir et al., 2003 Spain 4q13.1 Goertschees et al., 2003 Portugal 4q13.1 Martin Silva et al.,2003 Iceland 4q22 Jonasdottir et al., 2003 Iceland 4q22 Jonasdottir et al., 2003 Portugal 4q25 Martin Silva et al.,2003 Iceland 4q26 Jonasdottir et al., 2003 Portugal 4q32 Martin Silva et al.,2003 Iceland 4q33 Jonasdottir et al., 2003 N/Ireland 4q34 Heggarty et al., 2003 Finland 4q34.3 Laaksonen et al., 2003 Portugal 4q35 Santos et al., 2003 Portugal 4q35 Santos et al., 2003 Turkey 5p Eraksoy et al., 2003b Hungry 5p12 Rajda et al., 2003 Portugal 5p13 Martin Silva et al.,2003 Belgium 5p14 Goris et al., 2003 Turkey 5p15 Eraksoy et al., 2003a Turkey 5p15 Eraksoy et al., 2003b Spain 5p15.31 Goertschees et al., 2003 Spain 5q11.2 Goertschees et al., 2003 Iceland 5q12-13 Jonasdottir et al., 2003 Tajouri Page 245 1/11/2006 MS Thesis
Portugal 5q13 Martin Silva et al.,2003 N/Ireland 5q14 Heggarty et al., 2003 N/Ireland 5q14 Heggarty et al., 2003 Spain 5q14.3 Goertschees et al., 2003 Portugal 5q14.3 Martin Silva et al.,2003 Portugal 5q14.3 Santos et al., 2003 Turkey 5q15 Eraksoy et al., 2003b Turkey 5q15 Eraksoy et al., 2003b Portugal 5q21 Martin Silva et al.,2003 Turkey 5q22-23 Eraksoy et al., 2003a Portugal 5q23 Martin Silva et al.,2003 Belgium 5q23 Goris et al., 2003 Spain 5q23.1 Goertschees et al., 2003 Spain 5q23.2 Goertschees et al., 2003 Turkey 5q31 Eraksoy et al., 2003a Iceland 5q33 Jonasdottir et al., 2003 Hungry 5q33 Rajda et al., 2003 Iceland 5q34 Jonasdottir et al., 2003 Portugal 6p16 Martin Silva et al.,2003 Hungry 6p16 Rajda et al., 2003 Spain 6p21 Goertschees et al., 2003 Sardinia 6p21 Corradu et al., 2003 Poland 6p21 Bielecki et al., 2003 Scandinavia 6p21 Harbo et al., 2003 N/Ireland 6p21 Heggarty et al., 2003 N/Ireland 6p21 Heggarty et al., 2003 N/Ireland 6p21 Heggarty et al., 2003 Germany 6p21 Weber et al., 2003 Germany 6p21 Weber et al., 2003 France 6p21 Alizadeh et al., 2003 Spain 6p21 Goertschees et al., 2003 Spain 6p21 Goertschees et al., 2003 Spain 6p21 Goertschees et al., 2003 Scandinavia 6p21 Harbo et al., 2003 Spain 6p21.1 Goertschees et al., 2003 France 6p21.1 Alizadeh et al., 2003 Belgium 6p21.1 Goris et al., 2003 Spain 6p21.1 Goertschees et al., 2003 Portugal 6p21.3 Santos et al., 2003 Iceland 6p21.3 Jonasdottir et al., 2003 Iceland 6p21.3 Jonasdottir et al., 2003 Iceland 6p21.3 Jonasdottir et al., 2003 Iceland 6p21.3 Jonasdottir et al., 2003 Portugal 6p21.3 Martin Silva et al.,2003 Finland 6p21.3 Laaksonen et al., 2003 Finland 6p21.3 Laaksonen et al., 2003 Finland 6p21.3 Laaksonen et al., 2003 Belgium 6p21.3 Goris et al., 2003 Belgium 6p21.3 Goris et al., 2003 Belgium 6p21.3 Goris et al., 2003 Australia 6p21.3 Ban et al., 2003 Tajouri Page 246 1/11/2006 MS Thesis
Australia 6p21.3 Ban et al., 2003 Australia 6p21.3 Ban et al., 2003 Australia 6p21.3 Ban et al., 2003 Australia 6p21.3 Ban et al., 2003 Australia 6p21.3 Ban et al., 2003 Portugal 6p23 Martin Silva et al.,2003 Spain 6p24.3 Goertschees et al., 2003 Sardinia 6p25 Corradu et al., 2003 Germany 6p25 Weber et al., 2003 Spain 6q12 Goertschees et al., 2003 Portugal 6q13-q14 Martin Silva et al.,2003 Turkey 6q14 Eraksoy et al., 2003a Portugal 6q14 Martin Silva et al.,2003 Portugal 6q14 Martin Silva et al.,2003 Scandinavia 6q14 Harbo et al., 2003 Iceland 6q16 Jonasdottir et al., 2003 Hungry 6q16 Rajda et al., 2003 Spain 6q23.3 Goertschees et al., 2003 Iceland 6q25 Jonasdottir et al., 2003 Sardinia 7p12 Corradu et al., 2003 Spain 7p12.3 Goertschees et al., 2003 Poland 7p22 Bielecki et al., 2003 Scandinavia 7p22 Harbo et al., 2003 Iceland 7q11.1 Jonasdottir et al., 2003 Hungry 7q11.2 Rajda et al., 2003 Portugal 7q21 Santos et al., 2003 Hungry 7q21 Rajda et al., 2003 Belgium 7q21 Goris et al., 2003 Iceland 7q22 Jonasdottir et al., 2003 Portugal 7q24-q35 Martin Silva et al.,2003 Portugal 7q34 Martin Silva et al.,2003 Iceland 7q34 Jonasdottir et al., 2003 France 7q34 Alizadeh et al., 2003 Turkey 8p Eraksoy et al., 2003b Portugal 8q12 Martin Silva et al.,2003 Iceland 8q12 Jonasdottir et al., 2003 Belgium 8q12 Goris et al., 2003 Turkey 8q14.2 Eraksoy et al., 2003a Hungry 8q21.3 Rajda et al., 2003 Iceland 8q22 Jonasdottir et al., 2003 Finland 8q22.2 Laaksonen et al., 2003 Iceland 8q24.3 Jonasdottir et al., 2003 Iceland 9p12 Jonasdottir et al., 2003 Portugal 9p13 Martin Silva et al.,2003 Iceland 9p13 Jonasdottir et al., 2003 Scandinavia 9p21 Harbo et al., 2003 Spain 9p21.1 Goertschees et al., 2003 Sardinia 9p21-9p23 Corradu et al., 2003 Spain 9p22.2 Goertschees et al., 2003 Iceland 9p24 Jonasdottir et al., 2003 Hungry 9q11 Rajda et al., 2003 Tajouri Page 247 1/11/2006 MS Thesis
Portugal 9q13-q21 Martin Silva et al.,2003 Scandinavia 9q21 Harbo et al., 2003 Iceland 9q21 Jonasdottir et al., 2003 Spain 9q21.32 Goertschees et al., 2003 Iceland 9q33 Jonasdottir et al., 2003 Turkey 9q34 Eraksoy et al., 2003a Iceland 10p11.1 Jonasdottir et al., 2003 Iceland 10p11.2 Jonasdottir et al., 2003 Iceland 10p12 Jonasdottir et al., 2003 Belgium 10p12 Goris et al., 2003 Portugal 10p13 Santos et al., 2003 Finland 10q11. Laaksonen et al., 2003 Portugal 10q11.1-10p11.2 Martin Silva et al.,2003 Hungry 10q11.2 Rajda et al., 2003 Iceland 10q22 Jonasdottir et al., 2003 Belgium 10q22 Goris et al., 2003 Spain 10q22.3 Goertschees et al., 2003 Finland 10q23.2 Laaksonen et al., 2003 Iceland 10q24 Jonasdottir et al., 2003 Spain 10q25.1 Goertschees et al., 2003 Portugal 11p11.2 Martin Silva et al.,2003 Iceland 11p11.2 Jonasdottir et al., 2003 Iceland 11p13 Jonasdottir et al., 2003 Portugal 11p15 Santos et al., 2003 Finland 11p15.3 Laaksonen et al., 2003 Iceland 11q11 Jonasdottir et al., 2003 Iceland 11q13 Jonasdottir et al., 2003 Iceland 11q13 Jonasdottir et al., 2003 Turkey 11q13.3 Eraksoy et al., 2003a Spain 11q14.1 Goertschees et al., 2003 Portugal 11q21 Santos et al., 2003 Finland 11q22.2 Laaksonen et al., 2003 Australia 11q22.2 Ban et al., 2003 Portugal 11q23 Martin Silva et al.,2003 N/Ireland 11q23 Heggarty et al., 2003 Belgium 11q23 Goris et al., 2003 Australia 11q23 Ban et al., 2003 Portugal 11q23 (and 12p11.2) Santos et al., 2003 Germany 11q23.2 Weber et al., 2003 Iceland 12p11.2 Jonasdottir et al., 2003 Portugal 12p12 Martin Silva et al.,2003 Iceland 12p13 Jonasdottir et al., 2003 Iceland 12p13 Jonasdottir et al., 2003 Spain 12q12 Goertschees et al., 2003 Sardinia 12q12 Corradu et al., 2003 N/Ireland 12q13 Heggarty et al., 2003 Germany 12q13.2 Weber et al., 2003 Australia 12q15 Ban et al., 2003 Iceland 12q21 Jonasdottir et al., 2003 Iceland 12q21 Jonasdottir et al., 2003 Iceland 12q21 Jonasdottir et al., 2003 Tajouri Page 248 1/11/2006 MS Thesis
France 12q22 Alizadeh et al., 2003 Portugal 12q22-q24.1 Martin Silva et al.,2003 Spain 12q24 Goertschees et al., 2003 Turkey 12q24.3 Eraksoy et al., 2003a Finland 12q24.31 Laaksonen et al., 2003 Turkey 13q Eraksoy et al., 2003b Spain 13q12.11 Goertschees et al., 2003 Portugal 13q12.11 Martin Silva et al.,2003 Iceland 13q13 Jonasdottir et al., 2003 Portugal 13q14 Martin Silva et al.,2003 N/Ireland 13q14 Heggarty et al., 2003 Spain 13q21 Goertschees et al., 2003 N/Ireland 13q22 Heggarty et al., 2003 N/Ireland 14q13 Heggarty et al., 2003 Finland 14q21.1 Laaksonen et al., 2003 Australia 14q21.1 Ban et al., 2003 Hungry 14q22 Rajda et al., 2003 Spain 14q24 Goertschees et al., 2003 Belgium 14q24 Goris et al., 2003 France 14q32 Alizadeh et al., 2003 France 14q32 Alizadeh et al., 2003 Iceland 15p13 Jonasdottir et al., 2003 Iceland 15q11.1-2 Jonasdottir et al., 2003 Spain 15q11.2 Goertschees et al., 2003 Portugal 15q12 Martin Silva et al.,2003 Iceland 15q13 Jonasdottir et al., 2003 Belgium 15q13 Goris et al., 2003 Belgium 15q13-q21 Goris et al., 2003 N/Ireland 15q14 Heggarty et al., 2003 Portugal 15q21 Martin Silva et al.,2003 N/Ireland 15q21 Heggarty et al., 2003 Portugal 15q22 Martin Silva et al.,2003 Iceland 15q22 Jonasdottir et al., 2003 Iceland 15q23 Jonasdottir et al., 2003 Germany 15q24.1 Weber et al., 2003 Iceland 15q25 Jonasdottir et al., 2003 Poland 15q26 Bielecki et al., 2003 Sardinia 16p12 Corradu et al., 2003 Australia 16p13 Ban et al., 2003 Spain 16p13.13 Goertschees et al., 2003 Iceland 16p13.2 Jonasdottir et al., 2003 Portugal 16q21 Martin Silva et al.,2003 Hungry 16q21 Rajda et al., 2003 N/Ireland 16q22 Heggarty et al., 2003 Iceland 17p11.2 Jonasdottir et al., 2003 Spain 17p12 Goertschees et al., 2003 Belgium 17p13 Goris et al., 2003 Germany 17p13.1 Weber et al., 2003 N/Ireland 17q11 Heggarty et al., 2003 Spain 17q11.2 Goertschees et al., 2003 Iceland 17q11.2 Jonasdottir et al., 2003 Tajouri Page 249 1/11/2006 MS Thesis
Portugal 17q21 Martin Silva et al.,2003 Spain 17q23.2 Goertschees et al., 2003 Iceland 17q24 Jonasdottir et al., 2003 Belgium 17q24 Goris et al., 2003 Turkey 18p Eraksoy et al., 2003b Spain 18p11.31 Goertschees et al., 2003 Australia 18q11 Ban et al., 2003 Portugal 18q21 Martin Silva et al.,2003 Iceland 18q21 Jonasdottir et al., 2003 Iceland 18q21 Jonasdottir et al., 2003 Hungry 18q21 Rajda et al., 2003 Iceland 18q22 Jonasdottir et al., 2003 Finland 18q22.2 Laaksonen et al., 2003 Turkey 18q23 Eraksoy et al., 2003b Turkey 19p Eraksoy et al., 2003b Iceland 19p11 Jonasdottir et al., 2003 Portugal 19p13.1 Martin Silva et al.,2003 Iceland 19p13.1 Jonasdottir et al., 2003 Portugal 19p13.2 Martin Silva et al.,2003 Portugal 19p13.3 Martin Silva et al.,2003 Finland 19p13.3 Laaksonen et al., 2003 N/Ireland 19q13 Heggarty et al., 2003 Turkey 19q13.1 Eraksoy et al., 2003a Australia 19q13.1 Ban et al., 2003 Spain 19q13.14 Goertschees et al., 2003 Germany 19q13.2 Weber et al., 2003 Australia 19q13.2 Ban et al., 2003 Iceland 19q13.3 Jonasdottir et al., 2003 Iceland 19q13.3 Jonasdottir et al., 2003 Hungry 19q13.3 Rajda et al., 2003 Hungry 20p12 Rajda et al., 2003 Belgium 20p12 Goris et al., 2003 Spain 20p12.1 Goertschees et al., 2003 Spain 20p12.2 Goertschees et al., 2003 Spain 20p12.3 Goertschees et al., 2003 Hungry 20q13.1 Rajda et al., 2003 France 21p11.1 Alizadeh et al., 2003 Belgium 21q11.2 Goris et al., 2003 Iceland 21q21 Jonasdottir et al., 2003 Spain 21q21.3 Goertschees et al., 2003 Finland 21q22.12 Laaksonen et al., 2003 Spain 22q12.3 Goertschees et al., 2003 Iceland 22q13 Jonasdottir et al., 2003 Iceland c78-12480 Jonasdottir et al., 2003 Iceland CGAT1D12 Jonasdottir et al., 2003 Iceland D17S4131 Jonasdottir et al., 2003 Iceland DXS339 Jonasdottir et al., 2003 Portugal HO16369 (Ch6) Martin Silva et al.,2003 N/Ireland Xp11 Heggarty et al., 2003 Iceland Xp22.1 Jonasdottir et al., 2003 Spain Xq13.1 Goertschees et al., 2003 Tajouri Page 250 1/11/2006 MS Thesis
Germany Xq13.3 Weber et al., 2003 Scandinavia Xq22 Harbo et al., 2003 Iceland Xq22 Jonasdottir et al., 2003 Hungry Xq22.3 Rajda et al., 2003 Portugal Xq23 Martin Silva et al.,2003
Tajouri Page 251 1/11/2006